Short Run Fluctuations

Chapter 5

Neoclassical Dichotomy

• Theory of macroeconomy where output is given by labor, capital, and TFP.

• TFP is given by R & D (and possibly allocative efficiency)

• Capital investment is given by real interest rates which is given by savings which is in turn given by demographic factors and the dynamics of future income.

• Labor is given by labor-leisure trade-off, real labor productivity and turnover in job market.

• No relationship between output between money, prices or inflation.

Long run output, Y

Yπ

Y

Business Cycles

Link

GDP in Millions of 2009 Chained Dollars

0

50,000

100,000

150,000

200,000

250,000

300,000

350,000

400,000

450,000

500,000

1973

1984

1995

2006

HK GDP

In chained (2009) dollars

Pattern of production.

• GDP is growing over time.• GDP growth is not smooth. Sometimes GDP is

above and sometimes below the long term growth path.

• GDP has seasonal pattern with production consistently concentrated in 4th quarter. Christmas given as an explanation.

• These movements are so large they hide less predictable short-term movements in the economy. Solution: Seasonal adjustment. Smooth out the average changes associated with the season.

0

100000

200000

300000

400000

500000

1975 1980 1985 1990 1995 2000 2005 2010

GDP_SA GDP

Output Gap

• Study of long-term growth focuses on explaining the secular upward movement in GDP.

• Business cycles examine fluctuations around that trend. Object of interest is the output gap, the % deviation of GDP from its long-term trend path.

ln tt

t

YGAP

TREND

Measuring Trend

• Simplest way to measure trend is to assume that it grows at a constant rate over time. Ln(TRENDt) = α0 + α1∙t →

ΔLn(TRENDt)= Ln(TRENDt)- Ln(TRENDt-1) = α1

• In theory, corresponds with BGP of neoclassical growth model where α1 is the growth rate of technology.

Estimating Trend

• Construct Data• LHS: The natural log of

GDP • RHS: Index of Time• Source: FRED Database• Note: USA Annual Data

used here for convenience. Can easily be applied to quarterly data.

GDP ln(GDP) t

1974 4319.6 8.370918 11975 4311.2 8.368972 21976 4540.9 8.420881 31977 4750.5 8.466005 41978 5015 8.520189 51979 5173.4 8.551285 61980 5161.7 8.549021 71981 5291.7 8.573895 81982 5189.3 8.554354 91983 5423.8 8.598552 101984 5813.6 8.667955 111985 6053.7 8.708425 121986 6263.6 8.74251 131987 6475.1 8.775719 141988 6742.7 8.816216 151989 6981.4 8.851005 161990 7112.5 8.869609 171991 7100.5 8.86792 181992 7336.6 8.900631 191993 7532.7 8.927009 201994 7835.5 8.96642 211995 8031.7 8.991151 221996 8328.9 9.027487 231997 8703.5 9.071481 241998 9066.9 9.112386 251999 9470.3 9.155916 262000 9817 9.191871 272001 9890.7 9.19935 282002 10048.8 9.215209 292003 10301 9.239996 302004 10703.5 9.278326 312005 11048.6 9.310059 32

Estimate Regression Model

• Estimate Regression: ln(Yt) = α0 + α1∙t +εt

• Regression coefficient is α1 =.03068SUMMARY OUTPUT

Regression StatisticsMultiple R 0.997438R Square 0.994883Adjusted R Square0.994713Standard Error0.020981Observations 32

ANOVAdf SS MS F Significance F

Regression 1 2.567735 2.567735 5833.186 6.25E-36Residual 30 0.013206 0.00044Total 31 2.580941

CoefficientsStandard Error t Stat P-value Lower 95%Upper 95%Lower 95.0%Upper 95.0%Intercept 6.952588 0.024981 278.3116 9.51E-53 6.90157 7.003607 6.90157 7.003607X Variable 1 0.03068 0.000402 76.37529 6.25E-36 0.029859 0.0315 0.029859 0.0315

Output Gap

• The output gap is the % deviation from trend ln(Yt)-ln(TRENDt) which corresponds with εt.

• Use the fitted residual as a measure of the output gap.

