Workshop on Productivity Database in China, Japan, and Korea

Estimates of Gross Fixed Capital Formation, Net Capital
Stock and Capital Intensity in Korea: by 11 Assets andby 72 Industries (1970-2005)

July 23, 2007
Hak K. Pyo, Sunyoung Jung and Jeong Sam Cho
Seoul National University*Professor, Ph. D Candidate, and MA student respectively at Economics Division,
Seoul National University.
University Sunyoung Jung and Jeong Sam Cho currently participate in『The Second Brain Korea 21 Department of Economics, Seoul National University』
Project in 2007.

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Workshop on Productivity Database in China, Japan, and Korea

Ⅰ. Introduction
 This is the further study of Pyo(2003)
 The purpose of this paper is to construct database according to
the EU KLEMS guideline and discuss the application of the
KLEM-methodology to the Korean database and to present theresultlt off growthth accounting
ti andd productivity
d ti it analysis.
l i We have constructed the detailed database of consistent GFCF
and net capital stock data for the Korean economy for the periodof 1970-2005 according to the EU KLEMS guideline.
 We also generate quarterly net capital stock.
2Workshop on Productivity Database in China, Japan, and Korea

Ⅰ. Introduction
 The most significant contribution of this paper is to makeuse of I/O Matrix (Supporting table in I/O Table, Bank of
Korea)) that has not been used for these kinds of studies.
 We extended the category of the Capital Stock into 11 asset
type and 72 industrial sector. This decomposition make thestudy on productivity more delicate.

3Workshop on Productivity Database in China, Japan, and Korea

Ⅰ. Introduction
 Main Improvement of this paper
1) We decomposed the GFCF and Capital Stock using I/O
Matrix(2000 2003)
Matrix(2000,
2) We estimated 11 asset type (including Intangibles) and
72 industry following the guideline of EU KLEMS
project to make the international comparison of
productivity possible.
3) We estimated Intangible capital stock and ICT assets(Information and communication assets) using theGFCF
GC ddata oof Intangible
g b e fixed
ed assets
sse s (Co(Computerpu eSoftware) of BOK
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Workshop on Productivity Database in China, Japan, and Korea

Ⅱ. Classification and Definition of Net Capital Stock
1 EU KLEMS classification of Asset and Industry
1.

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Workshop on Productivity Database in China, Japan, and Korea

Ⅱ. Classification and Definition of Net Capital Stock
1 EU KLEMS classification
1.
l ifi ti off Asset
A t andd Industry
I d t

6

Workshop on Productivity Database in China, Japan, and Korea

Ⅱ. Classification and Definition of Net Capital Stock
1 EU KLEMS classification
1.
l ifi ti off Asset
A t andd Industry
I d t

7

Workshop on Productivity Database in China, Japan, and Korea

Ⅱ. Classification and Definition of Net Capital Stock
1 EU KLEMS classification
1.
l ifi ti off Asset
A t andd Industry
I d t

Industry classification of National Accounts

8Workshop on Productivity Database in China, Japan, and Korea

Ⅱ. Classification and Definition of Net Capital Stock
2 Definition2.
D fi iti off Net
N t Capital
C it l Stock
St k

 Net
N C
Capitali l Stock
S k means Gross
G
C
Capitali l Stock
S k minusi
GrossG
Capital depreciation cumulated until that time.
 Net Capital Stock=Gross Capital Stock + Gross Fixed
Capital Formation – Fixed Capital Depreciation + The valueof change by the other factor which alter the Capital Stock +The Gross value of the net change due to the change of
h ldi gain
holdingi fromf
theth changehoff assett pricei The economy
economy-wide
wide market value of fixed asset at period t
 NK t = I t + (1 − δ ) I t −1 + (1 − δ ) I t − 2 +L
2

+ (1 − δ ) s −1 I t − s +1 + (1 − δ ) s I t − s9Workshop on Productivity Database in China, Japan, and Korea

Ⅲ. Estimation of GFCF by Asset and Industry
1 Estimation of GFCF by Asset1.

