China KLEMS The First WORLD KLEMS Conference Harvard University 18-20 October 2010 Ren Ruoen Sun...
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Transcript of China KLEMS The First WORLD KLEMS Conference Harvard University 18-20 October 2010 Ren Ruoen Sun...
China KLEMS
The First WORLD KLEMS Conference
Harvard University
18-20 October 2010
Ren RuoenSun Linlin
BeiHang University, China .
Motivation
Whether China’s rapid growth after 1978 is mainly driven by productivity or factor accumulation.
• Mostly existing studies of China TFP using aggregate data.
• This project estimated TFP based on industry data Pursue the guidelines about the policy making for
improving industry international competitiveness Analyze the industry contribution to aggregate TFP Find what is the predominant source of China
industry economic growth (input growth or productivity)
Goals
• Compute industry TFP based on the estimation of output, capital input, labor input and intermediate input index
• Quantify input and TFP contributions to output growth for each industry
• Highlight data and conceptual issues with industry data
Background
• In 1986 when I was working on my Ph.D. dissertation I knew Professor Jorgenson’s papers on rental cost and investment function. In 1988 I started to work on the expenditure-side purchasing power parity (PPP) estimates between China and US, using ICP approach. This study was published in Review of Income and Wealth as Ren Ruoen and Chen Kai 1994. An Expenditure - based Bilateral Comparison of Gross Domestic Product between China and the United States.
Background
In 1993 I started to work on the production-side purchasing power parity (PPP) estimates between China and US, using ICOP approach and built the time series of comparative labor productivity between the two countries.
Background
This study was published by China Economic Review as Adam Szirmai and Ren Ruoen 2000. Comparative Performance in Chinese Manufacturing, 1980-1992.
Since 1994 I started to write a book (Ren Ruoen 1997. China's Economic Performance in an International Perspective) for the OECD Development Centre. In this book, I reconciled the two studies on PPPs from expenditure and production sides to develop a estimate of China’s GDP in US dollar and update it through 1994.
Background
• The first phase of the current project is ICPA -project funded by the Research Institute of Economy, Trade and Industry (RIETI), Tokyo, Japan, National Natural Science Foundation of China (grant no. 70173029, 70531010, 70521001) and the U.S. Environmental Protection Agency (EPA Work Order 3W-0258-NASX).
Background
• The ICPA –project has been focusing on an international comparison of productivity among Pan-Pacific countries to undertake a broad examination of the sources of economic growth and competitiveness through large-scale, internationally comparable databases of Pan-Pacific countries since 2001.
Background
• The estimation result is given in a chapter on the China in the book on Productivity in Asia: Economic Growth and Competitiveness edited by Dale Jorgenson, Masahiro Kuroda and Kazuyuki Motohashi, published by Edward Elgar Publishing in 2006 and in Cao, J., M. Ho, D. Jorgenson, R. Ren, L. Sun, X. Yue (2009) “Industrial and Aggregate Measures of Productivity Growth in China, 1982-2000,” Review of Income and Wealth, Volume 55, issue s1, 2009
Background
• The second phase of the current project is an international cooperation project on “International Comparison of Productivity among China, EU Countries and US and IGEM Study for China” funded by National Natural Science Foundation of China (grant no. 70620120444 )
Industry Productivity
• The method used in this study is described in detail in many book and papers (see Jorgenson, Gollop and Fraumeni, 1987, Jorgenson and Stiroh 2000, and Gu and Ho 2000, Jorgenson et al., 2005).
• The economy is divided into 33 sectors producing 33 different commodities.
Industry Productivity
• Gross output of sector j is assumed to be produced with a Hicks-neutral production function:
• Productivity growth
ln ln ln ln lnKjt Ljt Zjtjt jt jt jt jtd Y v d K v d L v d Z d A
1 1 1( ,.... , ,.... , ,.... )
1 33
jt jt jt kjt jt ljt jt njtY A f K K L L Z Z
j industries
Value-added Function
• The real value added of sector j is defined as output less an index of intermediate inputs :
• The following identity is implied:
ln ln lnjt Vjt jt Zjt jtd Y v d V v d Z
ln ln ln lnVjt jt Kjt jt Ljt jt jt
Kjt jt Ljt jtVjt
Yjt jt
v d V v d K v d L d A
P K P Lv
P Y
Input Index
• Express the growth rate of each input as the weighted average of the growth rates of individual components:
• Weights are given by the average shares of each component
1 1ln ln (ln ln ) X={K, L, Z} tt t t t
i iii
X X X Xv
Input Output Series
• First phase: Construct the output and input indices for sectors during 1981-2000.
