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Technology Diffusion: Any Further Evidence for Computer Industry?

Abstract

This paper explores the technology diffusion specifically in computer industry for a panel of 18 countries between the period 1999 and 2011. Strong evidence is found for the existence of diffusion of computer technology through bilateral capital good flows. This study shows that knowledge dissemination arises as an important determinant of output in computer sector. Still, domestic research and development efforts of countries are found to be the leading contributing factors in all model specifications. Besides, among two subgroups, in diffusion of computer technology, it is observed that USA contributes more to the knowledge dissemination in the related industry relative to three Asian countries i.e., Chinese Taipei, Korea and Singapore.

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Notes

  1. They report that in terms of “R&D flow intensity,” i.e., the world R&D flow into an equipment type divided by total sales made by R&D-performing countries, computer sector comes the second.

  2. R&D expenditure is expressed in the form of stocks constructing from flows using the perpetual inventory method.

  3. Sector code for capital good imports, final good imports, and R&D expenditure is D26. It is C30T33X for output and TTL_C30T33X for gross-fixed capital formation.

  4. Due to data unavailability, Hong Kong is not included in our estimation.

  5. Bilateral final good imports with sector code D26 is constructed for the countries of the sample. This variable represents the total final good imports of economy i from other countries in the sample.

  6. Patent variable is chosen in accordance with the inventor’s country of residence and priority date in order to be accurate about the location and the date of the invention. Patent applications to USPTO are chosen; hence, the organization received the largest number of applications in ICT technology.

  7. As stated byHoechle (2007), by applying a Newey-West-type correction, Driscoll-Kraay estimator guarantees that the covariance matrix estimator is consistent, independently of the cross-sectional dimension.

  8. The large sample is estimated with the R&D capital stocks calculated for 5, 10, and 15% depreciation rates, separately. It is obtained that the significance of variables does not change in accordance with different depreciation rates. The results reported in the paper belong to the estimates with 10% depreciation rate as in Henry et al. (2009). It still used different rates in the literature (Bloom and Van Reenen 2007).

References

  • Aghion, P., & Howitt, P. (1992). A model of growth through creative destruction. Econometrica, 60, 323–351.

    Article  Google Scholar 

  • Ahmed, E. M., & Ridzuan, R. (2013). The impact of ICT on east Asian economic growth: panel estimation approach. Journal of the Knowledge Economy, 4(4), 540–555.

    Article  Google Scholar 

  • Amann, E., & Virmani, S. (2015). Foreign direct investment and reverse technology spillovers. OECD Journal: Economic Studies, 2014(1), 129–153.

    Google Scholar 

  • Ang, J. B., & Madsen, J. B. (2013). International R&D spillovers and productivity trends in the Asian miracle economies. Economic Inquiry, 51(2), 1523–1541.

    Article  Google Scholar 

  • Assiotis, A., Zachariadis, M., & Savvides, A. (2015). What determines technology diffusion across frontiers? R&D content, human capital and institutions. Economics Bulletin, 35(2), 856–870.

    Google Scholar 

  • Bao, Q., Puyan, S. and Li, S. (2012). Do high-technology exports cause more technology spillover in China? 20(2). March–April 2012, pp. 1–22.

  • Belitz, H., & Mölders, F. (2016). International knowledge spillovers through high-tech imports and R&D of foreign-owned firms. Journal of International Trade and Economic Development, 25, 590–613.

    Article  Google Scholar 

  • Bernstein, J. I., & Mohnen, P. (1998). International R&D spillovers between U.S. and Japanese R&D intensive sectors. Journal of International Economics, 44, 315–333.

    Article  Google Scholar 

  • Bitzer, J., & Kerekes, M. (2008). Does foreign direct investment transfer technology across borders? New evidence. Economics Letters, 100(3), 355–358.

    Article  Google Scholar 

  • Blalock, G., & Gertler, P. (2005). Welfare gains from foreign direct investment through technology transfer to local suppliers. Forthcoming. Journal of International Economics, 74(2), 402–421.

    Article  Google Scholar 

  • Bloom, N. and Van Reenen, J. (2007). Identifying technology spillovers and product market rivalry. NBER Working Paper, No. 13060.

  • Bournakis, I., Christopoulos, D. and Mallick, S. (2015). Knowledge spillovers, absorptive capacity and growth: an industry-level analysis for OECD countries, FIW – Working Paper, no. 147.

  • Caselli, F., & Coleman, J. W. (2001). Cross-country technology diffusion: the case of computers. American Economic Papers and Proceedings, 91, 328–335.

    Article  Google Scholar 

  • Caselli, F., & Wilson, D. J. (2004). Importing technology. Journal of Monetary Economics, 51(1), 1–32.

    Article  Google Scholar 

  • Choi, H. (2017). Does FDI crowd out domestic firms? Micro-level evidence from the Republic of Korea. World Economy Brief, 7(1), 2233–9140.

    Google Scholar 

  • Coe, D. T., & Helpman, E. (1995). International R&D spillovers. European Economic Review, 39, 859–887.

    Article  Google Scholar 

  • Coe, D. T., Helpman, E., & Hoffmaister, A. (1997). North–South R&D spillovers. Economic Journal, 107, 134–150.

    Article  Google Scholar 

  • Coe, D. T., Helpman, E., & Hoffmaister, A. W. (2009). International R&D spillovers and institutions. European Economic Review, 53(7), 723–741.

    Article  Google Scholar 

  • Cohen, W. M. and Levinthal, D. A. (1990). Administrative science quarterly, special issue: technology, organizations, and innovation (Mar., 1990), 35(1), pp. 128–152.

