GLOBAL The Global Macro Outlook -...

Please refer to page 72 for important disclosures and analyst certification, or on our website

www.macquarie.com/research/disclosures.

GLOBAL

Key forecasts, changes this month

1) Tables for real GDP growth, CPI, interest

rates, currencies and commodity prices

are on pages 11-13. Online access to our

global macro forecasts is available on

request

2) With the global industrial production

growth trough now ten months ago

(December 2015) and the OECD LI

trough already eight months ago

(February 2016), the question has

become the durability of the up-cycle

3) We present 32 charts over ten pages,

arguing that the cycle continues through

2017

4) Being less than halfway into the upswing,

unsurprisingly, our forecasts are largely

unchanged this month

Analyst(s) Macquarie Capital Securities (Japan) Limited Peter Eadon-Clarke +81 3 3512 7850 [email protected] Macquarie Capital Markets Canada Ltd. David Doyle, CFA +1 416 848 3663 [email protected] Macquarie Securities (Australia) Limited James McIntyre, CFA +61 2 8232 8930 [email protected] Macquarie Capital Limited Larry Hu PhD +852 3922 3778 [email protected] Jerry Peng +852 3922 3548 [email protected] Macquarie Capital Securities India (Pvt) Ltd Tanvee Gupta Jain +91 22 6720 4355 [email protected] Macquarie Equities South Africa (Pty) Ltd Elna Moolman +27 11 583 2570 [email protected] Macquarie Capital (Europe) Limited Matthew Turner +44 20 3037 4340 [email protected] Colin Hamilton +44 20 3037 4061 [email protected]

18 October 2016

The Global Macro Outlook 2017: in 10 pages and 32 charts After a February 2016 trough, the OECD Leading Indicator has recovered for six

months. Please see the data on page 2. The industrial cycle was, we believe, the

principal cause of the 2014-16 deceleration in global growth, and will be the

driver of the forecast 2017-18 recovery.

The durability of this upswing is strengthened by: 1) the employment-led

recovery underway in Europe, 2) the healing of private sector balance sheets in

advanced economies, and 3) the expected second leg up in the US

consumption growth story, pages 2-10.

Global real GDP growth; Macquarie’s the long grinding cycle forecast

Note: The Total-16 is the IMF’s 10-advanced and 6 EM economies. Forecasts are Macquarie where available, alternatively the IMF – please see Fig 170. The country weights use market exchange rates, not PPP

Source: IMF, Macquarie Research, October 2016

Our 2016-18 global real GDP growth forecasts are 2.2%, 2.6% and 2.7%,

respectively, a continuation of our “the long grinding cycle” of neither global lift-

off nor slump. There are three core forecasts underpinning our outlook:

1) A slow and cautious trajectory of Fed Funds rate increases: Our

base case has a 25bp increase in December and then 25bps every six

months thereafter, eventually reaching 2% in 2019: 7 October 2016 US

Economics Wages, construction & edging to full employment.

2) We believe the Chinese authorities have the willingness and ability

to maintain control of the RMB. We expect the RMB to appreciate

modestly in 2017: 7 September 2016 China Macro: What is missing

from the Trilemma and the implications for the RMB.

3) Oil prices trade higher in 2017 and 2018, to (Brent) $61/bbl and

$68/bbl, whilst commodity prices are mixed reflecting China’s housing

sector softening, Fig.36.

Short-term business-cycle judgements are more likely to succeed with a deep

awareness of more medium- and longer-term issues. In global macroeconomics,

there are a considerable number of the latter. We examine 20 of them from page

30; topical issues investigated in our Macq-ro insights reports.

2.60 2.77 2.69 2.532.22 2.65 2.70 2.66 2.62

0.0

1.0

2.0

3.0

4.0

5.0

2012 2013 2014 2015 2016 2017 2018 2019 2020

16-Total Average 1980-2011, 3.0% p.a The long grinding cycle, 2.5% p.a

Average 1980-2011, 3.0% p.a

The long grinding cycle, 2.5% p.a

(Global real GDP growth)

Macquarie Research The Global Macro Outlook

18 October 2016 2

The cycle through 2017 In a further 9 pages and 31 charts

The global IP recovery is continuing post its December 2015 nadir of +0.4% YoY, with the

latest reading being +2.0% YoY in August 2016. Please see the 12 October 2016

Commodities Comment. Our 2017 forecast is +2.4%. This drives a mild acceleration in global

real GDP growth through 2017.

This broadening of growth is supported by the OECD LI, below, which focuses on GDP and

inflected in March 2016.

The eurozone is now following the US into an employment-led recovery, from page 3.

The US is expected to continue its long grinding cycle recovery, from page 5.

China’s real GDP growth rate is forecast to fade gently (2016 6.7%, 2017 6.4%, 2018 6.0%),

from page 7, whilst EM economies in general continue to grow at recent moderated rates.

The global real interest rate is expected to rise with the cycle, from page 9.

Fig 1 OECD Leading Indicators, YoY

OECD total US Germany OECD Europe Japan

Jan-16 -0.69 -1.49 -0.06 -0.11 -0.41 Feb-16 -0.71 -1.45 -0.17 -0.18 -0.51 Mar-16 -0.70 -1.39 -0.30 -0.24 -0.59 Apr-16 -0.66 -1.30 -0.35 -0.26 -0.67 May-16 -0.60 -1.20 -0.35 -0.25 -0.74 Jun-16 -0.52 -1.10 -0.31 -0.23 -0.76 Jul-16 -0.44 -0.98 -0.24 -0.21 -0.72 Aug-16 -0.37 -0.83 -0.15 -0.19 -0.63

Note: Pale red shading: up MoM (improving), grey shading down MoM (falling). The data is usually revised by a few basis points

Source: OECD, Macquarie Research, October 2016

Fig 2 OECD Leading indicator, YoY %

Note: The previous OECD LI trough month was October 2011


For advanced economies, a global industrial recovery and increasingly healthy private

sector non-financial credit growth is the correct time to reload policy weapons. Priorities vary

between countries with the US prioritizing monetary policy and Japan putting more emphasis

on fiscal reconstruction. At present, we believe the eurozone is still nurturing the private

sector back to full health.

Please see the 26 August 2016 Timing the exit from unconventional monetary policies: The

ECB & BOJ and the 26 July 2016 Financial repression for decades.

For EM economies, ongoing credit cycle and real property price adjustments temper the

industrial cyclical relief, as does expected weak inward FDI. Please see the 8 April 2016

What’s next for EM economies and from page 7 here for more.

-6

-4

-2

0

2

4

6 (%)OECD LI YoY

From the industrial

sector to broader

GDP growth

Policy priorities


18 October 2016 3

Advanced economies: Private sector balance sheet repair & revival

Debt is not inherently a problem. Intermediated by the financial system, it is the main way that

savers earn returns. Savers, to be sustainably paid, however, require debt to be deployed into

debt-serviceable activities. We regard private sector non-financial credit growth broadly in line

with nominal GDP growth to be healthy.

Private sector balance sheet repair and the revival of private sector non-financial credit

growth is a sign of progress, of the economy healing from its previous excesses.

The revival of private sector credit demand is a prerequisite for the successful withdrawal of

extraordinary central bank support for the economy.

In the case of Japan, the excess of credit growth over nominal GDP growth over the 1980s

“Bubble” was followed by a protracted period of balance sheet adjustment (credit growth

beneath nominal GDP growth, Fig.3). We believe Japan endured a vicious cycle of policy and

regulatory mistakes, which US policy avoided after the Global Financial Crisis, Fig.4.

Fig 3 Japan: private non-financial credit growth vs. Nominal GDP growth

Fig 4 US private sector nonfinancial credit is growing faster than GDP for the first time since 2008

Source: FRB of St Louis, Datastream, Macquarie Research, October 2016 Source: FRB of St. Louis, Macquarie Securities, October 2016

Nevertheless, even in the US, the repair process took a total of seven years. It took three

years from when private sector credit growth first collapsed (2008) until it first went positive

again (2011) and another four years until it exceeded nominal GDP growth (2015).

Fig 5 Euro Area: private nonfinancial credit growth vs. Nominal GDP growth

Fig 6 The fiscal impulse: the eurozone’s 2011-13 fiscal squeeze

Source: FRB of St Louis, Datastream, Macquarie Research, October 2016

Note: Year-over-year change in the cyclically adjusted net lending (+) or net borrowing (-) of general government, adjusted based on potential GDP, excessive deficit procedure. Forecasts for 2015-17 from the European Commission. Source: EC Annual Macroeconomic Database, Macquarie Research, October 2016

-12

-9

-6

-3

0

3

6

1992 1993 1995 1997 1999 2001 2003 2005 2007 2009 2011 2013 2015

(YoY % change)

Private nonfinancial credit

Nominal GDP

late

-4

-2

0

2

4

6

8

10

12(YoY% change) Private nonfinancial credit

Nominal GDP

latest

-6

-4

-2

0

2

4

6

8

10

12

14(YoY % change) Private nonfinancial credit

Nominal GDP

-2

-1

0

1

2

2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017

(% of potential GDP)

YoY change in cyclically adjusted budget balance

The case of Japan

The US


18 October 2016 4

The eurozone is behind the US because of the 2011-13 fiscal squeeze, Fig 6, and a second

credit crunch in 2011-13, Fig 7, such that private sector credit growth double-dipped and has

only gone positive again in 2015, four years behind the US (2015 versus 2011), Fig 5.

Nonetheless, a recovery is underway, led by strengthening employment. As employment

increases, Fig 8, households become more confident to borrow, Fig 9 and Fig 10. Auto sales

are also recovering across Europe, Fig 11 and Fig 12.

Fig 7 Euro-zone: Tight lending conditions 2007-09 and 2011-13

Fig 8 Eurozone employment growth, YoY, %, 2002 to latest: +1.5% YoY

Note: Net percentage is used. The net percentage is defined as the difference between the sum of the percentages for “tightened considerably” and “tightened somewhat”, and the sum of the percentages for “eased somewhat” and “eased considerably”. Positive numbers imply tight lending conditions.

Source: left-hand chart: ECB, Macquarie Research, October 2016, right-hand chart: Eurostat, Macquarie Research, October 2016

Fig 9 Euro area consumer credit outstanding, YoY, %, 2005 to latest

Fig 10 Germany, France and Spain: consumer credit outstanding, YoY, %, 2005 to latest

Note: the latest value is 605.4 billion Euro. Source: ECB, Macquarie Research, October 2016

Source: ECB, Macquarie Research, October 2016

Fig 11 European new vehicle registrations, YoY, % Fig 12 European car sales, units, SA

Source: National car data, Macquarie Research, October 2016 Source: ECB, Macquarie Research, October 2016

-40

-20

0

20

40

60

80

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016

(%)Changes in credit standards applied to enterprises over the past three months

-2.5

-2.0

-1.5

-1.0

-0.5

0.0

0.5

1.0

1.5

2.0

2.5

2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016

(%, YoY)Eurozone unemployment growth

-6

-4

-2

0

2

4

6

8

10

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016

(%, YoY)Loans to households consumer credit

-20

-15

-10

-5

0

5

10

15

20

25

30

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016

(%, YoY)Germany - Loans to households consumer credit

France - Loans to households consumer credit

Spain- Loans to households consumer credit

(20%)

(15%)

(10%)

(5%)

0%

5%

10%

15%

2010 2011 2012 2013 2014 2015 2016

YoY change12m moving average

800,000

850,000

900,000

950,000

1,000,000

1,050,000

1,100,000

1,150,000

1,200,000

1,250,000

Jan-12 Jan-13 Jan-14 Jan-15 Jan-16

The eurozone


18 October 2016 5

Whilst the eurozone is now following the US into an employment-led recovery, the US is

expected to continue its long grinding cycle recovery.

The energy-capex collapse induced growth slowdown in the US over 2015 and the 1H 2016

is over. After a forecast 1.5% real GDP growth this year, we are forecasting 2.4% pa real

GDP growth for both 2017 and 2018. Sometimes it is valuable to look backwards, to increase

one’s confidence in the future.

Fig 13 Energy-capex (red), Residential investment (green) and non-energy, non-resi. (blue) 2010=1.0

Fig 14 Energy & mining related investment as a share of non-residential investment, %

Source: BEA, Macquarie Research, October 2016 Source: BEA, Macquarie Research, October 2016

Fig 15 Average hourly earnings, YoY, %, oil states (blue), non-oil states (red), 3/2008 to latest

Fig 16 Civilian non-institutional population 25-54 year olds (12-month ma), 2002 to 2025E

Source: BLS, Macquarie Research, October 2016 Source: BLS, Census Bureau, Macquarie Research, October 2016

Fig 17 US residential investment share in GDP (%) Fig 18 US construction employment, % of total

Source: BEA, BLS, Macquarie Research, October 2016 Source: BEA, BLS, Macquarie Research, October 2016

0.3

0.5

0.7

0.9

1.1

1.3

1.5

1.7

1.9

2.1

2.3

1Q10 1Q11 1Q12 1Q13 1Q14 1Q15 1Q16 1Q17

Private investment (nominal $) (1Q 2010=1.00)

1Q10 = 1.00energy & mining

investment

non-residential investment ex-energy & mining investment

residentialinvestment

0%

2%

4%

6%

8%

10%

12%

14%

1959 1964 1969 1974 1979 1984 1989 1994 1999 2004 2009 2014

Energy & mining related investment as a share of non-residential investment

Average

+1STDEV

-1STDEV

0.0%

0.5%

1.0%

1.5%

2.0%

2.5%

3.0%

3.5%

4.0%

4.5%

Mar-08 Mar-09 Mar-10 Mar-11 Mar-12 Mar-13 Mar-14 Mar-15 Mar-16

Average hourly earnings YoY% change (3moMA)

current = 2.9%

non-oil

states

oil states

121,000,000

122,000,000

123,000,000

124,000,000

125,000,000

126,000,000

127,000,000

128,000,000

129,000,000

130,000,000

2002 2004 2006 2008 2010 2012 2014 2016 2018 2020 2022 2024

Civilian noninstitutional population25-54 years (12moMA)

Note: Projections in 25-54 population from BLS

2.0%

2.5%

3.0%

3.5%

4.0%

4.5%

5.0%

5.5%

6.0%

6.5%

7.0%

1970 1975 1980 1985 1990 1995 2000 2005 2010 2015

US residential investment share of GDP

+1 STDEV

Average

-1 STDEV

2005-6

1987

1973 1978

1999

Recession risks elevated when housing's importance is high

Expansions are likely when housing's importance is low and rising

4.0%

4.2%

4.4%

4.6%

4.8%

5.0%

5.2%

5.4%

5.6%

5.8%

1970 1975 1980 1985 1990 1995 2000 2005 2010 2015

2006

2000

1990

1979

1973

US construction employment as share of total employment

+1 STDEV

Avg

-1 STDEV

The US energy-

capex collapse


18 October 2016 6

The collapse in energy-capex 2015 through 2Q 2016, Fig 13, has taken around a cumulative

0.6% off overall GDP. Fortunately, energy & mining investment has now reached historic lows

as a percentage of overall non-residential investment, Fig 14. There have been negative spill-

overs into the surrounding economies, as illustrated in Fig 15, which shows the relative

weakness in average hourly earnings in oil states.

The prime household formation demographic, the 25-54 year-olds is emerging from being a

headwind to a tailwind, Fig 16. This supports another up leg for residential investment and

construction worker employment, Fig 17 and Fig 18, and the homes component of private

sector non-financial credit growth, Fig 19. Please note that the US jobs recovery has been led

by full-time positions, not part-time jobs, Fig 20.

Fig 19 US non-financial private sector credit growth by components: business (black), homes (blue), non-home household credit (red), YoY, %, since 1991

Fig 20 US employment, January 2010 = 1.00, part-time workers (red) , full-time workers (blue)

Source: Federal Reserve, Bloomberg, Macquarie Research, October 2016 Source: BLS, Macquarie Research, October 2016

Fig 21and Fig 22 are the conclusions from the 31 May 2016 Fortress America: Auto outlook,

upside risks to consensus, a demographically-driven macro scenario analysis of the North

American auto market.

Fig 21 Our demographics work suggests there is the potential for further upside in US autos sales... Fig 22 ...but not in Canada

Source: Bloomberg, BEA, BLS, Macquarie Research, October 2016 Source: Statistics Canada, Macquarie Research, October 2016

-12%

-9%

-6%

-3%

0%

3%

6%

9%

12%

15%

1991 1993 1995 1997 1999 2001 2003 2005 2007 2009 2011 2013 2015

non-mortgage HH

home mortgage

credit

US credit growth (nonfinancial private sector breakdown) - YoY % change

Non-financialbusiness

credit

0.92

0.96

1.00

1.04

1.08

1.12

2010 2011 2012 2013 2014 2015 2016

US employment (Jan 2010 = 1.00)

Jan 10 = 1.00

part-time

full-time

8

10

12

14

16

18

20

22

1977 1981 1985 1989 1993 1997 2001 2005 2009 2013 2017

US auto sales relative to mean-reverting level (millions of units)

auto sales

mean-reverting

level (based on 15-64 age pop)

Pent-up demand is created in downturns that leads to

overshootings during expansions

0.7

0.8

0.9

1.0

1.1

1.2

1.3

1.4

1.5

1.6

1.7

1981 1984 1987 1990 1993 1996 1999 2002 2005 2008 2011 2014

new motor vehicle sales (units)

population

New motor vehicles (rolling 12 mo sum) vs. population growth - 1981=1.00


18 October 2016 7

China, EM more generally and global trade growth

With the advanced economies doing a little better, global growth is able to accommodate the

ongoing gentle fade in China’s growth.

Rather than a hard stop of the investment-driven, credit-driven growth models of Malaysia,

Thailand, Indonesia and Korea as occurred in 1997, below, as marginal capital providers

(cross-border bank lending) withdrew, we expect the Chinese-case marginal capital providers

(households depositing into the Chinese banking system) to persist.

Fig 23 Gross fixed capital formation, % of GDP

Note: Investment is private investment and includes residential investment. The last two data points are IMF forecasts

Source: BIS, Macquarie Securities, October 2016

Whilst China’s ratio of investment (including residential investment) to GDP is declining

(Fig.24) as the rate of growth of investment slows (Fig 25), it still has a lot further to decline to

meet international norms.

Fig 24 China’s investment, % of GDP Fig 25 China’s investment (US$ tr)

Source: IMF WEO database, Macquarie Research, October 2016 Source: IMF WEO database, Macquarie Research, October 2016

China’s real GDP growth continues to fade as the relative productivity of marginal investment

deteriorates.

We are forecasting Chinese real GDP growth to be 6.4% in 2017 and 6.0% in 2018 after

6.7% this year.

For emerging market economies more generally, growth has been fading since 2012 as the

economies looks for a new growth engine, and unwinds the credit excesses of the past.

Fig 26 shows the ratio of private non-financial credit to GDP and its growth over the last five

years.

10

20

30

40

50

1970

1972

1974

1976

1978

1980

1982

1984

1986

1988

1990

1992

1994

1996

1998

2000

2002

2004

2006

2008

2010

2012

2014

(% of GDP) Malaysia Thailand Indonesia Korea

25

30

35

40

45

50

1980

1982

1984

1986

1988

1990

1992

1994

1996

1998

2000

2002

2004

2006

2008

2010

2012

2014

2016

(%GDP) China's investment, % of GDP

0.0

1.0

2.0

3.0

4.0

5.0

6.0

1980

1982

1984

1986

1988

1990

1992

1994

1996

1998

2000

2002

2004

2006

2008

2010

2012

2014

2016

(US$tr) China's investment

The ongoing gentle

fade in China’s

growth

Emerging market

economies more

generally


18 October 2016 8

Whilst the ratio to GDP generally increases with economic development and financial

deepening, relative to other EM economies shown below, some countries appear elevated,

implying a need to go through a period of private debt adjustment.

Fig 26 Private non-financial credit, level and growth, for leading EM economies

Note: The BIS does not have data for the Philippines

Source: BIS, Macquarie Research, October 2016

A particular challenge for non-China EM is our belief that China began a serious import

substitution phase in 2015 and this will continue for as long as the old growth model

persists, and SOE’s invest with a perceived near zero cost of capital.

The 1980-2008 6% pa global world trade volume growth average has stepped down, in our

opinion, to a new trend growth rate of 2-3% pa, Fig 27.

Fig 27 World Merchandise Trade, from 1992 to latest, rolling 3 months, YoY

Note: as a consistency check, we are looking for real GDP growth to accelerate 50bp, 2018 versus 2016 (chart front cover), and if advanced economies are the source of this (with global GDP 60:40 advanced economies: EM on market exchange rates) it implies advanced economies will accelerate by 80bp (80bp times 0.6 equals 48bp, approximately equal to 50bp). If the OECD LI needs to rise 80bp from its low of -71bp in February 2016, then it is only going to go marginally positive in this cycle, at +10bp or so. Given the relationship in the above chart, the reacceleration in world trade could be very modest

Source: CPB, Macquarie Research, October 2016

This reflects:

1) The maturing of a 50-year containerization trend

2) The completion of the integration of China into global supply chains post its

December 2001 WTO entry

3) The move by MNCs to regionalize production to dampen exchange rate risk

4) The transition of China’s investment and credit-driven growth model into an import

substitution stage for intermediate and capital goods, especially by those companies

that perceive their cost of capital to be very low

Brazil

Mexico

Russia

Turkey

India

China

Indonesia

Malaysia

Singapore

Thailand

0

10

20

30

40

50

60

0 50 100 150 200 250

2015 3Q vs 2010 3Q

Private debt as % of GDP

Change in five years (%)

-6

-4

-2

0

2

4

6

-23

-13

-3

7

17

1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016

World Merchandise Trade, YoY [LHS] OECD LI, YoY [RHS]

(%) (%)


18 October 2016 9

The late 2014/early 2015 air pocket in emerging market economies’ import growth, along with

the trend decline in its growth rate, is shown in Fig 28, red line, which uses rolling three-

month average YoY data.

These headwinds will persist even as the OECD LI recovers to a positive YoY level.

Fig 28 EM & Advanced economies import volumes


One consequence of the above is the muted response relative to history of the trade account

to exchange rate movements. This probably results in greater currency volatility. In the case

of EM currency depreciations, the consequence is likely to be more import volume

compression than export volume expansion.

The long, grinding cycle and low real interest rates

The principal driver of record low bond yields has evolved from cyclical factors (secular

stagnation), through a private sector balance sheet recession (completed in the US and

Japan, progressing, but ongoing in the eurozone) to fiscal reconstruction (reloading the fiscal

policy tool weapon) using the tool of financial repression.

The political consequences of ‘the long grinding cycle’ have been intensifying. Entitlement

program promises are under pressure. Politicians are not only looking to boost global growth,

somehow, but also to ensure low funding costs persist for as long as possible.

Fig 29 10-year real bond yields, G7 ex Italy, 1985-2013, quarterly, %

Note: National Bureau of Economic research (NBER) working paper “Measuring the world interest rate” by Mervyn King & David Low (2014) The US enters the sample in 1999 with the first TIPS issue.

Source: NBER above, Macquarie Research, October 2016

The 26 July 2016 Macq-ro insights: Financial repression for decades examined these issues,

and concluded that the 10-year US TIP yield was a reasonable proxy to monitor, Fig.30.

Please note how it (the red line) has trended down from ~2% in 2003 to ~10bps recently.

-5

0

5

10

15

20

25

2010 2011 2012 2013 2014 2015 2016

Advanced EM

(per 12 month % change)

LAST 3 MONTHS ON YEAR AGO

-1

0

1

2

3

4

5

6

1985 1987 1989 1991 1993 1995 1997 1999 2001 2003 2005 2007 2009 2011 2013

(%) Weighted real rate Unweighted real rate

Financial repression

for decades


18 October 2016 10

The 10-year TIPS yield was lowest during the most aggressive phase of US monetary easing

in 2012 (QE3), increased sharply with the May 2013 ‘Taper Tantrum’, and has drifted lower

since the Fed began to slowly and cautiously withdraw its extraordinary monetary easing.

Fig 30 US TIPs yields, %

Source: US Department of the Treasury, FED, Macquarie Research, October 2016

The cycle and the trend: Integrated global capital markets imply that we should expect a

mild recovery in global real GDP growth over 2017-18 to lead to a mild increase in the global

real interest rate (50bp or so). In addition to the global real interest rate, nominal bond yields

have an additional element relating to inflationary expectations. Fig.31 illustrates this for the

US 10-year bond. Our forecasts for US inflation suggest that the inflation compensation

element will increase going forward; leading to an overall increase in nominal US bond yields.

Nonetheless, real interest rates are expected to remain well beneath our 2.5% pa global real

GDP growth forecast.

Fig 31 We anticipate the inflation compensation element to drive an increase in the 10-year Treasury yield

Note: Over time US 10-year bond yields are expected to have a global real interest rate component of around 0.5%, and an inflation compensation component of around 2%.

Source: Bloomberg, Macquarie Research, October 2016

For advanced economies, a global industrial recovery and increasingly healthy private sector

non-financial credit growth is the correct time to reload policy weapons. Priorities vary

between countries with the US prioritizing monetary policy and Japan putting more emphasis

on fiscal reconstruction. The eurozone continues to focus on nurturing the private sector back

to robust health, in our opinion.

-2

-1

0

1

2

3

4

5

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016

(yield, %)Treasury inflation protected securities - 5 yearTreasury inflation protected securities - 7 yearTreasury inflation protected securities - 10 yearTreasury inflation protected securities - 20 yearTreasury inflation protected securities - long term

-1.5

-1.0

-0.5

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016

real yield

inflation compensation

2005-14 infl. comp avg

10 year Treasury yield components

forecast

forecast

Real interest rates

are expected to

remain well beneath

our 2.5% pa global

real GDP growth

forecast


18 October 2016 11

Forecasts and revisions Fig.32 & Fig.33 present our principal real GDP forecasts and revisions.

Revisions over the last month have been minor. Over the last four months:

1) UK real GDP growth forecasts are: 2016 2.0% (versus 1.9%), 2017 1.2% (2.3%).

2) Eurozone real GDP growth forecasts are: 2016 1.6% (1.8%), 2017 1.4% (1.7%)

For 2017, we are beneath consensus on Canada, Australia and Japan.

We are above-consensus in our 2017 forecasts for the US and most of Asia.

Fig 32 Macquarie’s real GDP forecasts

Calendar Year YoY (%) 4Q on 4Q (%) 2014 2015 2016 2017 2018 2014 2015 2016 2017 2018

US 2.4 2.6 1.6 2.4 2.1 2.5 1.9 2.0 2.3 2.0 Eurozone 0.9 1.9 1.6 1.4 1.6 1.0 1.9 1.5 1.6 1.6 Japan -0.1 0.6 0.4 0.6 0.7 -0.9 0.8 0.4 0.6 0.7 UK 2.9 2.2 2.0 1.2 1.2 2.9 2.2 2.0 1.2 1.2 Canada 2.5 1.1 1.2 1.8 1.6 2.4 0.3 1.6 1.7 1.5 Australia 2.6 2.4 2.8 2.3 3.2 2.2 2.8 2.3 2.7 3.5 New Zealand 3.7 2.5 3.4 3.3 2.4 4.1 2.3 3.5 3.0 2.2

China 7.2 6.8 6.7 6.4 6.0 7.2 6.8 6.7 6.4 6.0 S. Korea 3.3 2.6 2.9 2.9 2.7 2.7 3.1 2.7 2.8 2.7 Taiwan 3.9 0.6 1.3 2.0 2.3 3.4 -0.9 2.3 2.0 2.3 Hong Kong 2.6 2.4 1.2 1.5 2.0 2.5 1.9 1.2 1.5 2.0 Indonesia 5.0 4.8 4.9 5.0 5.2 5.0 5.0 4.5 5.0 5.2 Malaysia 6.0 5.0 4.3 4.7 5.1 5.7 4.5 5.0 4.7 5.1 Singapore 3.3 2.0 1.9 2.1 2.4 2.9 1.7 1.9 2.1 2.4 Philippines 6.2 5.9 6.2 6.1 6.3 6.6 6.6 5.6 6.1 6.3 Thailand 0.8 2.8 3.2 3.3 3.5 2.1 2.8 3.0 3.3 3.5 India 6.7 7.2 7.6 7.8 7.7 6.6 7.2 7.9 7.8 7.5

South Africa 1.5 1.2 0.4 0.9 1.7 1.3 0.0 0.7 0.9 1.3

Source: Macquarie Research, October 2016

Fig 33 Macquarie’s real GDP forecasts: revisions, and versus consensus

2016 YoY (%) 2017 YoY (%) Previous

Macquarie forecast (*)

Current Macquarie

Forecast Consensus Spread (2) versus (3)

Previous Macquarie forecast (*)

Current Macquarie

Forecast Consensus Spread (6) versus (7)

(1) (2) (3) (4) (5) (6) (7) (8)

US (**) 1.9 2.0 1.9 0.1 2.3 2.3 2.1 0.2 Eurozone 1.6 1.6 1.5 0.1 1.4 1.4 1.3 0.1 Japan 0.4 0.4 0.6 -0.2 0.6 0.6 0.8 -0.2 UK 1.9 2.0 1.7 0.3 1.1 1.2 0.7 0.5 Canada (**) 1.6 1.6 1.5 0.1 1.7 1.7 2.0 -0.3 Australia 3.0 2.8 2.9 -0.1 2.3 2.3 2.8 -0.5 New Zealand 3.2 3.4 3.0 0.4 3.3 3.3 2.8 0.5

China 6.7 6.7 6.6 0.1 6.4 6.4 6.3 0.1 S. Korea 2.9 2.9 2.6 0.3 2.9 2.9 2.6 0.3 Taiwan 1.3 1.3 1.0 0.3 2.4 2.0 1.7 0.3 Hong Kong 2.0 1.2 1.2 0.0 2.6 1.5 1.5 0.0 Indonesia 4.9 4.9 5.0 -0.1 5.0 5.0 5.3 -0.3 Malaysia 4.3 4.3 4.1 0.2 4.7 4.7 4.3 0.4 Singapore 1.9 1.9 1.7 0.2 2.1 2.1 1.8 0.3 Philippines 6.2 6.2 6.4 -0.2 6.1 6.1 6.1 0.0 Thailand 3.2 3.2 3.1 0.1 3.3 3.3 3.2 0.1 India (***) 7.6 7.6 7.6 0.0 7.6 7.6 7.7 -0.1

South Africa 0.3 0.4 0.4 0.0 0.9 0.9 1.3 -0.4

Note: (*) August 2016. Calendar year numbers for all countries bar the US and Canada, marked with a (**) which are 4Q on 4Q, and India, marked with a (***) which is fiscal year (to FY3/17 and FY3/18) and is based on the new series, growth measured on a GVA basis. Consensus numbers for calendar year countries are from Consensus Economics, otherwise the numbers are from Bloomberg.