GDP ln(GDP) t ln(TREND) OutputGap1974 4319.6 8.370918 1 8.364 0.0071975 4311.2 8.368972 2 8.395 -0.0261976 4540.9 8.420881 3 8.425 -0.0041977 4750.5 8.466005 4 8.456 0.0101978 5015 8.520189 5 8.487 0.0341979 5173.4 8.551285 6 8.517 0.0341980 5161.7 8.549021 7 8.548 0.0011981 5291.7 8.573895 8 8.579 -0.0051982 5189.3 8.554354 9 8.609 -0.0551983 5423.8 8.598552 10 8.640 -0.0411984 5813.6 8.667955 11 8.671 -0.0031985 6053.7 8.708425 12 8.701 0.0071986 6263.6 8.74251 13 8.732 0.0101987 6475.1 8.775719 14 8.763 0.0131988 6742.7 8.816216 15 8.793 0.0231989 6981.4 8.851005 16 8.824 0.0271990 7112.5 8.869609 17 8.855 0.0151991 7100.5 8.86792 18 8.885 -0.0171992 7336.6 8.900631 19 8.916 -0.0151993 7532.7 8.927009 20 8.947 -0.0201994 7835.5 8.96642 21 8.977 -0.0111995 8031.7 8.991151 22 9.008 -0.0171996 8328.9 9.027487 23 9.039 -0.0111997 8703.5 9.071481 24 9.069 0.0021998 9066.9 9.112386 25 9.100 0.0121999 9470.3 9.155916 26 9.131 0.0252000 9817 9.191871 27 9.162 0.0302001 9890.7 9.19935 28 9.192 0.0072002 10048.8 9.215209 29 9.223 -0.0082003 10301 9.239996 30 9.254 -0.0142004 10703.5 9.278326 31 9.284 -0.0062005 11048.6 9.310059 32 9.315 -0.005

Deviations from Trend

8.2

8.4

8.6

8.8

9

9.2

9.4

1974

1976

1978

1980

1982

1984

1986

1988

1990

1992

1994

1996

1998

2000

2002

2004

ln(GDP) ln(TREND)

US OutputGap

-0.06

-0.04

-0.02

0

0.02

0.04

1974

1976

1978

1980

1982

1984

1986

1988

1990

1992

1994

1996

1998

2000

2002

2004

Estimating Trend HK GDP

• Construct Data• LHS: The natural log

of GDP• RHS: Index of Time• Source: • Note: Annual Data

used here for convenience. Can easily be applied to quarterly data.