 To decompose the 6 asset type GFCF in 1970~2005
1970 2005 of National
Accounts into EU-KLEMS 11 asset types, we used the I/O Tables
existing irregularly in 1970~2003, and used the fixed weight of2003 for decompositon after 2003.
 We
W decomposeddd ‘Machinery‘M hiandd Equipment’E it’ intoi t ‘IT (Computing(Cti
Equipment)’ , ‘CT (Communication Equipment)’ and ‘Other
Machinery and Equipment’
Equipment using the weight from IO table, which
can tell ‘Computer Equipment’ and ‘Communication andBroadcasting Equipment’ from the ‘Machinery and Equipment’ in
the Fixed Capital Formation (private and public).
 For
F th
the year whenh thereth isn’t
i ’t I/O Table,
T bl we estimatedti t d theth weight
i ht
by linear interpolation of near year.
10Workshop on Productivity Database in China, Japan, and Korea

Ⅲ. Estimation of GFCF by Asset and Industry
1 Estimation of GFCF by Asset
1.

<Table 4> Weight of ICT assets in Machinery and Equipment from I/O Tables
Weignt from I/O Tables

1996

1997

1998 *

1999

2000 *

2001

2002

2003 *

2004

2005

5

Computing
Equipment

0.087

0.098

0.109

0.119

0.128

0.105

0.083

0.060

0.060

0.060

6

Communication
Equipment

0.107

0.140

0.173

0.175

0.178

0.157

0.136

0.115

0.115

0.115

7

Other Machinery andEquipment

0.806

0.762

0.718

0.706

0.694

0.738

0.781

0.825

0.825

0.825

* The
Th year whenh ththere exist
i t I/O T
Table
bl

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Workshop on Productivity Database in China, Japan, and Korea

Ⅲ. Estimation of GFCF by Asset and Industry
1 Estimation of GFCF by Asset
1.
<Table 5> The ggrowth rate of ICT asset ((%))
Growth rate (%)1971 1972 1973 1974 1975 1976 1977 1978 1979 1980 1981
5
Computing33.1 14.3 38.1 4.6 30.3 38.7 41.4 40.5 32.4 -21.4 12.1
6 Communication
Ci i
33 1 14.3
33.1
14 3 38.1
38 1 19.0
19 0 43.3
43 3 42.5
42 5 46.2
46 2 46.6
46 6 59.8
59 8 -9.4
9 4 21.3
21 3
10Software
5.9 -9.1 42.6 7.6 10.2 48.2 13.2 -1.6 27.2 11.4
6.6

1982
17.5
24 5
24.5
0.2

GrowthG
th ratet (%)1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993
5
Computing
21.2 24.0 10.8 66.1 -1.3 48.9
3.7
3.0 25.1
4.6
6.2
6 Communication 26.6
5.6 -6.6 24.8 14.7 -8.5 22.9 23.0 18.5 -0.5
1.4
10
S ft
Software3 0 37.1
3.0
37 1 68.0
68 0 29.3
29 3 28.5
28 5 11.0
11 0 24.6
24 6 10.6
10 6 27.0
27 0 18.4
18 4 14.6
14 6

1994
24.4
15.9
26 1
26.1

Growth rate (%)1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005
5
C
Computingti
24 9 24.9
24.9
24 9
2 8 -32.8
2.8
32 8 40.0
40 0 47.9
47 9 -24.2
24 2 -16.4
16 4 -25.9
25 9
72
7.2
74
7.4
6 Communication 15.8 57.8 19.5 -25.3 30.8 39.0 -18.7 -7.6 -13.5
7.2
7.4
10
Software21.3 16.2
6.4 -0.6 19.5 22.3
6.4 14.2 -0.9
0.9
8.1

Average
16 4
16.4
18.0
16.4

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Workshop on Productivity Database in China, Japan, and Korea

Ⅲ. Estimation of GFCF by Asset and Industry
1 Estimation of GFCF by Asset
1.

 In the averageg ggrowth rate of GFCF byy asset in the whole pperiods,,
Communication equipment(18.0%), Computing equipment(16.4%)
and Software(16.4%) shows the highest growth rate.
 Products of agriculture and forestry and Other products aren’t
identified in the statistical data,
data and Other Intangibles also doesn
doesn’tt
exist in the official statistical data.
 The growth rate of ICT asset GFCF in 1998~2005 is Computing
Equipment(0.4%), Communication Equipment(2.4%),
S f
Software(8.7%),(8 7%) whichhi h iis muchh lessl thanh the
h average ini allllperiods(1970~2005). Maybe IT boom didn’t affect gfcf in IT assets
much but affected buildings and other machinery and equipment
much,
only.