Source: Consensus Economics, Bloomberg, Macquarie Research, October 2016

For 2017, we are

beneath consensus

on Canada,

Australia and Japan

We are above

consensus in our

2017 forecasts for

the US and most of

Asia


18 October 2016 12

In line with the continuation of moderate real and nominal global real GDP growth, The Long

Grinding Cycle, our interest rate forecasts are commensurately subdued. Please note that we

are forecasting the US 10-year bond yield to have a cycle high in 2018 of only 2.70%.

Fig 34 Macquarie’s interest rate forecasts

Year end Policy or cash rate (*) (%) 10-year bond yield (%) 2014 2015 2016 2017 2018 2014 2015 2016 2017 2018

US 0.00 0.25 0.50 1.00 1.50 2.17 2.27 1.90 2.30 2.70 Eurozone 0.05 0.05 0.00 0.00 0.00 0.54 0.63 0.50 1.00 1.50 Japan 0.07 0.04 0.00 0.00 0.00 0.33 0.27 -0.10 -0.10 0.20 UK 0.50 0.50 0.25 0.25 0.50 1.79 1.96 1.20 1.20 1.75 Canada 1.00 0.50 0.50 0.50 0.75 1.79 1.39 1.25 1.40 1.50 Australia 2.50 2.00 1.50 1.00 1.00 2.81 2.88 1.75 1.90 2.10 New Zealand 3.50 2.50 1.75 1.25 1.75 3.67 3.58 2.40 2.60 2.70

China 5.60 4.35 4.10 4.10 4.10 S. Korea 2.00 1.50 1.25 1.50 1.75 Taiwan 1.88 1.63 1.50 2.00 2.50 Indonesia 7.75 7.50 6.50 6.50 6.50 Malaysia 3.25 3.25 2.75 2.50 2.50 Singapore 0.50 0.88 1.50 1.80 2.00 Philippines 4.00 4.00 2.75 2.50 2.50 Thailand 2.00 1.50 1.50 1.75 2.25 India 8.00 6.75 6.25 6.00 6.00

South Africa 5.75 6.25 7.00 7.00 7.00

Note: (*) Policy or cash rate, US: Fed Funds rate, Eurozone: EMU Refi Rate, Japan: overnight call rate, UK: Repo rate, Canada: Cash rate, Australia: Cash rate, New Zealand: Official cash rate, China: 1-year working capital, South Korea: Overnight call rate, Taiwan: Official discount rate; HK: discount window base; Indonesia: 1-month SBI rate, Malaysia: Overnight policy rate, Singapore: 3-month interbank rate, Philippines: Reverse repo rate, Thailand: 14-day repo rate, India: Repo rate, South Africa: Repo rate


We are forecasting calendar year 2016 CPI of 1.3% YoY in the US, 0.4% YoY in the Euro-

zone, and 2.0% YoY in China: so moderate inflation, not deflation. In 2017, the US and

eurozone inflation forecasts are 2.5% and 1.6% respectively.

After a period of broad US$ strength in 2015, we believe individual currencies will at different

times pass their lows versus the US$. Whilst relative monetary policy stances will remain

important, resulting capital flows now have to exceed mounting current account surpluses in

Japan and the Eurozone (partially reflecting the falls in oil and other resource prices). On our

forecasts, the Yen passes its weakest point first (4Q 2015), and then the Euro (1Q 2017).

Fig 35 Macquarie’s CPI and currency forecasts

Year end CPI (%, YoY) Currency versus US$ (Year-end) 2014 2015 2016 2017 2018 2014 2015 2016 2017 2018

US 1.6 0.1 1.3 2.5 2.4 Eurozone 0.4 0.0 0.4 1.6 1.5 1.21 1.09 1.08 1.11 1.12 Japan 2.7 0.8 -0.1 0.3 0.5 119.8 120.41 105.00 101.00 97.00 UK 1.5 0.0 0.7 2.3 2.5 1.56 1.47 1.27 1.35 1.40 Canada 1.9 1.1 1.5 1.8 2.0 1.16 1.39 1.36 1.45 1.45 Australia 2.5 1.5 1.2 1.9 1.8 0.82 0.73 0.76 0.72 0.73 New Zealand 1.2 0.3 0.5 1.1 1.6 0.78 0.68 0.72 0.68 0.67

China 1.5 1.5 2.0 2.0 2.5 6.20 6.49 6.60 6.40 6.20 S. Korea 1.3 0.7 1.1 1.9 2.0 1099 1173 1130 1150 1130 Taiwan 1.2 -0.3 1.3 1.4 1.5 31.60 32.85 33.40 34.00 35.00 Hong Kong 4.4 3.0 2.5 2.0 2.2 7.75 7.75 7.80 7.80 7.80 Indonesia 6.4 6.4 4.1 4.9 5.0 12440 13795 13500 13700 13500 Malaysia 3.1 2.1 2.7 2.8 2.6 3.50 4.29 4.20 4.15 4.10 Singapore 1.0 -0.5 -0.3 1.0 1.4 1.31 1.42 1.37 1.35 1.33 Philippines 4.2 1.4 1.6 2.8 3.3 44.73 47.06 46.50 46.00 45.50 Thailand 1.9 -0.9 0.3 1.7 2.2 32.92 36.04 35.50 36.20 36.00 India 6.7 4.9 5.2 5.0 5.0 62.71 66.50 68.20 69.69 70.57

South Africa 6.1 4.6 6.5 5.5 5.5 11.57 15.50 14.50 14.50 14.00

Note: The currency forecasts are presented in the most common format. Normally, this is per US$, but exceptions where it is US$ per other currency include: the Euro, Sterling, Australia and NZ dollars


We forecast the US

10-year bond yield

to have a cycle high

in 2018 of only

2.70%

We are not

forecasting deflation

After a period of

broad US$ strength

in 2015, we believe

individual

currencies will at

different times reach

their lows versus

the US$

Whilst relative

monetary policy

stances will remain

important, resulting

capital flows now

have to exceed

mounting current

account surpluses

in Japan and the

Eurozone

On our forecasts the

Yen passes its

weakest point first,

(4Q 2015) and then

the Euro (1Q 2017)


18 October 2016 13

The latest Macquarie commodity team commodity price forecasts are below. Commentary

follows the table. The next page looks at oil, with comments on other commodities on the

subsequent pages.

Fig 36 Macquarie’s commodity price forecasts

2015 2016 2016 2016 2017 2017 2017 2018 2019 2020 2021

Unit CY CY Q3 Q4 Q1 Q2 CY CY CY CY CY LT $2016

Base Metals Copper $/tonne 5,503 4,693 4,772 4,600 4,500 4,650 4,563 4,413 4,650 5,188 6,100 5,900 Aluminium $/tonne 1,663 1,547 1,620 1,480 1,450 1,450 1,438 1,425 1,413 1,413 1,450 1,350 Zinc $/tonne 1,932 2,038 2,255 2,300 2,200 2,400 2,425 2,700 2,825 2,663 2,380 2,300 Nickel $/tonne 11,836 9,522 10,265 10,500 11,000 11,500 11,625 13,000 14,000 15,000 16,000 15,000 Lead $/tonne 1,786 1,819 1,873 1,940 1,910 1,960 2,003 2,190 2,085 1,945 1,928 1,950 Tin $/tonne 16,077 17,141 18,624 17,500 17,500 17,500 17,500 18,000 18,500 19,000 19,500 18,000 Steel and Raw Materials Iron ore - 62% Fe $/t CFR 56 53 59 50 52 52 50 47 50 60 60 60 Hard coking coal $/t FOB 102 107 93 170 140 115 121 115 120 125 125 105 Steel - World Export HRC

$/tonne 370 363 372 380 370 370 370 350 335 345 345 380

Energy Crude Oil - Brent $/barrel 52 44 45 52 56 62 61 68 73 75 77 68 Crude Oil - WTI $/barrel 49 43 44 49 51 57 56 62 67 69 71 63 Henry Hub Gas $/MMBTU 2.6 2.5 2.9 2.9 3.2 3.0 3.2 3.3 3.3 3.2 3.2 2.9 Thermal coal - Aus Spot $/t FOB 59 58 67 63 60 58 58 55 53 50 50 48 Uranium $/lb 37 28 26 27 29 29 29 31 34 37 40 43 Lithium carbonate $/t CFR

China 5,190 7,547 8,300 8,275 8,300 8,300 8,250 7,500 7,000 6,750 6,750 6,000

Precious Metals Gold $/oz 1,160 1,262 1,335 1,275 1,325 1,375 1,381 1,375 1,406 1,438 1,388 1,250 Silver $/oz 16 17 20 18 19 20 20 21 22 23 23 18 Platinum $/oz 1,053 1,000 1,085 1,000 1,025 1,050 1,094 1,219 1,331 1,363 1,325 1,400 Palladium $/oz 692 604 675 650 625 625 644 775 781 763 738 800 Agriculture MacPI 1997-

2000=100 149 148 145 152 153 154 155

Potash $/t FOB 303 247 220 225 225 220 221 230 240 250 250 280 Urea $/t FOB 273 195 184 190 220 200 203 200 200 210 215 240 Ammonia $/t FOB 385 231 204 185 215 225 223 230 230 230 245 250 Natural Rubber USc/kg 137 126 117 118 118 120 118 120 123 126 129 115 Others Alumina $/t FOB 301 236 234 235 250 250 248 240 223 223 230 225 Manganese ore $/mtu CIF 2.9 3.5 4.0 3.5 3.0 3.0 3.0 3.3 3.3 3.5 3.8 2.8 Ferrochrome (EU contract)

c/lb 107 96 98 110 100 105 103 100 105 110 110 105


Whilst the US Federal Reserve and their policies are regarded as the fulcrum of global capital

markets, the commodity complex provides a useful spyglass on global developments.

Based on a simple up/down ratio, 2016 is expected to be another challenging year of trying to

align supply with sluggish demand growth, Fig.37.

Fig 37 Macquarie commodity price forecasts, YoY simple up/down ratio

2015 2016 2017 2018 2019 2020 2021

YoY, number of forecasts up 2 8 16 15 16 17 12 YoY, number of forecasts down 23 19 10 11 6 6 5 YoY, number of forecasts unchanged 0 3 1 0 4 3 9

Note: The two commodity price rises in 2015 were uranium and potash



18 October 2016 14

Oil The oil supply and demand modelling undertaken by Vikas Dwivedi indicates that beyond short-term disruptions, crude remains on a path to structural rebalance.

Vikas continues to believe that the market will reach a more sustainable balance marked by

seasonally normal draws in 4Q16, driven by further U.S. onshore declines and continued

demand growth.

Fig 38 Oil demand remains highly correlated to global growth

Source: World Bank, BP Statistical, Macquarie Research, October 2016

Vikas’ crude price forecasts remains unchanged; believing that the price levels forecast at the

start of the year continue to remain appropriate given the global crude fundamental backdrop.

Vikas expects Brent prices to average $45/bbl in 2016, and WTI to average $42/bbl.

Beyond the current year, he expects Brent to average $61/bbl in 2017 and $68/bbl in 2018,

and for WTI to average $56/bbl and $62/bbl, respectively.

Fig 39 Annual Brent & WTI forecast

Source: Macquarie Research, Annual Price Forecasts, October 2016

Fig 40 Quarterly Brent and WTI forecast

Source: Macquarie Research, Bloomberg, October 2016

For more detail behind the above, please see 22 June 2016 Through the looking glass: stage

set for global crude rebalance and 30 September 2016 OPEC’s fuzzy agreement.

2016 2017 2018

Base Case $45 $61 $68

WTI Base Case $42 $56 $62

WTI - Brent ($3) ($5) ($6)

$68

($6)

Normalized Price

$74

3Q16E 4Q16E 1Q17E 2Q17E 3Q17E 4Q17E 1Q18E 2Q18E 3Q18E 4Q18E

Brent forecast $47 $52 $56 $62 $65 $62 $65 $67 $70 $69

WTI - Brent ($3) ($3) ($5) ($5) ($5) ($5) ($6) ($6) ($6) ($6)

WTI $45 $49 $51 $57 $60 $57 $59 $61 $64 $63

Consensus $46 $49 $51 $54 $56 $59 $61 $62 $62 $63

Forward Curve $51 $52 $52 $53 $53 $54 $54 $55 $55 $55

Brent vs. Cons $1 $3 $5 $9 $10 $3 $4 $5 $8 $6

Brent vs. Fwds ($4) $0 $4 $9 $12 $8 $11 $12 $15 $14

We expect Brent to

average $61/bbl in

2017 and $68/bbl

in 2018

Vikas continues to

believe that the

market will reach a

more sustainable

balance marked by

seasonally normal

draws in 4Q16,

driven by further

U.S. onshore

declines and

continued demand

growth


18 October 2016 15

Commodities If the first leg of the recovery in commodity prices this year was sentiment-driven, being a

realisation that China was not going to collapse and the Fed was not going to tighten

aggressively, the second has been based more on the fundamentals. For some, especially

the industrial-focused commodities, stronger demand growth has driven the delta. In others,

supply cuts have been overdone. The end result is similar. Prices across a broad range of

commodities have had to rise to invoke a positive supply reaction, the polar opposite of end-

2015. These are topics we explore further in our recent Commodities Compendium.

We are comfortable that, after a year-end dip, the first half of 2017 will see a continuation of

the factors that have assisted commodity markets in recent times, with manufacturing and

Chinese construction outperforming. Our confidence that January 2016 marked the nadir

continues to grow.

But to be clear, fundamentals do not point to any sustained inflationary bottlenecks ex raw

material constraints. The long-term challenges of overcapacity and lower industrial demand

growth than recent norms are still very much in place, while the semi-permanent state of low

interest rates means the ‘reset button’ of producer failures has essentially been removed,

particularly as governments become more and more involved.

Thus, if 2016 was the year of relief for commodity producers, then 2017 provides a window of

opportunity for sustainable strategy to be formed, as the long-term prognosis of weaker

economic growth has not changed. Commodity price inflation over 2016 has eased the

pressure on producer balance sheets, but growth options remain limited in the main. In both

metals and energy, we expect 2017 to mark a pick-up in industry capex and also a return to

cost inflation.

Fig 41 Current price levels are unlikely to yield further supply cuts

Fig 42 The 4Q hard coking coal contract rose over 100% QoQ

Source: Wood Mackenzie, CRU, Macquarie Research, October 2016 Source: TEX Report, Macquarie Research, October 2016

In oil, the agreement among OPEC members to cut production to a range between 32.5 and

33.0 MM BPD certainly stunned the market. The agreement, even if it is ratified at the

November 30th OPEC meeting and tightly executed, only changes our rebalancing base

marginally. It does however cut off the upwardly biased production skews that could have

stretched the rebalancing period out as far as one year beyond our mid-2017 base case. In

our assessment, the 33.0 MM BPD target is achievable and may turn out to be a smart move.

In a recent note we analysed scenarios below which allow the agreement to work. The deal

will have to (1) allow members which have ongoing supply disruptions to grow, (2) allow

weaker members to stay flat, (3) have buy-in from rich members for material production cuts,

and (4) have Russia participate. The risk to OPEC is that the desired price response may be

a needle threading exercise – not enough price action results in a market share giveaway and

too much price action accelerate shale growth, i.e. market share giveaway.

The coal markets remain a key area of focus. Notably, 4Q hard coking coal has settled at

$200/t FOB Australia – up over 100% QoQ. This level, while still slightly below current spot,

comes in above most expectations (our forecast was for $170/t) and marks the highest USD

settlement since 3Q12 and the highest in AUD since 2011.

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Premium hard coking coal settlements

If the first leg of the

recovery in

commodity prices

this year was

sentiment-driven,

being a realisation

that China was not

going to collapse

and the Fed was not

going to tighten

aggressively, the

second has been

based more on the

fundamentals


18 October 2016 16

The catalyst for tightness in the coal market has been the Chinese supply restrictions seen

this year. However, with prices now accelerating higher, these restrictions are being eased.

Prior to the October Golden Week holiday, the NDRC issued a notice that 791 coal mines that

met the “Level 1 safety standard” in 2015 would be allowed to lift their operating rate to their

previous 330-day registered capacity level rather than operate at the restricted 276-day

output level for the remainder of the year. In all, our industry contacts expect up to 900 mines

could lift output in 4Q16. The impact of these coal mines lifting output back to the full 330-day

output rate should be around 60–80mt of additional coal supply in 4Q alone, but this supply is

likely to be biased more to thermal coal than met. Nonetheless, we expect this supply

increment to result in lower coal prices for both thermal and met in the months ahead.

Agricultural commodity markets have underperformed other commodities since the start of

the year, dragged down by continued weakness in grains. Indeed, Macquarie’s proprietary

MacPI agricultural commodity index ended August at 143.1, just below end-December levels,

but with the staple grains component down 13.5% over the same period. While weather risks

may have been building into mid-year, they have since dissipated. As a result, we have now

seen four seasons in a row with close on perfect production, and with crops all but realised,

US ending stocks are set to be once again higher. With this, the pressures on agricultural

supply are increasing. Even in a low-interest-rate environment, farmers are struggling. The

potential for more widespread farmer bankruptcies in the US is rising, and while this will not

cause permanent supply reduction it may lead to a loss of planted area in 2017.

For the remainder of 2016, a combination of a likely Federal Reserve rate hike and the

standard 4Q Northern Hemisphere industrial slowdown does not bode well for commodity

prices. Already in October bullion prices have tumbled as a hike comes into view, while the

noticeable increase in long-term bond yields could mark the start of a structural shift which

may have large repercussions, something we considered here.

While improved Chinese confidence means the 2015 whiplash event and subsequent

demand vacuum is highly unlikely to be repeated, we expect steel and bulk commodities to

come under some pressure, while precious metals will also underperform. In contrast, we

believe US natural gas, nickel, alumina and nitrogen will outperform. Met coal is very much a

special situation, with acute supply constraint likely to be transient.

In the medium to longer term, supply remains a differentiating factor across commodity

markets. Exposure to those commodities for which demand growth will need to reincentivise

latent supply through price inflation is preferable, while exposure to those with true raw

material constraints is a must. On an 18-month view we are bullish on US natural gas, crude

oil, nickel, zinc, gold, silver and chrome from today’s levels.

We are concerned that the longer-term challenges of persistent overcapacity are

underappreciated for potash, alumina, aluminium and steel.

Fig 43 Positions of key mined/extracted commodities in the fundamental cycle – arrow shows 2-year progression


Strong Demand Push Demand destruction Market back in balance Strong supply grow th High stocks Stocks Draw ing Supply constraint

or deficit market Capex accelerating Capex peaking Stocks building Strong supply reaction Limited new supply Capex lagging

Price Acceleration Price peaking Prices falling Severe price decline Prices stablise at low level Prices stable Pricing to encourage supply

Manganese

Lead

Uranium

Thermal Coal

Met Coal

Iron Ore

Aluminium

Zinc

Copper

Nickel

Chrome

Palladium

Gold

Potash

Platinum

Tin

Oil

US Natural Gas

Silver

Bauxite

LNG

Diamonds

Nitrogen

Steel

Alumina

Lithium

Macquarie’s

proprietary MacPI

agricultural

commodity index

ended August at

143.1, just below

end-December

levels, but with the

staple grains

component down

13.5% over the

same period


18 October 2016 17

United States Economic activity appears to once again be expanding at an above potential pace following a

slower pace of growth around the turn of the year. In Fortress America – It’s go time: Growth

drags complete we highlighted that inventories and energy & mining investment were a

substantial headwind to growth, subtracting ~ 1.1 percentage points from GDP over the last

four quarters. These drags now look to have dissipated, a development that should lead to a

firmer underlying trend.

Further supporting this view is that the ISM manufacturing PMI has now shown expansion in

6 of the last 7 months, with particular strength in the forward-looking new orders component.

Additionally, readings on consumer spending have continued to be strong, supported by

persistent job gains and improving wage growth. With a personal savings rate that is 1.8 ppt

above its 2002-7 average, the consumer is well positioned to continue to support the outlook.

September’s employment report further solidified that the job market remains on firm footing.

Over the past 3 months job gains have averaged ~190k, a healthy rate that should dispel the

notion that the economy is slowing. However, employment gains are now showing signs of

moderating amidst a labour market that is close to full employment. Thus far in 2016 job gains

have averaged ~180k/month which is noticeably slower than the monthly pace of ~230k seen

in 2015.

We attribute the slowdown in job growth to reduced labour market slack as opposed to

decreased employment demand. Jobless claims remain at historically low levels while job

openings are at an all-time high, suggesting worker demand remains healthy. As unabsorbed

worker capacity increasingly diminishes we expect jobs gains to further slow to ~150k/month

through end-17, a pace nearly double what is required to further reduce slack. This should

continue to put upward pressure on wages, which have already shown clear signs of moving

higher particularly in the construction industry (Fig 44).

Most importantly, the outlook for residential investment remains strong despite a softer

reading in 2Q. It is low and rising as a share of GDP, a dynamic that insulates the economy

from any potential downturn. We believe that this area can rise at a double-digit pace for the

next 3-4 years, a thesis we outlined in Accelerating Housing, Macro Impact.

On the policy front, we believe that the Federal Reserve is poised to continue a rate hike

cycle that should prove gradual, cautious, and supportive of risk-taking. The pace of hikes is

likely to be, on average, 50bps per year until the upper end of the fed funds rate range

reaches our forecasted terminal level of 2%. We foresee this occurring in mid-2019. A key

input into our thesis is our belief that the neutral policy rate in the US is likely to remain at

present levels rather than increase over time. This will lead to a slower pace of rate hikes for

the duration of the cycle than the FOMC currently projects.

Fig 44 Construction wages are showing particular strength

Source: BLS, Macquarie Research, October 2016

0%

1%

2%

3%

4%

5%

6%

1995 1997 1999 2001 2003 2005 2007 2009 2011 2013 2015

YoY % change

YoY % change (3moMA)

Average hourly earnings of prod & nonsupervisory employees: construction

After subtracting ~

1.1 percentage

points from growth

over the past four

quarters, the drag

from inventories

and energy &

mining investment

looks complete

We expect

employment gains

to average

~150k/month

through end-17 as

the economy nears

full employment

The Fed is likely to

raise rates gradually

and to a lower level

than in previous

expansions


18 October 2016 18

China Recovery continued in September: China will release September and 3Q data on October

19. Thanks to the property market and price reflation, the economy continues to improve. For

September, industrial production (IP) growth could be stable at around 6.3% YoY. We expect

real GDP to grow 6.7% YoY in 3Q16, the same as in the previous two quarters. But nominal

GDP growth, which improved to 7.2% YoY in 1H16 from 6.4% in 2015, is set to pick up

further in 2H16 (see September data preview: Recovery on reflation and real estate).

PMIs suggest stable growth in Sep: The NBS manufacturing PMI came in flat at 50.4 in

Sep, which is the highest level since Nov 2014. Meanwhile, the Caixin PMI edged up slightly

to 50.1 from 50.0 in Aug. At this moment, the economy is supported by the property market

and price reflation, which has led to a rebound in corporate earnings. Industrial profits jumped

20% yoy in Aug, the fastest growth in three years. As such, the PBoC would postpone cutting

the interest rate. Rather, the focus has shifted to managing the financial risks in the bond and

property markets

A temporary triumph on capital outflows: The detailed 2Q16 Balance of Payment data

released last month gives us more information on the current state of capital outflows. It

shows that China’s FX reserves dropped by US$35bn in 2Q16, which is much improved from

the US$100+bn decline in each of the prior three quarters. Meanwhile, hot money outflows

started to stall in 2Q16 (Fig 45). It’s in line with our previous analysis of capital flows based on

the 2015 BoP data (Dissecting China’s capital outflows in 2015 ). Essentially, because hot

money has been largely exhausted after two years of outflows, also capital controls are more

effective for domestic money than foreign money, China’s capital outflows pressure would be

much eased in 2016. Therefore, the market fears on capital outflows earlier this year are

overdone. That said, for the PBoC, it’s just a triumph of a battle, not a war, because the

slowdown of capital outflows has been achieved with tightened capital controls, which run

against China’s long-term goal of the RMB internationalization and Capital Account

openness.

The next battle for the PBoC: Last month, we published a report on the long-term outlook

for the RMB (How to think about the RMB?). Against the consensus, which expects the RMB

to have a trend depreciation, we forecast the USD/CNY to end 2017 at 6.4 and appreciate

more in the long run. The report has received a lot of push-back, just like many of our reports

related to the RMB. For instance, on the same day of the RMB devaluation last August, we

forecasted that the depreciation would be less than 5% from then on to the year-end (link). In

our 2016 outlook (link), we forecasted the USD/CNY to end 2016 at 6.6. Earlier this year, we

forecasted that capital outflows are easily manageable as hot money has largely gone (link).

Fig 45 Carry trade unwinding reversed in 2Q16

Source: CEIC, Macquarie Research, October 2016

-150

-100

-50

0

50

100

150

Mar-

09

Jun

-09

Sep

-09

Dec-0

9

Mar-

10

Jun

-10

Sep

-10

Dec-1

0

Mar-

11

Jun

-11

Sep

-11

Dec-1

1

Mar-

12

Jun

-12

Sep

-12

Dec-1

2

Mar-

13

Jun

-13

Sep

-13

Dec-1

3

Mar-

14

Jun

-14

Sep

-14

Dec-1

4

Mar-

15

Jun

-15

Sep

-15

Dec-1

5

Mar-

16

Jun

-16

Capital flows due to carry tradeUSD bn

Outflows

Inflows (1Q09-2Q14)US$742bn

Outflows (3Q14-1Q16)US$452bn

Recovery continued

in Sep

Capital outflows

have slowed

We expect RMB to

appreciate in 2017


18 October 2016 19

Admittedly, the dominant expectation is a trend depreciation for the RMB. With that, the RMB

internationalization has backtracked as the RMB deposits in HK have already dropped to

RMB670bn from the peak of RMB1tn in Dec 2014. For the Chinese government, which has

spent tons of effort on things like the SDR and AIIB, it has so much to lose from the

termination of RMB internationalization, which is also important to One-Belt-One-Road.

Therefore, the next target for the PBoC has to be the prevalent depreciation expectations.

How to win the battle with depreciation expectation? Over the past year, the RMB has

had a slow depreciation and limited volatility. Since most people are trend-followers, no

wonder the depreciation expectation is so prevalent at this moment. To win the battle with

depreciation expectation, the PBoC needs a new strategy, which is to guide the RMB

stronger while increasing the volatility. Under the new strategy, the market knows the long-

term direction of the RMB but not the short-term trading band. Therefore, when the RMB falls

to some extent, speculators would expect it to reverse and start buying. By doing so, the

PBoC essentially changes the one-way expectation by winning allies among market

participants. Over time, the PBoC could gradually increase the band and ultimately let the

RMB be determined by market forces. To be sure, at the beginning of the year when lots of

people forecasted a one-off depreciation, we argued that the best strategy for the PBoC in

2016 is a stable RMB (link), because at that time the credibility for the PBoC was not enough

and capital outflow pressure was high. It turns out that a stable RMB is also the actual

strategy adopted by the PBoC. However, the situation has changed as capital flows have

eased. So it’s time to move on.