GDP ln(GDP) t1961 82,121 11.31595 1

1962 93,750 11.44839 2

1963 108,479 11.59431 3

1964 117,772 11.67651 4

1965 134,834 11.8118 5

1966 137,187 11.8291 6

1967 139,503 11.84584 7

1968 144,226 11.87914 8

1969 160,503 11.98607 9

1970 175,299 12.07425 10

1971 187,844 12.14337 11

1972 207,627 12.2435 12

1973 233,178 12.35956 13

1974 238,488 12.38207 14

1975 239,471 12.38619 15

1976 278,332 12.53657 16

1977 311,170 12.64809 17

1978 337,258 12.7286 18

1979 376,461 12.83857 19

1980 415,388 12.93697 20

1981 454,388 13.02671 21

1982 467,941 13.0561 22

1983 495,643 13.11361 23

1984 544,737 13.20806 24

1985 548,633 13.21519 25

1986 609,183 13.31987 26

1987 690,849 13.44568 27

1988 749,189 13.52675 28

1989 765,837 13.54872 29

1990 795,693 13.58697 30

1991 841,004 13.64235 31

1992 892,247 13.7015 32

1993 946,167 13.76017 33

1994 1,003,063 13.81857 34

1995 1,026,066 13.84124 35

1996 1,069,088 13.88232 36

1997 1,123,144 13.93164 37

1998 1,055,459 13.86949 38

1999 1,082,436 13.89472 39

2000 1,168,506 13.97124 40

2001 1,174,317 13.9762 41

2002 1,195,936 13.99444 42

2003 1,231,886 14.02406 43

2004 1,336,185 14.10533 44

2005 1,430,815 14.17375 45

2006 1,531,255 14.2416 46

2007 1,629,092 14.30353 47

2008 1,666,664 14.32633 48

2009 1,622,322 14.29937 49

2010 1,735,399 14.36675 50

2009r

2010r

2005

2006

2007

2008

2001

2002

2003

2004

1997

1998

1999

2000

1993

1994

1995

1996

1989

1990

1991

1992

1985

1986

1987

1988

1981

1982

1983

1984

1977

1978

1979

1980

1973

1974

1975

1976

1969

1970

1971

1972

1965

1966

1967

1968

1961

1962

1963

1964

Estimate Regression Model

• Estimate Regression: ln(Yt) = α0 + α1∙t +εt

• Regression coefficient is α1 =.0255SUMMARY OUTPUT

Regression StatisticsMultiple R 0.985722R Square 0.971647Adjusted R Square0.971057Standard Error0.155519Observations 50

ANOVAdf SS MS F Significance F

Regression 1 39.78556 39.78556 1644.97 8.46E-39Residual 48 1.160937 0.024186Total 49 40.94649

CoefficientsStandard Error t Stat P-value Lower 95%Upper 95%Lower 95.0%Upper 95.0%Intercept 11.54049 0.044656 258.433 4.06E-77 11.4507 11.63028 11.4507 11.63028X Variable 1 0.061814 0.001524 40.55823 8.46E-39 0.058749 0.064878 0.058749 0.064878

Output Gap

• The output gap is the % deviation from trend ln(Yt)-ln(TRENDt) which corresponds with εt.

• Use the fitted residual as a measure of the output gap.