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Workshop on Productivity Database in China, Japan, and Korea

Ⅲ. Estimation of GFCF by Asset and Industry
1 Estimation of GFCF by Asset1.

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Workshop on Productivity Database in China, Japan, and Korea

Ⅲ. Estimation of GFCF by Asset and Industry
1 Estimation of GFCF by Asset
1.

<Table 7> GFCF of ICT sector in 1996~2005 (Billion won, 2000 constant prices)
1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

5

Computingequipment

5,051

5,193

3,488

4,884

7,222

5,473

4,577

3,392

3,637

3,906

6

Communicationequipment

6,183

7,387

5,516

7,212

10,023

8,146

7,526

6,508

6,979

7,494

10

Software

5 873
5,873

6 249
6,249

6 209
6,209

7 420
7,420

9 071
9,071

9 650
9,650

11 025
11,025

10 931
10,931

11 027
11,027

11 91911,91915

Workshop on Productivity Database in China, Japan, and Korea

Ⅲ. Estimation of GFCF by Asset and Industry
2. Estimation of GFCF by Industry
A. Estimation of GFCF by Industry in 1970~1997

 Mining,
Mi i
M f
Manufacturing
i Survey
S(R(Reporton Industrial
I d
i l Census)C) existi
only after 1999, and I/O Matrix also exist only in 1990, 1995,
2000 2003
2000,
 We have decomposed 13-industry data of GFCF from National
Accounts into 72 EU-KLEMSEU KLEMS industries
industries’ GFCF by making use of
the difference between two benchmark years’ NWS capital stock
as decompositionpweights
g for the pperiod of 1970-1997.
1) Reduction the NWS in 1968,1977,1987,1997 into 72 industries
2) Estimate the weights by the three inter-period differences of NWS

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Workshop on Productivity Database in China, Japan, and Korea

Ⅲ. Estimation of GFCF by Asset and Industry
2. Estimation of GFCF by Industry
A. Estimation of GFCF by Industry in 1970~1997

 Decomposition 13-industry data of GFCF from National Accountsiinto
72 EU-KLEMSEU KLEMS iindustries’di ’ GFCF byb making
ki use off thehdifference between two benchmark years’ NWS capital stock as
decomposition weights for the period of 1970-1997.
1970-1997pweightsg mean the weights
g in each 13
 In this decompositionindustries of National Accounts, so that GFCF in each 13
industries of National Accounts remain unchanged.

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Workshop on Productivity Database in China, Japan, and Korea

Ⅲ. Estimation of GFCF by Asset and Industry
2. Estimation of GFCF by Industry
B. Estimation of GFCF by Industry in 1998~2005

1) Mining and Manufacturing
 For the period of 1998-2005, we have used Report on
Industrial Census to redistribute Mining and Manufacturingindustries for further detailed industrial classification
 We used the Intangible asset increase as the decompositon
weight.

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Workshop on Productivity Database in China, Japan, and Korea

Ⅲ. Estimation of GFCF by Asset and Industry
2. Estimation of GFCF by Industry
B. Estimation of GFCF by Industry in 1998~2005

2) Agriculture,
Agriculture Forestry and Fishery and Service industries① For Decomposition, We used I/O Matrix(96-asset by 71i d t nott owner basedindustry,b d butb t activity
ti it based)b d)② For further decomposition, we estimated the decomposition
weight by making use of 1997 NWS(Net value, ownerbased)In this decomposition weights mean the weights in each 13
industries of National Accounts, so that GFCF in each 13
i d t i off National
industries
N ti l AccountsAt remaini unchanged.
hd19Workshop on Productivity Database in China, Japan, and Korea

Ⅲ. Estimation of GFCF by Asset and Industry
2. Estimation of GFCF by Industry
B. Estimation of GFCF by Industry in 1998~2005

