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The Determinants of High-Technology Exports: A Panel Data Analysis

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Abstract

This paper uses a panel dataset from 1980 to 2008 to examine the determinants of high-technology exports. This research finds evidence that human capital, inflows of foreign direct investments, and openness to international trade are the major factors impacting the performance of a country's high-tech industry in the global market. It also shows that institutions do not have a direct impact on high-tech exports. However, institutions might impact high-tech exports indirectly via their effect on proximate factors such as human capital and inflows of foreign direct investments. This paper also demonstrates that gross capital formation, savings, and macroeconomic volatility have no significant effect on high-tech exports.

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Notes

  1. According to the World Bank’s definition, high-technology goods are products with high R&D intensity, such as in aerospace, computers, pharmaceuticals, scientific instruments, and electrical machinery.

  2. See Eaton and Kortum (2001) for details regarding this specification.

  3. R&D investment is an obvious regressor in this equation. However, there are major data limitations (e.g. missing data) in the R&D investment data provided by the World Bank, preventing the use of R&D investment in this study. Nevertheless, R&D investment is highly correlated with human capital, so any bias due to the omission of R&D investment is minimizes by including human capital in the set of regressors.

  4. See Table 1 for a complete list of the variables used in this study.

  5. This approach is consistent with several studies including Gittell and Tebaldi (2010) and Forbes (2000).

  6. Political institutions are treated as exogenous. However, a more robust approach would treat institutions as a endogenous variable and, consequently, deal with potential endogeneity.

  7. The term “proximate factors” was popularized by Acemoglu et al. (2005) and Acemoglu (2008).

  8. The coefficient on political institutions is also statistically insignificant in several other specifications not reported in the paper.

  9. Unaccounted endogencity might be driving this result. So, further investigation on the relationship between institutions and high-tech exports might be necessary.

  10. The coefficients on openness are marginally significant.

References

  • Acemoglu, D. (2008). Introduction to modern economic growth. Princeton: Princeton University Press.

    Google Scholar 

  • Acemoglu, D., Johnson, S., & Robinson, J. A. (2005). Institutions as a fundamental cause of long-run growth. In P. Aghion & S. Durlauf (Eds.), Handbook of economic growth, vol 1, part 1, chapter 6. North Holland: Elsevier.

    Google Scholar 

  • Barlevy, G. (2004). On the timing of innovation in stochastic schumpeterian growth models. NBER Working Paper Series, 10741.

  • Barro, R. J. & Lee, J.-W. (2010). A new data set of educational attainment in the world, 1950–2010. NBER Working Paper Series, 15902.

  • Bernard, A. B., & Jensen, J. B. (2004). Exporting and productivity in the USA. Oxford Review of Economic Policy, 20(3), 343–357.

    Article  Google Scholar 

  • Braunerhjelm, P., & Thulin, P. (2008). Can countries create comparative advantages? R&D expenditures, high-tech exports and country size in 19 OECD countries, 1981–1999. International Economic Journal, 22(1), 95–111.

    Article  Google Scholar 

  • Eaton, J., & Kortum, S. (2001). Technology, trade and growth: A unified framework. European Economic Review, 45(4–6), 742–755.

    Article  Google Scholar 

  • Falk, M. (2009). High-tech exports and economic growth in industrialized countries. Applied Economics Letters, 16(10–12), 1025–1028.

    Article  Google Scholar 

  • Forbes, K. J. (2000). A reassessment of the relationship between inequality and growth. The American Economic Review, 90(4), 869–887.

    Article  Google Scholar 

  • Gittell, R., & Tebaldi, E. (2010). Poverty in U.S. metropolitan areas: What are the key determinants and what is the role of local fiscal structure? Public Finance and Management, 10(3), 411–442.

    Google Scholar 

  • Hall, R. E., & Jones, C. I. (1999). Why do some countries produce so much more output per worker than others? Quarterly Journal of Economics, 114(1), 83–116.

    Article  Google Scholar 

  • Head, K., & Ries, J. (1998). Immigration and trade creation: Econometric evidence from Canada. Canadian Journal of Economics, 31(1), 47–62.

    Article  Google Scholar 

  • Madsen, J. B. (2009). Trade barriers, openness, and economic growth. Southern Economic Journal, 76(2), 397–418.

    Article  Google Scholar 

  • Peri, G. & Requena, F. (2009). The trade creation effect of immigrants: Testing the theory on the remarkable case of Spain. CReAM Discussion Paper Series, No 0915. Centre for Research and Analysis of Migration (CReAM), University College London.

  • Rauch, J. E., & Trindade, V. (2002). Ethnic Chinese networks in international trade. The Review of Economics and Statistics, 84(1), 116–130.

    Article  Google Scholar 

  • Spulber, D. F. (2008). Innovation and international trade in technology. Journal of Economic Theory, 138(1), 1–20.

    Article  Google Scholar 

  • Srholec, M. (2007). High-tech exports from developing countries: A symptom of technology spurts or statistical illusion? Review of World Economics/Weltwirtschaftliches Archiv, 143(2), 227–255.

    Article  Google Scholar 

  • Zhang, K. H. (2007). Determinants of complex exports: Evidence from cross-country data for 1985–1998. Economia Internazionale/International Economics, 60(1), 111–122.

    Google Scholar 

  • Zhu, L., & Jeon, B. N. (2007). International R&D spillovers: Trade, FDI, and information technology as spillover channels. Review of International Economics, 15, 955–976.

    Article  Google Scholar 

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Correspondence to Edinaldo Tebaldi.

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Tebaldi, E. The Determinants of High-Technology Exports: A Panel Data Analysis. Atl Econ J 39, 343–353 (2011). https://doi.org/10.1007/s11293-011-9288-9

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