The Role of ICT in Economic Growth of Korea · 2009. 2. 2. · The Role of ICT in Economic Growth of Korea • Since the financial turmoil, capital deepening in Korea has been relatively

The Role of ICT

in Economic Growth of Korea:Productivity Changes across Industries since 1985

January, 29, 2009

Chang-Ho Yoon*, Kyoung-Youn Na** and Hyun-Joon Jung***

* Professor, Department of Economics, Korea University** Ph.D. student, Department of Economics, Korea University

*** Researcher, Korea Information Society Development Institute

The Role of ICT in Economic Growth of Korea

I. Introduction

II. Empirical Model and Estimation

III. Concluding Comments


I. Introduction

• Information Technology and Productivity Growth in OECD countries (2003): Diverging patterns of ICT diffusion across countries and industries, and differential impact over time.

• Need to examine a case of ICT leading country where a sustained increase of productivity has been traced in ICT intensive industries.

• Recovery of Korea after financial turmoil in the late 1990s.


• Since the financial turmoil, capital deepening in Korea has been relatively modest compared to the previous rapidly growing period. The annual rate of growth of net capital stock of the Korean economy over the period of 1970- 2005 was 10.8%, while 6.0% for 1998 – 2005. In the case of ICT sector, the rate was 41.2% for the period of 1984-1998, and then reduced to 3.4% for 1998 – 2005.

• The trend growth rate of Korea has been lowered after the crises with much less volatility until 2007.


- Source : Bank of Korea

• Sources of GDP growth using best estimate and harmonized prices

- Source : Takahito Kanamori and Kazuyuki Motohashi (2007)


• Decomposition of TFP Growth

- Source : Takahito Kanamori and Kazuyuki Motohashi (2007)



• Literature on growth enhancing effects of ICT: Jorgenson, D and K. Stiroh (1999, 2000), Stiroh, K. (2002), Jorgenson, D and Motohashi, K (2005), Kanamori, T and Motohashi, K (2008)

• Suspicious perspective on the New Economy: Gordon (2000)

• Roller and Waverman (2001) on the positive role of ICT infrastructure in economic growth.


II. Empirical Model and Estimation

Methodological comments on previous research

(1) Technology specification– Suppose the economy is divided into ICT producing

sector and using sector. Then ICT capital stock of ICT producing sector often becomes the ICT infrastructure of the whole economy and complementary to ICT capital of ICT using sector (e.g. fixed and wireless networks, R&D facilities)

– The effects of ICT on productivity of ICT using industry can be underestimated if focusing on ICT capital of that industry alone.

• The Ratio of ICT capital stock (OECD 2002 classification)

0.1

.2.3

.4

1985 1990 1995 2000 2005year

ICT_MAN ICT_SERICT

- Source : EU KLEMS



(2) OECD ICT sector definition- capital measurement

– OECD ICT sector definition(2007): “The production (goods and services) of a candidate industry must primarily be intended to fulfill or enable the function of information processing and communication by electronic means, including transmission and display.”

– New ICT definition exclude the sentence that “Industries producing products (technologies) that use electronic processing to detect, measure, record or control a physical process.”

• ICT Convergence sectors use more and more ICT intermediate inputs or ICT capital which are not classified as ICT.

– Motor vehicle is a good example. – The components of Motor vehicle such as ECU, sensors

and embedded SWare not classified as ICT.– ECU or sensors uses electronic processing to detect,

measure, record or control a physical process (sensing, computing and communicating).


(3) Inter-industry spill-over effects

– In many competitive or oligopoly industries, an investment game in ICT often results in cost and price reduction, and wealth redistribution from firms to consumers. Gain in consumer surplus boosts consumption in other industries.

– Due to heavy development cost and low marginal cost of ICT equipment and software, strong network effects prevail among the users across industries (e.g. software for internet security).


- Source: EU KLEMS

Industrial Classifications



Estimation of spill-over effects

• We consider aggregate production function

• is aggregate ICT capital stock at t.

• Let denote the proportion of ICT capital stock of industry i at t.

• Then

),,,( tICKKLfY tititit =

tICK

itθ

∑=i

ititt KICK θ

1. Standard Cobb-Douglas Function

2. Other specification to emphasize the dependency of industry spill-over on

γβαtititiititiiit ICKKLtBKLtAFY )(),),(( ==

γγ θ )(∑=i

ititt KICK

0,, >γβα


itθ

ittititiit ICKKLtBY θγβα ⋅= )(

• Specification for industrial value added. All the variables are in natural logarithms.

• Both and are determined endogenously within the system (depend on current and lagged output levels as well as technology shocks)

)( itititickitkitnit mickkny +++++= νηβββ

ittiit ev += −1,αν1|| <α

)0(~, MAme itit


n k

• Dynamic representation(1)

(2)

• In either case we can obtain consistent estimates of the unrestricted parameter vector using the GMM methods.