GDP ln(GDP) t Trend Gap1961 82,121 11.31595 1 11.60233 -0.286381

1962 93,750 11.44839 2 11.66417 -0.215783

1963 108,479 11.59431 3 11.72601 -0.131698

1964 117,772 11.67651 4 11.78785 -0.111344

1965 134,834 11.8118 5 11.84969 -0.03789

1966 137,187 11.8291 6 11.91153 -0.08243

1967 139,503 11.84584 7 11.97337 -0.127529

1968 144,226 11.87914 8 12.03521 -0.156073

1969 160,503 11.98607 9 12.09705 -0.110982

1970 175,299 12.07425 10 12.15889 -0.084642

1971 187,844 12.14337 11 12.22073 -0.077363

1972 207,627 12.2435 12 12.28257 -0.039072

1973 233,178 12.35956 13 12.34441 0.015147

1974 238,488 12.38207 14 12.40625 -0.024176

1975 239,471 12.38619 15 12.46809 -0.081902

1976 278,332 12.53657 16 12.52993 0.00664

1977 311,170 12.64809 17 12.59177 0.056325

1978 337,258 12.7286 18 12.65361 0.074993

1979 376,461 12.83857 19 12.71545 0.12312

1980 415,388 12.93697 20 12.77729 0.159678

1981 454,388 13.02671 21 12.83913 0.187577

1982 467,941 13.0561 22 12.90097 0.155127

1983 495,643 13.11361 23 12.96281 0.150801

1984 544,737 13.20806 24 13.02465 0.183408

1985 548,633 13.21519 25 13.08649 0.128695

1986 609,183 13.31987 26 13.14833 0.171544

1987 690,849 13.44568 27 13.21017 0.235507

1988 749,189 13.52675 28 13.27201 0.254737

1989 765,837 13.54872 29 13.33385 0.214875

1990 795,693 13.58697 30 13.39569 0.191279

1991 841,004 13.64235 31 13.45753 0.184822

1992 892,247 13.7015 32 13.51937 0.182128

1993 946,167 13.76017 33 13.58121 0.178964

1994 1,003,063 13.81857 34 13.64305 0.175519

1995 1,026,066 13.84124 35 13.70489 0.136353

1996 1,069,088 13.88232 36 13.76673 0.115587

1997 1,123,144 13.93164 37 13.82857 0.103072

1998 1,055,459 13.86949 38 13.89041 -0.020924

1999 1,082,436 13.89472 39 13.95225 -0.057525

2000 1,168,506 13.97124 40 14.01409 -0.042853

2001 1,174,317 13.9762 41 14.07593 -0.099733

2002 1,195,936 13.99444 42 14.13777 -0.14333

2003 1,231,886 14.02406 43 14.19961 -0.175553

2004 1,336,185 14.10533 44 14.26145 -0.156121

2005 1,430,815 14.17375 45 14.32329 -0.149535

2006 1,531,255 14.2416 46 14.38513 -0.143532

2007 1,629,092 14.30353 47 14.44697 -0.143437

2008 1,666,664 14.32633 48 14.50881 -0.182475

2009 1,622,322 14.29937 49 14.57065 -0.271281

2010 1,735,399 14.36675 50 14.63249 -0.265742

11.3

11.8

12.3

12.8

13.3

13.8

14.3

14.8

1961

1964

1967

1970

1973

1976

1979

1982

1985

1988

1991

1994

1997

2000

2003

2006

2009

ln(GDP) Trend

Business Cycles?

Gap

-0.4

-0.3

-0.2

-0.1

0

0.1

0.2

0.3

1961

1964

1967

1970

1973

1976

1979

1982

1985

1988

1991

1994

1997

2000

2003

2006

2009 Gap

Stochastic Trends

• Trend line may change over time, if long-run technology also changes.

• We want to distinguish between short-run deviations from trend from long-lasting changes in the trend path.

• Allow for a smoothly changing trend, known as a Hodrick Prescott trend. Examine Data in Growth Rates

HP Trend and ln(GDP)

11.2

11.6

12.0

12.4

12.8

13.2

13.6

14.0

14.4

65 70 75 80 85 90 95 00 05 10

ln(GDP) HPTREND

HP Filtered Output Gap

-.10

-.05

.00

.05

.10

65 70 75 80 85 90 95 00 05 10

GAP

Expenditure Cycles in the Closed Economy

• Planned Expenditure is C + I + G.• Investment is sensitive to the real interest rate.

Consumer spending is sensitive to disposable income YD = Y – T.

• Draw a planned expenditure curve that shows response of demand to GDP

IS Curve

• When the real interest rate rises, investment will fall. This, along with knock-on multiplier effects, will lead to a contraction in demand.

• IS curve maps out the relationship between real interest rate and demand for goods (taking into account the multiplier effect)

• Q: What shifts the IS curve?• A: Shifts in Fiscal Policy, optimism about future

income, expectations about future MPK, wealth effects of asset prices.

Planned Expenditure

IS

r

Y

MPr(π)

Y*

Monetary Policy Reaction Function

• Central bank controls the money supply.

• Central bankers set money supply in response to economic conditions.

• When economy is booming or prices are rising to quickly, central banks raise real interest rates.

( , )r MP Y

How does the central bank set real interest rates?

• The central bank participates in the money market to control the real interest rate.

• Central bank has control over the money supply M. If prices do not respond 1-for-1 with money (due to pricing stickiness), they can control the supply of real balances.

• From Baumol-Tobin, the demand for real balances is determined by nominal interest rates and output. Nominal interest rates are a function of real interest rates and expected inflation.

( ) ( )EM Y YP V i V r

Money Demand Curve

MP

( )EYV r

*MP

r(π,Y)

Money Market Equilibrium

• Equilibrium under fixed money supply: If real interest rate is higher than money market equilibrium, money supply will be higher than money demand. Households will not want to hold cash and will deposit it into banks. Banks with a surplus of liquidity will lower equilibrium rates.

• Equilibrium under interest target: Under interest rate targets, if money supply is higher than money demand at the desired real interest rate, the central bank must sell some of its holdings of interest paying assets (typically government bonds).

Increase in expected inflation

MP

( )EYV r

*MP

r(π)

Increase in Inflation

*MP

MP

( )EYV r

**MP

r(π,Y)

Increase in Output

*MP

MP

( )EYV r

r(π,Y)

**MP

Planned Expenditure

IS

r

Y

MP

r*(π)

Y*(π)

Inflation Rises

IS

r

Y

MP

r*(π)

Y*(π)

MPʹ

r**(πʹ)

Y**(πʹ)

Aggregate Demand Curve

• Negative relationship between inflation and output generated by monetary policy response to inflation.

Q: What causes AD curve to shift?

Answer

• Shifts in the IS curve

• Shifts in Monetary Policy

AD Curve

Y

π

Aggregate Supply Curve

• Keynesian model: Firms will increase output if the inflation rate is high.