Property prices and exchange rate: One push-back to our positive RMB view is that the

PBoC has to depreciate the currency to keep property prices near the current level. We agree

that rising home prices could cause more Chinese residents to sell their property in China and

buy foreign assets. However, there are other and probably more important channels to

influence the RMB, such as trade balances and economic growth. That’s why China’s home

prices have increased rapidly over the past 15 years but the RMB has also appreciated.

Moreover, while in this round of property up-cycle, home prices do increase quickly in certain

cities, but the rise is not a broad-based one (Fig 46). Over the past 12 months, 48 out of the

70 biggest cities had home price growth of less than 5%. As such, if the property market

could cool down in the next six months as we are expecting, the negative impact on the RMB

will be limited.

More cities introducing property curbs: Over the past couple of weeks, more than a dozen

cities tightened their property measures. It’s not surprising at all, as China had four such

property short-cycles in the past decade. This is just the fifth one. According to past

experience, the sector could cool down in 1H17 and the rate-cutting cycle would resume

around mid-2017 to support the economy. But for 4Q16, the property sector should remain

supportive, as developers are quickening the pace of construction after the strong sales in the

past few months.

Fig 46 Home prices increase mainly in top cities

Source: CEIC, Macquarie Research, October 2016

100

110

120

130

140

150

160

170

180

190

Feb-1

1

Aug

-11

Feb-1

2

Aug

-12

Feb-1

3

Aug

-13

Feb-1

4

Aug

-14

Feb-1

5

Aug

-15

Feb-1

6

Aug

-16

Tier 1 Tier 2 Tier 3

2010=100

More volatility for

RMB is needed

Limited impact of

property market on

RMB

Property sector to

cool down in 2017


18 October 2016 20

Eurozone The Euro-zone economy continues its recent trend of steady but slow growth. We see some

darker clouds on the horizon however from higher oil prices and the collapse in Sterling.

Economic data in the last month has been mixed. The PMI surveys remain gloomy - in

September the Eurozone composite was just 52.6, its lowest since January 2015, and

averaged over the quarter pointing to slower GDP than 2Q’s 0.3%. But the PMIs look a little

strange, with a very weak Germany services sector the main drag. In contrast the European

Commission sentiment indicator in September saw its highest since January 2016.

Both surveys agree the industrial sector has improved. The manufacturing PMI rose to 52.6 in

September, its best in three months. Industrial output gained 1.6% MoM, and over the quarter

as whole - assuming a flat September - will eke out a modest 0.4% QoQ growth. In the past

this has been consistent with our forecast for GDP of around 0.3% QoQ.

Fig 47 Eurozone IP growth, QoQ (assuming Sep flat) Fig 48 Oil to take toll on buoyant retail sector, % YoY

Source: Eurostat, Macquarie Research, October 2016 Source: Macrobond, Macquarie Research, October 2016

Two new concerns on the growth front are coming in to view. The first is the higher oil price

and the impact it will have on consumer incomes. From being down 50% YoY in the middle of

2015, oil is now higher YoY, and if the current euro price is maintained will be up 30% YoY in

1Q. We think this is likely to see retail sales growth slow, something that we have already

seen initial signs of (Fig.48).

Second, Brexit. The recession in the UK many forecast hasn’t materialised, and as such our

expectation of only a modest impact on the Eurozone economic is playing out. But a new

problem is the steep devaluation of Sterling against the euro. There is a good correlation

between the exchange rate and Eurozone exports to the UK, and if the current devaluation is

sustained history suggests imports might fall 15% - €3bn a month. This is not a huge amount

in the context of a €10 trillion economy. But it is a fair amount in the context of a 1.5% growth

rate. We think it means Eurozone GDP will be a below consensus 1.4% in 2017, and the euro

will weaken against Sterling.

This brings us onto the ECB, and the thorny issue of its QE programme expiring in March.

Ahead of its October and - more importantly - December meetings the usual series of press

leaks about policy have started. Some excitement came from a press report that the bank

was considering ‘tapering’, but a closer reading suggests policymakers were only saying

when the time comes to end QE they would ‘taper’, rather than do a hard stop. We think that

time is a long way off (see “Timing the exit from unconventional monetary policies: the ECB &

BOJ) and December is likely to see the ECB announce an extension plus changes to its rules

on eligibility. It remains debatable whether the ECB should have started QE; we see no

reason why they should now stop.

Survey data mixed,

IP improving

Oil and Sterling

present new

headwinds

ECB will not taper


18 October 2016 21

United Kingdom Sterling is becoming an issue. The UK currency suffered a torrid time in the wake of a speech

by the UK Prime Minister, Theresa May, on 2 October putting some flesh on how the UK

government plans to exit from the European Union (EU). By 13 October it had fallen 4%

against the euro and 6% against the dollar, against the latter hitting repeated 31-yr lows.

The Chancellor (finance minister) Phillip Hammond attributed the weakness to financial

markets only now realising the UK really was going to leave the EU. But May’s

announcement that the UK would by March 2017 file Article 50 to start the two-year process

of leaving was not that remarkable (if at the earlier end of consensus).

We see two more plausible reasons for sterling’s slump. First, the extent of the powers the

government wants to take back from the EU - basically all of them (May cited the need to

control immigration, prevent the ECJ having a sway in the UK and even the right to ‘label our

food’) means Single Market membership is a long shot, and being outside will hit trade.

Second, the government has radical plans for what it wants to do with that power, with the PM

in a second speech promised a ‘revolution’, outlining a more interventionist economic policy

with politics such as worker board representation. For good measure she added a critique of

the side-effects of the Bank of England’s cheap money policy. If she is serious then a weaker

currency is likely to be a feature, not a fault.

But how serious is she? The remarks came at a party conference, not the most reliable guide,

and a number of clarifications have since been made, suggesting there is still much left

undecided about both Brexit and future economic policy. Sterling is probably due a bounce -

something which should be aided by a record short-position on the CME futures market.

Fig 49 Sterling v USD/EUR/BoE Index, 1995 = 100

Fig 50 UK core goods inflation (lagged 12m) v sterling, % YoY

Source: Macrobond, Markit, Macquarie Research, September 2016 Source: ONS, Macquarie Research, September 2016

That said, FX markets are not so prone to be being ‘too short’ - after all natural longs and

shorts are so large - and there seems little reason to expect a quick strengthening while so

much uncertainty prevails. Neither the government nor Bank of England officials seem too

concerned. The question that now arises is how the sterling devaluation will start to feed into

the real economy.

The bad news will come from inflation, and down the line consumer spending. The headline

rate was set to rise sharply on the back of the higher oil price, and now imported food, but

even the core rate will be affected – Fig.50 shows a good correlation between the change in

Sterling on a YoY basis and that index lagged 12 months. Market inflation measures are

rising sharply - the 5yr implied rate reached 3%, its highest in 15months.

The good news should be a better economy. Oxford Economics’ global model suggests a 5%

fall in Sterling adds about 0.1% QoQ to GDP growth. Of course if FX markets are selling

Sterling on fears of lower growth this might be offset by other factors, but very short-term we

raise our GDP forecasts modestly.

Trade and the

economy threaten

Sterling

Inflation and growth

to be boosted…at

least in the

short-term


18 October 2016 22

Japan Our real GDP growth forecasts remain anaemic, with modest contributions expected from

consumption and net exports.

Fig 51 Japan: key macroeconomic forecasts

CY11 CY12 CY13 CY14 CY15 CY16E CY17E CY18E CY19E

GDP (YoY, %) -0.5 1.7 1.6 -0.1 0.6 0.4 0.6 0.7 0.8 CPI (YoY, %) -0.3 0.0 0.4 2.7 0.8 -0.1 0.3 0.5 0.9 (**) Overnight call rate (*) 0.1 0.1 0.0 0.1 0.0 0.0 0.0 0.0 0.0 10-year JGB (*) 0.99 0.79 0.74 0.3 0.3 -0.1 -0.1 0.2 0.3 ¥/$ (*) 77.6 86.3 105.4 119.8 120.4 105 101 97 95 Note: CPI is the headline CPI ex fresh foods. (*): per period end, Macquarie forecasts. (**) The consumption tax rate increase to 10% from 8% is now scheduled for October 2019

Source: Bloomberg, Macquarie Research, September 2016

The impact of financial repression on savings is leading households to be subdued

consumers. For more, please see the 5 October 2016 PEC’s Japan strategy: Accentuated

sector rotation.

One developing positive is the return to export growth to the US and the EU, Fig 52.

Fig 52 Japan export to US and EU

Source: BOJ, Macquarie Research, September 2016

Whilst we have been forecasting a trend appreciation in the Yen, the move has been much

stronger than expected. The Yen has been very low/cheap on a REER, and the current

account surplus has improved from 0.5% in 2014 to an estimated 3.3% in 2015 mainly due to

lower energy prices, and 3.5–4.0% is possible in 2016.

As such, the BOJ’s campaign against deflation and entrenched deflationary expectations has

entered a new phase, with the currency now a headwind to the policy goal. Even our modest

inflation forecasts above could prove to be optimistic.

We believe the BOJ is now essentially subordinate to fiscal reconstruction, working to

minimize the government’s interest expense through a policy of financial repression. The new

arrangement to target the 10-year JGB yield “around zero” makes this more explicit. Please

see the 26 July 2016 Macq-ro insights: Financial repression for decades and the 12 October

2016 PEC’s Japan strategy: the cycle through 2017. The BOJ’s FY3/18 of 1.3% assumes a

big boost from the government’s headline ¥28.1tr supplementary budget, just announced. We

are much more cautious.

PM Abe has established a panel to make labour market reform proposals and instructed them

to prioritize “equal pay for equal work” and the reduction in long work hours. There have been

trial balloons suggesting a 10% increase in hourly rates for part-time workers, i.e. the

government becoming directly involved in wage setting.

.

-30

-15

0

15

30

45

60(%, YoY) US EU

Our real GDP

growth forecasts

remain anaemic

One developing

positive is the return

to export growth to

the US and the EU

PM Abe has

established a panel

to make labour

market reform

proposals


18 October 2016 23

Canada In 2Q16 Canada saw growth contract at the fastest pace since 2009. While the majority of

this weakness can be attributed to the wildfire in Fort McMurray, even after excluding this

impact underlying activity slowed markedly. However, looking ahead, we expect the domestic

economy to continue to improve in 2H as a result of: i) a pickup in US activity, ii) federal fiscal

stimulus, iii) a snapback in oil production and exports, iv) a lessening drag from energy

investment, and v) strong monthly GDP numbers for June and July.

Despite our expectation for a near-term rebound, beyond this growth should be subdued.

Significant structural headwinds are likely to weigh on the outlook including i) elevated levels

of household debt, ii) stretched residential investment, iii) unfavourable demographics, and

iv) a lack of competiveness.

Due to these headwinds, we expect the BoC overnight rate will rise to just 1.0% in the current

expansion with the next hike not coming until 2Q19. This forecast reflects increased

confidence in the theme of economic divergence in North America as tailwinds to growth in

the US (consumer spending and residential investment) are substantial headwinds in

Canada. As a result, we remain below consensus in our currency forecast. We anticipate that

a widening in the two year sovereign yield differential between Canada and the US will lead to

a $0.74 CADUSD ($1.36 USDCAD) at the end-16 and $0.69 ($1.45 USDCAD) at end-17.

Although signs that inflation is softening as well as the federal government’s recently

announced housing measures argue in favour of additional monetary accommodation, we

think the BoC will remain on hold. Low estimates of potential together with high debt levels

suggest there is a high threshold to cut rates. Consequently, we expect that the stimulus

baton will increasingly rest with the fiscal authorities, rather than their monetary counterparts.

While federal government stimulus will provide a boost to activity, the impact will be modest.

Federal spending represents just 30% of total government expenditures and will be partially

offset by continued weak spending growth from municipal and provincial governments. We

anticipate another federal stimulus announcement will occur in 2017/18.

Hopes for a reorientation in the economy towards non-energy exports have been slow to

transpire. Canada’s manufacturing sector continues to be challenged from a prolonged period

of weak investment and growing competition from Mexico (Fig 53). These factors will limit the

potential benefit to Canada’s outlook despite improvements in the US.

Fig 53 Canada has continued to under-invest in manufacturing

Source: BEA, Statistics Canada, Macquarie Research, October 2016

0.7

1.1

1.5

1.9

2.3

1991 1993 1995 1997 1999 2001 2003 2005 2007 2009 2011 2013 2015

Manufacturing investment (nominal local$) - indexed to 1991

US

CAN

1991 = 1.00

Growth should

rebound in 2H, but

remain subdued in

the years ahead

Canada’s

manufacturing

sector continues to

be challenged

We expect the BoC

overnight rate will

peak at just 1.0% in

the current

expansion

The stimulus baton

will increasingly

rest with the fiscal

authorities


18 October 2016 24

Australia With few pieces of ‘big news’ on the Australian macro front our key views remain unchanged.

Australia’s new central bank Governor, Philip Lowe, assumed the reins at the RBA with little

perceptible change in tone (see: Aussie Macro Moment – RBA: New message, or

messenger). The RBA’s communications became a little more nuanced, but the messages

remained broadly unchanged.

Improved commodity prices and a somewhat more positive tone from the RBA, particularly

around the terms of trade bottoming, have seen market expectations of further easing

reduced. This has, arguably, supported the A$ over recent weeks in the face of a firmer US$.

The RBA’s description of the Australian dollar has shifted slightly from ‘is helping’ the

economy’s transition, to ‘has been’.

New nuance around the housing market was delivered in the RBA’s semi-annual Financial

Stability Review. Trends in Australia’s house prices are dominated by Sydney and Melbourne.

And as illustrated by the chart below established house prices across the rest of Australia

have remained well contained. The risks now predominantly lie in how well the oncoming

surge of supply of new medium density housing in Brisbane and Melbourne are absorbed.

On the commodities front, as we highlighted last month, a sustainment of current commodity

prices is likely to lead to an improvement in the outlook for mining investment. The latest

capex expectations survey contained an upgrade to mining investment expectations.

However, this was for FY17, the final year of decline following the mining capex boom.

We estimate that, based on the improvement in actual and projected commodity prices, a

new mining capex cycle could begin from FY18. The pace and extent of investment upswing

will be determined by a number of factors, particularly the commodity price trajectory.

However, the weakest of the last few capex cycles saw a near doubling of investment

expenditure in the 5 years from the low point of spending.

Whilst FY18 may appear to be a better year for mining investment, any upswing in mining

investment is unlikely to become labour intensive until the latter years of the cycle, if major

greenfield projects are brought forward. The economy still needs to negotiate FY17, which, in

our view, is likely to see continued accumulation of slack, disinflation, and further RBA cash

rate cuts. Rate cuts in February and May 2017 remain our base case.

Fig 54 House prices outside of Sydney and Melbourne have remained, in aggregate, well contained over recent years

Source: ABS, Macquarie Research, October 2016

95

105

115

125

135

145

95

105

115

125

135

145

Sep-13 Mar-14 Sep-14 Mar-15 Sep-15 Mar-16

Sydney

Melbourne

Rest of Australia

Index Index

Australia: House Prices(Index, September 2013 = 100)

2.2% CAGR

8.0% CAGR

12.3% CAGR

The RBA’s

description of the

A$ has morphed

from ‘is helping’ to

‘has been’ for the

economy


18 October 2016 25

New Zealand There is little change in our outlook for the New Zealand economy. Incoming data over the

month has revealed a continuation of our major themes. The NZ$ remains too high, dairy

prices have softened somewhat. Inflation expectations remain contained, but initial signs from

the latest tightening of macro prudential policy suggest some potential easing of concerns.

New Zealand’s growth pulse remains intact, but there are continued signs that growth

remains disinflationary. The latest NZIER Quarterly Survey of Business Opinion suggests that

confidence and activity remain high. But inflation, indicated by selling prices, remains weak.

Net migration inflows also remain elevated, with the annual total returning to a record high.

Financial stability concerns could still ultimately provide a handbrake to our base case for

RBNZ rate cuts. Our monitoring of weekly housing finance approvals – which the RBNZ will

shortly cease publishing – suggests that the most recent tightening may be having a more

enduring impact than previous (October 2013 and November 2015) efforts. Fewer, smaller,

loans are being taken out.

Initial signs of progress on the financial stability front should provide the RBNZ with more

comfort around cutting rates, if needed. That need will be based on two factors, in our view.

Inflation expectations, and the currency.

The latest quarterly reading on inflation expectations showed that the critical 2yr-ahead

expectations held steady. Inflation outcomes have undershot the RBNZ’s 1-3% target band

for some time, and we think they will disappoint again in the upcoming 3Q16 CPI outcome.

Where the RBNZ continues to face a challenge is on the currency. The NZ$ remains, on a

trade weighted basis, above the RBNZ’s currency ‘risk case’ published in the August

Monetary Policy Statement. That’s despite a softer outcome in the most recent dairy auction.

We remain of the view that the RBNZ is likely to cut rates further, with the next move at the

November 10 OCR review. This will be one of the first central bank moves following the

outcome of the US Presidential election.

Fig 55 Weekly housing finance data demonstrates the – initial – impacts on borrowing activity from the latest tightening of macro prudential policy.

Source: RBNZ, Macquarie Research, October 2016

-10

-5

0

5

10

15

20

25

30

35

-10

-5

0

5

10

15

20

25

30

35

01-Jun-15 01-Dec-15 01-Jun-16

New Zealand: Housing loan approvals(experimental weekly estimates, 3m YoY%change)% %

Value of loans approved

Number ofloansapproved

Signs that macro

prudential policy

tightening may be

having an impact

should clear the way

for the RBNZ to

lower the OCR

further


18 October 2016 26

South Africa We are not making any changes to our South African economic forecasts this month, but we

highlight key forecast risks. Our baseline view is for a gradual economic growth recovery,

supported by a smaller drag from agricultural and mining commodities, marginal fiscal

tightening (as per the latest official forecasts) and steady monetary policy. This scenario

assumes that the rand remains relatively steady around R14-R14.50/$ in nominal terms (thus

appreciating slightly in real terms) although political noise and global newsflow and changes

in risk appetite will likely continue to underpin significant volatility. This assumes the rand is

pricing in a single-notch downgrade by S&P in December (only).

In the absence of a political shock, similar to the “9/12” Finance Minister reshuffling, we

believe that the currency risks are biased towards the stronger side. This increases the

possibility of inflation that retreats sufficiently to compel the SARB to cut interest rates. We

believe that inflation forecasts persistently below 5% would open the door for monetary

easing. We recently illustrated the significant boost to consumers’ spending power in this

scenario (see Economic insights - Consumer cross-currents unpacked). We attach a

relatively high probability to this scenario.

Unfortunately there is still a non-negligible risk of a political shock, although the probability

seems to have eased since “9/12” given inter alia the growing strength of open civil society.

Slow traction with growth reform adds to the longer-term fiscal and credit rating risks, and

means that growth will not resolve the elevated poverty and unemployment problems. We do

not at this stage believe that the recent summonsing of the Finance Minister to appear in

court on charge of fraud will lead to his removal, but the situation remains very fluid and partly

dependent on civil society’s responses to political events.

The market’s focus will increasing shift to the Medium-Term Budget Policy Statement on 26

October. We expect government to keep the cornerstone of its fiscal consolidation plan, the

expenditure ceiling, to remain intact, despite additional spending pressures including to fund

the freezing of poor students’ university fees. Although the revenue risks remain biased

downwards given sluggish economic growth, the tax revenue performance has been

improving in recent months and the outperformance of non-tax revenues (including forex

gains on historical foreign exchange purchases) is at this stage sufficient to offset the

potential tax shortfall. We therefore do not expect the fiscal announcements and choices to

support credit rating downgrades in the upcoming rating reviews; instead this will largely

depend on whether the rating agencies will regard the incremental progress to improve the

growth framework as sufficient for now.

Fig 56 Consumer real income growth after tax and interest rates (2017, baseline view)

Fig 57 Consumer real income growth after tax and interest rates (2017, with lower inflation and interest rates)

Source: Eighty20, Stats SA, Treasury, SARB, Macquarie Research, October 2016

Source: Eighty20, Stats SA, Treasury, SARB, Macquarie Research, October 2016

0.0%

0.5%

1.0%

1.5%

2.0%

2.5%

% YoY

Real income growth Real after-tax Real after tax and interest

0.0%

0.5%

1.0%

1.5%

2.0%

2.5%

3.0%

3.5%

% YoY

Real income growth Real after-tax Real after tax and interest

Key forecast risks


18 October 2016 27

India US$80bn of dollar flows and counting: India has the second-largest overseas population

after China, and it is the largest recipient of remittances (in value terms) in the world. Inflows

from overseas Indians (including private transfers and NRI deposits) stood at US$79bn in

FY16. These flows (a) help boost household income and, hence, support private

consumption, (b) play a key role in bringing stability to India’s CAD, and (c) act as a source of

foreign exchange reserves to help bridge the funding gap in the event of global risk aversion

and restoring external stability. Going forward, we believe policymakers should try to leverage

these flows to fund infrastructure and other development projects to have a multiplier effect

on overall growth.

Rich overseas Indians have an annual GDP >US$750bn: An estimated ~27mn Indians

resided overseas as of April 2016, with an annual GDP of ~US$750bn, on our estimates,

implying an average per capita income of ~US$29,000. This is ~18x the per capita income of

India, with an annual GDP of US$2tn and a 1.3bn population. We believe overseas Indians’

wealth, including gold, property and other assets, to be much higher, at above US$1.5tn.

Private transfers critical for stabilising India’s CAD: India has been the top recipient of

migrant remittance inflows (private transfers) in 16 out of last 20 years and for the past 8

years consecutively. The migrant remittance (net) inflows to India increased nearly 2.8 times

in the last decade to US$67bn (3% of GDP) in CY15 from US$24bn in CY05. The private

transfers (including remittances) have been largely stable, in the 3–4% range of GDP in the

past 10 years, and helped offset India’s wide trade deficit to a large extent. Indeed, India’s

FY16 current account deficit (CAD) excluding private transfers was a high US$85bn (4.1% of

GDP) vs US$22bn (1.1% of GDP) including private transfers.

Slowing private transfers, not quite a worry: For the first time since FY05, India saw a

decline in private transfers, by 5% YoY in FY16. This weakness seems to be driven by (a)

slowing global economic growth and (b) a weakened economic environment in the GCC

countries due to a sharp fall in global crude oil prices. We believe the narrowing of India’s

CAD and rising FDI flows imply that slowing remittance flows would not result in exacerbating

the macro stability risks. Indeed, we do not expect the trend of falling remittances to be

sustained beyond a few quarters, because a) our global commodities team expects the Brent

crude oil price to pick up to US$61/bbl in 2017 and US$68/bbl in 2018 and b) improving

growth and employment prospects in the US economy will likely support remittances.

Inflows under NRI deposits are interest rate-sensitive: The outstanding NRI deposits

have increased 2.5 times to US$127bn as of March 2016 (vs US$52bn five years ago). Unlike

remittances, inflows under NRI deposits are interest rate-sensitive and add to India’s external

vulnerability. Hence, policymakers should try to use them judiciously to meet the capital-flow

requirement in the event of a crisis (like measures to attract dollar deposits in 2013 to deal

with taper tantrums) or to fund infrastructure development projects.

Fig 58 Flows from overseas Indians

Fig 59 Current account balance: With and without support of private transfers

Source: CEIC, Macquarie Research, October 2016 Source: CEIC, Macquarie Research, October 2016

-10

10

30

50

70

90

110

FY00 FY03 FY06 FY09 FY12 FY15

Private transfers (including remittances) Non Resident Deposit

US$ bn

-9%

-7%

-5%

-3%

-1%

1%

3%

FY

00

FY

01

FY

02

FY

03

FY

04

FY

05

FY

06

FY

07

FY

08

FY

09

FY

10

FY

11

FY

12

FY

13

FY

14

FY

15

FY

16

Current Account

Current Account excluding Private Transfers

as % of GDP

India has the

second-largest

overseas population

after China, and it is

the largest recipient

of remittances (in

value terms) in the

world


18 October 2016 28

ASEAN Growth has been fading across ASEAN since 2012, Fig 60, as the region looks for a new

growth engine, and unwinds the credit excesses of the past. Fig 2661 shows the ratio of

private non-financial credit to GDP and its growth over the last five years.

Whilst the ratio to GDP generally increases with economic development and financial

deepening, relative to other EM economies shown below, some ASEAN countries appear

elevated, implying a need to go through a period of private debt adjustment.

Fig 60 Real GDP growth for ASEAN-5 (weighted by GDP in current US$), 2000 to 2020. 2016-20 are Macquarie forecasts

Note: Please see Fig 169 and Fig 170 for the underlying data. The horizontal dashed line above is 5% pa real GDP growth. The ADB estimates 4.9% pa over 2011-20 and 4.2% pa over 2021-30, whilst the Economic Complexity Project forecasts 4.3% pa. 5% pa is therefore a potential future “lid”.

Source: IMF, World Bank, Macquarie Research, October 2016

Fig 61 Private non-financial credit, level and growth, for leading EM economies

Note: The BIS does not have data for the Philippines


A subdued external environment and restrained credit expansion is suggestive of real GDP

growth modestly beneath potential, which we estimate at around 5.0% pa for the ASEAN-5,

Fig.60, and the room for monetary policy to have an easing bias.

However, in advance of an expected December 25bp increase in US policy interest rates, we

judge most ASEAN central banks to be on hold for now, Fig.62.

For EM economies generally, ongoing credit cycle and real property price adjustments temper

the industrial cyclical relief, as does expected weak inward FDI. Please see the 8 April 2016

What’s next for EM economies and page 51 in this report for more.

0

2

4

6

8

10

2000 2002 2004 2006 2008 2010 2012 2014 2016 2018 2020

(%)

ASEAN

Brazil

Mexico

Russia

Turkey

India

China

Indonesia

Malaysia

Singapore

Thailand

0

10

20

30

40

50

60

0 50 100 150 200 250

2015 3Q vs 2010 3Q

Private debt as % of GDP

Change in five years (%)

A subdued external

environment and

restrained credit

expansion is

suggestive of real

GDP growth

modestly beneath

potential, which we

estimate at around

5.0% pa for the

ASEAN-5...

...and the room for

monetary policy to

have an easing bias


18 October 2016 29

Fig 62 Monetary policy, key interest rates, in basis points (bp)

End 2014 End 2015 End 2Q 2016 Outlook

Singapore 50 125 125 Stable Malaysia 325 325 325 25bp cut 13 July, more likely Thailand 200 150 150 Stable Indonesia 775 750 650 Another 25bp cut possible Philippines 400 400 300 (*) Stable

Korea 200 125 150 Another 25bp made on 9 June Taiwan 188 163 150 Another 12.5bp cut possible

Note: Singapore: 3-month interbank rate, Malaysia: overnight policy rate, Thailand: 14-day repo rate, Indonesia: 1-month SEBI rate, Philippines: reverse repo rate, Korea: overnight call rate, Taiwan: official discount rate. Please note that the exchange rate, not interest rates, is the main policy in Singapore. (*) The new institutional arrangements mean that the old 400bp policy target rate is now equivalent to a 300bp rate.


A particular challenge for ASEAN is their role in the East Asian export supply chain. Our

house view has a gradual fade in Chinese growth as the old investment/credit growth model

persists, but generates diminishing returns. China began a serious import substitution phase

in 2015 and this will continue for as long as the old growth model persists, and SOEs invest

with an essentially zero cost of capital.

Fig 63 Import volumes and import prices/unit values, YoY, %


As shown above, in 2015 on CPB data Asia emerging economies had -1.0% import volume

growth, whilst prices/unit values fell -12.2%. Please note that the import volume shrinkage

was an Asia emerging economies’ experience, not a worldwide event.

Service sector development, more broadly than just tourism, is one possible region-wide

growth driver. Please see the 9 May 2016 Macq-ro insights: Global services, a new

economic order.

We believe the next global growth engine is innovation clusters, or “brain-belts” as described

in the book by Antoine van Agtmael and Fred Bakker: The Smartest Places on Earth (2016).

Please see page 34. These tend to be leading-university centred and more difficult for

ASEAN in general to develop.

-20

-15

-10

-5

0

5

10

15(%, YoY)

World import volumesAsia emerging economies import volumesWorld import prices/unit valuesAsia emerging economies import prices/unit values

The need for a new

growth engine


18 October 2016 30

Macq-ro insights Short-term business-cycle judgements are more likely to succeed with a deep awareness of

more medium- and longer-term issues. In global macroeconomics there are a considerable

number of the latter.