2) Agriculture,
Agriculture Forestry and Fishery and Service industries③ Redistribution of Public CapitalIn making use of I/O Matrix, first, We need to redistributethe 71th industrial sector named ‘Public
Public Capital
Capital’ .
For this, we have consolidated I/O Matrix into 9-asset by
72-industry matrix. Public capital are distributed by only
three types of assets: Residential Buildings, Civil
E iEngineering
i WorkW k andd OtherOth Structures
St t

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Workshop on Productivity Database in China, Japan, and Korea

Ⅲ. Estimation of GFCF by Asset and Industry
2. Estimation of GFCF by Industry
B. Estimation of GFCF by Industry in 1998~2005

2) Agriculture,
Agriculture Forestry and Fishery and Service industries③ Redistribution of Public Capitala. Civil Engineering Work
Following the SOC composition ratio (Table 9, p.25) in
1997 NWS, we redistributed 55.4% of public capital into
Transport sector
sector, 77.3%
3% into Communication sector,
sector 13% into
Electricity, Gas Supply sector, 5.7% into Water supply
sector,, and 18.6% into irrigationgand flood control sector.
b. Other Structures
Redistribution into 72 industries by the weight of eachindustry except public capital

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Workshop on Productivity Database in China, Japan, and Korea

Ⅲ. Estimation of GFCF by Asset and Industry
2. Estimation of GFCF by Industry
B. Estimation of GFCF by Industry in 1998~20052)) Agriculture,g, Forestryy and Fisheryy and Service industries③ Redistribution of Public Capitalc. Residential
id i l Buildings
ildi
According to 1997 NWS, 273,743 billion won (about 90% of Residentialbuildings) belong to household sector, and 31,694 billion won(about
10% of Residential buildings) belong to Non-Household sector.

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Workshop on Productivity Database in China, Japan, and Korea

Ⅲ. Estimation of GFCF by Asset and Industry
2. Estimation of GFCF by Industry
B. Estimation of GFCF by Industry in 1998~2005

2) Agriculture,
Agriculture Forestry and Fishery and Service industries③ Redistribution of Public Capitalc. Residential Buildings

AccordingA
di tot thisthi ratio,
ti first,
fi t we redistributed
di t ib t d 22,858
22 858 billion
billi
won (about 90% of public capital in residential buildings)
into Real Estate Activity.
Activity
Then, we redistributed 2,373 billion won (about 10% of
public capital) into 72 industries by the weight of eachindustry in residential buildings.
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Workshop on Productivity Database in China, Japan, and Korea

Ⅲ. Estimation of GFCF by Asset and Industry
2. Estimation of GFCF by Industry
B. Estimation of GFCF by Industry in 1998~2005

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Workshop on Productivity Database in China, Japan, and Korea

Ⅲ. Estimation of GFCF by Asset and Industry
2. Estimation of GFCF by Industry
B. Estimation of GFCF by Industry in 1998~2005

25

Workshop on Productivity Database in China, Japan, and Korea

Ⅲ. Estimation of GFCF by Asset and Industry
2. Estimation of GFCF by Industry
B. Estimation of GFCF by Industry in 1998~2005

2) Agriculture,
Agriculture Forestry and Fishery and Service industries④ After the redistribution of public capital, we decomposedth Agriculture,theA i ltForestryFt andd Fishery
Fi handd Service
S i industries
i d ti
into 72 industries using the sum of 72 industries in I/Omatrix as the decomposition weight26

Workshop on Productivity Database in China, Japan, and Korea

Ⅲ. Estimation of GFCF by Asset and Industry
2. Estimation of GFCF by Industry
B. Estimation of GFCF by Industry in 1998~2005

2) Agriculture,
Agriculture Forestry and Fishery and Service industries
IIn <Table<T bl 11>,11> tot lookl k att theth trendt d off GFCF byb industry,i d t wereclassified the EU KLEMS 72 industries into 7 industry
category Specially,
category.
Specially we categorized service sector into 4
industry sector according to J.H.Kim, ‘Reviving
manufacturing in Korea’, KDI Report.
<Table 12> shows that Mining/ Manufacturing/ Electricity,
G W
Gas,
Water
t Supply
S l (12.5%)(12 5%) anddD
Destribution
t ib ti Service(12.5%)
S i (12 5%)
were highest in GFCF growth rate, and IT industry(5.4%) was
relatively low.
low
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Workshop on Productivity Database in China, Japan, and Korea

