ICT Capital Investment and Productivity Growth: Granger Causality in Japanese and the USA Industries Koji SHINJO Kwansei Gakuin University, JAPAN and Xingyuan.

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ICT Capital Investment and Productivity Growth: Granger Causality in Japanese and the USA Industries Koji SHINJO Kwansei Gakuin University, JAPAN and Xingyuan ZHANG Okayama University, JAPAN September, 2004

This paper is intended to use a panel data of Japanese and the USA industries, to tackle the following issues: (1)Does ICT capital investment cause, in the Granger sense, productivity growth at the industry level?; (2)What is the lag structure between ICT capital investment and the productivity growth?; (3)What is the difference, if any, in timing and magnitude of the Granger causality between Japanese and the USA industries?

Robert J. Gordon (2003) : The delay in the effect of ICT (information and communication technology) capital investment on the productivity growth Beil et al. (2003): A Granger-Sim causality test for examining the lag relationship between the investment by telecommunications firms and gross domestic product in the United States.

Problem: A sufficiently long time series necessary for using Granger causality test is not currently available for either the macro or micro economy Method: Dynamic panel data estimation (Arellano and Bond (1991), Arellano and Bover (1995) and Blundell and Bond (1998)) Application: R&D-productivity, FDI-productivity causality analyses, and so on

Regression Framework dlog A : the growth rate of the value-added labor productivity of the ith industry, in the tth year, RIK : the share of IT investment to total equipment investment RIL : ICT-capital per worker RIY : the ratio of ICT capital to output

Econometric Methodology GMM-DIF: using the dynamic first-differenced panel data equation GMM-SYS: GMM-SYS can be defined as GMM-DIF above, but with individual i’s differenced and level equations stacked together

Data Japan: 38 industries from 1987 to Source: the annual input-output (I-O) (METI), Fixed Capital Matrix of Inter- Industry Relations Tables (MPHPT) The USA: 31 industries for Source: BEA Gross Product Originating Data (87SIC)

Summary 1. Granger causality test Japan: the causality running from the ICT investment to the productivity growth is shown significant in many cases for all three indicators of ICT intensity. However, the significance of the reverse causality from the productivity growth to the ICT investment is not so consistent The USA: the strong causality running both ways between the ICT investment and the productivity growth is confirmed.

2. Dynamic Panel Data Estimators The parameter estimates suggest that the ICT investment affects the productivity growth not only concurrently but also in the long-run. The long-run effects of ICT on productivity growth in the USA are estimated somewhat larger numerically, and have shorter lag structure than those in Japan.