)( 1*11,17116151,14131,1211 itititttiittiitit wyickickkknny ++++++++= −−−− ηπππππππ

)( 2*21,27126251,24231,2221 itititittittiittiitit wyickickkknny +++⋅+⋅++++= −−−− ηπθπθπππππ

),,,,,,( 7654321 ππππππππ =


Variables Definition

GO Gross output at current basic prices (million won)

VA Gross value added at current basic prices (million won)

GO_P Gross output, price indices, 1995 = 100

VA_P Gross value added, price indices, 1995 = 100

L Total hours worked by employees (millions)

KICT ICT assets, Real fixed capital stock, 1995 prices

K All assets, Real fixed capital stock, 1995 prices

LAB Labor compensation (million won)

CAP Capital compensation (million won)

TFP TFP (value added based) growth, 1995=100

Data

- Source : EU KLEMS


• Descriptive Statistics

Variable Obs Mean Std. Dev. Min Max

(ln level)

VA 630 15.862 1.011 13.098 18.347

n 630 6.449 1.106 3.341 8.271

k 630 16.655 1.366 13.359 20.150

ick 630 17.015 0.772 15.658 18.060

Learning 630 18.996 1.064 15.676 21.406

rTFP 600 0.033 0.074 -0.243 0.372

rGO 600 0.073 0.097 -0.459 0.942

rick 600 0.120 0.043 0.039 0.185

630 0.039 0.055 0.001 0.339


θ

Estimation of production function


• Production Function Estimation Result (conti…)

*, ** and *** denote significance of the test statistic at the 10, 5 and 1% level of significance, respectively.


• rTFP Regressions

• is TFP of industry i in year t.

• is Gross Output of industry i in year t.

• is cumulative Gross Output of industry from year t-5 to year t-1.

• is ICT capital stock of all industries in year t.

itA

itGO

itLearning

ittititit ICKdLearningGOdAd εδγβα ++++= lnlnlnln

tICK


• rTFP Regressions Result



• Dummy Variable rTFP Regressions

(1)

• if , otherwise.

• if ICT using industry, if ICT producing industry.

ittitit ICKdGOdCDAd εφδγβα +++++= lnlnln

1=D 1998≤t 0=D

1=C

0=C


• Dummy Variable rTFP Regressions Result



• Continuous ICT Variable rTFP Regressions

(2)

(3)

ittittit ICKdGOdICKdDAd 11111 lnlnlnln εφδβα +++⋅+=

itittitittit ICKdGOdCICKdDAd 2122122 lnlnlnln εθλφδθγβα ++++⋅+⋅+=


• Continuous ICT Variable rTFP Regressions Result



• Aggregate TFP growth rate

– Source : EU KLEMS

-.04

-.02

0.0

2.0

4.0

6to

tal_

r_T

FP

1985 1990 1995 2000 2005year


• ICT producing industries

13 ELECTRICAL AND OPTICAL EQUIPMENT

23 POST AND TELECOMMUNICATIONS

id = 13

Variable Obs Mean Std. Dev.

indus_rTFP 20 0.1076 0.0847

id = 23


indus_rTFP 20 0.1190 0.0576


• ICT producing industries

– ICT producing industries (both manufacturing and service) show consistently higher productivity growth. During the financial crisis, still positive growth.

-.4

-.2

0.2

.4

1985 1990 1995 2000 20051985 1990 1995 2000 2005

1 3 2 3

indus_r_TFP total_r_TFP

year

G rap h s b y id


• ICT intensive industries– The proportion of ICT capital( ) is greater than the

average proportion of all the industries. The status can change over time.

• Among the industries which use ICT intensively, select industries with TFP growth rate persistently higher than economy wide growth rate since 2002.

θ

8 Chemicals and chemical

12 MACHINERY, NEC

14 TRANSPORT EQUIPMENT


• ICT intensive industries (code 8, 12, 14)

id = 8


indus_rTFP 20 0.0524 0.0453

id = 12


indus_rTFP 20 0.0745 0.1079

id = 14


indus_rTFP 20 0.0648 0.0870


• ICT intensive industries

– Among ICT intensive industries, industries 12 and 14 show high volatility.


-.4

-.2

0.2

.4

1985 1990 1995 2000 20051985 1990 1995 2000 2005

1 2 1 4

indus_r_T F P total_r_TF P

year

G rap h s b y id

• ICT intensive industries (conti…)

– Industry 8 shows consistently higher productivity growth with small volatility.

-.4

-.2

0.2

.4

1985 1990 1995 2000 2005

8


year

Graphs by id


• ICT intensive service industry

24 FINANCIAL INTERMEDIATION

id = 24


indus_rTFP 20 0.0447 0.0995


• 23 Post and Telecommunications • 24 Financial Intermediation

-.4

-.2

0.2

.4

1985 1990 1995 2000 20051985 1990 1995 2000 2005

23 24


year

G raph s by id


• Service industries with increasing ICT intensity since mid 1990s

18 Sale, maintenance and repair of motor vehicles and motorcycles; retail sale of fuel

19 Wholesale trade and commission trade, except of motor vehicles and motorcycles

20 Retail trade, except of motor vehicles and motorcycles; repair of household goods


• Right axis =share

– ICT intensity rises and then declines recently. Better performance recently.