Ⅲ. Estimation of GFCF by Asset and Industry
2. Estimation of GFCF by Industry
B. Estimation of GFCF by Industry in 1998~2005<Table 11> Classification of 7 Industries
Code

Industry

EU-KLEMS code

1

Agriculture, forestry and fishing

1~3

2a

ICT
(Computing and communication equipment)

26,30

2b

Other manufacturing/Mining//Electricity,
ec c y, G
Gas,
s, W
Water
e SuppSupplyy4~25, 27~29, 31~43

3aProducer service

52~62

3b

Distribution service

44~46, 48~51

3cConsumer service

47, 68~71

3dSocial Service

63~67
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Workshop on Productivity Database in China, Japan, and Korea

Ⅲ. Estimation of GFCF by Asset and Industry
2. Estimation of GFCF by Industry
B. Estimation of GFCF by Industry in 1998~2005

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Workshop on Productivity Database in China, Japan, and Korea

Ⅲ. Estimation of GFCF by Asset and Industry
3 Estimation
3.
E ti ti off Q
Quarterlyt l GFCF byb AssetA t

 Using the weight which was used in the estimation ofyyearlyy GFCF byy asset,, We decomposedp
the Q
Quarterlyy GFCFby 6 assets in National Account into EU-KLEMS 11 Assets.
 We decomposed ‘Machinery
Machinery and Equipment’
Equipment into
‘IT(Computing Equipment)’ , ‘CT(Communication
Equipment)’ and ‘Other Machinery and Equipment’ using
the weight from IO table, which can tell ‘Computer
Equipment’ and ‘Communication and Broadcasting
E i
Equipment’t’ fromftheth ‘Machinery‘M hiandd Equipment’
E i
t’ in
i the
th
Fixed Capital Formation (private+public).
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Workshop on Productivity Database in China, Japan, and Korea

Ⅳ. Estimation of Capital Stock by Asset and Industry
1. Estimation of Capital Stock by Asset
A. Estimation of Capital Stock by Asset in 1970~1997

1) Change the National Wealth Survey(NWS,
Survey(NWS ownership based,based
current prices) in 1968, 1977, 1987, 1997 into 2000 constantprices usingpg the GFCF Deflator in the National Account.
Table) GFCF Deflator
Deflator(2000=100)
1968

5.23

1977

19.29

1987

48.64

1997

91.11

2) Reduction into 6 assets, and interpolation the years when
NWS doesn’t
doesn t exist.
exist3) Using the weight from IO Table, We decomposed theCapital Stock by 6 assets in the National Account into EUEUKLEMS 11 Assets.

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Workshop on Productivity Database in China, Japan, and Korea

Ⅳ. Estimation of Capital Stock by Asset and Industry
1. Estimation of Capital Stock by Asset
B. Estimation of Capital Stock by Asset in 1998~2005

1) Fixing the NWS(ownership based,based net value) in 1997 by 6
assets into 1997 Capital Stock by asset.
2) Intangible
I t ibl assett doesn’td’t existi t ini theth NWS.
NWS Therefore
Th fwe
estimated intangible asset in 1997 by adding the Intangible
asset investment of National Account with the depreciation rateof 31.5% (recommended by EU-KLEMS).

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Workshop on Productivity Database in China, Japan, and Korea

Ⅳ. Estimation of Capital Stock by Asset and Industry
1. Estimation of Capital Stock by Asset
B. Estimation of Capital Stock by Asset in 1998~2005

3) Using the GFCF by 11 assets in 1998~2005, we estimatedCapital Stock by 11 assets by Perpetual Inventory Method
In this method, we used the estimated depreciation rate in Pyo,
‘Estimate of Capital Stock by Industry and by
Asset(1953~2000) in Korea’ (Table 4, p.216). We also usedthe depreciation rate of 31.5% in the Intangible assets

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Workshop on Productivity Database in China, Japan, and Korea