• Positive relationship between inflation level and output is called AS curve.

• Fluctuations in output are caused by fluctuations in the AD curve which are in turn caused by fluctuations in the

Equilibrium

Y

π

SRAS

AD

π*

Y*

AD Curve Shifts

Y

π

SRAS

AD

π*

Y*

AD’

π**

Y**

Monetary Policy and the Demand Curve

Y

Sπ

π*

Y

Strong Stance

Weak Stance

Demand Curve/Supply Curve

Y

Sπ

π* Strong Stance

Weak Stance

Supply Curve

• The supply curve is based on the notion that wages are sticky.

• So far, we have thought of real wages as being determined in a competitive market with a supply curve and a demand curve for labor.

• In Keynesian theory, wages are set by contract. Workers choose a wage and firms hire as many workers as desired at that wage rate.

Inflation and Labor Demand

• Workers base wage demands on what they believe the price level will be. Workers are backward looking in their expectations Wt = w×Pt

E = w×Pt-1.

• Firms choose a quantity of workers so Wt = Pt×MPLt=w×Pt-1.

• In equilibrium,

1

1t tt t

t

w wMPL MPL

PP

Equilibrium Labor

L

MPL

1

w

L*

W

P

Inflation Rises, Real Wages Fall

L

MPL

1

w

L*L**

W

P

Inflation/Employment Tradeoff

• Keynesian economists perceived that the government faced a choice between high inflation on the one hand and unemployment on the other.

• If the government wanted to push up employment, they could (through expansionary monetary or fiscal policy) push out the demand curve if they were willing to bear the consequences in terms of inflation.

Tradeoff Inflation & Unemployment USA 1948-1969 Source: St. Louis Fed Database

0

1

2

3

4

5

6

7

8

-2 0 2 4 6 8

Inflation

Un

em

plo

ym

en

t R

ate

Critics• Critics of this business cycle theory pointed out

that the ability of the government to increase employment was based on the notion that workers would expect zero employment.

• Phelps and Friedman suggested that it might be more realistic to imagine that workers would have some forecast of inflation πE

t. Then they would demand wages that would maintain their standard of living in the face of this inflation. Wt = w×Pt

E = w×(1+ πEt ) ×Pt-1.

Inflation and inflation expectations

• Firms would hire workers up until that point where MPL = real wage.

• Inflation reduces real wages and increases employment only to the extent that it stays ahead of workers expectations.

• There is some level of employment (referred to as the natural level) and corresponding level of output (referred to as potential output) which prevails when output inflation equal expectation.

1

1

1

Et

t tt t

t

wMPL w MPL

PP

IA CurveYP

π

YAD

πE

Y*

SRAS

Supply Curve

• A more realistic supply curve rule, might say that output is above potential output only when inflation is above expected inflation.

• SRAS: πEt Expected Inflation

• Expectations Augmented Philips curve

πt = πEt + θ∙[yt – yP]

• Adaptive Expectations

πt = πt-1 + θ∙[yt – yP]

Short-run Inflation/Output Tradeoff

• But workers will demand wages that will support their real wages, which will require wage growth to keep up with expected inflation.

• Friedman says workers will base inflation expectations on inflation that has been observed in the past. π =πt-1

Adaptive Expectations

• Adaptive expectations generate some dynamics to inflation-output trade-off.

• In the short-run, an expansion in money growth will lead to an increase in inflation and output.

• But after a period, inflation expectations will increase, leading to more inflation. Eventually output will return to its long run level. – Only accelerating inflation can lead to long run output

increases. – Once the government increases money supply growth,

they cannot reduce inflation without incurring a recession.

Y

π

Y

ADt

πE

ADt’

μ ↑

SRASt

πt+1

SRASt+1

SRASt+2

πt+2

SRASt+∞

πt+∞

Breakdown in Inflation and Unemployment Relationship

0

2

4

6

8

10

12

0 2 4 6 8 10

Inflation

Un

emp

loye

men

t R

ate

Final Exam

Material including taxes, money demand, inflation, Keynesian model, rational expectations model

• 14/12/2011 12:30-15:00 LTF

• Semi-open book: 1 L4 paper w/ handwritten notes both sides, calculator, writing materials.