•
• Second phase: Update the time series to 2005.
Input Output Series
• The NBS used the Material Product System (MPS) before 1987.
• Transformed to the System of National Accounts (SNA) after 1987.
• The IO time series were constructed with the National Bureau of Statistics of China.
Input-Output Time Series (First phase)• Compiled annual nominal value of industry input and
industry value-added, the final uses for total consumption, investment and net exports, for 1981-2000.
• Constructed 4 current value benchmark I-O tables (1981,1987, 1992, 1997) including A tables and U tables Consistent with the coverage and definitions of the 1997 I-O table and
scaled to the latest GDP series
• Constructed the 1981-2000 current value U tables based on the 4 benchmark tables
• Constructed the 1981-2000 real value U tables based on the current value U tables and price indices
• Estimated output and intermediate input index time series based on the I-O tables
Input-output series (Second Phase)
• Based on the suggestions made in our
workshop on Oct. 12, 2009, we made some
updates to our comparable Input-output table series .
• We compiled the IO table series from 2000 to 2005, based on the new 2005 extended IO table and 2004 Census coverage and results. we updated the former 1981 to 1999 IO table series into the same standard of the second phase.
Input-output series (Second Phase)
• The 2007 benchmark IO table has been published and has been changed in coverage and other details from the 2005 extended IO table.
• If we decide to expand our comparable IO table series till 2007, we need cooperate with NBS team to look into all the differences between our IO series and their new 2007
benchmark table and build up a new comparable IO series from 1981
to 2007.
Industry Output Index Results
Wide range of industry output growth rates varies from -0.176%(oil and gas extraction) to 22.10%
(electrical machinery) We compare two sub-period, 1982-1994,1994-2005. Some industry output growth decelerate Food and kindred products(11% to 7%); Apparel(19% to 7%); Paper
and allied(19% to 11%); Leather(19% to 9%);Communication(17% to 0%); Finance(15% to 2%).
Some industry output growth acceleratePetroleum and coal products(4% to 11%); Primary metal(9% to 14%);
Transportation(9% to 14%); Electric utilities(
9% to 14%)
-2.00-1.000.001.002.003.004.005.006.007.008.009.00
10.0011.0012.0013.0014.0015.0016.0017.0018.0019.0020.0021.0022.0023.0024.00
04 O
il an
d ga
s ex
trac
tion
01 A
gric
ultu
re
14 P
etro
leum
and
coa
l pro
duct
s
33 P
ublic
ser
vice
03 M
etal
and
non
-met
allic
min
ing
02 C
oal m
inin
g
27 C
omm
unic
atio
ns
07 T
extil
e m
ill p
rodu
cts
31 F
inan
ce In
sura
nce
and
Rea
l Est
ate
06 F
ood
and
kind
red
prod
ucts
05 C
onst
ruct
ion
25 M
isc.
man
ufac
turin
g
24 R
ubbe
r an
d m
isc
plas
tics
30 T
rade
29 G
as u
tiliti
es
28 E
lect
ric u
tiliti
es
13 C
hem
ical
s
26 T
rans
port
atio
n
17 P
rimar
y m
etal
18 F
abric
ated
met
al
16 S
tone
, cla
y, g
lass
32 O
ther
priv
ate
serv
ice
10 F
urni
ture
and
fixt
ures
09 L
umbe
r an
d w
ood
19 M
achi
nery
, non
-ele
ct
08 A
ppar
el
22 T
rans
port
atio
n eq
uipm
ent &
ord
nanc
e
23 In
stru
men
ts
12 P
rintin
g, p
ublis
hing
and
alli
ed
15 L
eath
er
21 M
otor
veh
icle
s
11 P
aper
and
alli
ed
20 E
lect
rical
mac
hine
ry
Industry output Growth(%)1981-2005
Note: Industries sorted by growth, in percentage points. Annex Table A1 in text.