Ⅳ. Estimation of Capital Stock by Asset and Industry
1. Estimation of Capital Stock by Asset
B. Estimation of Capital Stock by Asset in 1998~2005

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Workshop on Productivity Database in China, Japan, and Korea

Ⅳ. Estimation of Capital Stock by Asset and Industry
1. Estimation of Capital Stock by Asset
B. Estimation of Capital Stock by Asset in 1998~2005<Table 14> The Recommended depreciationprate byy EU KLEMSEU KLEMS

Minimum
rate overIndustries

Residential structures

0.011

0.011

0.033

Non-residential structures

0.023

0.069

0.03

Infrastructure

0 023
0.023

0 069
0.069

0 01
0.01

Transport equipment

0.061

0.246

0.139

Computing equipment

0.315

0.315

0.092

Communications equipment

0.115

0.115

0.092

Other machinery and equipment

0.073

0.164

0.092

Products of agriculture andforestry

0.073

0.164

n.a.

Other products

0.073

0.164

n.a.

S ft
Software

0 315
0.315

0 315
0.315

n.a.

Other intangibles

0.315

0.315

n.a.

Maximum
rate overIndustries

Rate from
Pyo (2003):1987-1997

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Workshop on Productivity Database in China, Japan, and Korea

Ⅳ. Estimation of Capital Stock by Asset and Industry
1. Estimation of Capital Stock by Asset
B. Estimation of Capital Stock by Asset in 1998~2005

 Software(19.5%), Communications Equipment(16.3%),
Computing equipment(12.0%)
equipment(12 0%) show the highest growth rate overall periods ComputingCti equipmentit showshtheth negative
ti growthth ratet ini
1998~2005, maybe this is because the depreciation of 31.5% in thecomputing equipment is too high.
high

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Workshop on Productivity Database in China, Japan, and Korea

Ⅳ. Estimation of Capital Stock by Asset and Industry
1. Estimation of Capital Stock by Asset
B. Estimation of Capital Stock by Asset in 1998~2005

37

Workshop on Productivity Database in China, Japan, and Korea

Ⅳ. Estimation of Capital Stock by Asset and Industry
2. Estimation of Capital Stock by Industry
A. Estimation of Capital Stock by Industry in 1970~1997

1) Change the NWS (net value,
value current prices) by 72 Industries
in 1997 into 2000 constant prices using the GFCF Deflator
in the National Account.
2) Using the GFCF by 72 industries in 1998~2005, weestimated Capital Stock by 72 industries by Perpetual
Inventory Method38

Workshop on Productivity Database in China, Japan, and Korea

Ⅳ. Estimation of Capital Stock by Asset and Industry
2. Estimation of Capital Stock by Industry
B. Estimation of Capital Stock by Industry in 1998~2005

 In this method,
method we used the estimated depreciation rate byindustries in Pyo, ‘Estimate of Capital Stock by Industry andby Asset(1953~2000) in Korea’ (Table 6, p.216).

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Workshop on Productivity Database in China, Japan, and Korea

Ⅳ. Estimation of Capital Stock by Asset and Industry
2. Estimation of Capital Stock by Industry
B. Estimation of Capital Stock by Industry in 1998~2005

40

Workshop on Productivity Database in China, Japan, and Korea

Ⅳ. Estimation of Capital Stock by Asset and Industry
2. Estimation of Capital Stock by Industry
B. Estimation of Capital Stock by Industry in 1998~2005

 ICT sector (22(22.4%)
4%) shows the highest average growth rateover the all periods, followed by Producer Service
sector(13.9%),(), Social Service sector(11.8%)()
 But the growth rate of ICT sector drops 41.2% in 1984~1997
to 3.4%
3 4% in 1998
1998~2005
2005.