The following pages provide “executive summaries” on:

Fig 64 Medium- and longer-term global macro issues

1) Global policy coordination 11) Chinese corporate debt

2) Global services 12) Oil & sovereign defaults

3) Innovation clusters/”brainbelts” 13) What’s next for EM economies?

4) The private sector’s appetite for credit 14) Global private investment indicators

5) Global trade in goods 15) Local factors determine core inflation

6) Global trade in services 16) Income shares: from labour to capital

7) Fading fiscal policy tailwinds 17) The corporate savings “glut”

8) Financial repression for decades 18) Global income distribution

9) Housing, globally, a good news story 19) Demographic Tectonics

10) Global liquidity & EM credit cycles 20) The long grinding cycle continues


Our Macq-ro insights series have been tackling these with an emphasis on quality data,

presented in numerous tables and charts.

Fig 65 Macq-ro insights 2016 publications

Date Title Topic Pages Data banks

12 Jan. Diminishing “Japanization” fears The revival of private sector credit demand in advanced economies

34 BIS domestic credit growth

21 Jan. The corporate savings ”glut” & cross-border M&A

Company cash-flow choices 16 Cross-border M&A (Factset, RECOF, Reuters, Datastream)

25 Jan. Global liquidity The credit down-cycle in emerging market economies 19 BIS cross-border debt

05 Feb. Global liquidity #2, ASEAN Contrasting today with the Asian Financial Crisis 24 ASEAN Economic Community

11 Feb. Oil & sovereign defaults A decade-long wave of defaults in the 1980s, then and now

19 CRAG sovereign defaults

26 Feb. The G-20 in Shanghai Policy coordination challenges 3

08 Apr What’s next for EM economies? An extended period of subdued growth 45 UNCTAD FDI, Conference Board productivity statistics

14 Apr. Global policy coordination dreams From fiscal stimulus to boosting consumption 24 BIS real residential property prices

9 May Global services: a new economic order The rise of services, now the key driver of global growth 34 ILO, UN: Labour/Services

20 May Income shares: from labour to capital A 5% shift over the last 35 years 21

28 June Brexit: stay calm and carry on Economic impacts: the UK, eurozone and beyond 8

18 July Fiscal winds of change Global fiscal policy tailwinds fade significantly from 2017 30 IMF, World Bank fiscal sustainability databases

22 July Residential investment, globally A good news story: around 4% of global GDP and will grow between 3.5% and 4.0% pa through 2020

58 Residential investment/GDP ratios, BIS price indices

26 July Financial Repression for decades A conscious policy choice to minimise public debt funding costs that began in Japan and is spreading to Europe

21 Global real interest rates, inflation-linked bonds

11 Aug. The Great Divergence: Inflation and Policy

Core inflation is determined by local factors, such that policy divergence is expected to persist

28 Model-based monetary policy rules

26-Aug Timing the exit from unconventional monetary policies: The ECB & BOJ

Using the US experience as a roadmap, but the analysis is complicated by relative fiscal reconstruction priorities

24


Short-term

business-cycle

judgements are

more likely to

succeed with a deep

awareness of more

medium and longer-

term issues


18 October 2016 31

Global policy coordination Over 2016-18, national perspectives are expected to dominate:

1) The US, having achieved domestic balance, will slowly raise policy interest rates

2) The eurozone will nurture the revival of its private sector

3) China will focus on the quality of its growth

Consumption is the key to global growth forecasts. At the global level, we are expecting

investment to be a mild headwind (pages 52-57), whilst fiscal spending is shifting to a mild

headwind. Trade growth is expected to remain modest and, therefore, we do not expect it to

be a material catalyst of efficiency gains. This leaves consumption, including residential

investment which we believe will be a pocket of strength.

We expect the G7/G20 forums to shift focus from fiscal stimulus to boosting consumption.

Seeking a high frequency indicator for global consumption, Fig 66 presents the OECD US

and eurozone consumer confidence monthly series along with the Oxford Economics global

real private consumption series (quarterly data, 4Q ma).

Consumer confidence in both the US and the eurozone remain at high levels. The benefit to

household real incomes from plunging oil prices is still positive, though at a diminishing rate.

Retail sales data in advanced economies is reassuring, Fig 67.

Fig 66 Global real private consumption is growing around 2.5% pa, consumer confidence indices for the US and the eurozone, 2006-2015

Source: OECD, Oxford Economics, Macquarie Research, October 2016

Fig 67 Retail sales volumes (3m % YoY)

Source: Datastream, Macquarie Research, October 2016

Within consumption, services are becoming ever more important. For example, 67% of US

personal consumption expenditures are now services, with goods just 33%.

-2.0

-1.0

0.0

1.0

2.0

3.0

4.0

5.0

94

95

96

97

98

99

100

101

102

2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016

(%) US - Consumer Confindence [LHS] Eurozone - Consumer Confidence [LHS]World - Consumption [RHS]

(%)

-10

-8

-6

-4

-2

0

2

4

6

8(%) UK US Japan Eurozone

We expect the

G7/G20 forums to

shift focus from

fiscal stimulus to

boosting

consumption

Consumption

growth has softened

over the last six

months


18 October 2016 32

Global services The service sector has been understudied due to its relative stability. This is despite the

increasing role it is playing in the global economy as its share of output has grown steadily.

Over the past quarter century, ~1 billion new jobs have been created globally; ~75% of these

have been in services. This has caused services employment to rise from ~34% of the global

total in 1991 to ~46% in 2016, a gain of half a percentage point per year. Output data tells a

similar story, with the services share of GDP having risen steadily in both developed and

emerging markets over the past four decades, Fig 68.

Fig 68 Services as a share of GDP, 1970-2014: a secular shift to services

Source: United Nations, Macquarie Research, October 2016

These trends are likely to persist. Growth in per-capita incomes (particularly in EMs),

demographics (aging populations), and firmer relative trends in services inflation all suggest

services will form a greater share of consumer spending and total output in the years ahead.

Fig 69 Services become more important with a higher GDP per capita

Source: IMF, UN, Macquarie Research, October 2016

Country 1970 1975 1980 1985 1990 1995 2000 2005 2010 2014

change

1970 to

2014

change

1995 to

2014

Australia 53.8 57.1 56.9 60.0 66.3 67.8 70.2 69.1 69.0 70.1 16.4 2.3

Canada 59.4 58.7 58.3 61.4 65.8 66.4 64.5 65.8 70.8 69.9 10.5 3.5

France 59.9 62.9 65.2 67.9 69.6 72.7 74.3 76.6 78.6 78.9 19.0 6.1

Germany 48.9 55.2 56.8 59.0 61.1 66.0 68.0 69.8 69.1 69.0 20.1 2.9

Italy 53.4 55.4 57.4 62.4 65.6 67.6 70.0 71.9 73.7 74.3 21.0 6.7

Japan 49.8 54.6 58.1 59.4 59.6 65.2 67.3 70.6 71.3 72.0 22.2 6.8

Republic of Korea 41.2 40.9 46.3 49.5 51.6 54.6 57.5 59.4 59.3 59.4 18.2 4.8

Spain 47.8 49.4 55.0 59.4 60.5 65.1 65.1 66.5 71.4 75.1 27.3 9.9

United Kingdom 58.5 61.6 60.1 62.6 67.0 68.5 72.0 76.0 78.5 78.4 19.9 9.9

United States 65.5 66.5 67.2 70.0 72.6 74.5 76.3 77.5 78.8 78.4 12.9 3.9

DM average (level) 53.8 56.2 58.1 61.2 64.0 66.8 68.5 70.3 72.0 72.5 18.7 5.7

Argentina 48.1 47.0 55.1 56.1 59.1 68.3 69.2 56.9 60.9 63.0 14.8 -5.3

Brazil 52.6 48.9 49.2 46.7 52.9 68.5 67.7 65.9 67.8 71.0 18.4 2.5

China 24.7 22.2 21.8 29.0 32.0 33.3 39.5 40.9 43.7 47.7 23.0 14.3

India 32.5 34.4 33.9 35.9 36.6 39.1 44.2 46.4 48.2 53.0 20.5 13.8

Indonesia 40.1 40.9 37.7 47.1 47.9 47.6 42.9 44.8 41.8 43.3 3.3 -4.2

Mexico 54.1 53.5 49.5 46.8 53.0 57.9 57.1 58.1 58.3 59.0 4.9 1.1

Russian Federation 32.5 53.5 54.0 57.0 61.4 59.1 26.6 5.6

Saudi Arabia 36.8 27.3 27.8 55.2 45.7 45.5 41.5 35.0 39.2 40.6 3.7 -5.0

South Africa 54.4 51.0 45.7 51.5 55.4 61.3 64.8 67.1 67.2 68.0 13.6 6.8

Turkey 41.0 43.4 49.5 51.0 47.8 50.0 59.4 61.4 64.2 64.9 23.9 14.9

EM average 42.7 41.0 41.1 46.6 46.3 52.5 54.0 53.3 55.3 57.0 15.3 4.5

Emerging markets

Services share of GDP

Developed markets

$-

$10

$20

$30

$40

$50

$60

$70

40 45 50 55 60 65 70 75 80 85

GD

P p

er cap

ita (th

ou

san

ds) U

S$

Services share of output (%)

AUS

CAN

DEU

USA

GBR

FRA

ITAJPN

KOR

BRA

ZAF

TUR

ARG

MEX

RUS

IND

CHN

IDN

SAU

line of best fit

GDP per capita vs. services share of output (2014)

ESP

Over the past

quarter century ~1

billion new jobs

have been created

globally; ~75% of

these have been in

services

We expect services

will form a greater

share of consumer

spending and total

output in the years

ahead


18 October 2016 33

The rising importance of services has played a key role in our view that the current expansion

should continue to be characterized by structurally lower growth rates, but also by incredible

persistency and resiliency. We see five major implications:

1) Reduced volatility in economic growth

Services output is much less volatile than industrial output leading to more stable

employment trends. This also means that the business cycle will be less cyclical

supporting longer expansions and limiting the severity of downturns.

2) Central bank policy divergence and less inflation variability

The rise of services means that inflation prospects are going to be increasingly driven by

domestic forces, such as wage growth, and less by external factors such as commodity

prices and exchange rates. As a result, divergent domestic outlooks are likely to enable

desynchronized central bank policy.

Fig 70 US services inflation has shown far more stability relative to goods

Fig 71 ...and has been stronger on average with lower variation

Source: BEA, Macquarie Research, October 2016 Source: Bloomberg, Macquarie Research, October 2016

Fig 72 Euro area services inflation has shown greater stability than goods...

Fig 73 ...and a similar story in China, with services more stable and stronger than goods

Source: Bloomberg, Macquarie Research, October 2016 Source: Bloomberg, Macquarie Research, October 2016

-5%

-3%

-1%

1%

3%

5%

1991 1994 1997 2000 2003 2006 2009 2012 2015

US PCE price index YoY % change

services

goods

0.0%

0.5%

1.0%

1.5%

2.0%

2.5%

3.0%

3.5%

Average STDEV

Services

PCE price inflation descriptive statistics: 1991 to 2015

GoodsServices

Goods

-3

-2

-1

0

1

2

3

4

5

6

7

1991 1994 1997 2000 2003 2006 2009 2012 2015

services

goods

Euro area CPI price index YoY % change

-4

-2

0

2

4

6

8

10

12

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016

goods

services

China CPI price index YoY % change

The current

expansion should

continue to be

characterized by

structurally lower

growth rates, but

also by incredible

persistency and

resiliency


18 October 2016 34

3) Increased trade in services

Trade in services has been rising rapidly worldwide, but a steep run-up in commodity

prices between 1998 and 2014 led to disproportionate gains in the trade of goods,

particularly from EM exports. Going forward, our expectation for a flatter commodity price

environment means that services exports are likely to make up a greater share of overall

export growth and rise in importance worldwide. Please see page 40.

4) Relative investment in IT and intellectual property

Service economies, which tend to be centred on knowledge-based industries, are

increasingly investing in IT and intellectual property relative to other investment areas. This

shift is likely to influence growth globally as these forms of investment tend to be less trade

dependent and contribute the majority of the economic benefit to the domestic economy.

Fig 74 Intellectual property products have risen to one-third of non-commodity US business investment

Fig 75 ...and the biggest increases have come from the R&D and software components

Source: BEA, Macquarie Research, October 2016 Source: BEA, Macquarie Research, October 2016

5) Lower productivity growth and real rates

The services sector has historically had lower productivity levels and growth rates than the

goods/manufacturing sector. A greater share of services employment and output will act as

a drag on productivity growth as a higher share of output will come from areas with lower

productivity growth.

In the years ahead, EMs are likely to continue to experience the strongest output gains as

productivity growth rates tend to be highest when countries undergo urbanization. This

allows workers with very low marginal productivity in the agricultural sector to be

redeployed into higher productivity employment in either the industrial/goods or service

sector.

0%

10%

20%

30%

40%

50%

60%

70%

80%

1959 1964 1969 1974 1979 1984 1989 1994 1999 2004 2009 2014

all other non-resi

investment

intellectual property

products

information processing

equipment

Share of US nonresidential private investment (ex mining and oil & gas)

0%

2%

4%

6%

8%

10%

12%

14%

16%

18%

20%

1959 1964 1969 1974 1979 1984 1989 1994 1999 2004 2009 2014

Share of US nonresidential private investment excl mining and oil & gas

Software

R&D

Enetertainment, literary, and

artistic orginals


18 October 2016 35

Innovation clusters, “Brainbelts” After a week visiting the Southern California brain belt bringing to life the book by Antoine van

Agtmael and Fred Bakker: The Smartest Places on Earth (2016), we are optimistic about a

new global growth engine.

The catalyst for the above book was the insight that “Making things cheap to gain an edge

over high-cost Western companies just wasn’t cutting it anymore. The days of the low-cost

advantage were essentially over”. This led to an understanding that cheap is giving way to

smart, where high value-added products are being created in collaborative environments, in

“brainbelts”. The latter, to quote Antoine van Agtmael and Fred Bakker are:

Research facilities with deep, specialist knowledge; educational institutions; government

support for basic research; appealing work and living environments; capital; and, most

important, the atmosphere of trust and the freedom of thinking that stimulates unorthodox

ideas and accepts failure as a necessary part of innovation – different from the hierarchical,

regimented thinking so prevalent in many Asian and MIST economies.

MIST stands for Mexico, Indonesia, South Korea and Turkey.

In addition to the brainbelts listed in Fig 76, Antoine van Agtmael and Fred Bakker identified

many others in their book, but virtually all were in North America and Europe.

Fig 76 “Brainbelts”: The Smartest Places on Earth

Country Region Name/place Focus Universities, research institutes, hospitals

United States: Well-known

California West Silicon Valley IT, bioscience, electric car, next gen bendable and wearable electronic devices

Stanford, University of California, Caltech

Massachusetts East Cambridge (and Route 128) Bioscience, robotics MIT, Harvard

Texas South Austin (Silicon Hills) Computers, new materials, bioscience University of Texas

Focus of the book

North Carolina South-East Durham-Raleigh-Chapel Hill (Research Triangle Park)

Bioscience, new materials, energy (LED) Duke, UNC, NC State

New York East Albany (Hudson Tech Valley) Semiconductors SUNY, RPI

Ohio Midwest Akron New materials, polymers University of Akron, Kent State

Minnesota Midwest Minneapolis-St.Paul Medical devices/bioscience University of Minnesota

Oregon West Portland (Silicon Forest) Bioscience OHSU

Northern Europe: in book

Netherlands Eindhoven (High Tech Campus)

Semiconductors. New materials Technical University

Sweden Lund-Malmo (Ideon) Life science, new materials Lund University

Finland Oulu (Technopolis) Medical instruments, wireless Oulu University

Germany Dresden (Silicon Saxony) Semiconductors Max Planck

Switzerland Zurich Life science Technical University

Note: from the book by Antoine van Agtmael and Fred Bakker: The Smartest Places on Earth (2016)

Source: Antoine van Agtmael and Fred Bakker above, Macquarie Research, October 2016

Beyond expensive, multidisciplinary, complex new product development, these innovation

clusters are also undertaking manufacturing, highly automated, custom runs, using 3-D

printers, produced in close proximity to the customer.

From an employment perspective, Antoine van Agtmael and Fred Bakker are optimistic, citing

Enrico Moretti’s book The New Geography of Jobs (2013).

For each new urban high-tech job there are five additional jobs created, three for

professionals and two for lower-wage non-professionals.

For each new urban

high-tech job there

are five additional

jobs created

Cheap is giving way

to smart, where high

value-added

products are being

created in

collaborative

environments, in

“brainbelts”


18 October 2016 36

The private sector’s appetite for credit Debt is not inherently a problem. Intermediated by the financial system, it is the main way that

savers earn returns. Savers, to be sustainably paid, however, require debt to be deployed into

debt-serviceable activities. We regard private sector non-financial credit growth broadly in line

with nominal GDP growth to be healthy.

The revival of private sector credit demand is a prerequisite for the successful withdrawal of

extraordinary central bank support for the economy.

In the case of Japan, the excess of credit growth over nominal GDP growth over the 1980s

“Bubble” was followed by a protracted period of balance sheet adjustment (credit growth

beneath nominal GDP growth, Fig.77). We believe Japan endured a vicious cycle of policy

and regulatory mistakes, which US policy avoided after the Global Financial Crisis, Fig.78.

Fig 77 Japan: private non-financial credit growth vs. Nominal GDP growth

Fig 78 US private sector nonfinancial credit is growing faster than GDP for the first time since 2008

Source: FRB of St Louis, Datastream, Macquarie Research, October 2016 Source: FRB of St. Louis, Macquarie Securities, October 2016

Nevertheless, even in the US it took four years between the year private sector credit growth

turned positive (2011) until it exceeded nominal GDP growth (2015).

The eurozone is behind the US because of the 2011-13 fiscal squeeze, Fig.79, such that

private sector credit growth double-dipped and has only gone positive again in 2015, four

years behind the US (2011), Fig.80.

Fig 79 The fiscal impulse: the eurozone’s 2011-13 fiscal squeeze

Fig 80 Euro Area: private nonfinancial credit growth vs. Nominal GDP growth

Note: Year-over-year change in the cyclically adjusted net lending (+) or net borrowing (-) of general government, adjusted based on potential GDP, excessive deficit procedure. Forecasts for 2015-17 from the European Commission. Source: EC Annual Macroeconomic Database, Macquarie Research, October 2016 Source: FRB of St Louis, Datastream, Macquarie Research, October 2016

-12

-9

-6

-3

0

3

6

1992 1993 1995 1997 1999 2001 2003 2005 2007 2009 2011 2013 2015

(YoY % change)

Private nonfinancial credit

Nominal GDP

late

-4

-2

0

2

4

6

8

10

12(YoY% change) Private nonfinancial credit

Nominal GDP

latest

-2

-1

0

1

2

2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017

(% of potential GDP)

YoY change in cyclically adjusted budget balance

-6

-4

-2

0

2

4

6

8

10

12

14(YoY % change) Private nonfinancial credit

Nominal GDP

The case of Japan

The US

The eurozone


18 October 2016 37

The BIS Financial cycle

Claudio Borio in his December 2012 BIS working paper: The financial cycle and

macroeconomics: What have we learnt? (http://www.bis.org/publ/work395.pdf) detailed the

existence of financial cycles: “Arguably, the most parsimonious description of the financial

cycle is in terms of credit and property prices (Drehmann et al (2012)). These variables tend

to co-vary rather closely with each other, especially at low frequencies, confirming the

importance of credit in the financing of construction and the purchase of property.”

Like business cycles, financial cycles are not mechanistic, but do appear as patterns in the

data. One problem is that whilst business cycles average 3-4 years, financial cycles average

16. Averages are just that, so let's say 16 years plus or minus 5. A lot depends on how policy

responds in the business cycle downturns prior to the financial cycle's peak/bust. On average

there will be three prior business cycle downturns, and if policy aggressively counteracts them

then moral hazard/credit leverage builds. We believe the private sectors of the major

economies/blocs are at very different stages in this “financial cycle”, below. The credit cycle in

EM economies is examined on page 45.

Fig 81 BIS-defined 16-year private sector “financial cycle”


Fig 82 presents the last 35 years of financial history in one chart. The rise and fall in the ratio

of private non-financial credit/GDP has coincided with major events. China is included to put

the relentless rise in its private non-financial credit/GDP ratio into context. China’s corporate

debt issue is examined on page 47.

Fig 82 Private non-financial credit as a % of GDP: significant peaks*

Note: (*) 1) 1990 saw the start of Japan’s lost decade 2) 1995 was Mexico’s peso crisis 3) 1997 saw Thailand kick-off the Asian crisis 4) 2008 was the USA’s subprime crisis 5) 2011 was the start of the Euro crisis that included Spain

Source: The Economist, BIS, Macquarie Research, October 2016

0

50

100

150

200

250(% of GDP)

Japan US Spain Mexico Thailand China

Like business

cycles, financial

cycles are not

mechanistic, but do

appear as patterns

in the data

We believe the

private sectors of

the major

economies/blocs

are at very different

stages in this

“financial cycle”


18 October 2016 38

Global trade in goods The 1980-2008 6% pa global world trade volume growth average has stepped down, in our

opinion, to a new trend growth rate of 2-3% pa, Fig.83.

Fig 83 World Merchandise Trade, from 1992 to latest, rolling 3 months, YoY

Note: Source: CPB, Macquarie Research, October 2016

This reflects:

5) The maturing of a 50-year containerization trend

6) The completion of the integration of China into global supply chains post its

December 2001 WTO entry

7) The move by MNCs to regionalize production to dampen exchange rate risk

8) The transition of China’s investment and credit-driven growth model into an import

substitution stage for intermediate and capital goods, especially by those companies

that perceive their cost of capital to be very low

The late 2014/early 2015 air pocket in emerging market economies’ import growth, along with

the trend decline in its growth rate, is shown in Fig.84, red line, which uses rolling three-

month average YoY data.

Fig 84 EM & Advanced economies import volumes


One consequence of the above is the muted response relative to history of the trade account

to exchange rate movements. This probably results in greater currency volatility.

In the case of EM currency depreciations, the consequence is likely to be more import volume

compression than export volume expansion.

For the identification of global trade trends, we recommend the comprehensive database of

the CPB Netherlands Bureau for Economic Policy Analysis. Data for both volume and price/

unit values is available geographically on a monthly basis. Importantly, the data is seasonally

adjusted. Their website is here: http://www.cpb.nl/en and their key summary table is Fig 85.

-23

-13

-3

7

17

1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016

World

-5

0

5

10

15

20

25

2010 2011 2012 2013 2014 2015 2016

Advanced EM

(per 12 month % change)

LAST 3 MONTHS ON YEAR AGO

Please note the late

2014/early 2015 air

pocket in emerging

market economies’

import growth,

along with the trend

decline in its growth

rate


18 October 2016 39

For those interested in going deeper into last year’s developments in China, the May 2016

IMF working paper by Joong Shik Kang and Wei Liao: Chinese imports, What’s behind the

slowdown? provides a comprehensive analysis of recent trends in Chinese trade.

Fig 85 World merchandise trade (% changes) – latest month July 2016

YoY QoQ momentum (note #1) MoM

Volumes (s.a) 2013 2014 2015 2015q4 2016q1 2016q2 2016m06 2016m07 2016m05 2016m06 2016m07

World trade 2.6 2.9 1.6 0.6 0.0 -0.8 -0.8 -0.8 -0.4 0.8 -1.1

World imports 2.2 2.9 1.4 0.9 -0.5 -0.8 -0.9 -0.4 0.6 0.8 -1.2

Advanced economies 0.0 3.3 3.6 0.9 0.9 -0.7 -0.7 -0.6 -0.8 1.3 -0.6 US 0.7 5.1 6.2 0.1 0.2 -0.6 -0.7 0.4 0.7 1.6 -1.1 Japan 1.6 2.2 0.1 -0.9 0.9 -1.3 -1.3 1.5 5.0 0.4 -1.1 Eurozone -0.3 2.8 3.3 1.2 1.0 -1.8 -1.8 -1.6 -1.5 0.3 0.7 Other advanced economies -0.8 2.8 2.5 1.7 1.3 1.5 1.6 -0.6 -3.0 3.4 -2.3

Emerging economies 5.6 2.3 -1.7 0.9 -2.4 -1.0 -1.2 0.0 2.7 0.0 -2.1 Asia 6.6 3.8 -1.0 0.6 -3.1 -0.1 -0.2 1.6 5.3 -1.3 -2.1 Central & Eastern Europe -2.1 -12.0 -25.1 1.4 6.9 -0.3 -0.6 -1.6 -1.3 1.0 -2.1 Latin America 5.2 3.0 -0.8 1.1 -2.1 -2.2 -2.1 -3.8 -5.3 5.8 -3.9 Africa & Middle East 4.9 0.3 5.6 2.1 -2.4 -5.6 -6.3 -3.5 -0.9 1.0 0.1

World exports 2.9 2.9 1.8 0.4 0.3 -0.7 -0.7 -1.2 -1.3 0.9 -0.9

Advanced economies 1.7 2.0 2.0 0.8 -0.3 -0.7 -0.6 -1.2 -1.8 0.9 -0.5 US 2.6 3.2 -1.1 -1.3 -0.8 0.4 0.4 0.1 -1.3 0.1 2.8 Japan -1.4 1.7 2.7 1.7 -0.1 1.0 1.0 1.1 0.0 4.2 -3.2 Eurozone 0.6 2.0 2.4 1.5 0.4 -0.7 -0.5 -1.5 -1.9 0.5 -0.7 Other advanced economies 5.1 1.2 3.3 0.7 -1.5 -2.5 -2.1 -2.7 -2.7 1.2 -1.2

Emerging economies 4.4 3.9 1.5 -0.1 1.0 -0.6 -0.9 -1.1 -0.7 0.8 -1.4 Asia 6.0 4.6 0.2 -0.5 1.1 -0.7 -1.0 -1.5 -0.9 0.6 -1.9 Central & Eastern Europe 0.1 -0.8 -0.4 3.6 -1.9 1.4 0.8 0.3 -0.4 1.4 -0.3 Latin America 2.4 5.2 9.8 1.2 4.0 -4.1 -4.2 -4.4 -2.1 1.6 -1.8 Africa & Middle East -0.6 1.1 2.8 -0.6 -1.0 2.8 2.8 3.9 2.3 0.6 0.8

Prices/unit values US$ (s.a.)

World trade -1.0 -1.8 -13.4 -2.9 -2.9 2.9 3.1 2.0 0.2 0.9 -1.0

World imports -1.3 -1.7 -13.2 -3.2 -2.5 2.7 2.9 1.6 -0.1 0.8 -1.4

Advanced economies -0.6 -1.2 -14.1 -2.8 -2.8 2.5 2.5 1.1 0.0 0.5 -1.8 US -1.1 -1.1 -10.2 -2.4 -2.5 1.8 1.8 2.3 1.2 0.7 0.1 Japan -7.3 -4.7 -20.2 -5.6 -3.4 2.1 2.1 1.9 -3.0 3.5 1.0 Eurozone 1.8 -1.5 -17.4 -2.7 -1.7 3.0 3.0 1.3 0.1 0.5 -1.8 Other advanced economies -2.3 0.8 -9.4 -2.6 -5.1 2.5 2.4 -0.6 -0.3 -0.7 -4.5

Emerging economies -2.4 -2.3 -11.6 -3.8 -2.0 3.1 3.4 2.3 -0.2 1.2 -0.8 Asia -3.5 -3.0 -12.2 -3.4 -2.5 4.0 4.0 2.6 -0.7 2.0 -0.7 Central & Eastern Europe 1.3 -1.7 -12.6 -11.2 12.3 -5.5 -6.1 -5.9 -1.7 0.5 -5.8 Latin America -1.5 -2.8 -9.6 -5.1 -1.4 1.2 1.3 2.1 1.1 0.4 -0.9 Africa & Middle East 0.7 2.2 -11.3 -2.3 -3.7 4.5 6.7 3.7 2.1 -1.7 0.0

World exports -0.6 -1.9 -13.6 -2.5 -3.3 3.1 3.2 2.4 0.5 1.0 -0.6

Advanced economies 0.3 -0.8 -12.9 -2.5 -1.9 2.7 2.6 1.5 0.3 0.3 -1.2 US -0.4 -0.5 -6.3 -1.9 -2.2 1.3 1.3 1.9 1.1 0.7 0.2 Japan -9.1 -5.2 -11.9 -3.4 0.6 2.7 2.7 3.0 -0.7 0.8 2.9 Eurozone 3.0 -0.1 -15.3 -2.0 -0.9 2.8 2.8 1.1 0.1 0.2 -1.5 Other advanced economies -1.8 -0.9 -12.9 -3.7 -4.7 3.6 3.2 1.3 0.7 0.1 -3.5

Emerging economies -1.8 -3.2 -14.3 -2.5 -5.0 3.6 4.0 3.5 0.7 1.9 0.0 Asia -1.2 -1.2 -5.8 -0.8 -3.4 1.5 1.8 1.5 -0.2 1.4 0.3 Central & Eastern Europe -2.8 -5.3 -31.8 -8.5 -9.8 1.4 1.6 2.8 0.2 7.2 -3.5 Latin America -2.1 -6.3 -19.7 -3.0 -5.5 4.2 4.4 3.9 0.7 -0.2 1.1 Africa & Middle East -0.7 -6.9 -38.7 -10.3 -14.4 23.5 26.6 22.2 9.1 5.0 -0.9

World prices/unit values in US$

Fuels (HWWI) 1.5 -6.8 -44.1 -13.8 -20.3 28.9 28.9 24.7 10.8 7.0 -4.9 Primary commodities ex fuels -6.6 -9.2 -22.8 -6.2 -1.2 10.2 10.2 6.6 0.8 1.2 0.7

Notes: (#1): average of the three months up to the report month over average of the preceding three months



18 October 2016 40

Global trade in services The share of global trade in services has been flat for close to 20 years, Fig 86, as much of

the delta in global trade growth has come from EM goods.