Industry Intermediate Input Index Results
• Wide range of industry intermediate input and energy input growth rates varies from 7.93%(textile) to 18.08% (electrical
machinery) Varies from -0.52%(public service) to 14.16%(electrical
machinery)
• Intermediate input experienced stronger growth than capital input and labor input.
Industry Intermediate Input Index (%)1981-2005
0.001.002.003.004.005.006.007.008.009.00
10.0011.0012.0013.0014.0015.0016.0017.0018.0019.00
text
ile m
ill p
rodu
cts
agric
ultu
re
trad
e
publ
ic s
ervi
ces
food
s an
d ki
ndre
d pr
oduc
ts
rubb
er a
nd m
isc
plas
tics
oil a
nd g
as e
xtra
ctio
n
com
mun
icat
ion
mis
c m
fg
chem
ical
met
al a
nd n
onm
etal
lic m
inin
g
finan
ce in
sura
nce
and
real
est
ate
cons
truc
tion
fab.
,met
al
mot
. Veh
petr
oleu
m a
nd c
oal p
rodu
cts
prim
. Met
al
lum
ber
tras
p. E
quip
and
ord
nanc
e
coal
min
ing
mac
hine
ry
furn
iture
prin
ting
inst
rum
ent
appr
al
ston
e cl
ay ,g
lass
tran
spor
tatio
n
othe
r pr
ivat
e se
rvic
es
pape
r
leat
her
gas
elec
tric
al
elc.
Mac
hine
ry
Note: Industries sorted by growth, in percentage points.
Industry Energy Input Index (%)1981-2005
-2.00-1.000.001.002.003.004.005.006.007.008.009.00
10.0011.0012.0013.0014.0015.00
public
serv
ices
com
munic
atio
n
trasp. E
quip
and o
rdnance
agricultu
re
chem
ical
transport
atio
n
petr
ole
um
and c
oal p
roducts
finance in
sura
nce a
nd r
eal e
sta
te
instr
um
ent
trade
prim
. M
eta
l
oil
and g
as e
xtr
actio
n
lum
ber
constr
uctio
n
ele
ctr
ical
machin
ery
sto
ne c
lay ,gla
ss
fab. ,m
eta
l
oth
er
private
serv
ices
coal m
inin
g
furn
iture
textil
e m
ill p
roducts
rubber
and m
isc p
lastic
s
foods a
nd k
indre
d p
roducts
meta
l and n
onm
eta
llic m
inin
g
mis
c m
fg
mot. V
eh
printin
g
gas
leath
er
paper
appra
l
elc
. M
achin
ery
Note: Industries sorted by growth, in percentage points.
Labor Input Index
• Labor input is a divisia aggregate over workers distinguished by sex, age and education attainment using wages as weights.
• Sex: male, female• Educational attainment: college, high school, junior
high school, elementary school, no schooling.• Age: 16-34, 35-54, 55+
Labor input index
• Number of workers for benchmark is based on the Population Cencuses(1982,1990,2000), and Sample Population Surveys(1987,1995,2005).
• Number of workers of other years is estimated from the Labor Force of Society ( prior to 1990), the annual Population Change Surveys (since 1990).
• Hours data is from the 1995 Sample Population Survey, and incorporate the changes in institutional arrangement.
• Relative costs of different workers using the Chinese Household Income Project (CHIP) Surveys.
• Sum of different categories of workers is equal to the labor compensation of IO table for each industry.
Industry labor Input Index results
• Wide range of industry labor input growth rates varies from 1.18%(metal and nonmetallic
mining) to 13.16%(gas utilities)Larger labor growth for labor intensive
manufacturing (such as apparel, leather, lumber and wood), as well as energy sectors (gas , electrical), some service( communication , finance).
• We compare two sub-period, 1982-1994,1994-2005.
Labor input increase for all service industry. Labor input fell for agriculture, mining sectors,
and some manufacturing (chemical, machinery).