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Workshop on Productivity Database in China, Japan, and Korea

Ⅳ. Estimation of Capital Stock by Asset and Industry
2. Estimation of Capital Stock by Industry
B. Estimation of Capital Stock by Industry in 1998~2005

42

Workshop on Productivity Database in China, Japan, and Korea

Ⅳ. Estimation of Capital Stock by Asset and Industry
3. Balancing Capital Stock by Industry with by Asset We need the ‘balancingbalancing processprocess’ to coincide the sum ofcapital stock by industries with the sum of capital stock byassets.
1) Comparison the sum of capital stock by assets with the sumof capital stock by assets in 1970
1970~2005
20052) Distribution the gap between the two sums in to 72
industries of capital stock by industry.
industry
For the distribution, we used the weight of each sector inth sum off capitaltheit l stockt k byb 72 industries.
i d ti43

Workshop on Productivity Database in China, Japan, and Korea

Ⅳ. Estimation of Capital Stock by Asset and Industry
4. Estimation of Quarterly Capital StockA. Estimation of Quarterly Capital StockWe estimated the Quarterly Capital stock by asset from theYearly Capital stock by asset, using the weight from the
Quarterly GFCF by assets in National Account.
 We decomposed the Yearly Capital stock into the Quarterly
Capital stock using the weight of the quarterly sum of capitalstock over the 11 assets.

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Workshop on Productivity Database in China, Japan, and Korea

Ⅳ. Estimation of Capital Stock by Asset and Industry
4. Estimation of Quarterly Capital StockB. Estimation of Quarterly Capital Stock by Industry

 The Quarterly GFCF by industry doesn’t exist in National
Account. Therefore we estimated the Quarterly Capital Stockby subdividing the sum of the quarterly Capital Stock by assets
over 11 assets into 72 industries.
 For subdividing, we used the weight of the ratio of eachindustry in the whole capital stock in the near year.

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Workshop on Productivity Database in China, Japan, and Korea

Ⅴ. Estimation of Capital Intensity and TFP
1 Growth Accounting Model1.

 We tried to run Growth Accounting in Korean economy in1970~2005 using the estimated Capital Stock and Gross ValueAdded by industry (Y), Population (N), Number of Employees (E),
Average hours worked (h) in EU-KLEMS Korea Databasey We followed the ggrowth accountingg method in HayashiPrescott(2002) , which mainly use the capital intensity (K/Y ) We modified the method in Hayashi
Hayashi-Prescott(2002),
Prescott(2002), in that we
divided Capital-Labor ratio (k=K/N ) and Capital-Employment ratio (k*=K/E ), and we applied the growth accounting into 72
industries as well.

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Workshop on Productivity Database in China, Japan, and Korea

Ⅴ. Estimation of Capital Intensity and TFP
1 Growth Accounting Model1.
 <Figureg2> shows the trend of the variables used in the Growth Accountingg
in Korea economy(1970~2004)
 5% detrended Real GDP per capita shows the Korean economy crisis in
1997~1998
 Average working hours over the whole industry decrease from the peak in
1986 Capital
C i l intensityii showshtheh increasingii trendd except theh period
i d 1997~1998
1997 1998
 Capital intensity shows almost the same trend with that in Hayashi- Prescott(2002)47

Workshop on Productivity Database in China, Japan, and Korea

Ⅴ. Estimation of Capital Intensity and TFP
1 Growth Accounting Model
1.
<Figure 2> Trends of Macroeconomic variables in Korea

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Ⅴ. Estimation of Capital Intensity and TFP
1 Growth Accounting Model
1.
Prescott and Hayashi(2002)

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Ⅴ. Estimation of Capital Intensity and TFP
1 Growth Accounting Model
1.

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Ⅴ. Estimation of Capital Intensity and TFP
1 Growth Accounting Model
1.

51

Workshop on Productivity Database in China, Japan, and Korea

Ⅴ. Estimation of Capital Intensity and TFP
1 Growth Accounting Model
1.

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Ⅴ. Estimation of Capital Intensity and TFP
1 Growth Accounting Model1.

 <Table 19> shows the GDP per capita(15~69)
capita(15 69) growth rateusing the above growth accounting equation
 In the whole industry in the period 1970~2004,
1970~2004 GDP per
capital growth rate(6.5%) is decomposed into TFP(), capitalpintensity(1.4%),y(), averageg hours worked((factor(2.1%),
0.3%) and employment rate(1.6%), and employment
rate(1.6%) equals the growth rate of the capital-laborratio(7.9%)
i () minusitheh growthh rate off capital-employment
i l
l
ratio
i
(6.3%)
 The relative contribution of TFP factor to GDP per capita(100*2.1%/6.5%=32.3% ) is estimated very high, which rejectth Krugman
theK
hypothesis.
h
th i
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Workshop on Productivity Database in China, Japan, and Korea

Ⅴ. Estimation of Capital Intensity and TFP
1 Growth Accounting Model1.