The result of this development is that services have become far less trade-intensive relative

to goods. To provide some context, the average dollar value of world exports per employee in

the goods sector is ~$11,000, nearly 3x the same figure for the services sector, Fig 87. This

represents a significant increase from just ~2x in 1991.

Fig 86 Flat global services export share, 1982-2015 Fig 87 A higher trade intensity in goods

Source: WTO, Macquarie Research, October 2016 Source: WTO, Macquarie Research, October 2016

Partially fuelled by a boom in commodity prices from 1998 to 2014, global trade growth has

been increasingly driven by EMs, where exports are more concentrated in goods. We believe

this contributed to outsized gains in the exports of goods.

Prior to 1998, growth in services exports for both EMs and DMs outpaced the growth in goods

(Fig 88) whereas after 1998 EM goods exports outperformed (Fig 89).

Fig 88 Services trade outperformed from 86 to 98 … Fig 89 Underperformed during the commodity boom

Source: WTO, Macquarie Research, October 2016 Source: WTO, Macquarie Research, October 2016

Going forward, it may be many years before there is another commodity boom. As a result,

global trade growth is likely to come increasingly from services.

Policymakers are already showing signs of awareness on this front. Recent trade

agreements, such as the Trans-Pacific Partnership, have chapters dedicated specifically to

liberalizing the trade in services and removing barriers.

5%

10%

15%

20%

25%

30%

1982 1987 1992 1997 2002 2007 2012

Share of exports that are services (USD basis)

G20-DM

G20-EM

world

$-

$2,000

$4,000

$6,000

$8,000

$10,000

$12,000

1991 1994 1997 2000 2003 2006 2009 2012

goods

services

World exports (USD basis) per employee

0

1

2

3

4

5

1982 1984 1986 1988 1990 1992 1994 1996 1998

Export growth - G20 countries (1982= 1.00)

EM services

DM services

DM goods

EM goods

1982 = 1.00

During flat commodity price period EM service

exports outperformed

0

1

2

3

4

5

6

7

8

1998 2000 2002 2004 2006 2008 2010 2012 2014

DM goods

Export growth - G20 countries (1998 = 1.00)

EM goods

EM services

DM services

1998 = 1.00

During commodity boom EM goods

exports outperformed

The share of global

trade in services

has been flat for

close to 20 years

Going forwards,

global trade growth

is likely to come

increasingly from

services


18 October 2016 41

Fading fiscal policy tailwinds In the immediate aftermath of the global financial crisis (GFC), global fiscal policy was very

expansionary, with global budget deficits widening by nearly 2% of GDP in 2008 and a further

5% of GDP in 2009, Fig 90. Aggregate revenue weakness was accommodated and spending

was increased. However, the fiscal expansion was tempered from 2010, when global budget

balances improved by 1% of GDP (each) in 2010 and 2011, as economies began reloading

their fiscal arsenal.

This continued, albeit less aggressively, in 2012-13, with an average improvement of 0.7%

of GDP per year. From 2014-16, however, aggregate fiscal budget balances deteriorated

modestly (on average by 0.2% of GDP per year), as the global economic recovery became

less sure-footed and put pressure on developing economy tax revenues in particular. Global

fiscal policy has now reached an inflexion point again, as it is forecast to become a

significantly weaker cyclical tailwind, with aggregate budget balances forecast to improve

modestly (by around 0.5% of GDP each in 2017 and 2018).

Fig 90 Advanced versus developing countries: primary budget balances


Fig 91 Budget balance 2016 and change to 2017


-6.00

-5.00

-4.00

-3.00

-2.00

-1.00

0.00

1.00

2.00

3.00

% of GDP, YoY change

Advanced weighted Developing economies (weighted)

Philippines

Hungary

Mauritius

Thailand

Indonesia SingaporeIsrael Chile

Brazil SAUSNZ

IndiaChinaNigeria

Croatia

MalaysiaMexico

TurkeyCanada

Ireland

Japan Australia

ArgentinaUK

EgyptRussia

Swaziland

Namibia

-0.5

0.0

0.5

1.0

1.5

2.0

-12 -10 -8 -6 -4 -2 0 2

2017 - 2016 (% of GDP)

(2016, % of GDP)

Fiscal headwind that fades

Fiscal tailwind that intensifies

Fiscal tailwind that fades

Global fiscal policy

has now reached an

inflexion point, as it

is forecast to

become a

significantly weaker

cyclical tailwind,

with aggregate

budget balances

forecast to improve

modestly (by around

0.5% of GDP each in

2017 and 2018)

Those countries

with larger budget

deficits (horizontal

scale) are forecast,

on average, to see

the biggest

improvements

(reduction in the

budget deficit) 2017

versus 2016

(vertical scale)


18 October 2016 42

Financial repression for decades We disagree that record low bond yields are signalling a global slump. Rather, we believe that

it is a conscious policy choice to minimise public debt funding costs that began in Japan and

is spreading to Europe. Nonetheless, budget realities, below, will leave government

investment expenditure under pressure. The secular trends of privatisation and public-private

infrastructure partnerships are expected to continue.

Fig 92 G7 public debt/GDP ratios, %

2007 2016E 2020E

Gross Net Gross Net Gross Net

US 64.0 44.5 107.5 82.2 106.1 81.4 Japan 183.0 80.5 249.3 129.6 251.8 132.2 Germany 63.6 48.1 68.2 46.7 58.4 39.1 UK 43.5 38.2 89.1 80.6 79.4 70.8 France 64.2 57.7 98.2 90.5 95.4 87.7 Italy 99.8 84.1 133.0 111.8 124.2 104.4 Canada 66.8 22.1 92.3 27.5 83.4 18.6

G7 81.1 52.1 120.1 84.4 115.8 81.3 Euro area 64.9 45.5 92.5 69.3 85.5 64.3

Note. 2016 and 2020 estimates IMF. Source: IMF, Macquarie Research, October 2016

Fig 93 10-Advanced economies: Government investment to GDP ratio

Note: 10-Advanced economies are US, Japan, Germany, France, Italy, Spain, UK, Australia, Canada, and South Korea. Oxford Economics’ forecasts. Source: Oxford Economics, Macquarie Research, October 2016

The principal driver of record low bond yields since 2009 has evolved, from cyclical

factors (secular stagnation), through a private sector balance sheet recession (completed in

the US and Japan; ongoing, but progressing in the eurozone) to fiscal reconstruction

(reloading the fiscal policy tool weapon) using the seductive tool of financial repression.

Fig 94 10-year real bond yields, G7 ex Italy, 1985-2013, quarterly, %

Note: National Bureau of Economic research (NBER) working paper “Measuring the world interest rate” by Mervyn King & David Low (2014) The US enters the sample in 1999 with the first TIPS issue.

Source: NBER above, Macquarie Research, October 2016

3.0

3.3

3.6

3.9

4.2

4.5

2000 2002 2004 2006 2008 2010 2012 2014 2016 2018 2020

10-Total

-1

0

1

2

3

4

5

6

1985 1987 1989 1991 1993 1995 1997 1999 2001 2003 2005 2007 2009 2011 2013

(%) Weighted real rate Unweighted real rate

We disagree that

record low bond

yields are signalling

a global slump

Rather, we believe

that it is a

conscious policy

choice to minimise

public debt funding

costs that began in

Japan and is

spreading to Europe

The principal driver

of record low bond

yields since 2009

has evolved

...to fiscal

reconstruction

(reloading the fiscal

policy tool weapon)

using the seductive

tool of financial

repression


18 October 2016 43

Japan illustrates well the pressures being faced by policymakers.

Japan’s public debt to GDP ratio built over the 24 years 1990-2014 from around 65% to

240%. Only in 2006 and 2007 did the ratio decline. Japan’s public debt to GDP has far

exceeded the previous high in 1945, Fig 95.

Please note, however, that Japan’s public debt ratio has stabilised over the last few years.

Fig 95 Japan’s gross government debt, as a percentage of GDP

Source: IMF, Datastream, Macquarie Research, October 2016

Japan’s considerable progress over the last three years towards stabilizing its public debt to

GDP ratio can be illustrated by using the formula for the primary budget balance necessary

for stabilization:

(Bond yields minus nominal GDP growth) x (Public debt/GDP)

In 2012, Japan needed a primary budget surplus of 2.4% (1% minus 0% times 2.4).

Today, thanks to the consequences of financial recession, Japan only needs a primary

budget deficit of 2.4% (zero minus 1% times 2.4) to stabilize the public debt to GDP ratio.

That’s a 4.8% of GDP swing. There is no “free lunch,” however.

An implicit tax on savers resulting in weak consumption

Savings behaviour is not mechanical, but the hypothesis that households smooth their

consumption by saving for retirement seems to work well in practice. Reducing the returns on

savings leads to higher required savings. The implicit tax on savings leads to weak

consumption. If consumption stagnates, companies do not invest and do not raise wages.

Achieving fiscal reconstruction with financial repression, in the context of very high (around

250% of GDP) household financial assets, has led Japan into a low growth trap.

Fig 96 Household saving rate, 1990 to latest

Source: Datastream, Macquarie Research, October 2016

0

50

100

150

200

250

1875 1885 1895 1905 1915 1925 1935 1945 1955 1965 1975 1985 1995 2005 2015

Gross government debt(as % of GDP)

Gross government debt (as % of GDP)

Bubble bursts

1936 Takahashi assassinated for trying to

rein in military expenditures

(%)

-5

0

5

10

15

20

1990 1992 1995 1997 2000 2002 2005 2007 2010 2012 2015

Housholds saving rate(%, seasonally adjusted, 6m average)

Japan’s public debt

ratio has stabilised

If consumption

stagnates,

companies do not

invest and do not

raise wages


18 October 2016 44

Housing, globally, a good news story Private sector credit growth needs to revive for central banks to end their extraordinary

support. A recovery in home loan demand could be the key driver. Home loans are on

average ~40% of total loans.

A good news story: We believe residential investment is around 4% of global GDP and will

grow between 3.5% and 4.0% pa through 2020. The latter is supported by recovery in many

advanced economies, whilst financial deepening and the upgrading of the housing stock

underpin growth in EM economies. There are exceptions.

Housing is a lead indicator and an important driver of the business cycle, as well as being

intertwined with credit growth and financial stability. Nonetheless, there is a paucity of globally

consistent data.

Fig 97 10-Advanced economies residential investment to GDP ratio

Note: 10-Advanced economies are US, Japan, Germany, France, Italy, Spain, UK, Australia, Canada, and South Korea. Source: IMF, National sources, Oxford Economics, Macquarie Research, October 2016

The 22 July 2016 Macq-ro insights: Residential investment, globally looked at residential

investment data and residential price trends across 23 countries. The key observations are

summarized below.

Fig 98 Key residential investment observations

Country

USA 10% pa real growth through 2019 would only return residential investment/GDP to the post-1970 average level

France Germany has been recovering since 2010, whilst France is still at cyclical lows. We believe a mild recovery is beginning

Japan The Affluent Elderly is supporting renovation and reform, with the upgrading of the housing stock a major government priority

China Due to lower mortgage rates and aggressive policy relaxation, 2016 will be remembered as a year of a property up-cycle like 2013. From a long-term perspective, we believe China’s housing demand has peaked

Source: Macquarie Research, September 2016

Fig 99 Residential investment to GDP ratio for Germany and France

Source: Oxford Economics, Macquarie Research, October 2016

3.5

4.0

4.5

5.0

5.5

6.0

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020

10-Total

4.0

5.0

6.0

7.0

8.0

9.0

10.0 (%) Germany residential investment - % share of GDP

France residential investment - % share of GDP

Residential

investment is

around 4% of global

GDP and will grow

between 3.5%-4.0%

pa through 2020

Recovery in many

advanced

economies...

Financial deepening

and the upgrading

of the housing stock

underpin growth in

EM economies

We looked at

residential

investment data and

residential price

trends across 23

countries


18 October 2016 45

Global liquidity & EM credit cycles Global liquidity, as defined by the BIS, is the ease of financing by companies in international

markets.

Global liquidity moves in irregular and powerful waves, appearing to be stronger when the

US$ is depreciating, and weaker when the US$ is appreciating, chart below.

Fig 100 Cumulative flows, gross, in US$-denominated cross-border loans outside the US (US$tr): The dark shaded areas indicate depreciations in the US dollar effective exchange rate

Sources: S Avdjiev, C Koch and H S Shin “Exchange rates and foreign borrowing in international currencies” (2015, in progress); BIS effective exchange rate statistics; BIS locational banking statistics by residence. In addition to cross-border bank loans shown above, the BIS include bond issues in their total debt data

Source: BIS as noted above, Macquarie Research, October 2016

Swings in global liquidity are associated with credit booms and subsequent financial

vulnerability in emerging market economies (EMEs). Into the credit-growth contraction phase

across EMEs, we expect 2016 to see some major debt restructurings, but no cascading

cross-border banking crisis.

This will provide opportunities for well-funded MNCs. Please see the 21 January 2016 Macq-

ro insights: The corporate savings “glut” & cross-border M&A.

We believe the EM private non-financial credit cycle peaked with the May-June 2013 ‘taper

tantrum’. However, the following three charts on the next page suggest that this could be

optimistic as private sector credit ratios are still increasing in most EMEs.

The distribution of debt by currency and sectors

We believe that within foreign currency denominated debt, private sector debt is more

vulnerable to destabilization than sovereign debt (the government sector), Fig 101. For more

comprehensive tables, please see the 25 January 2016 Macq-ro insights: Global liquidity.

Fig 101 Key debt ratios, % of GDP

Singapore Malaysia Thailand Indonesia China Brazil S. Korea

External debt1/GDP NA 40 NA 32 10 31 13

US$-denominated corporate debt2/GDP

NA 6 NA 12 8 9 8

Corporate debt2/GDP 82 64 51 23 157 49 105

Notes: (1): all sectors, all currencies, (2): non-financial corporate debt

Source: BIS, Macquarie Research October 2016

Chinese corporate debt is examined in the next section.

Global liquidity, as

defined by the BIS,

is the ease of

financing by

companies in

international

markets

We believe the EM

private non-financial

credit cycle peaked

with the May-June

2013 ‘taper tantrum’


18 October 2016 46

Fig 102 Private non-financial sector credit as a % of GDP: selected EMEs #1

Note: The BIS does not have data for Nigeria


Fig 103 Private non-financial sector credit as a % of GDP: selected EMEs #2

Note: The BIS does not have data for Taiwan. Japan and Korea are included as benchmarks


Fig 104 Private non-financial sector credit as a % of GDP: ASEAN

Note: The BIS does not have data for the Philippines and Vietnam


10

25

40

55

70

85

100 (% of GDP)

Turkey Poland Mexico BrazilArgentina Russia Saudi Arabia

0

50

100

150

200

250 (% of GDP) Japan China India Korea

0

40

80

120

160

200 (% of GDP) Indonesia Thailand Singapore Malaysia


18 October 2016 47

Chinese corporate debt Please see Fig 82 on page 37 and Fig 101 on page 45 for context. For more details, please

see Larry Hu’s 8 June 2016 China’s debt: Myths and Realities.

It’s popular to argue that China will run into a debt crisis in either local government debt or

corporate debt. By contrast, our long-held view is that China’s debt problem is very different

from many other countries. The risk of a debt crisis is small because policy-makers could

reshuffle debt among different entities: central government, local government, SOEs and

banks. In 2015, China’s total government debt was RMB37tn, of which RMB27tn was owned

by local governments, Fig 105 and Fig 106). Since last year, China has conducted local

government debt swaps, which essentially converts local government debt to sovereign debt.

Banks also share the costs by swapping loans to bonds, which are safe but offer lower yields.

Fig 105 Corporate leverage is high in China

Fig 106 China’s debt breakdown


In 2015, China’s total corporate debt was RMB106tn, or 157% of GDP. While it’s large, over

70% of China’s corporate debt is owned by SOEs. The discussion on debt/equity swap

suggests that it’s possible to transfer the SOE debt burden to governments and banks. By

doing so, the government also lowers the odds for a corporate debt crisis.

Fig 107 Annual new loans vs. interest payments Fig 108 Leverage ratio: SOE vs. private enterprises


In our view, the real risk behind China’s debt is capital misallocation, as the majority of credit

is poured to the less-efficient SOEs and local governments rather than the private sector. The

debt swap for local governments and SOEs could worsen the problem if it is not designed

well, as it could delay the exit of inefficient firms and worsen the soft budget constrains for

SOEs. Such capital misallocation could undermine China’s potential growth in the long run,

causing the country to become stuck in the so-called “middle-income trap”.

0

20

40

60

80

100

120

Non-financial corporate Government Households

RMB tn China's debt breakdown

SOE

Private enterprise

Local govt

Central govt

11 13 14 15 17 21 24 32 40 46 5462 70 76

2 3 3 4 5 6 79

1214

18

2125

30

1 2 2 2 23

4

6

89

10

13

15

19

2 2 2 3 45

5

6

7

7

8

9

10

11

1 2 2 3 45

6

9

11

13

16

20

24

27

0

20

40

60

80

100

120

140

160

180 SOE debt

Private corporate debt

Household debt

Central governmt debt

Local government debt

RMB tn

5

10

87

89

10

12

2 23

44

56 6

0

2

4

6

8

10

12

14

20

08

20

09

20

10

20

11

20

12

20

13

20

14

20

15

Annual new loans

Loan interest payment

RMB tn

50

52

54

56

58

60

62

64

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

SOE

Private enterprise

% Industrial enterprise: Debt-to-assets ratio

Government debt

Corporate debt

Capital misallocation


18 October 2016 48

Fig 109 Gross fixed capital formation, % of GDP, 1970-2015

Note: Latest data for Thailand is 2014.

Source: CAO, World Bank, Macquarie Research, October 2016

During the Asian Financial Crisis, the average step-down in gross capital formation to GDP,

1996-98, for Malaysia, Thailand, Indonesia and Korea was approximately 14%. The catalyst

was a hard-stop by capital providers, cross-border bank lending. The equivalent today in

China would be a hard-stop of capital provision by the household sector, i.e. bank deposits

leaving the Chinese banking system en masse.

Fig 110 Core debt of the non-financial sectors, as a % of GDP

Level in 2014 Change since end-2007 (1)

Households Corporate Government Total Households Corporate Government Total

Advanced economies (2) 73 81 110 265 -7 1 41 36

Australia 119 77 35 230 11 -4 26 33

Canada 93 104 70 267 15 15 19 49

France 56 124 109 288 10 20 43 72

Germany 54 54 82 191 -7 -1 18 10

Italy 43 78 151 272 5 3 46 53

Japan 66 105 222 393 0 5 72 77

Spain 71 111 110 293 -10 -14 74 50

Sweden 83 165 47 295 18 27 7 52

Switzerland 120 91 34 245 13 15 -4 26

United Kingdom 87 77 107 271 -9 -11 61 41

United States 78 69 92 239 -18 -1 39 21

Eurozone 61 103 106 270 1 4 39 45

Emerging market economies (2) 30 94 44 167 10 35 4 50

Argentina (3) 6 9 43 58 2 -1 -1 -1

Brazil (4) 25 49 64 139 12 18 1 32

China 36 157 41 235 17 58 6 82

Hong Kong SAR 66 217 5 287 14 85 3 103

India 9 50 66 125 -1 8 -8 -1

Indonesia 17 23 25 64 6 8 -8 5

Korea 84 105 38 228 12 14 14 40

Malaysia (3) 69 64 53 186 15 4 13 32

Mexico 15 22 33 70 1 7 13 21

Russia (3) 20 58 18 95 8 16 9 33

Singapore 61 82 99 242 22 24 13 59

South Africa 37 33 55 125 -4 -2 23 17

Thailand 69 51 30 151 25 5 7 37

Turkey 21 33 34 108 9 28 -8 30

Notes: (1): in percentage points of GDP. (2): weighted average of the economies listed based on rolling GDP and PPP exchange rates. (3): breakdown of household and corporate debt is estimated based on bank credit data. Please note that Government debt data is the BIS core debt (credit to the government) at market values except for countries where only nominal values are available.

Source: BIS, Macquarie Research October 2016

10

20

30

40

50

1970

1972

1974

1976

1978

1980

1982

1984

1986

1988

1990

1992

1994

1996

1998

2000

2002

2004

2006

2008

2010

2012

2014

(% of GDP) Malaysia Thailand Indonesia Korea

The Asian Financial

Crisis


18 October 2016 49

Oil & sovereign defaults The last great collapse in oil and commodity prices from the end of the 1970s led to a

decade-long wave of sovereign defaults, below. The defaults data is available both by creditor

and defaulting country, below.

Fig 111 Sovereign debt default as a share of world public debt and world GDP

Source: CRAG, Macquarie Securities, October 2016

Fig 112 Total sovereign debt in default, by creditor

Source: CRAG, Macquarie Securities, October 2016

In the 1980s, there was a reluctance to address the fiscal deficits that resulted from less tax

revenues from lower oil and commodity prices. Fifteen countries saw an increase of public

debt to GDP in excess of 40%. With global capital markets up until 1980 consisting largely of

fixed exchange rates and national controls on capital flows, falling exports led to current

account deficits and persistent forex reserves erosion, Fig 113.

Fig 113 Foreign exchange reserves, in US$, the 1980s and now

1980 forex reserves

as a % of GDP Decline in forex reserves,

start 1980 to 1980s low End-2015 reserves

as a % of GDP

Forex reserves to GDP difference:

2015 vs 1980

Nigeria 4.9 -93% 5.9 1.0 South Africa 8.2 -79% 14.4 6.2 Argentina 3.9 -77% 4.4 0.5 Saudi Arabia 10.1 -66% 98.6 88.5 Brazil 5.8 -64% 19.8 14.0 Colombia 9.1 -64% 17.0 7.9 Indonesia 4.9 -38% 12.1 7.3 Malaysia 14.3 -23% 27.7 13.4 Venezuela 10.4 -15% 12.4 2.0

Note: The above does not include an analysis of forward book positions, which is important for sum including

Brazil. Source: IMF/Oxford Economics/Haver, Macquarie Research, October 2016

0

1

2

3

4

5

6

71980

1981

1982

1983

1984

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

(%) % of World Public Debt % of Gross World Product

0

100

200

300

400

500 US$bnIMF World Bank Paris Club Other official creditorsPrivate creditors FC Bank Loans FC Bonds LC Debt

Falling exports led

to current account

deficits and

persistent forex

reserves erosion

A decade-long wave

of sovereign

defaults


18 October 2016 50

Whilst this time, greater exchange rate flexibility is absorbing some of the risk related to

capital flight, Fig 114, cross-border capital account flows are enormously more important.

The decade from 2011

For countries with a high export dependency on oil and commodities, the decade from 2011

could evolve as follows:

1) A major fall in export revenues leading to a current account deficit, and the policy

decision to allow the currency to depreciate.

2) The latter could be of the order of 30-50%, chart below, causing a significant

increase in inflation, and the need for nominal local interest rates to increase.

Fig 114 Emerging Market currencies (nominal)

Note: Latest data point: June 2016


3) Initially, there is a reluctance to increase policy interest rates rapidly given concerns

for economic growth, but capital outflows and an increase in sovereign risk spreads

lead to a tightening of monetary policy.

4) The fiscal position deteriorates with a fall in oil- and commodity-related taxes, and the

weakening economy. The initial reluctance to cut public expenditures is reinforced by

the tightening of monetary policy’s negative impact on economic growth, and the

escalating debt service costs.

At this point, fiscal deficits become persistent.

The ratio of public debt to GDP begins to trend higher.

The following formula gives the primary budget balance (excludes interest expense)

necessary for public debt/GDP stabilization:

(Bond yields minus nominal GDP growth) x (Public debt/GDP)

For example, 10% bond yields, nominal GDP growth of 5% and a public debt/GDP ratio of 50%

would require a primary budget balance of 2.5% of GDP (a surplus).

As the public debt/GDP ratio rises over time, then the required primary budget balance

becomes bigger, e.g. at 100%, not 50%, the required primary balance would be a surplus of 5%

of GDP, not 2.5% of GDP.

The last great collapse in oil and commodity prices from the end of the 1970s led to a

decade-long wave of sovereign defaults.

We believe another wave is coming, involving multiple debt restructurings over many

years.

60

80

100

120

1999 2001 2003 2005 2007 2009 2011 2013 2015

Emerging Market Currencies (nominal)

Fiscal deficits

become persistent


18 October 2016 51

What’s next for EM economies? An extended period of subdued growth: The major six emerging market economies’

aggregate real GDP growth is expected to trend around 4.6% pa 2017-20, some 2.8% pa less

than the 7.4% pa achieved over 2003-11.

Versus the ten advanced economies, the real GDP growth premium was +5.2% pa over

2003-11, falling to an expected +2.9% over 2013-18. Contributions from all three growth

accounting factors (labour supply, capital accumulation, and total factor productivity) are

fading.

Fig 115 Seven negative headwinds for emerging market economies since 2011

1) The headwind from falling commodity prices since 2011

2) The turn in the EME credit cycle post the 22 May 2013 to 28 June 2013 ‘Taper tantrum’

3) The deceleration in global industrial production growth since early 2014 has led to a fading of the export growth engine

4) The US$, which had been appreciating gradually since mid-2011, rose rapidly from mid-2014 through end-2015

5) Oil prices breaking decisively through US$100 from July 2014

6) Declining import volumes into China since early 2015 partially reflecting import substitution. Whilst not a net negative for EM economies initially, second round effects such as the tightening of policy by countries suffering deteriorating trade balances is a negative.

7) The start of a US Fed Funds policy interest rate up-cycle since December 2015, which puts upward pressure on nominal local rates in fixed/semi-fixed exchange rate regimes

Note: Remembering the good times: The 2009-11 commodity price boom, a weak US$ facilitating access to global capital markets and strong credit growth had enabled rapid growth to persist across the EM economies. However, over the past five years, conditions have become progressively tougher


Emerging market economies (EME) have been battered by seven negatives since 2011, table

above. Whilst some of these are abating, two new headwinds worry us: falling property values

with the credit down-cycle, and declining FDI inflows as the elevated global investment-to-

GDP ratio adjusts.

These are headwinds for consumption and investment, respectively.

Fig 116 Real residential property prices, YoY growth

Note: Housing price movements are deflated by the CPI. Aggregates are weighted by GDP in current US$. Advanced consists of 10 advanced countries (US, Japan, Germany, France, Italy, Spain, UK, Aust, Canada and South Korea) and emerging consists of 6 emerging countries (Brazil, Mexico, Russia, Turkey, India and China). 16-Total is the sum of advanced and emerging countries. ASEAN consists of 5 ASEAN countries (Indonesia, Malaysia, Singapore, Philippines and Thailand).

Source: BIS, IMF, Macquarie Research, October 2016

-12

-9

-6

-3

0

3

6

9

12

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016

(%) Advanced Emerging 16-Total ASEAN

Two new headwinds

worry us:

1) Falling

property

values with

the credit

down-cycle

2) Declining FDI

inflows as the

elevated global

investment-to-GDP

ratio adjusts

These are

headwinds for

consumption and

investment,

respectively


18 October 2016 52

Global private investment indicators This is a six-page section, as we believe that there is widespread misunderstanding about the

existing elevated level of global private investment. Given the relative volatility of private

investment, this implies that it is the major downside risk to global growth.

Lead indicators of capital expenditure

We are unaware of any composite global machinery order indicators. We present indicators

for the US, China, Germany and Japan. The overall impression is one of softness.

We believe Germany is the key series to follow, Fig 119, below (bottom), for the reasons

shown in Fig 117 and Fig 118.

On the basis of exports as a percentage of that country’s GDP, Germany is the most exposed

to emerging markets, at roughly 11.0%, Fig 117. Japan has the highest exports to GDP ratio

to China but emerging markets in total are just 7%. The US is approximately 5%.