Industry Labor Input Index (%)1982-2005
0.00
1.00
2.00
3.00
4.00
5.00
6.00
7.00
8.00
9.00
10.00
11.00
12.00
13.00
14.00
met
al a
nd n
onm
etal
lic m
inin
g
mac
hine
ry
inst
rum
ent
ston
e cl
ay ,g
lass
agric
ultu
re
coal
min
ing
text
ile m
ill p
rodu
cts
chem
ical
mis
c m
fg
furn
iture
pape
r
fab.
,met
al
food
s an
d ki
ndre
d pr
oduc
ts
prim
. Met
al
petr
oleu
m a
nd c
oal p
rodu
cts
oil a
nd g
as e
xtra
ctio
n
prin
ting
rubb
er a
nd m
isc
plas
tics
cons
truc
tion
tran
spor
tatio
n
publ
ic s
ervi
ces
othe
r pr
ivat
e se
rvic
es
elec
tric
al
elc.
Mac
hine
ry
trad
e
lum
ber
leat
her
appr
al
tras
p. E
quip
and
ord
nanc
e
finan
ce in
sura
nce
and
real
est
ate
com
mun
icat
ion
mot
. Veh
gas
Note: Industries sorted by growth, in percentage points.
Capital Input Index
• Estimated the capital stock under the Perpetual Inventory Method with the geometrically declining pattern, classified by asset type – structure, equipment and auto
• Estimated the capital rental price with the help of the property compensation from the input-output series
• Aggregation of capital services over different asset types with the weight of capital rental price
Capital input index
• We adjust the “fixed asset investment” to “gross capital formation” of each industry.
• Asset price index comes from the NBS, the IO table series.
• Depreciation rate is estimated base on the asset life assumption.
• We estimate the land capital stock for agriculture.
• We consider the self-employed compensation problem during the internal rate of return estimation.
Industry Capital Input Index Results
• Wide range of industry capital input growth rates, service had a high capital accumulation speed. varies from 1.02%(machinery) to 15.91%
(communication)• We compare two sub-period, 1982-1994,1994-
2005. Most manufacturing experience higher capital input.
(apparel, lumber, furniture, paper, instrument, etc). Only few industries experience lower capital input.(metal and nonmetallic mining, oil and gas extraction,
finance insurance and real estate, other private services).
Industry Capital Input Index (%)1981-2005
0.001.002.003.004.005.006.007.008.009.00
10.0011.0012.0013.0014.0015.0016.0017.00
mac
hine
ry
agric
ultu
re
coal
min
ing
inst
rum
ent
rubb
er a
nd m
isc
plas
tics
tras
p. E
quip
and
ord
nanc
e
trad
e
text
ile m
ill p
rodu
cts
leat
her
furn
iture
prim
. Met
al
fab.
,met
al
prin
ting
met
al a
nd n
onm
etal
lic m
inin
g
chem
ical
lum
ber
petr
oleu
m a
nd c
oal p
rodu
cts
pape
r
mis
c m
fg
cons
truc
tion
appr
al
food
s an
d ki
ndre
d pr
oduc
ts
ston
e cl
ay ,g
lass
tran
spor
tatio
n
oil a
nd g
as e
xtra
ctio
n
mot
. Veh
elec
tric
al
elc.
Mac
hine
ry
com
mun
icat
ion
publ
ic s
ervi
ces
othe
r pr
ivat
e se
rvic
es
gas
finan
ce in
sura
nce
and
real
est
ate
Note: Industries sorted by growth, in percentage points.
Industry TFP Results
• Wide range of industry TFP growth rates varies from -9.71%(oil and gas extraction)
to 6.46%(electrical machinery) Many energy industries (oil and gas
extraction, gas, petroleum and coal products), and some service (finance, public service, communication) show negative TFP growth rate.
Some manufacturing especially ICT manufacturing see high TFP rates.( electrical manufacturing, machinery, motor vehicle, instrument, paper).
Industry TFP Results
• Compare 2 sub-period, 1982-1994,1994-2000.• Some industries TFP slowdown:
apparel, paper, leather, transportation equipment,
transportation, communication.• Few industries TFP accelerate:
coal mining, Primary metal, metal and nonmetallic mining.