.015

.02

.025

.03

.015

.02

.025

.03

.015

.02

.025

.03

-.05

0.0

5.1

-.1

0.1

.2

-.1

0.1

1998 2000 2002 2004 2006

1998 2000 2002 2004 2006

18 19

20

indus_rTFP total_r_TFPshare

year

Graphs by id

θ


• Export ratio of ICT using industry and producing industry

– Source : Bank of Korea


.2.2

5.3

.35

.4

1990 1995 2000 2005 2010year

ex_ratio_ICT_high ex_ratio_ICT_pro

• Export volume indices (1995=100)

5010

015

020

0

1990 1995 2000 2005 2010year

ex_vol_ICT_high ex_vol_ICT_proex_vol_sum

- Source : Bank of Korea



III. Concluding Comments

• In contrast to previous research, ICT has strong effects on the productivity of ICT using export industries (notwithstanding ICT producing industries).

• Dynamic comparative advantage has been revealed toward the ICT using export industries which have managed to adopt convergent technologies. However from the 4th quarter of 2008, exports began to decline rapidly.

• Does technology convergence extend to other promising industries?

References

• Bailey, Martin N. and Robert Lawrence (2001), “Do We Have a New E-Conomy?”, NBER Working Paper 8243.

• Basu, Susanto, Fernald, John G., Oulton , Nicholas and Srinivasan , Sylaja (2003), “The Case of the Missing Productivity Growth: Or, Does Information Technology Explain why Productivity Accelerated in the US but not the UK?”, NBER Working Paper, No. W10010.

• Blundell R.W. and S.R. Bond (2000), “GMM Estimation with Persistent Panel Data: An Application to Production Functions”, Econometric Reviews, 19, pp.321-340.

• Daveri, Francesco (2003), “Information Technology and Productivity Growth Across Countries and Sectors”, IGIER Working Paper, No. 227

• Dewan, S., Kraemer, K. L. (2000), “Information technology and productivity: evidence from country-level data.”, Management Science, 46, pp.548-562.

• Gordon, Robert J. (2000), "Does the “New Economy” Measure up to the Great Inventions of the Past?”, Journal of Economic Perspectives, Vol. 14, pp.49-74.

• Greene, W.H. (2002), Econometric Analysis, 5th ed. Upper Saddle River, NJ: Prentice-Hall.

• Hausman J. A, (1978), “Specification tests in econometrics”, Econometrica, 46, pp.1251-1271.

References

• Il Houng Lee and Yougesh Khatri (2003), “IT and Productivity Growth in Asia”, IMF working paper WP/03/15.

• Jorgenson, Dale W. and Kevin J. Stiroh(2000), “Raising the Speed Limit: U. S. Economic Growth in the Information Age”, Brookings Papers on Economic Activity.

• Jorgenson , Dale W. (2001), “Information Technology and the U.S. Economy”, Harvard Institute of Economic Research Paper, No. 1911.

• Kevin J. Stiroh (2001), “Information Technology and the U.S. Productivity Revival: What Do the Industry Data Say?”, Federal Reserve Bank of New York.

• _____________ (2002), “Information Technology and the U.S. Productivity Revival: What Do the Industry Data Say?”, The American Economic Review, Vol. 92, No. 5, pp.1559-1576.

• Ki-Dong Lee (2001), “An Analysis on the Productivity Effects of the Information and Communication Technology Investment in Korean Industries”, Kukje Kyungje Yongu, Vol.7, No.2. (in Korean)

• KwanHo Shin, YoungSoo Lee and JongWha Lee (2004), “Productivity Growth in Information Communication Technology Industries and Their Impacts on Other Industries”, KukjeKyungje Yongu, Vol.10, No.2. (in Korean)

References

• Lars-Hendrik Roller and Leonard Waverman (2001), "Telecommunications Infrastructure and Economic Development: A Simultaneous Approach" , The American Economic Review, Vol. 91, No. 4, pp. 909-923.

• Marcel Timmer, Ton van Moergastel and Edwin Stuivenwold et al. (2007) “EU KLEMS Growth and Productivity Account”, Version 1.0, PART I Methodology.

• Oliner, Stephen D. and Sichel, Daniel E. (1994), “Computers and Output Growth Revisited: How Big Is the Puzzle?,”Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 25, pp.273-334.

• ________________ (2000), “The Resurgence of Growth in the Late 1990s: Is Information Technology the Story?”, FEDS Working Paper, No. 2000-20.

• ________________ (2003), “Information technology and productivity: where are we now and where are we going?”, Journal of Policy Modeling, Vol. 25, Issue 5, Special Silver Anniversary Issue, The New Economy and Growth, pp.477-503.

• Sargan, J. (1958), “The estimation of economic relationships using instrumental variables”, Econometrica, 26(3), pp.393–415.

• Takahito Kanamori and Kazuyuki Motohashi (2007), “Information Technology and Economic Growth: Comparison between Japan and Korea”, RIETI Discussion Paper Series, 07-E-009.

Thank You

Documents

The Role of ICT in Economic Growth of Korea · 2009. 2. 2. · The Role of ICT in Economic Growth of Korea • Since the financial turmoil, capital deepening in Korea has been relatively