Fig 117 Emerging Market export exposures Fig 118 Germany: Goods exports to China

Source: Oxford Economics/Haver Analytics, Macquarie Research, October 2016

Source: Oxford Economics/Haver Analytics, Macquarie Research, October 2016

Fig 119 shows trends in Germany, which are currently a little beneath zero.

Fig 119 Germany VDMA plant & machinery orders, 1999 to latest

Source: VDMA, Bloomberg, Macquarie Research, October 2016

Fig 120 is the well-known US non-defence capital goods orders (excluding aircraft). The case

for excluding aircraft orders relates to both the lumpiness of orders historically and the long

lag between order receipt and the start of work on such orders.

Energy and other commodity-related capital expenditures are expected to stay weak, but the

fall is almost complete, in our opinion.

-40%

-30%

-20%

-10%

0%

10%

20%

30% Germany Plant&Machinery Orders(YoY%, 3mma)

The overall

impression is one of

softness


18 October 2016 53

Fig 120 US non-defence capital goods orders (excluding aircraft), 2000 to latest

Source: US Census Bureau, Macquarie Research, October 2016

Japanese machinery orders are broadly stable to soft; Fig 121 and Fig 122.

For Larry Hu’s recent insights on the China business cycle, please see his Macro Monday

reports from which Fig 123 and Fig 124 come.

Fig 121 Japanese machinery orders: total (¥tr) Fig 122 ...and by geography (¥tr)

Source: CAO, Macquarie Research, October 2016 Source: CAO, Macquarie Research, October 2016

Fig 123 Chinese fiscal spending Fig 124 Chinese fixed asset investment


-30

-25

-20

-15

-10

-5

0

5

10

15

20 (YoY%, 3mma) Non-defence capital goods orders, ex aircraft

1.2

1.4

1.6

1.8

2.0

2.2

2.4

2.6

2.8

3.0

04/0

5

10/0

5

04/0

6

10/0

6

04/0

7

10/0

7

04/0

8

10/0

8

04/0

9

10/0

9

04/1

0

10/1

0

04/1

1

10/1

1

04/1

2

10/1

2

04/1

3

10/1

3

04/1

4

10/1

4

04/1

5

10/1

5

04/1

6

(¥tr)Machinery orders (total, SA)

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

04/0

5

11/0

5

06/0

6

01/0

7

08/0

7

03/0

8

10/0

8

05/0

9

12/0

9

07/1

0

02/1

1

09/1

1

04/1

2

11/1

2

06/1

3

01/1

4

08/1

4

03/1

5

10/1

5

05/1

6

Domestic Overseas

(¥tr)

-10

-5

0

5

10

15

20

25

30

35

40

Fe

b-1

3

Ma

y-1

3

Au

g-1

3

No

v-1

3

Fe

b-1

4

Ma

y-1

4

Au

g-1

4

No

v-1

4

Fe

b-1

5

Ma

y-1

5

Au

g-1

5

No

v-1

5

Fe

b-1

6

Ma

y-1

6

Au

g-1

6

Fiscal spending

% yoy

2013: 10.9% 10.5%

2014: 8.2%

2015: 13.2%

-5

0

5

10

15

20

25

30

Jun

-14

Au

g-1

4

Oct-

14

Dec-1

4

Fe

b-1

5

Apr-

15

Jun

-15

Au

g-1

5

Oct-

15

Dec-1

5

Feb-1

6

Apr-

16

Jun

-16

Au

g-1

6

Overall FAI Manufacturing

Infrastructure Real Estate

% yoy FAI


18 October 2016 54

The following charts from the IMF include residential investment; 2015-16 are IMF forecasts

Please note that at the global level, private investment is already at elevated levels.

Fig 125 World investment (US$tr) Fig 126 World investment (% of current GDP)


Fig 127 Advanced economies’ investment (US$ tr)

Fig 128 Advanced economies’ investment (% of current GDP)


Fig 129 US investment (US$tr) Fig 130 US investment (% of current GDP)


0

5

10

15

20

25

1980

1982

1984

1986

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1990

1992

1994

1996

1998

2000

2002

2004

2006

2008

2010

2012

2014

2016

(US$tr) World investment

20

21

22

23

24

25

26

27

19

80

19

82

19

84

19

86

19

88

19

90

19

92

19

94

19

96

19

98

20

00

20

02

20

04

20

06

20

08

20

10

20

12

20

14

20

16

(%)World investment, % of GDP

0

2

4

6

8

10

12

1980

1982

1984

1986

1988

1990

1992

1994

1996

1998

2000

2002

2004

2006

2008

2010

2012

2014

2016

(US$tr) Advanced economies, investment

15

17

19

21

23

25

27

1980

1982

1984

1986

1988

1990

1992

1994

1996

1998

2000

2002

2004

2006

2008

2010

2012

2014

2016

(%) Advanced economies, investment, % of GDP

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

1980

1982

1984

1986

1988

1990

1992

1994

1996

1998

2000

2002

2004

2006

2008

2010

2012

2014

2016

(US$tr) US's investment

10

12

14

16

18

20

22

24

26

1980

1982

1984

1986

1988

1990

1992

1994

1996

1998

2000

2002

2004

2006

2008

2010

2012

2014

2016

(%GDP) US's investment, % of GDP


18 October 2016 55

Anxiety normally revolves around China, which is the difference between a currently strong

level of world investment activity, Fig 126, and the depressing picture presented in Fig 128.

As Fig 129 and Fig 130 show, the IMF has positive 2015-16 growth forecasts for the US.

Fig 131 World investment by economic groups

Fig 132 World investment by economic groups (% of current GDP)


Fig 133 Emerging & developing economies’ investment (US$tr)

Fig 134 Emerging & developing economies’ investment (% of current GDP)


Fig 135 China’s investment (US$tr) Fig 136 China’s investment, % of GDP


0

5

10

15

20

25

1980

1982

1984

1986

1988

1990

1992

1994

1996

1998

2000

2002

2004

2006

2008

2010

2012

2014

2016

(US$tr) Emerging and developing economies investment

Advanced economies, investment

15

17

19

21

23

25

27

29

31

33

35

1980

1982

1984

1986

1988

1990

1992

1994

1996

1998

2000

2002

2004

2006

2008

2010

2012

2014

2016

(%) Advanced economies, investment, % of GDP

Emerging and developing economies investment, % of GDP

0

2

4

6

8

10

12

1980

1982

1984

1986

1988

1990

1992

1994

1996

1998

2000

2002

2004

2006

2008

2010

2012

2014

2016

(US$tr) Emerging and developing economies investment

20

22

24

26

28

30

32

34

1980

1982

1984

1986

1988

1990

1992

1994

1996

1998

2000

2002

2004

2006

2008

2010

2012

2014

2016

(%)

Emerging and developing economies investment, % of GDP

0.0

1.0

2.0

3.0

4.0

5.0

6.0

1980

1982

1984

1986

1988

1990

1992

1994

1996

1998

2000

2002

2004

2006

2008

2010

2012

2014

2016

(US$tr) China's investment

25

30

35

40

45

50

1980

1982

1984

1986

1988

1990

1992

1994

1996

1998

2000

2002

2004

2006

2008

2010

2012

2014

2016

(%GDP) China's investment, % of GDP


18 October 2016 56

Whilst China is still growing in absolute terms (Fig 135, previous page), a slow rebalancing of

the economy is underway (Fig 136). EM ex China has been stagnant, 2011-15, Fig 137.

Fig 137 Emerging and developing economies ex China investment

Fig 138 Emerging and developing economies ex China investment, % of GDP


Fig 139 India’s investment Fig 140 India’s investment, % of GDP

Source: IMF WEO database, Macquarie Research, October 2016 Source: IMF WEO database, Macquarie Research, October October 2016

Fig 141 Brazil’s investment Fig 142 Brazil’s investment, % of GDP


0.0

1.0

2.0

3.0

4.0

5.0

6.0

1980

1982

1984

1986

1988

1990

1992

1994

1996

1998

2000

2002

2004

2006

2008

2010

2012

2014

2016

(US$tr) Emerging and developing economies ex China

15

17

19

21

23

25

27

29

1980

1982

1984

1986

1988

1990

1992

1994

1996

1998

2000

2002

2004

2006

2008

2010

2012

2014

2016

(%) Emerging and developing economies ex China, % of GDP

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

1980

1982

1984

1986

1988

1990

1992

1994

1996

1998

2000

2002

2004

2006

2008

2010

2012

2014

2016

(US$tr) India's investment

15

20

25

30

35

40

45

1980

1982

1984

1986

1988

1990

1992

1994

1996

1998

2000

2002

2004

2006

2008

2010

2012

2014

2016

(%GDP) India's investment, % of GDP

0.0

0.1

0.2

0.3

0.4

0.5

0.6

1980

1982

1984

1986

1988

1990

1992

1994

1996

1998

2000

2002

2004

2006

2008

2010

2012

2014

2016

(US$tr) Brazil's investment

10

12

14

16

18

20

22

24

26

1980

1982

1984

1986

1988

1990

1992

1994

1996

1998

2000

2002

2004

2006

2008

2010

2012

2014

2016

(%GDP) Brazil's investment, % of GDP


18 October 2016 57

Fig 143 Russia’s investment Fig 144 Russia’s investment, % of GDP


Fig 145 Indonesia’s investment Fig 146 Indonesia’s investment, % of GDP


Fig 147 Investment by World ex China

Fig 148 Investment by World ex China, % of GDP


0.0

0.1

0.2

0.3

0.4

0.5

1980

1982

1984

1986

1988

1990

1992

1994

1996

1998

2000

2002

2004

2006

2008

2010

2012

2014

2016

(US$tr) Russia's investment

10

15

20

25

30

35

40

1980

1982

1984

1986

1988

1990

1992

1994

1996

1998

2000

2002

2004

2006

2008

2010

2012

2014

2016

2018

2020

(%GDP) Russia's investment, % of GDP

0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

1980

1982

1984

1986

1988

1990

1992

1994

1996

1998

2000

2002

2004

2006

2008

2010

2012

2014

2016

(US$tr) Indonesia's investment

0

5

10

15

20

25

30

35

40

45

501980

1982

1984

1986

1988

1990

1992

1994

1996

1998

2000

2002

2004

2006

2008

2010

2012

2014

2016

(%GDP) Indonesia's investment, % of GDP

0

4

8

12

16

19

80

19

82

19

84

19

86

19

88

19

90

19

92

19

94

19

96

19

98

20

00

20

02

20

04

20

06

20

08

20

10

20

12

20

14

20

16

(US$tr)

Investmet by World ex China

18

19

20

21

22

23

24

25

26

27

19

80

19

82

19

84

19

86

19

88

19

90

19

92

19

94

19

96

19

98

20

00

20

02

20

04

20

06

20

08

20

10

20

12

20

14

20

16

(% GDP)

Investment by World ex China, % of GDP


18 October 2016 58

Local factors determine core inflation One popular perspective holds a global view of inflation - that global slack determines local

inflation. However, there is significant evidence that local conditions drive underlying inflation.

For example, Fig 149 shows that divergence in CPI-services for the US and the eurozone. Of

personal consumption expenditures in advanced economies, three-quarters is on services.

Fig 149 A dramatic divergence between the US and Euro area services inflation


We believe Fig 150 explains the confusion. Currently, the average pair-wise correlation on

core inflation measures is near zero, and near 40-year lows. At the same time, the average

pair-wise correlation on headline inflation measures is as elevated today as during the first oil

shock of the early 1970s. From late 2014 until February 2016 oil prices plunged 80%.

Fig 150 International synchronisation of inflation (headline and core)

Notes: From Bank of England Governor, Mark Carney’s speech at the 2015 Jackson Hole symposium: Inflation in a globalised world. Average pair-wise rolling (15 years) correlation of seasonally-adjusted quarterly headline and core inflation. Source: OECD, Global Financial Data, DataStream, National sources, and Bank Staff calculation

Source: BoE, Macquarie Research, October 2016

We believe that core inflation is driven locally, through the influence of local output gaps and

the slack in the local labour market.

The US: The CPI services for the US, shown in Fig 149, reflects the acceleration in US wage

growth, following six years of employment growth above labour force growth, and the

unemployment rate approaching full employment.

The eurozone: Conversely, the tightening of fiscal policy in the eurozone over 2011-13 and a

second credit crunch there during 2011-12, leaves the eurozone approximately four years

behind the US in the business cycle. Nonetheless, we are forecasting accelerating eurozone

inflation from 0.0% in 2015, to 0.5% this year, and to 1.5% in 2017.

0%

1%

2%

3%

4%

5%

1998 2000 2002 2004 2006 2008 2010 2012 2014 2016

1998-2011 correl = +0.47 2012-16 correl = -0.55

Services CPI

US

Euro area

We believe that core

inflation is driven

locally, through the

influence of local

output gaps and the

slack in the local

labour market

Of personal

consumption

expenditures in

advanced

economies, three-

quarters is on

services


18 October 2016 59

Income shares: from labour to capital To the benefit of capital, there has been a 5% decline in the labour share globally since 1980,

Fig 151.

We believe the main driver has been technology, facilitated by globalisation with MNCs as the

main agents of change. As a consequence, MNCs have been the major beneficiaries.

Fig 151 Declining global labour share: 0.65 means 65%

Note: Loukas Karabarbounis & Brent Neiman, The global decline of the labour share, June 2013. “The figure shows year fixed effects from a regression of corporate and overall labour shares that also include country fixed effects to account for entry and exit during the sample. The regressions are weighted by corporate gross value added and GDP measured in U.S. dollars at market exchange rates. We normalize the fixed effects to equal the level of the global labour share in our dataset in 1975”

Source The global decline of the labour share above, Macquarie Research, October 2016

MNCs are a global macro dimension needing attention. The last 30 years have seen the

emergence of global oligopolistic competition. Following waves of M&A activity, the top MNCs

now dominate their global markets, entrenching their position by undertaking the vast

proportion of R&D in their industries. The result is the control of leading technologies and

brands.

We believe one consequence of global oligopolistic competition is to limit the diffusion of new

techniques and labour productivity growth across the economy.

Fig 152 Labour productivity growth: the issue of diffusion

Note: Each line shows the average labour productivity (value added per worker). The “Top 5%” and “Top 100” are the globally most productive firms in each two-digit industry. “Non-frontier firms” is the average of all firms, excluding the Top 5%. Included industries are manufacturing and business services, excluding the financial sector. The coverage of firms in the dataset varies across the 24 countries in the sample and is restricted to firms with at least 20 employees. Source: OECD preliminary results based on Andrews, D., C. Criscuolo and P. Gal (2016), “Mind the Gap: Productivity Divergence between the Global Frontier and Laggard Firms”, OECD Productivity Working Papers, forthcoming; Orbis data of Bureau van Dijk Source: OECD, Macquarie Research, October 2016

We believe one

consequence of

global oligopolistic

competition is to

limit diffusion of

new techniques,

labour productivity

growth across the

economy

The last 30 years

have seen the

emergence of global

oligopolistic

competition

We believe the main

driver has been

technology,

facilitated by

globalisation with

MNCs as the main

agents of change

There has been a

5% decline in the

labour share

globally since 1980


18 October 2016 60

The corporate saving “glut” Savings-Investment balances, net lending/borrowing by sector, the net acquisition of financial

assets (NAFA) are terms used interchangeably in the literature.

The corporate sector in most advanced economies is running a savings-investment surplus.

We believe this is an unintended by-product of the monetary policy response to credit bubble/

busts that transfers income from the household sector to the corporate sector: the lowering of

policy interest rates to near zero and the flattening of the yield curve.

The corporate sector in Japan is a representative example. Japan’s data goes back to 1994,

just far enough to capture the swing from net investing (borrowing) to net saving (lending),

below. Looking at the numbers:

The ¥35.4tr swing over 1994-2013 from annual net borrowing (-¥2.0bn) to net lending

(¥33.4bn, pale red highlights) compares to reduced interest payments of ¥28.6tr (from

¥32.2bn to ¥3.6bn, blue highlights).

We’ve also highlighted (in orange) how the surplus of gross fixed capital formation over

consumption of fixed capital has shrunk from ¥11.9tr in 1994 to ¥2.0tr in 2013.

In turn, this narrowing of ¥9.9tr reflects a gradual upward drift in the consumption of fixed

capital charge (¥2.7tr) and a marked fall in gross fixed capital formation (¥7.2tr).

Dividend payments increased from ¥4.6tr in 1994 to ¥15.1tr in 2013, for an increase over the

period of ¥10.5tr.

So rather than paying interest, non-financial corporations have paid down net debt.

Rather than growing their fixed capital base, non-financial corporations have paid out

dividends.

Fig 153 Non-financial corporations’ flow of funds (¥tr), 1994 to latest available (2013)

CY 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003

Gross fixed capital formation 72.9 74.5 75.6 81.1 74.7 70.6 74.2 71.0 64.6 65.3 Consumption of fixed capital 61.0 59.5 60.2 63.3 64.9 64.0 63.7 63.6 63.3 61.8 changes in inventories -1.4 1.6 2.2 2.5 1.4 -3.5 -0.5 -0.1 -1.9 -0.4 purchases of land, net -7.7 3.9 -3.1 0.5 -0.2 -0.3 9.3 5.7 -4.9 3.7 Net lending/net borrowing -2.0 -13.7 -2.5 -8.3 22.3 9.3 3.4 3.8 28.4 21.5 Net saving -3.7 1.7 6.7 8.3 5.2 11.7 17.3 13.2 19.7 24.0 Net capital transfers 4.5 5.0 5.2 4.3 28.1 0.4 5.6 3.7 3.3 4.3 Interest payable 32.2 28.8 23.8 21.9 17.3 13.9 12.1 9.4 7.0 6.3 Dividends 4.6 5.1 5.2 5.2 5.0 5.6 4.8 5.3 7.1 6.8

CY 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

Gross fixed capital formation 66.3 69.2 73.4 76.9 74.8 62.2 61.2 62.6 64.8 65.7 Consumption of fixed capital 61.8 62.2 64.4 66.5 68.6 67.7 65.0 63.4 62.8 63.7 changes in inventories 1.7 0.5 -0.5 1.7 2.9 -5.2 1.1 -1.7 -0.9 -2.8 purchases of land, net -1.8 -8.7 -0.1 5.1 3.8 5.3 -0.6 5.8 0.2 2.2 Net lending/net borrowing 29.8 32.0 17.7 13.1 12.5 29.9 39.3 27.4 33.5 33.4 Net saving 31.4 28.0 24.0 28.1 23.3 22.1 33.0 27.2 31.6 31.5 Net capital transfers 2.7 2.8 2.1 2.1 2.1 2.5 3.0 3.5 3.3 3.3 Interest payable 5.3 4.6 4.9 5.8 5.1 4.8 4.7 4.2 3.7 3.6 Dividends 9.3 13.0 15.7 16.4 14.3 11.6 11.9 11.3 13.5 15.1

Source: CAO, ESRI, CEIC, Datastream, Macquarie Research October 2016

The corporate savings “glut”: variations by geography

Fig 154 presents the US data. In the case of the US, below, the weakness of investment post

the TMT Bubble (1998-2001) led to a small corporate surplus over the years 2002-05. The

post Global Financial Cycle corporate Saving-Investment surpluses, however, have been

much more substantial, 2-3% versus 1%. The corporate surplus calculation used in Fig 154 is

net of both dividend payments and share buy-back activity.

The corporate

sector in most

advanced

economies is

running a savings-

investment surplus

….an unintended

by-product of the

monetary policy

response to credit

bubble/busts that

transfers income

from the household

sector to the

corporate sector

The US


18 October 2016 61

Fig 154 Net lending of US non-financial corporations

Note: Savings (the blue line) is calculated as the undistributed profits of non-financial corporations, that is after-tax profits less dividends to shareholders. Investment (the red line) represents spending by non-financial companies on capital formation. Any excess of savings over investment represents net lending to the rest of the economy, the black bars at the bottom of the charts. More precisely:

Source: Gruber, Joseph W., and Steven B. Kamin (2015). The Corporate Saving Glut in the Aftermath of the Global Financial Crisis International Finance Discussion Papers 1150, Macquarie Research, October 2016

Japan is as has been indicated earlier: A rapid growth in gross saving since the 1987-1991

bubble-bust, and a trend decline in gross investment. The trend decline in investment in

Japan began a decade earlier in Japan than in the USA (1991 versus 2001). The post-GFC

corporate Saving-Investment surplus has averaged 5%.

Germany has seen similar trends, a trend increase in gross savings, a trend decrease in

gross investment, but the latter could be described two ways: either as a very mild downtrend

since 1991, or broadly sideways until the Global Financial Crisis, and then a step-decline

thereafter. However, the German corporate sector surplus is less than 1%.

The trends are far from uniform. Canada has seen a trend improvement in gross savings,

but gross investment has been broadly stable. The UK does not appear to have experienced

a trend improvement in gross savings, but a trend decline in gross investment has occurred.

Both Canada and UK do have corporate sector surpluses, of 1-2%.

However, since 1990 the corporate sectors in both France and Italy have had persistent

deficits of 2-3%. As a consequence, a weighted average of the corporate Saving-Investment

balances for the three euro-zone majors of Germany, France and Italy is mildly negative.

We believe the above is facilitating global cross-border M&A, which in 2015 was 40% above

its previous high of 2007. We expect 2016 to be another year of intense cross-border M&A,

with the trend towards global oligopolistic competition amongst MNCs continuing.

Fig 155 Total & cross-border M&A, 2007 to latest

Total M&A (US$bn) Cross-border M&A (US$bn) % of cross-border M&A to

total M&A Global Japan Global Japan Global Japan

2007 2391.6 111.7 1050.3 52.4 43.9 46.9 2008 1398.9 138.2 569.4 87.1 40.7 63.1 2009 1033.3 85.2 286.5 38.4 27.7 45.1 2010 1369.9 82.0 551.6 51.7 40.3 63.0 2011 1465.8 139.1 556.2 94.5 37.9 67.9 2012 1405.4 123.5 598.8 89.6 42.6 72.5 2013 1489.5 78.1 468.0 62.1 31.4 79.6 2014 2400.9 71.9 1075.4 58.3 44.8 81.2 2015 3429.4 127.3 1298.0 102.8 37.9 80.7

2016 YTD 1404.3 84.5 624.4 66.9 44.5 79.2

Note: Data for Japan from RECOF. Cross-border for Japan is both In-Out and Out-In.

Source: FactSet, RECOF, Macquarie Research, October 2016

Japan

Germany

Canada, U.K.

France and Italy

We expect 2016 to

be another year of

intense cross-

border M&A


18 October 2016 62

Global income distribution Income gains have varied markedly over the 20 years since 1988, Fig.156. The relative

winners have been “the top 1%” and the one-fifth of the world’s population in the 40th to 60th

percentile range. In nine out of ten cases, the latter live in the emerging Asia economies of

China, India, Thailand, Vietnam and Indonesia, and are around the median income earners in

their countries. Whilst they are often referred to in the media as the “emerging global middle

class” they are still economically below the lower middle class of the rich nations, as

commonly understood.

Fig 156 Relative gain in real per capita income by global income level, 1988-2008

Note: World Bank Economic Review, Lakner, Christoph & Branko Milanovic, 2015, Global income distribution: From the fall of the Berlin Wall to the great Recession. The following notes come from the book Global inequality by Branko Milanovic:

This graph shows relative (percentage) gain in household per capita income (measured in 2005 international dollars) between 1988 and 2008 at different points of the global income distribution (ranging from the poorest ventile, at 5, to the richest global percentile, at 100). Real income gains were greatest around the 50th percentile of the global income distribution (the median; at point A) and among the richest (the top 1%; at point C). They were lowest among people who were around the 80th percentile globally (point B), most of whom are in the lower middle class of the rich world

Source: World Bank above, Macquarie Securities, October 2016

The relative losers are the lower middle class of the rich nations, who cluster around the 80th

percentile, point B above. As a consequence estimates of global income distribution have

shown declined inequality, but increased inequality in advanced economies such as the US.

Please note that US inequality is currently much lower than global inequality.

Fig 157 Global and US inequality, 1820-2011

Note: This graph shows global and US income inequalities (calculated across world and US citizens, respectively). In the recent period, global inequality is decreasing while US inequality is going up.

Sources: Milanovic Branko: Global inequality, page 124, with the 2003, 2008 and 2013 estimates and the 2035 forecast for global inequality from the paper The future of worldwide income distribution, April 2015, by Tomas Hellebrandt and Paolo Mauro

Source: Various as noted above, Macquarie Research, October 2016

0

10

20

30

40

50

60

70

80

90

100

0 10 20 30 40 50 60 70 80 90 100

Cum

ulat

ive

gain

in re

al i

ncom

e (in

%)

Ventile/percentile of global income distribution

A

B

C

30

35

40

45

50

55

60

65

70

75

1800 1850 1900 1950 2000 2050

US inequality Global (B-M series) Global (L-M series) Global (H-M series)

The relative winners

have been “the top

1%” and the one-

fifth of the world’s

population in the

40th to 60th

percentile range

The relative losers

are the lower middle

class of the rich

nations, who cluster

around the 80th

percentile

As a consequence

estimates of global

income distribution

have shown

declined inequality,

but increased

inequality in

advanced

economies such as

the US

Please note that US

inequality is

currently much

lower than global

inequality


18 October 2016 63

Demographic Tectonics Demographic Tectonic reports so far have included:

a) China – A V-shaped age profile

b) ASEAN – The rise of ASEAN affluence

c) Japan – Aging Japan it’s wonderful (the Affluent Elderly)

d) India – The young and restless

The affluent Elderly

To focus on the Affluent Elderly, for those that have prepared well for retirement, this

demographic cluster has both the cash-flow and the time to be a prime consumer. One

example is Japan. The Affluent Elderly are approximately 20% of Japan’s population, and

30% of annual consumption. Their total income in 2015 at US$1tr makes them equal to about

half the size of Italian GDP, and unlike Italy, the Affluent Elderly in Japan remains a growing

market.

Fig 158 The Affluent Elderly: a massive market that will continue to grow

Persons, by household head age and income bracket (millions) 2005 2015 2025 2025 vs 2015

65+ with income $50,000 to $120,000 13.3 18.4 20.0 +1.6

65+ with income $120,001 plus 3.0 5.0 5.7 +0.7

Affluent Elderly households’ total 16.3 23.4 25.7 +2.3

Affluent Elderly households’ total

household income (US$ billions) 629 1,022 1,223 +201

Note: The total income of the above affluent, elderly in 2015 at US$1tr makes them equal to about half the size of Italian GDP

Source: Global Demographics Ltd, Macquarie Research, October 2016

This group are consumers of premium services and goods: a) luxury brands, b) increased

quality of living through the progressive upgrading in the unit size of dwellings and the overall

building and furnishing standards; and c) increased wellness & health expenditures –

increased expenditures on wellbeing, covering everything from skin care and nutritional

supplements through to medical expenses.

The global labour supply

This is a demographic headwind.

Fig 159 Global changes in working age populations (2025 less 2015)

Note: To calculate working age population we have used the definition of 15-64 years for economies including Africa, Central & South America, Developing Asia, India, North Africa & Middle East and South Asia. For the rest, we have used the definition of 15-74 years to calculate working age population as the life expectancy in these countries is higher

Source: Global Demographics, Macquarie Research, October 2016

100

5344 39 35

2814

1 0

-1 -5

-29

-60

-20

20

60

100

140

Ind

ia

No

rth

Afr

ica

& M

idd

le E

as

t

Afr

ica

De

ve

lop

ing

Asia

So

uth

Asia

Ce

ntr

al

& S

ou

th A

me

rica

No

rth

Am

eri

ca

We

ste

rn E

uro

pe

Ru

ss

ia

Ea

ste

rn E

uro

pe

Aff

lue

nt

As

ia

Ch

ina

Persons mn

Affluent Elderly

demographic

opportunities


18 October 2016 64

The world’s working age population is now growing quite modestly, Fig 159. An extra 260m

over a decade on 4.6bn is approximately 0.5% pa. Please note the divergence in working

age populations, 2025 versus 2015, for India and China.

Fig 160 shows the impact of labour retirement ages.

Fig 161 shows the ongoing fade in growth of the working population in EM economies.

Fig 160 Global population & labour supply Fig 161 Annual growth in the working population

Note: from the December 2015, Bank of England staff working paper No. 571, Secular drivers of the global real interest rate by Lukasz Rachel and Thomas D Smith. Black lines shows growth in the global working aged 20 to retirement. Retirement ages are calculated using OECD data on average effective retirement ages. Over the future, global retirement ages are assumed to grow by one and a half years every decade to keep pace with expected rises in longevity

Source: UN population projections, OECD, Macquarie Research, October 2016

Source: Oxford Economics, Macquarie Research, October 2016

The US labour supply

One of David Doyle’s key themes has been lower potential growth for the United States, of

around 1.5% to 2% pa, with US labour force growth only able to provide 0.5% pa of that. Due

to an ageing population, the unemployment rate can be reduced by jobs growth as low as

55,000-115,000 per month.