 In the growth accounting result in the period
1998~2004, GDP per capital growth rate(4.3%) is
decomposed to TFP growth rate(0.5%), capital intensity
growth rate, (3.9%), average hours worked growth rate(-0.6%) and employment rate growth rate(0.6%)
 In this period, the relative contribution of TFP growthrate to GDP growth rate(100rate(100*0.5%/4.3%=11.6%
0.5%/4.3% 11.6% ) ismuch lower than that in the previous periods, but therelative contribution of capital intensity is much higher(100*3.9%/4.3%=90.7% )54Workshop on Productivity Database in China, Japan, and Korea

Ⅴ. Estimation of Capital Intensity and TFP
1 Growth Accounting Model
1.
<Table 19> 72-sector Growth Accounting: Korea (1970-2004)

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Ⅴ. Estimation of Capital Intensity and TFP
1 Growth Accounting Model
1.

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Ⅴ. Estimation of Capital Intensity and TFP
1 Growth Accounting Model
1.

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Ⅴ. Estimation of Capital Intensity and TFP
2 Revised Hayashi-Prescott Growth Accounting for Korea
2.

 We have also adopted a production function approach with
unemployment rate (u) and capacity utilization ratio (v).
 So, equation (1) can be expressed like below:θ1−θ

Y = A(vK ) ((1 − u ) hE )(1)’

 <Table 20> has shown the growth accounting results based on (1)’58

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Ⅴ. Estimation of Capital Intensity and TFP
2 Revised Hayashi-Prescott Growth Accounting for Korea
2.
<Table 20> 72-sector Growth Accounting with Capacity Utilization andUnemployment Rate Considered: Korea (1970-2004)

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Ⅴ. Estimation of Capital Intensity and TFP
2 Revised Hayashi-Prescott Growth Accounting for Korea
2.

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Ⅴ. Estimation of Capital Intensity and TFP
2 Revised Hayashi-Prescott Growth Accounting for Korea
2.

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Ⅵ Conclusion
Ⅵ.

 In the average growth rate of GFCF by asset in the whole
pperiods,, Communication equipment(18.0%),
q p(), Computingpgequipment(16.4%) and Software(16.4%) shows the highest
growth rate.
 Products of agriculture and forestry and Other products
aren’t identified in the statistical data, and Other
Intangibles also doesn’t exist in the official statistical data.

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Ⅵ ConclusionⅥ.
 When we see the trend of the estimated GFCF by industry,
Mining/Manufacturing/Electricity, Gas, Water Supply(12.5%) andDistribution Service sector(12.5%) show the highest growth rate,and IT Industry(5Industry(5.4%)4%) show relatively very low growth rate.
rate When we see the trend of the estimated Capital Stock by asset,
Software(19.5%), Communications Equipment(16.3%), Computing
equipment(12.0%) show the highest growth rate over all periods.
 Computing equipment shows the negative growth rate(-8.5%), andthis suggest that the depreciation of 31.5%
31 5% in the computing
equipment which is recommended by EU-KLEMS is too high.

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Ⅵ ConclusionⅥ.
 When we see the Capital stock by industry, ICT
industry(22.4%) show the highest growth rate, followed by
Producer service sector(13.9%) and Social Service
sector(11.8%)
t (11 8%)
 The growth rate of ICT manufacture industry dropped
from 41.2% in 1984~1997 to 3.4% in 1998~2005
 In the result of Growth Accounting, GDP per capital
growth rate(6.5%) is decomposed into TFP factor(2.1%),
capitalit l intensity(1.4%),i t it (1 4%) average hourshworked(-0.3%)
k d( 0 3%) andd
employment rate(1.6%), and employment rate(1.6%) equals
the growth rate of the capital
capital-labor
labor ratio(7.9%) minus thegrowth rate of capital-employment ratio(6.3%)
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