  • Comin, D. A., & Mestieri, M. (2014). Technology diffusion: measurement, causes and consequences. In P. Aghion & S. Durlauf (Eds.), Handbook of economic growth (Vol. 2, pp. 565–622). Amsterdam: Elsevier.

    Google Scholar 

  • Falvey, R., Foster, N., & Greenaway, D. (2002). North–south trade, knowledge spillovers and growth. Journal of Economic Integration, 17, 650–670.

    Article  Google Scholar 

  • Falvey, R., Foster, N., & Greenaway, D. (2004). Imports, exports, knowledge spillovers and growth. Economics Letters, 85(2), 209–213.

    Article  Google Scholar 

  • Ferrier, G., Reyes, J., & Zhu, Z. (2016). Technology diffusion on the international trade network. Journal of Public Economic Theory, 18(2), 291–312.

    Article  Google Scholar 

  • Funk, M. (2001). Trade and international R&D spillovers among OECD countries. Southern Economic Journal, 3, 725–736.

    Article  Google Scholar 

  • Gehringer, A., Zarsazo, I. M. and Danzinger, F. N. (2013). The determinants of total factor productivity in the EU: insights from sectoral data and common dynamic processes. Working Paper EcoMod 2013.

  • Grossman, G., & Helpman, E. (1991). Innovation and growth in the global economy. MIT Press, Cambridge.

  • Hallward-Driemeier, M., Iarossi, G. and Sokoloff, K. (2002). Exports and manufacturing productivity in East Asia: a comparative analysis with firm-level data. Working paper. UCLA.

  • Henry, M., Klenner, R., & Milner, C. (2009). Trade, technology transfer and national efficiency in developing countries. European Economic Review, 53, 237–254.

    Article  Google Scholar 

  • Hoechle, D. (2007). Robust standard errors for panel regressions with cross–sectional dependence. Stata Journal, 7(3), 281–312.

    Article  Google Scholar 

  • Keller, W. (1998). Are international R&D spillovers trade-related?: analyzing spillovers among randomly matched trade partners. European Economic Review, 42(8), 1469–1481.

    Article  Google Scholar 

  • Keller, W. (2004). International technology diffusion. Journal of Economic Literature, 42(3), 752–782.

    Article  Google Scholar 

  • Liang, F. (2008). Does foreign direct investment improve the productivity of domestic firms? Technology spillovers, industry linkages, and firm capabilities. Haas School of Business, University of California, Berkeley. Durlauf (eds.), Handbook of Economic Growth Vol. 2B, Amsterdam: Elsevier Press.

  • Lichtenberg, F., & van Pottelsberghe de la Potterie, B. (1998). International R&D spillovers: a comment. European Economic Review, 42(8), 1483–1491.

    Article  Google Scholar 

  • Lichtenberg, F., & van Pottelsberghe de la Potterie, B. (2001). Does foreign direct investment transfer technology across borders? Review of Economics and Statistics, 83(3), 490–497.

    Article  Google Scholar 

  • Madsen, J. B. (2008). Economic growth, TFP convergence and the world export of ideas: a century of evidence. Scandinavian Journal of Economics, 110(1), 145–167.

    Article  Google Scholar 

  • Mendi, P. (2007). Trade in disembodied technology and total factor productivity in OECD countries. Research Policy, 36, 121–133.

    Article  Google Scholar 

  • Romer, P. (1990). Endogenous technological change. Journal of Political Economy, 98, 71–102.

    Article  Google Scholar 

  • Seck, A. (2012). International technology diffusion and economic growth: Explaining the spillover benefits to developing countries. Structural Change and Economic Dynamics, 23(4), 437–451.

    Article  Google Scholar 

  • Tian, X. (2007). Accounting for sources of FDI technology spillovers: evidence from China. Journal of International Business Studies, 38(1), 147–159.

    Article  Google Scholar 

  • Wang, Y., Ning, L., Li, J., & Prevezer, M. (2016). Foreign direct investment spillovers and the geography of innovation in Chinese regions: the role of regional industrial specialization and diversity. Regional Studies, 50(5), 805–822.

    Article  Google Scholar 

  • Xu, B., & Chiang, E. (2005). Trade, patents and international technology diffusion. Journal of International Trade and Economic Development, 14(1), 115–135.

    Article  Google Scholar 

  • Xu, B., & Wang, J. (1999). Capital goods trade and R&D spillovers in the OECD. Canadian Journal of Economics, 32(5), 1258–1274.

    Article  Google Scholar 

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Correspondence to Cemil Faruk Durmaz.

Appendix

Appendix

Domestic R&D capital stocks of the countries are calculated using the perpetual inventory method. Capital stock for the initial year is calculated as in Eq. (1). The term E0 denotes the R&D expenditure in the first year of the data, i.e., year 1999, and g stands for the average annual logarithmic growth of R&D expenditures in all years and δ for the depreciation rate taken as 10%.Footnote 8

$$ {R}_0={E}_0/\left(g+\delta \right) $$

In Eq. (2), Rt − 1 stands for the capital stock in year t − 1 and Et denotes the expenditure on R&D in year t. (1 − δ) represents the remaining capital stock after the depreciation.

$$ {R}_t=\left(1\hbox{--} \delta \right){R}_{t-1}+{E}_t $$

It should be noted that Rt for each year and country is shown as \( {RD}_{it}^D \) for the domestic R&D capital stock of the receiver and \( {RD}_{jt}^D \) for the domestic knowledge capital of the exporter country.

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Durmaz, C.F., Polat, U. Technology Diffusion: Any Further Evidence for Computer Industry?. J Knowl Econ 11, 356–372 (2020). https://doi.org/10.1007/s13132-018-0549-6

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Keywords

  • R&D spillover
  • Technology diffusion
  • Computer sector

JEL Classification

  • L6
  • O3
  • O4