Fig 162 The US labour force growth has been in a multi-decade decline

Source: Bureau of Labour Statistics, Macquarie Research, October 2016

-1.0%

0.0%

1.0%

2.0%

3.0%

4.0%

1971 1976 1981 1986 1991 1996 2001 2006 2011

Labour force growth YoY change in twelve month moving average

Due to an ageing

population, the

unemployment rate

can be reduced by

jobs growth as low

as 55,000-115,000

per month


18 October 2016 65

The Long Grinding Cycle continues We believe the pace of the current expansion should continue to prove to be structurally

lower than in previous cycles, as fiscal reconstruction, demographic factors, low productivity

growth and sub-optimal global policy making are likely to remain as headwinds.

Fig 163 shows data since 1999, breaking real GDP growth down into contributing parts:

labour, “capital deepening” (labour quality, non-IT capital, IT capital) and total factor

productivity (TFP) growth. Fig 164 provides more detail on TFP.

Fig 163 Contributions of sources of growth to aggregate GDP growth, 1999-2014

GDP Growth Labour Labour Quality Non-IT Capital IT Capital TFP Growth

World

99-06 4.1 0.7 0.2 1.2 0.7 1.3 07-12 3.3 0.3 0.1 1.7 0.7 0.5 2012 3.0 0.6 0.1 1.7 0.7 -0.1 2013 3.1 0.5 0.1 1.7 0.7 0.0 2014 3.2 0.6 0.1 2.0 0.6 -0.2

Mature

99-06 2.7 0.3 0.2 0.8 0.6 0.8 07-12 0.9 -0.1 0.1 0.5 0.4 0.0 2012 1.1 0.4 0.1 0.4 0.4 -0.2 2013 1.4 0.2 0.1 0.4 0.5 0.2 2014 1.8 0.8 0.1 0.6 0.5 -0.2

EM economies

99-06 5.9 1.1 0.2 2.0 0.7 1.9 07-12 5.8 0.6 0.1 3.3 1.0 0.8 2012 4.7 0.7 0.1 3.3 0.9 -0.3 2013 4.6 0.7 0.1 3.3 1.0 -0.5 2014 4.3 0.4 0.1 3.6 0.8 -0.7

United States

99-06 3.0 0.3 0.2 0.7 0.7 1.0 07-12 0.8 -0.3 0.1 0.4 0.4 0.2 2012 2.3 1.0 0.1 0.3 0.4 0.5 2013 2.2 0.7 0.1 0.3 0.5 0.6 2014 2.4 1.1 0.1 0.6 0.4 0.1

Japan

99-06 1.2 -0.4 0.2 0.4 0.2 0.7 07-12 0.2 -0.4 0.1 0.1 0.3 0.2 2012 1.7 0.6 0.1 0.0 0.4 0.7 2013 1.6 0.0 0.1 0.1 0.4 1.0 2014 0.0 0.3 0.1 0.4 0.3 -1.2

Euro Area

99-06 2.2 0.5 0.2 0.7 0.4 0.4 07-12 0.3 -0.2 0.2 0.5 0.3 -0.4 2012 -0.8 -1.0 0.2 0.2 0.4 -0.6 2013 -0.5 -0.7 0.2 0.1 0.5 -0.5 2014 0.9 0.5 0.2 0.3 0.4 -0.4

China

99-06 10.4 0.3 0.2 4.4 1.2 4.4 07-12 9.6 0.0 0.1 5.8 0.9 2.7 2012 7.4 0.2 0.1 5.9 0.9 0.4 2013 7.4 0.4 0.1 5.8 0.9 0.1 2014 7.1 0.1 0.1 6.2 0.8 -0.1

India

99-06 6.6 1.8 0.2 2.6 0.6 1.3 07-12 7.4 0.1 0.2 3.4 1.0 2.7 2012 4.7 1.0 0.2 2.9 1.4 -0.7 2013 4.6 0.9 0.2 2.5 1.5 -0.5 2014 5.5 0.9 0.2 2.9 1.4 0.2

Brazil

99-06 2.8 1.3 0.1 0.8 0.9 -0.4 07-12 3.6 0.9 0.2 1.6 1.0 -0.1 2012 1.0 1.2 0.2 1.9 0.0 -2.2 2013 2.5 0.3 0.2 2.0 0.2 -0.2 2014 0.1 -0.1 0.2 2.0 0.3 -2.3

Source: The Conference Board Summary Table, Macquarie Research, October 2016

Fiscal reconstruction,

demographic factors,

low productivity

growth and sub-

optimal global policy

making are likely to

remain as headwinds

Ma

cq

ua

rie R

es

ea

rch

T

he

Glo

ba

l Macro

Outlo

ok

18

Octo

be

r 20

16

66

Fig 164 Growth of total factor productivity (TFP) per annum, %, aggregates weighted by GDP in current US$ shares

Country Name 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014

Advanced US 0.9 -0.1 1.0 1.8 2.0 1.3 0.2 -0.1 -0.9 -0.2 2.1 0.1 0.4 -0.2 0.1 Japan 1.2 -0.1 0.6 0.8 1.8 0.7 0.5 1.2 -1.0 -3.3 4.0 -0.5 0.7 1.0 -1.1 Germany 2.0 1.3 -0.1 -0.5 0.5 1.4 1.9 1.2 -0.5 -4.4 2.8 1.9 -0.3 -0.6 -0.2 France 1.7 -0.4 0.9 0.1 0.1 0.0 1.4 -0.4 -1.7 -2.6 0.9 0.6 -0.7 0.4 -0.9 Italy 1.6 -0.5 -1.9 -1.6 0.1 -0.4 -0.2 -0.5 -1.7 -4.0 1.9 0.3 -1.4 -0.5 -0.5 Spain -0.6 -1.2 -1.0 -0.7 -1.1 -1.0 -0.5 -0.5 -1.8 -1.6 0.4 -0.3 -0.5 -0.5 -0.2 UK 0.7 -0.1 0.4 1.9 0.5 0.1 1.2 0.4 -1.6 -4.3 0.8 0.4 -1.5 -0.5 0.0 Australia 0.0 0.8 0.9 -0.9 0.1 -1.2 -1s.6 -0.4 -1.5 -1.6 -1.1 -1.0 -0.7 -2.0 -1.7 Canada 1.2 -0.7 0.2 -0.6 -0.4 0.6 -0.6 -1.4 -1.6 -2.3 1.0 0.5 -0.8 -0.2 -0.3 S. Korea 2.4 0.4 3.3 1.8 2.4 1.9 2.3 3.5 2.0 -0.6 4.7 3.0 -3.1 2.5 -1.2

10-advanced total 1.1 0.0 0.6 0.9 1.2 0.7 0.5 0.2 -0.9 -1.7 1.8 0.2 -0.1 0.0 -0.2

Emerging Brazil 1.9 -0.2 0.3 -1.4 2.0 -0.7 -0.7 1.0 -0.9 -3.7 1.7 -1.0 -2.1 -0.4 -2.8 Mexico 3.4 -2.7 -3.5 -0.3 1.0 -0.9 1.4 -0.5 -3.5 -6.2 -0.6 0.7 -0.2 -2.3 -1.2 Russia 5.6 6.5 4.5 7.6 6.2 4.4 4.4 2.9 -0.2 -8.3 4.0 3.5 2.8 1.1 -0.3 Turkey 3.8 -8.7 3.9 2.4 3.9 0.6 -1.5 -1.8 -4.3 -8.0 3.6 2.1 -3.6 -1.3 -2.5 India 0.1 -1.2 -0.6 1.6 0.6 3.4 4.1 3.3 2.2 1.2 3.7 2.0 -0.6 0.8 China – Old series 3.3 4.7 5.9 7.8 2.7 3.5 4.6 5.9 2.2 1.8 2.7 2.0 0.5 0.4 -0.1

6-EM total 2.4 0.5 1.9 4.1 2.9 2.7 3.9 4.8 0.6 -2.6 5.3 3.5 0.1 0.2 -1.3

16-Total 1.3 0.0 0.8 1.3 1.5 1.1 1.1 1.2 -0.6 -1.9 2.7 1.2 -0.1 0.0 -0.6

Other Indonesia 1.6 0.2 1.9 1.9 0.5 2.4 1.1 -0.5 1.0 -0.6 0.9 2.3 1.5 -0.1 2.1 Malaysia 4.0 -2.6 1.9 2.0 3.8 2.5 2.0 2.5 1.6 -4.9 1.3 1.2 1.3 0.0 0.6 Singapore 4.0 -1.5 1.0 0.7 3.8 0.7 2.4 3.3 -0.3 -2.2 3.2 -1.8 3.7 3.2 1.4 Philippines 4.7 -7.3 3.2 3.7 8.4 5.0 2.5 3.7 -4.3 -4.1 8.1 1.7 -1.9 -0.3 -0.9 Thailand 2.9 1.2 2.8 4.3 2.3 1.0 1.1 1.5 -2.1 -4.0 4.5 -2.1 4.0 0.4 -0.3

ASEAN 5 -Total 3.2 -1.4 2.2 2.6 3.1 2.4 2.0 1.9 -0.6 -3.7 4.8 1.3 3.4 0.8 1.7

China – New series 1.3 0.5 3.8 1.1 1.7 0.7 3.8 3.6 -2.7 -0.5 3.1 -1.6 -3.3 -2.1 -2.7

Note: estimated as a Tornqvist index

Source: The Conference Board, IMF, Macquarie Research, October 2016

Fig 165 China’s growth of total factor productivity, (TFP) per annum, %

Country 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014

China - Old -0.6 2.4 4.6 3.4 3.4 8.0 -4.4 -1.1 -5.7 0.6 3.3 4.7 5.9 7.8 2.7 3.5 4.6 5.9 2.2 1.8 2.7 2.0 0.5 0.4 -0.1

China - New -4.5 1.1 4.1 2.9 1.1 2.0 -1.1 0.4 -6.3 -0.9 1.3 0.5 3.8 1.1 1.7 0.7 3.8 3.6 -2.7 -0.5 3.1 -1.6 -3.3 -2.1 -2.7


The Conference board provides an explanation of the methodological differences between the old and new series here: https://www.conference-board.org/retrievefile.cfm?filename=FAQ-for-China-GDP-vs4_10nov15.pdf&type=subsite. “The Maddison-Wu approach, which the Conference Board has adopted, reconstructs aggregate real GDP growth from the bottom-up, on a sector-by-sector basis. The biggest adjustments are for the industrial sector and the so-called “non-material services” sector, which includes banking & financing, real estate, professional services, education, healthcare, culture & entertainment services, and government services. We argue that the upward bias in the published GDP numbers in China is attributable to two sources: (1) a ‘misreporting effect” which accounts for about two-thirds of the upward bias; and (2) a “price effect” which accounts for the remaining one third. The price effect includes the adjustment for the “non-material services” sector, where the Conference Board has introduced judgemental labour productivity growth estimate of 1% pa 1982-91 and 2% from 1992 onwards – in line with common experience at China’s level of development. In contrast, the official data has 6% pa growth on average.”

Source: The Conference Board, Macquarie Research, October 2016


18 October 2016 67

TFP is the increase in the overall efficiency in production, reflecting innovation and the

adoption of new technologies. We are not productivity pessimists, as implied by the

discussion about innovation clusters/brain-belts on page 35.

However, TFP growth has been very weak recently, Fig 163 to Fig 165. TFP in the US has

fallen from 0.9% pa 2000-07 to 0.5% pa 2010-14 to zero pa 2013-14, Fig 166.

Fig 166 Growth of total factor productivity (TFP), per annum, %

2000-07 2010-14 2013-14 2013-14 minus 2000-07

Brazil 0.3 -0.9 -1.6 -1.9 Mexico -0.3 -0.7 -1.7 -1.4 Russia 5.3 2.2 0.4 -4.9 Turkey 0.3 -0.3 -1.9 -2.2 India 1.4 1.3 0.6 -0.8 China – old methodology 4.8 1.1 0.2 -4.6 China – new methodology 2.1 -1.3 -2.4 -4.5

US 0.9 0.5 0.0 -0.9


Source: The Conference Board, IMF, Macquarie Research, October 2016

This decline of 0.9% pa 2013-14 versus 2000-07 has been exceeded by all the major EM

economies with the exception of Turkey (-0.8% pa). Russia and China have seen TFP per

annum declines 2013-14 versus 2000-07 of over 4%. For a more extensive discussion,

please see the 19 April 2016: The Global Macro Outlook – The long grinding cycle, pages 41-

58. Fig 167 provides a decomposition of our global growth expectations.

Fig 167 Global growth and components, per annum, %, 2016-20

Labour supply

growth Capital

deepening TFP Total

Advanced economies 0.2 0.8 0.5 1.5

EM economies 0.8 2.3 1.0 4.0

Global 0.4 1.4 0.7 2.5

Note: Macquarie estimates. Weights used: advanced economies 0.6, EM economies 0.4. Pale red shading: most vulnerable, highest downside risk. Blue shading: most upside risk, in our opinion


Our real GDP growth forecasts by country are shown in Fig.168, which shows the aggregates

out to 2020. The long grinding cycle continues.

Fig 168 Real GDP growth for ten advanced economies and six emerging market economies, in current US$: The long grinding cycle continues

Note: Global real GDP growth (10-Advanced & 6-Emerging) is forecast to be 2.2% in 2016, 2.6% in 2017, and 2.7% in 2018. Macquarie forecasts where available. Please see Fig 169 and Fig 170 for the constituents & weights used. The above uses market exchange rates. Using PPP weights would boost the numbers by about 0.5-0.6% pa

Source: IMF, World Bank, OECD, Macquarie Research, October 2016

-6

-4

-2

0

2

4

6

8

10

12

2000 2002 2004 2006 2008 2010 2012 2014 2016 2018 2020

Advanced Emerging 16-Total(%)

Russia and China

have seen TFP per

annum declines

2013-14 versus

2000-07 of over 4%

The long grinding

cycle continues

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Fig 169 GDP in current US$ for 10-Advanced countries and 6-Emerging market economies. Also for the 5-ASEAN majors

Country Name

2000 % of total

2001 % of total

2002 % of total

2003 % of total

2004 % of total

2005 % of total

2006 % of total

2007 % of total

2008 % of total

2009 % of total

2010 % of total

2011 % of total

2012 % of total

2013 % of total

2014 % of total

2015 % of total

10-advanced countries (GDP in trillion) US 10.3 38% 10.6 40% 11.0 40% 11.5 37% 12.3 36% 13.1 35% 13.9 35% 14.5 33% 14.7 31% 14.4 32% 15.0 30% 15.5 29% 16.2 29% 16.8 30% 17.3 30% 17.9 32% Japan 4.7 18% 4.2 16% 4.0 14% 4.3 14% 4.7 13% 4.6 12% 4.4 11% 4.4 10% 4.8 10% 5.0 11% 5.5 11% 5.9 11% 6.0 11% 4.9 9% 4.6 8% 4.1 7% Germany 1.9 7% 1.9 7% 2.1 7% 2.5 8% 2.8 8% 2.9 8% 3.0 8% 3.4 8% 3.7 8% 3.4 8% 3.4 7% 3.8 7% 3.5 6% 3.7 7% 3.9 7% 3.4 6% France 1.4 5% 1.4 5% 1.5 5% 1.8 6% 2.1 6% 2.2 6% 2.3 6% 2.7 6% 2.9 6% 2.7 6% 2.6 5% 2.9 5% 2.7 5% 2.8 5% 2.8 5% 2.4 4% Italy 1.1 4% 1.2 4% 1.3 5% 1.6 5% 1.8 5% 1.9 5% 1.9 5% 2.2 5% 2.4 5% 2.2 5% 2.1 4% 2.3 4% 2.1 4% 2.1 4% 2.1 4% 1.8 3% Spain 0.6 2% 0.6 2% 0.7 3% 0.9 3% 1.1 3% 1.2 3% 1.3 3% 1.5 3% 1.6 3% 1.5 3% 1.4 3% 1.5 3% 1.4 2% 1.4 2% 1.4 2% 1.2 2% United Kingdom

1.5 6% 1.5 6% 1.7 6% 1.9 6% 2.3 7% 2.4 7% 2.6 7% 3.0 7% 2.8 6% 2.3 5% 2.4 5% 2.6 5% 2.6 5% 2.7 5% 3.0 5% 2.8 5%

Australia 0.4 2% 0.4 1% 0.4 1% 0.5 2% 0.6 2% 0.7 2% 0.7 2% 0.9 2% 1.1 2% 0.9 2% 1.1 2% 1.4 3% 1.5 3% 1.6 3% 1.5 2% 1.3 2% Canada 0.7 3% 0.7 3% 0.8 3% 0.9 3% 1.0 3% 1.2 3% 1.3 3% 1.5 3% 1.5 3% 1.4 3% 1.6 3% 1.8 3% 1.8 3% 1.8 3% 1.8 3% 1.6 3% S. Korea 0.6 2% 0.5 2% 0.6 2% 0.7 2% 0.8 2% 0.9 2% 1.0 3% 1.1 3% 1.0 2% 0.9 2% 1.1 2% 1.2 2% 1.2 2% 1.3 2% 1.4 2% 1.4 2%

(Advanced) 23.3 87% 23.1 87% 23.9 86% 26.6 86% 29.4 85% 30.9 84% 32.4 82% 35.0 79% 36.7 77% 34.8 76% 36.3 74% 38.8 71% 39.0 71% 39.1 69% 39.8 68% 38.0 68%

6-emerging market economies (GDP in trillion) Brazil 0.6 2% 0.6 2% 0.5 2% 0.6 2% 0.7 2% 0.9 2% 1.1 3% 1.4 3% 1.7 3% 1.6 4% 2.1 4% 2.5 5% 2.2 4% 2.2 4% 2.4 4% 1.8 3% Mexico 0.7 3% 0.7 3% 0.7 3% 0.7 2% 0.8 2% 0.9 2% 1.0 2% 1.0 2% 1.1 2% 0.9 2% 1.1 2% 1.2 2% 1.2 2% 1.3 2% 1.3 2% 1.1 2% Russia 0.3 1% 0.3 1% 0.3 1% 0.4 1% 0.6 2% 0.8 2% 1.0 2% 1.3 3% 1.7 3% 1.2 3% 1.5 3% 1.9 4% 2.0 4% 2.1 4% 2.0 3% 1.3 2% Turkey 0.3 1% 0.2 1% 0.2 1% 0.3 1% 0.4 1% 0.5 1% 0.5 1% 0.6 1% 0.7 2% 0.6 1% 0.7 1% 0.8 1% 0.8 1% 0.8 1% 0.8 1% 0.7 1% India 0.5 2% 0.5 2% 0.5 2% 0.6 2% 0.7 2% 0.8 2% 0.9 2% 1.2 3% 1.2 3% 1.4 3% 1.7 3% 1.8 3% 1.8 3% 1.9 3% 2.0 3% 2.1 4% China 1.2 4% 1.3 5% 1.5 5% 1.6 5% 1.9 6% 2.3 6% 2.7 7% 3.5 8% 4.5 10% 5.0 11% 5.9 12% 7.3 13% 8.2 15% 9.2 16% 10.4 18% 10.9 19%

(Emerging) 3.5 13% 3.6 13% 3.8 14% 4.3 14% 5.1 15% 6.1 16% 7.2 18% 9.1 21% 10.9 23% 10.7 24% 13.1 26% 15.5 29% 16.3 29% 17.5 31% 18.9 31% 17.9 31%

Total 26.9 26.7 27.7 30.9 34.5 37.0 39.6 44.1 47.5 45.5 49.4 54.3 55.3 56.7 58.7 55.9

5-Asean Countries (GDP in trillion) Indonesia 0.2 30% 0.2 30% 0.2 33% 0.2 35% 0.3 34% 0.3 34% 0.4 36% 0.4 36% 0.5 37% 0.5 39% 0.8 42% 0.9 43% 0.9 43% 0.9 41% 0.9 40% 0.9 40% Malaysia 0.1 17% 0.1 17% 0.1 17% 0.1 16% 0.1 16% 0.1 17% 0.2 16% 0.2 16% 0.2 17% 0.2 15% 0.3 14% 0.3 15% 0.3 14% 0.3 14% 0.3 15% 0.3 14% Singapore 0.1 17% 0.1 17% 0.1 15% 0.1 14% 0.1 15% 0.1 15% 0.1 15% 0.2 15% 0.2 14% 0.2 14% 0.2 13% 0.3 13% 0.3 13% 0.3 13% 0.3 14% 0.3 14% Philippines 0.1 15% 0.1 14% 0.1 14% 0.1 12% 0.1 12% 0.1 12% 0.1 12% 0.1 12% 0.2 12% 0.2 12% 0.2 11% 0.2 11% 0.3 12% 0.3 12% 0.3 13% 0.3 14% Thailand 0.1 22% 0.1 22% 0.1 21% 0.2 22% 0.2 22% 0.2 22% 0.2 22% 0.3 21% 0.3 21% 0.3 20% 0.3 19% 0.4 18% 0.4 18% 0.4 19% 0.4 18% 0.4 18%

5-ASEAN 0.6 100 0.5 100 0.6 100 0.7 100 0.8 100 0.8 100 1.0 100 1.2 100 1.4 100 1.4 100 1.8 100 2.1 100 2.2 100 2.2 100 2.2 100 2.1 100

Note: The GDP trillions numbers are to one decimal point, so rounding plays an important part in the ASEAN part of the table


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Fig 170 Real GDP growth (annual %), totals weighted by GDP in current US$ shares, Macquarie where available (shaded in grey)

Country Name 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020

Advanced US 1.9 -0.1 3.6 2.7 4.0 2.7 3.8 4.5 4.5 4.8 4.1 1.0 1.8 2.8 3.8 3.3 2.7 1.8 -0.3 -2.8 2.5 1.6 2.3 2.2 2.2 2.6 1.6 2.4 2.1 1.9 1.8 Japan 5.6 3.3 0.8 0.2 0.9 1.9 2.6 1.6 -2.0 -0.2 2.3 0.4 0.3 1.7 2.4 1.3 1.7 2.2 -1.0 -5.5 4.7 -0.5 1.8 1.6 0.4 0.6 0.4 0.6 0.7 0.8 0.8 Germany 5.3 5.1 1.9 -1.0 2.5 1.7 0.8 1.8 2.0 2.0 3.0 1.7 0.0 -0.7 1.2 0.7 3.7 3.3 1.1 -5.6 4.1 3.6 0.4 0.4 1.6 1.5 1.5 1.6 1.5 1.3 1.3 France 2.9 1.0 1.6 -0.6 2.3 2.1 1.4 2.3 3.6 3.4 3.9 2.0 1.1 0.8 2.8 1.6 2.4 2.4 0.2 -2.9 2.0 2.1 0.3 0.7 0.2 1.2 1.2 1.5 1.6 1.7 1.9 Italy 2.0 1.5 0.8 -0.9 2.2 2.9 1.3 1.8 1.6 1.6 3.7 1.8 0.3 0.2 1.6 0.9 2.0 1.5 -1.0 -5.5 1.7 0.6 -2.3 -1.7 -0.4 0.8 0.8 1.3 1.2 1.1 1.1 Spain 3.8 2.5 0.9 -1.0 2.4 2.8 2.7 3.7 4.3 4.5 5.3 4.0 2.9 3.2 3.2 3.7 4.2 3.8 1.1 -3.6 0.0 -0.6 -2.1 -1.2 1.4 3.1 3.1 2.5 2.2 2.0 1.9 UK 0.5 -1.2 0.4 2.6 4.0 2.5 2.7 2.6 3.5 3.2 3.8 2.7 2.5 4.3 2.5 2.8 3.0 2.6 -0.3 -4.3 1.9 1.6 0.7 1.7 2.9 2.2 2.0 1.2 1.2 1.6 1.7 Australia 3.5 -0.4 0.4 4.0 4.0 3.9 3.9 3.9 4.4 5.0 3.9 1.9 3.9 3.1 4.2 3.2 3.0 3.8 3.7 1.7 2.0 2.3 3.7 2.5 2.6 2.4 2.8 2.3 3.2 2.8 2.3 Canada 0.1 -2.1 0.9 2.6 4.6 2.7 1.7 4.3 4.1 5.0 5.1 1.7 2.8 1.9 3.1 3.2 2.6 2.0 1.2 -2.7 3.4 2.5 1.7 2.0 2.5 1.1 1.2 1.8 1.6 1.4 1.4 S. Korea 9.3 9.7 5.8 6.3 8.8 8.9 7.2 5.8 -5.7 10.7 8.8 4.5 7.4 2.9 4.9 3.9 5.2 5.5 2.8 0.7 6.5 3.7 2.3 3.0 3.3 2.6 2.9 2.9 2.7 2.6 2.6 10-Total 3.7 1.3 1.5 2.1 3.0 2.5 2.7 2.3 0.1 -3.6 2.9 1.5 1.4 1.5 1.7 2.0 1.5 1.9 1.8 1.7 1.6 Emerging Brazil -4.3 1.5 -0.5 4.7 5.3 4.4 2.1 3.4 0.0 0.3 4.3 1.3 2.7 1.1 5.7 3.2 4.0 6.1 5.2 -0.3 7.5 2.7 1.0 2.7 0.1 -3.0 -3.0 -1.0 2.3 2.4 2.5 Mexico 5.1 4.2 3.6 4.1 4.7 -5.8 5.9 7.0 4.7 2.7 5.3 -0.6 0.1 1.4 4.3 3.0 5.0 3.1 1.4 -4.7 5.1 4.0 4.0 1.4 2.1 2.3 2.3 2.8 3.1 3.2 3.3 Russia -3.0 -5.0 -14.5 -8.7 -12.6 -4.1 -3.6 1.4 -5.3 6.4 10.0 5.1 4.7 7.3 7.2 6.4 8.2 8.5 5.2 -7.8 4.5 4.3 3.4 1.3 0.6 -3.8 -3.8 -0.6 1.0 1.5 1.5 Turkey 9.3 0.7 5.0 7.7 -4.7 7.9 7.4 7.6 2.3 -3.4 6.8 -5.7 6.2 5.3 9.4 8.4 6.9 4.7 0.7 -4.8 9.2 8.8 2.1 4.2 2.9 3.0 3.0 2.9 3.7 3.5 3.5 India 5.5 1.1 5.5 4.8 6.7 7.6 7.5 4.0 6.2 8.8 3.8 4.8 3.8 7.9 7.9 9.3 9.3 9.8 3.9 8.5 10.3 6.6 5.1 6.9 6.7 7.2 7.6 7.8 7.7 7.5 7.5 China 3.8 9.2 14.2 14.0 13.1 10.9 10.0 9.3 7.8 7.6 8.4 8.3 9.1 10.0 10.1 11.3 12.7 14.2 9.6 9.2 10.4 9.3 7.7 7.7 7.2 6.8 6.7 6.4 6.0 6.0 6.0

6-Total 6.4 3.9 5.2 6.5 7.9 7.8 8.8 9.6 6.2 3.8 8.8 6.9 5.4 5.6 4.7 3.7 3.7 4.2 4.6 4.6 4.7

16-Total 4.1 1.7 2.0 2.7 3.7 3.4 3.9 3.8 1.5 -1.8 4.5 3.0 2.6 2.8 2.7 2.5 2.2 2.6 2.7 2.7 2.6

ASEAN Indonesia 9.0 8.9 7.2 7.3 7.5 8.4 7.6 4.7 -13.1 0.8 4.9 3.6 4.5 4.8 5.0 5.7 5.5 6.3 6.0 4.6 6.2 6.5 6.3 5.8 5.0 4.8 4.9 5.0 5.2 5.0 5.0 Malaysia 9.0 9.5 8.9 9.9 9.2 9.8 10.0 7.3 -7.4 6.1 8.9 0.5 5.4 5.8 6.8 5.3 5.6 6.3 4.8 -1.5 7.4 5.2 5.6 4.7 6.0 5.0 4.3 4.7 5.1 5.1 5.1 Singapore 10.0 6.7 7.1 11.5 10.9 7.0 7.5 8.3 -2.2 6.1 8.9 -1.0 4.2 4.4 9.5 7.5 8.9 9.1 1.8 -0.6 15.2 6.1 2.5 3.9 2.9 2.0 1.9 2.1 2.4 2.6 2.6 Philippines 3.0 -0.6 0.3 2.1 4.4 4.7 5.8 5.2 -0.6 3.1 4.4 2.9 3.6 5.0 6.7 4.8 5.2 6.6 4.2 1.1 7.6 3.7 6.8 7.2 6.1 5.9 6.2 6.1 6.3 6.0 6.0 Thailand 11.2 8.6 8.1 8.3 9.0 9.2 5.9 -1.4 -10.5 4.4 4.8 2.2 5.3 7.1 6.3 4.6 5.1 5.0 2.5 -2.3 7.8 0.1 7.7 1.8 0.9 2.8 3.2 3.3 3.5 3.5 3.5 5-ASEAN 6.2 1.9 4.7 5.4 6.5 5.5 5.9 6.5 4.3 1.2 8.0 4.8 6.0 4.8 4.2 4.2 4.3 4.4 4.6 4.5 4.5

Note: Totals are weighted by the respective year ‘GDP in current US$’ weights from Fig 169. 2016-20 use 2015 weights.