Industry TFP Growth(%)1982-2005
-11.00-10.00
-9.00-8.00-7.00-6.00-5.00-4.00-3.00-2.00-1.000.001.002.003.004.005.006.007.008.00
oil a
nd g
as e
xtra
ctio
n
finan
ce in
sura
nce
and
real
est
ate
gas
publ
ic s
ervi
ces
petr
oleu
m a
nd c
oal p
rodu
cts
com
mun
icat
ion
cons
truc
tion
elec
tric
al
met
al a
nd n
onm
etal
lic m
inin
g
othe
r pr
ivat
e se
rvic
es
food
s an
d ki
ndre
d pr
oduc
ts
mis
c m
fg
appr
al
text
ile m
ill p
rodu
cts
coal
min
ing
agric
ultu
re
leat
her
prim
. Met
al
tran
spor
tatio
n
furn
iture
lum
ber
ston
e cl
ay ,g
lass
fab.
,met
al
chem
ical
rubb
er a
nd m
isc
plas
tics
prin
ting
tras
p. E
quip
and
ord
nanc
e
trad
e
pape
r
inst
rum
ent
mot
. Veh
mac
hine
ry
elc.
Mac
hine
ry
Note: Industries sorted by growth, in percentage points
Domar-Weighted TFP
China has a moderate productivity growth, Domar-weighted TFP growth is estimated at 3.89%. 1987-90, 1995-96 and 1999-2000 experienced
negative domar-weighted TFP TFP acceleration is obvious during the
beginning of reform, 1982-1985.
• Agriculture and electrical machinery – biggest contribution to aggregate TFP among 33 industries agriculture, for the largest average share of
gross output to total value-added over 1982-2005
Electrical machinery, for the fastest TFP growth rate over 1982-2005.
Domar-Weighted TFP
-15.00
-10.00
-5.00
0.00
5.00
10.00
15.0019
82-1
983
1983
-198
4
1984
-198
5
1985
-198
6
1986
-198
7
1987
-198
8
1988
-198
9
1989
-199
0
1990
-199
1
1991
-199
2
1992
-199
3
1993
-199
4
1994
-199
5
1995
-199
6
1996
-199
7
1997
-199
8
1998
-199
9
1999
-200
0
2000
-200
1
2001
-200
2
2002
-200
3
2003
-200
4
2004
-200
5
-0.10
0.00
0.10
0.20
0.30
0.40
0.50
0.60
0.70
0.80
agric
ultu
re
coal
min
ing
met
al a
nd n
onm
etal
lic m
inin
g
oil a
nd g
as e
xtra
ctio
n
cons
truc
tion
food
s an
d ki
ndre
d pr
oduc
ts
text
ile m
ill p
rodu
cts
appr
al
lum
ber
furn
iture
pape
r
prin
ting
chem
ical
petr
oleu
m a
nd c
oal p
rodu
cts
leat
her
ston
e cl
ay ,g
lass
prim
. Met
al
fab.
,met
al
mac
hine
ry
elc.
Mac
hine
ry
mot
. Veh
tras
p. E
quip
and
ord
nanc
e
inst
rum
ent
rubb
er a
nd m
isc
plas
tics
mis
c m
fg
tran
spor
tatio
n
com
mun
icat
ion
elec
tric
al
gas
trad
e
finan
ce in
sura
nce
and
real
est
ate
othe
r pr
ivat
e se
rvic
es
publ
ic s
ervi
ces
Domar-Wtd Productivity Contributions1982-2005
Note: Industries sorted by productivity contribution, in percentage points.
Industry Source of Output Growth
• Input growth: predominant source of output growth in most industries
• Intermediate input growth: primary source of output growth in most industries over 1984-88, 1988-94 and 1994-2000,2000-2005.
• TFP growth: primary source of output in most industries over 1982-84
• Capital input growth: became a more important source of output growth over the four periods
• Labor input growth: few industries relied on labor input as primary source of expansion
Predominant Source of Output Growth
0123456789
10111213141516171819202122232425262728293031323334
82-84 84-88 88-94 94-2000 2000-2005Capital Input Contribution Labor Input ContributionIntermediate Input Contribution TFP growth
industry number
Conclusions
Domar-weighted TFP growth is estimated at 3.89%.
TFP acceleration is obvious during the beginning of reform, 1982-1985.
Agriculture and electrical machinery – biggest contribution to aggregate TFP among 33 industries.
• Intermediate input growth is the most important source of growth
Thank you very much