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Fig 171 CPI, YoY, forecasts Macquarie where available (shaded in grey), totals weighted by GDP in current US$ shares

Country Name 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020

Advanced US 5.4 4.2 3.0 3.0 2.6 2.8 2.9 2.3 1.6 2.2 3.4 2.8 1.6 2.3 2.7 3.4 3.2 2.9 3.8 -0.4 1.6 3.2 2.1 1.5 1.6 0.1 1.3 2.5 2.4 2.4 2.4 Japan 3.0 3.3 1.7 1.3 0.7 -0.1 0.1 1.8 0.7 -0.3 -0.7 -0.8 -1.3 0.2 0.0 -0.3 0.2 0.1 1.4 -1.3 -0.7 -0.3 0.0 0.4 2.8 0.8 -0.1 0.3 0.5 0.9 1.3 Germany 5.1 4.4 2.7 1.7 1.4 1.9 0.9 0.6 1.5 2.0 1.4 1.0 1.7 1.5 1.6 2.3 2.6 0.3 1.1 2.1 2.0 1.5 0.8 0.2 1.2 1.5 1.6 1.8 1.9 France 3.4 3.2 2.4 2.1 1.7 1.8 2.0 1.2 0.6 0.5 1.7 1.6 1.9 2.1 2.1 1.7 1.7 1.5 2.8 0.1 1.5 2.1 2.0 0.9 0.6 0.1 1.0 1.1 1.3 1.5 1.7 Italy 6.5 6.3 5.1 4.5 4.0 5.2 4.0 2.0 2.0 1.7 2.5 2.8 2.5 2.7 2.2 2.0 2.1 1.8 3.4 0.8 1.5 2.7 3.0 1.2 0.2 0.2 0.7 1.0 1.1 1.2 1.3 Spain 6.7 5.9 5.9 4.6 4.7 4.7 3.6 2.0 1.8 2.3 3.4 3.6 3.1 3.0 3.0 3.4 3.5 2.8 4.1 -0.3 1.8 3.2 2.4 1.4 -0.2 -0.3 0.9 1.0 1.2 1.4 1.5 UK 7.0 7.5 4.3 2.5 2.0 2.7 2.5 1.8 1.6 1.3 0.8 1.2 1.3 1.4 1.3 2.0 2.3 2.3 3.6 2.2 3.3 4.5 2.8 2.6 1.5 0.0 0.7 2.3 2.5 1.7 1.8 Australia 7.3 3.2 1.0 1.8 1.9 4.6 2.6 0.3 0.9 1.5 4.5 4.4 3.0 2.8 2.3 2.7 3.5 2.3 4.4 1.8 2.8 3.4 1.8 2.4 2.5 1.5 1.2 1.9 1.8 2.0 2.0 Canada 4.8 5.6 1.5 1.8 0.2 2.2 1.6 1.6 1.0 1.7 2.7 2.5 2.3 2.8 1.9 2.2 2.0 2.1 2.4 0.3 1.8 2.9 1.5 0.9 1.9 1.1 1.5 1.8 2.0 2.0 2.0 S. Korea 8.6 9.3 6.3 4.7 6.3 4.5 4.9 4.4 7.5 0.8 2.3 4.1 2.8 3.5 3.6 2.8 2.2 2.5 4.7 2.8 3.0 4.0 2.2 1.3 1.3 0.7 1.1 1.9 2.0 2.0 2.0 10-Total 2.1 2.0 1.3 1.8 2.0 2.3 2.4 2.2 3.2 0.0 1.4 2.5 1.8 1.4 1.5 0.3 1.0 1.9 1.9 2.0 2.0 Emerging Brazil 2948 432.8 951.6 1928 2076 66.0 15.8 6.9 3.2 4.9 7.0 6.8 8.5 14.7 6.6 6.9 4.2 3.6 5.7 4.9 5.0 6.6 5.4 6.2 8.9 8.9 6.3 5.2 5.0 4.8 4.6 Mexico 26.7 22.7 15.5 9.8 7.0 35.0 34.4 20.6 15.9 16.6 9.5 6.4 5.0 4.5 4.7 4.0 3.6 4.0 5.1 5.3 4.2 3.4 4.1 3.8 4.0 2.8 3.0 3.0 3.0 3.0 3.0 Russia 874.6 307.6 197.5 47.7 14.8 27.7 85.7 20.8 21.5 15.8 13.7 10.9 12.7 9.7 9.0 14.1 11.7 6.9 8.4 5.1 6.8 7.8 15.8 8.6 7.3 5.0 4.0 4.0 Turkey 60.3 66.0 70.1 66.1 106.3 88.1 80.3 85.7 84.6 64.9 54.9 54.4 45.0 25.3 10.6 10.1 9.6 8.8 10.4 6.3 8.6 6.5 8.9 7.5 8.9 7.4 7.0 6.5 6.5 6.5 6.5 India 9.0 13.9 11.8 6.4 10.2 10.2 9.0 7.2 13.2 4.7 4.0 3.7 4.4 3.8 3.8 4.2 6.1 6.4 8.4 10.9 12.0 8.9 9.3 10.9 6.7 4.9 5.2 5.0 5.0 5.0 5.0 China 3.1 3.5 6.3 14.6 24.2 16.9 8.3 2.8 -0.8 -1.4 0.3 0.7 -0.8 1.2 3.9 1.8 1.5 4.8 5.9 -0.7 3.3 5.4 2.7 2.6 1.5 1.5 2.0 2.0 2.5 2.5 2.5 6 -Total 9.4 7.9 6.6 6.9 5.7 5.2 4.5 5.6 7.6 3.9 5.5 6.3 4.5 4.8 4.3 4.2 3.7 3.4 3.6 3.5 3.4 16-Total 3.0 2.8 2.0 2.5 2.5 2.8 2.7 2.9 4.2 0.9 2.5 3.6 2.6 2.4 2.4 1.5 1.8 2.3 2.4 2.4 2.5 ASEAN Indonesia 7.8 9.4 7.5 9.7 8.5 9.4 8.0 6.2 58.4 20.5 3.7 11.5 11.9 6.6 6.2 10.5 13.1 6.4 9.8 4.8 5.1 5.4 4.3 6.4 6.5 6.4 4.1 4.9 5.0 5.0 5.0 Malaysia 2.6 4.4 4.8 3.5 3.7 3.5 3.5 2.7 5.3 2.7 1.5 1.4 1.8 1.0 1.5 3.0 3.6 2.0 5.4 0.6 1.7 3.2 1.7 2.1 2.1 2.1 2.7 2.8 2.6 2.5 2.5 Singapore 3.5 3.4 2.3 2.3 3.1 1.7 1.4 2.0 -0.3 0.0 1.4 1.0 -0.4 0.5 1.7 0.4 1.0 2.1 6.5 0.6 2.8 5.3 4.5 2.4 -0.4 -0.5 -0.3 1.0 1.4 1.5 1.5 Philippines 12.7 18.5 8.6 6.9 8.4 6.7 7.5 5.6 9.3 5.9 4.0 5.3 2.7 2.3 4.8 6.5 5.5 2.9 8.3 4.2 3.8 4.6 3.2 3.0 1.4 1.4 1.6 2.8 3.3 3.0 3.0 Thailand 5.9 5.7 4.1 3.3 5.0 5.8 5.8 5.6 8.0 0.3 1.6 1.6 0.7 1.8 2.8 4.5 4.6 2.2 5.5 -0.8 3.3 3.8 3.0 2.2 -0.8 -0.9 0.3 1.7 2.2 2.0 2.0 5-ASEAN 2.5 5.0 4.7 3.2 3.8 5.9 7.1 3.7 7.5 2.4 3.8 4.7 3.6 4.0 2.9 2.8 2.2 3.2 3.4 3.4 3.3

Note: On the above data, for advanced countries the CPI increases at 1.8% pa1999-2020, emerging economies 5.3% and the 16-Total 2.6%. Brazil’s inflation 1990-1994 has been rounded to the nearest percent.

For advanced countries the GDP deflator increases at 1.5% pa1999-2014, emerging economies 6.8% and the 16-Total 2.5%

Source: World Bank, IMF, Macquarie Research, October 2016

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Fig 172 G20 real GDP growth softened over 3Q and 4Q 2015, YoY based on quarterly data

2011 2012 2013 2014 2015 2016

Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4

G20 4.8 4.3 3.9 3.5 3.5 3.2 3.0 2.6 2.6 2.9 3.2 3.6 3.5 3.3 3.2 3.1 3.2 3.2 3.1 3.0 3.1

Argentina 9.5 5.3 5.6 4.3 0.8 -3.7 -1.5 0.2 1.1 5.3 2.7 0.2 -1.0 -2.5 -4.0 -2.6 0.3 2.9 3.8 2.6 0.2

Australia 2.0 2.5 3.1 3.1 4.4 3.9 3.2 2.7 1.8 2.0 2.0 2.3 3.0 2.7 2.6 2.3 2.3 2.1 2.7 2.9 3.1

Brazil 5.0 4.7 3.5 2.6 1.6 1.0 2.6 2.6 3.0 3.8 2.8 2.5 2.5 -0.4 -1.0 -0.6 -2.2 -2.9 -4.4 -5.9 -5.1

Canada 3.1 2.8 3.5 3.1 2.4 2.6 1.4 0.7 1.7 1.8 2.3 3.1 2.2 2.7 2.5 2.4 2.0 1.0 1.0 0.3 1.1

China 10.2 9.9 9.4 8.7 8.0 7.5 7.4 8.0 7.8 7.5 7.9 7.6 7.3 7.4 7.1 7.2 7.0 7.0 6.9 6.8 6.7

France 2.8 2.1 1.9 1.5 0.4 0.3 0.2 0.0 0.0 0.9 0.7 0.9 0.9 0.4 0.7 0.7 1.3 1.1 1.1 1.3 1.3

Germany 5.6 3.7 3.3 2.4 0.9 0.8 0.6 0.1 -0.5 0.3 0.5 1.3 2.3 1.4 1.2 1.5 1.1 1.6 1.7 1.3 1.6

India 9.8 8.5 5.3 4.7 4.2 4.3 6.2 5.8 6.1 6.5 6.3 6.9 6.8 7.1 7.4 7.1 7.3 7.3 7.3 7.6 8.0

Indonesia 6.3 6.2 6.2 6.0 6.1 6.1 6.0 5.9 5.7 5.6 5.5 5.4 5.2 5.1 5.0 4.8 4.8 4.7 4.8 4.9 4.9

Italy 2.0 1.5 0.5 -1.1 -2.3 -3.2 -3.2 -2.7 -2.7 -2.0 -1.4 -0.9 -0.1 -0.2 -0.4 -0.4 0.1 0.6 0.8 1.1 1.0

Japan 0.1 -1.6 -0.5 0.3 3.3 3.5 0.3 0.0 0.1 1.1 2.1 2.1 2.4 -0.4 -1.5 -0.9 -0.9 0.7 1.8 0.8 0.0

Korea 4.8 3.7 3.4 2.9 2.6 2.4 2.1 2.1 2.2 2.7 3.2 3.5 3.9 3.5 3.3 2.7 2.4 2.2 2.8 3.1 2.8

Mexico 4.2 3.6 4.2 4.2 4.0 4.5 3.3 3.4 3.1 0.6 1.5 1.1 1.1 3.0 2.3 2.6 2.5 2.4 2.7 2.5 2.8

Russia 3.3 4.2 4.0 4.6 5.3 4.3 3.1 1.8 0.6 1.1 1.2 2.1 0.6 1.1 0.9 0.2 -2.8 -4.5 -3.7 -3.8 -1.2

Saudi Arabia .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..

South Africa 3.9 3.8 2.9 2.6 2.1 2.4 2.4 2.0 2.0 2.1 2.2 3.0 2.2 1.4 1.6 1.4 2.3 1.6 1.1 0.2 -0.6

Turkey 11.9 9.1 9.2 5.2 2.3 2.9 1.9 1.4 3.4 4.4 4.5 4.6 4.6 2.2 2.3 3.0 2.5 4.0 4.7 4.7 4.4

United Kingdom 2.3 1.3 1.2 1.3 1.2 1.0 1.8 1.3 1.5 2.1 1.7 2.4 2.6 3.1 3.1 3.5 2.9 2.3 2.0 1.8 2.0

United States 1.9 1.7 1.2 1.7 2.8 2.5 2.4 1.3 1.3 1.0 1.7 2.7 1.6 2.4 2.9 2.5 3.3 3.0 2.2 1.9 1.6

European Union (28 countries) 2.8 1.9 1.6 0.8 -0.1 -0.4 -0.6 -0.7 -0.6 0.1 0.5 1.1 1.5 1.3 1.3 1.4 1.7 1.9 1.9 2.0 1.8

Euro area (19 countries) 2.8 1.8 1.4 0.5 -0.5 -0.8 -0.9 -1.0 -1.1 -0.4 0.0 0.6 1.1 0.8 0.8 1.0 1.3 1.6 1.6 1.7 1.7

Note: all data from the OECD with the exception of the pale green highlighted numbers which come from National Statistics sources

Aggregates above use PPP weights. Using market exchange rates would reduce the G20 real GDP growth numbers by 0.5-0.6%

“The G7 was established in 1976 as an informal forum of seven major industrial economies: Canada, France, Germany, Italy, Japan, the United Kingdom and the United States of America. It was re-named the G8 after the entry of Russia in 1998. In March 2014, the G7 voted to suspend Russia in response to escalating tensions with Ukraine that led to Russia's annexation of Crimea. However, the suspension is designed to be temporary. Where the G7 seeks agreement on current economic issues based on the interests of those countries, the G20 reflects the wider interests of both industrial and emerging-market economies. The G20 is made up of the finance ministers and central bank governors of 19 countries: Argentina, Australia, Brazil, Canada, China, France, Germany, India, Indonesia, Italy, Japan, Mexico, Russia, Saudi Arabia, South Africa, South Korea, Turkey, the United Kingdom, the United States of America” - plus the EU (Source: the Telegraph newspaper)



18 October 2016 72

Important disclosures:

Recommendation definitions

Macquarie - Australia/New Zealand Outperform – return >3% in excess of benchmark return Neutral – return within 3% of benchmark return Underperform – return >3% below benchmark return Benchmark return is determined by long term nominal GDP growth plus 12 month forward market dividend yield

Macquarie – Asia/Europe Outperform – expected return >+10% Neutral – expected return from -10% to +10% Underperform – expected return <-10%

Macquarie – South Africa Outperform – expected return >+10% Neutral – expected return from -10% to +10% Underperform – expected return <-10%

Macquarie - Canada Outperform – return >5% in excess of benchmark return Neutral – return within 5% of benchmark return Underperform – return >5% below benchmark return

Macquarie - USA Outperform (Buy) – return >5% in excess of Russell 3000 index return

Neutral (Hold) – return within 5% of Russell 3000 index return Underperform (Sell)– return >5% below Russell 3000 index return

Volatility index definition*

This is calculated from the volatility of historical price movements. Very high–highest risk – Stock should be expected to move up or down 60–100% in a year – investors should be aware this stock is highly speculative. High – stock should be expected to move up or down at least 40–60% in a year – investors should be aware this stock could be speculative. Medium – stock should be expected to move up or down at least 30–40% in a year. Low–medium – stock should be expected to move up or down at least 25–30% in a year. Low – stock should be expected to move up or down at least 15–25% in a year. * Applicable to Asia/Australian/NZ/Canada stocks only

Recommendations – 12 months Note: Quant recommendations may differ from

Fundamental Analyst recommendations

Financial definitions

All "Adjusted" data items have had the following adjustments made: Added back: goodwill amortisation, provision for catastrophe reserves, IFRS derivatives & hedging, IFRS impairments & IFRS interest expense Excluded: non recurring items, asset revals, property revals, appraisal value uplift, preference dividends & minority interests EPS = adjusted net profit / efpowa* ROA = adjusted ebit / average total assets ROA Banks/Insurance = adjusted net profit /average total assets ROE = adjusted net profit / average shareholders funds Gross cashflow = adjusted net profit + depreciation *equivalent fully paid ordinary weighted average number of shares All Reported numbers for Australian/NZ listed stocks are modelled under IFRS (International Financial Reporting Standards).

Recommendation proportions – For quarter ending 30 September 2016

AU/NZ Asia RSA USA CA EUR Outperform 47.26% 55.50% 38.46% 45.47% 59.09% 48.21% (for US coverage by MCUSA, 8.20% of stocks followed are investment banking clients)

Neutral 38.01% 29.31% 42.86% 48.77% 37.88% 36.79% (for US coverage by MCUSA, 8.25% of stocks followed are investment banking clients)

Underperform 14.73% 15.19% 18.68% 5.76% 3.03% 15.00% (for US coverage by MCUSA, 8.00% of stocks followed are investment banking clients)

Company-specific disclosures: Important disclosure information regarding the subject companies covered in this report is available at www.macquarie.com/research/disclosures.

Analyst certification: We hereby certify that all of the views expressed in this report accurately reflect our personal views about the subject company or companies and its or their securities. We also certify that no part of our compensation was, is or will be, directly or indirectly, related to the specific recommendations or views expressed in this report. The Analysts responsible for preparing this report receive compensation from Macquarie that is based upon various factors including Macquarie Group Ltd total revenues, a portion of which are generated by Macquarie Group’s Investment Banking activities. General disclaimers: Macquarie Securities (Australia) Ltd; Macquarie Capital (Europe) Ltd; Macquarie Capital Markets Canada Ltd; Macquarie Capital Markets North America Ltd; Macquarie Capital (USA) Inc; Macquarie Capital Limited and Macquarie Capital Limited, Taiwan Securities Branch; Macquarie Capital Securities (Singapore) Pte Ltd; Macquarie Securities (NZ) Ltd; Macquarie Equities South Africa (Pty) Ltd; Macquarie Capital Securities (India) Pvt Ltd; Macquarie Capital Securities (Malaysia) Sdn Bhd; Macquarie Securities Korea Limited and Macquarie Securities (Thailand) Ltd are not authorized deposit-taking institutions for the purposes of the Banking Act 1959 (Commonwealth of Australia), and their obligations do not represent deposits or other liabilities of Macquarie Bank Limited ABN 46 008 583 542 (MBL) or MGL. MBL does not guarantee or otherwise provide assurance in respect of the obligations of any of the above mentioned entities. 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Recommendations contained in one type of research product may differ from recommendations contained in other types of research, whether as a result of differing time horizons, methodologies, or otherwise. Before making an investment decision on the basis of this research, you need to consider, with or without the assistance of an adviser, whether the advice is appropriate in light of your particular investment needs, objectives and financial circumstances. There are risks involved in securities trading. The price of securities can and does fluctuate, and an individual security may even become valueless. International investors are reminded of the additional risks inherent in international investments, such as currency fluctuations and international stock market or economic conditions, which may adversely affect the value of the investment. 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18 October 2016 73

distributed by Macquarie Capital (Europe) Ltd, which is authorised and regulated by the Financial Conduct Authority (No. 193905). Germany: In Germany, this research is issued and/or distributed by Macquarie Capital (Europe) Limited, Niederlassung Deutschland, which is authorised and regulated by the UK Financial Conduct Authority (No. 193905). and in Germany by BaFin. France: In France, research is issued and distributed by Macquarie Capital (Europe) Ltd, which is authorised and regulated in the United Kingdom by the Financial Conduct Authority (No. 193905). Hong Kong & Mainland China: In Hong Kong, research is issued and distributed by Macquarie Capital Limited, which is licensed and regulated by the Securities and Futures Commission. In Mainland China, Macquarie Securities (Australia) Limited Shanghai Representative Office only engages in non-business operational activities excluding issuing and distributing research. 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Asia Research Head of Equity Research

Peter Redhead (Global – Head) (852) 3922 4836

Jake Lynch (Asia – Head) (852) 3922 3583

David Gibson (Japan – Head) (813) 3512 7880

Conrad Werner (ASEAN – Head) (65) 6601 0182

Automobiles/Auto Parts

Janet Lewis (China) (852) 3922 5417

Zhixuan Lin (China) (8621) 2412 9006

Leo Lin (China) (852) 3922 1098

Takuo Katayama (Japan) (813) 3512 7856

James Hong (Korea) (822) 3705 8661

Amit Mishra (India) (9122) 6720 4084

Financials

Scott Russell (Asia) (852) 3922 3567

Dexter Hsu (China, Taiwan) (8862) 2734 7530

Elaine Zhou (Hong Kong) (852) 3922 3278

Keisuke Moriyama (Japan) (813) 3512 7476

Chan Hwang (Korea) (822) 3705 8643

Suresh Ganapathy (India) (9122) 6720 4078

Thomas Stoegner (65) 6601 0854 (Malaysia, Singapore)

Gilbert Lopez (Philippines) (632) 857 0892

Passakorn Linmaneechote (Thailand) (662) 694 7728

Conglomerates

David Ng (China, Hong Kong) (852) 3922 1291

Conrad Werner (Singapore) (65) 6601 0182


Consumer and Gaming

Linda Huang (Asia, China, Hong Kong) (852) 3922 4068

Zibo Chen (China, Hong Kong) (852) 3922 1130

Terence Chang (China, Hong Kong) (852) 3922 3581

Satsuki Kawasaki (Japan) (813) 3512 7870

Mike Allen (Japan) (813) 3512 7859

Kwang Cho (Korea) (822) 3705 4953

KJ Lee (Korea) (822) 3705 9935

Stella Li (Taiwan) (8862) 2734 7514

Amit Sinha (India) (9122) 6720 4085

Fransisca Widjaja (65) 6601 0847 (Indonesia, Singapore)

Karisa Magpayo (Philippines) (632) 857 0899

Chalinee Congmuang (Thailand) (662) 694 7993

Emerging Leaders

Jake Lynch (Asia) (852) 3922 3583

Aditya Suresh (Asia) (852) 3922 1265

Timothy Lam (China, Hong Kong) (852) 3922 1086

Mike Allen (Japan) (813) 3512 7859

Kwang Cho (Korea) (822) 3705 4953

Corinne Jian (Taiwan) (8862) 2734 7522

Marcus Yang (Taiwan) (8862) 2734 7532

Conrad Werner (ASEAN) (65) 6601 0182

Industrials

Janet Lewis (Asia) (852) 3922 5417

Patrick Dai (China) (8621) 2412 9082

Leo Lin (China) (852) 3922 1098

Kunio Sakaida (Japan) (813) 3512 7873

James Hong (Korea) (822) 3705 8661

Inderjeetsingh Bhatia (India) (9122) 6720 4087

Internet, Media and Software

Wendy Huang (Asia, China) (852) 3922 3378

David Gibson (Asia, Japan) (813) 3512 7880

Hillman Chan (China, Hong Kong) (852) 3922 3716

Nathan Ramler (Japan) (813) 3512 7875

Soyun Shin (Korea) (822) 3705 8659

Abhishek Bhandari (India) (9122) 6720 4088

Oil, Gas and Petrochemicals

Polina Diyachkina (Asia, Japan) (813) 3512 7886

Aditya Suresh (Asia, China) (852) 3922 1265

Anna Park (Korea) (822) 3705 8669

Duke Suttikulpanich (ASEAN) (65) 6601 0148

Isaac Chow (Malaysia) (603) 2059 8982

Pharmaceuticals and Healthcare

Abhishek Singhal (India) (9122) 6720 4086

Wei Li (China, Hong Kong) (852) 3922 5494

Property

Tuck Yin Soong (Asia, Singapore) (65) 6601 0838


Raymond Liu (China, Hong Kong) (852) 3922 3629

Wilson Ho (China) (852) 3922 3248

William Montgomery (Japan) (813) 3512 7864


Abhishek Bhandari (India) (9122) 6720 4088

Aiman Mohamad (Malaysia) (603) 2059 8986

Kervin Sisayan (Philippines) (632) 857 0893

Patti Tomaitrichitr (Thailand) (662) 694 7727

Resources / Metals and Mining

Polina Diyachkina (Asia, Japan) (813) 3512 7886

Coria Chow (China) (852) 3922 1181

Anna Park (Korea) (822) 3705 8669

Technology

Damian Thong (Asia, Japan) (813) 3512 7877

George Chang (Japan) (813) 3512 7854

Daniel Kim (Korea) (822) 3705 8641

Allen Chang (Greater China) (852) 3922 1136

Jeffrey Ohlweiler (Greater China) (8862) 2734 7512

Patrick Liao (Greater China) (8862) 2734 7515

Louis Cheng (Greater China) (8862) 2734 7526

Kaylin Tsai (Greater China) (8862) 2734 7523

Telecoms

Nathan Ramler (Asia, Japan) (813) 3512 7875

Danny Chu (Greater China) (852) 3922 4762

Soyun Shin (Korea) (822) 3705 8659

Chirag Jain (India) (9122) 6720 4352

Prem Jearajasingam (ASEAN) (603) 2059 8989

Kervin Sisayan (Philippines) (632) 857 0893

Transport & Infrastructure

Janet Lewis (Asia) (852) 3922 5417


Azita Nazrene (ASEAN) (603) 2059 8980

Utilities & Renewables

Alan Hon (Hong Kong) (852) 3922 3589


Prem Jearajasingam (Malaysia) (603) 2059 8989

Karisa Magpayo (Philippines) (632) 857 0899

Commodities

Colin Hamilton (Global) (44 20) 3037 4061

Ian Roper (65) 6601 0698

Jim Lennon (44 20) 3037 4271

Lynn Zhao (8621) 2412 9035

Matthew Turner (44 20) 3037 4340

Economics

Peter Eadon-Clarke (Global) (813) 3512 7850

Larry Hu (China, Hong Kong) (852) 3922 3778

Tanvee Gupta Jain (India) (9122) 6720 4355

Quantitative / CPG

Gurvinder Brar (Global) (44 20) 3037 4036

Woei Chan (Asia) (852) 3922 1421

Danny Deng (Asia) (852) 3922 4646

Per Gullberg (Asia) (852) 3922 1478

Strategy/Country

Viktor Shvets (Asia, Global) (852) 3922 3883

Chetan Seth (Asia) (852) 3922 4769


Erwin Sanft (China, Hong Kong) (852) 3922 1516

Peter Eadon-Clarke (Japan) (813) 3512 7850

Chan Hwang (Korea) (822) 3705 8643

Jeffrey Ohlweiler (Taiwan) (8862) 2734 7512


Jayden Vantarakis (Indonesia) (6221) 2598 8310

Anand Pathmakanthan (Malaysia) (603) 2059 8833


Conrad Werner (Singapore) (65) 6601 0182

Alastair Macdonald (Thailand) (662) 694 7753

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Sales - Japan Tokyo Sales

David Shirt (Head of Equities) (813) 3512 7922 Nick Cant (Head of Sales) (65) 6601 0210 Hiroyuki Yokoyama (813) 3512 7822 Tomohiro Takahashi (813) 3512 7823 Mark Wild (813) 3512 7820 George Hamada (813) 3512 7836 Alisaun Binder (813) 3512 7924 Eileen Lee (813) 3512 7921 Shunsuke Kuriyama (813) 3512 7919

Europe Sales

London

Ben Musgrave (Head of Japan Equity Sales) (44 20) 3037 4882 Daniel Pittorino (Head of Intl Equity Sales) (44 20) 3037 4831 Brent Smith (44 20) 3037 4887 Christina Lee (44 20) 3037 4873

Europe Sales

Geneva

Thomas Renz (41 22) 818 7712

US Sales

New York

Eric Roles (Head of Intl Equity Sales) (1 212) 231 2559 Jeff Seo (1 212) 231 2422 Alex Mirarchi (1 212) 231 2562 Jean Zhang (1 212) 231 6397

Boston

Jeff Evans (1 617) 598 2508 Shun Aonuma (1 617) 598 2535

San Francisco

Todd Narter (1 415) 835 1239 Paul Colaco (1 415) 762 5003

Japan Sales Trading

Christopher Miller (Head of Sales Trading) (813) 3512 7831 Mateen Chaudhry (813) 3512 7819 Takehiko Masuzawa (813) 3512 7837 Kazuya Kuramochi (813) 3512 7832 Christopher Schaffner (813) 3512 7838 Akihiro Ohara (813) 3512 7828 Mitsuharu Tanaka (813) 3512 7834 Naoya Kikuchi (813) 3512 7835 Scott Sakima (813) 3512 7915 Mike Keen (44 20) 3037 4905 Mike Gray (1 212) 231 2555 Chris Reale (1 212) 231 2616 Marc Rosa (1 212) 231 2531

This publication was disseminated on 17 October 2016 at 19:00 UTC.

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