Determinants of high-tech export: evidence from a cross-country analysis
Abstract
Relevance. The adoption of new technologies and the rapid emergence of innovation spur high-tech production and export-led economic growth. We aim to provide fresh evidence on the determinants of high-tech exports, considering different macroeconomic factors within the framework of the gravity model.
Research Objective. The aim of the research is to empirically assess the impact of macroeconomic instability, tax policies, natural resources endowment, human capital, and institutional environment on the promotion of high-tech exports.
Data and Methods. In considering the institutional indicator, six distinct indices from the World Bank are examined, and a common indicator is computed using principal component analysis. The econometric modeling uses a panel dataset covering the world's 80 largest economies from 1996 to 2019. To test the assumptions of the gravity model and tackle the heteroscedasticity problem, the Poisson Pseudo Maximum Likelihood methodology is employed.
Results. Higher inflation and unemployment rates are found to significantly decrease high-tech exports, while government external debt contributes to their enhancement. Tight tax policy and an increase in tax contribution are counterproductive in spurring high-tech exports. A negative and significant result is found for resource endowment, indicating that an increase in resource exports is counterproductive for technological advances and high-tech production. In most cases, the institutional environment and human capital significantly promote high-tech exports.
Conclusions. Based on the presented empirical findings, we offer recommendations for the government to stimulate high-tech exports.
Keywords
Full Text:
PDFReferences
Alsharif, N. N. (2018). Natural resources and economic diversification: Evidence from the GCC countries. In Economic Diversification in the Gulf Region (21-49). Singapore: Palgrave Macmillan.
Arif, I. (2022). Educational attainment, corruption, and migration: an empirical analysis from a gravity model. Economic Modelling, 110, 105802. https://doi.org/10.1016/j.econmod.2022.105802
Bierut, B. K., & Dybka, P. (2021). Increase versus transformation of export through technological and institutional innovation: evidence from Bayesian model averaging. Economic Modelling, 99, 105501. https://doi.org/10.1016/j.econmod.2021.105501
Chandra, V. (2006). Technology, Adaptation, and Export: How Some Developing Countries Got It Right. Washington DC: World Bank. Available at: https://openknowledge.worldbank.org/handle/10986/7118 (Assessed on: June, 2022)
Chaudhry, A., & Bukhari, S. K. H. (2013). A structural VAR analysis of the impact of macroeconomic shocks on Pakistan’s textile export. Economic Modelling, 32, 302–315. https://doi.org/10.1016/j.econmod.2013.01.043
Chen, S., & Liu, X. (2022). Innovation spillovers in production networks: evidence from the establishment of national high-tech zones. China Economic Quarterly International, 2(1), 42–54. https://doi.org/10.1016/j.ceqi.2022.03.001
Cheung, K. Y. (2010). Spillover effects of FDI via export on innovation performance of China's high-technology industries. Journal of Contemporary China, 19(65), 541-557. https://doi.org/10.1080/10670561003666152
Cirera, X., & Maloney, W. (2017). The innovation paradox: developing-country capabilities and the unrealized promise of technological catch-up. Washington DC: World Bank. https://doi.org/10.1596/978-1-4648-1160-9
Dai, X., & Chapman, G. (2022). R&D tax incentives and innovation: examining the role of programme design in China. Technovation, 113, 102419. https://doi.org/10.1016/j.technovation.2021.102419
Entele, B. R. (2021). Impact of institutions and ICT services in avoiding resource curse: lessons from the successful economies. Heliyon, 7(2), e05961. https://doi.org/10.1016/j.heliyon.2021.e05961
Federici, D., Parisi, V., & Elliott, C. (2015). Do corporate taxes reduce investments? Evidence from Italian firm-level panel data. Cogent Economics & Finance, 3, 1012435. https://doi.org/10.1080/23322039.2015.1012435
Federici, D., Parisi, V., & Ferrante, F. (2020). Heterogeneous firms, corporate taxes and export behavior: A firm-level investigation for Italy. Economic Modelling, 88, 98–112. https://doi.org/10.1016/j.econmod.2019.09.012
Freeman, R., & Lewis, J. (2021). Gravity model estimates of the spatial determinants of trade, migration, and trade-and-migration policies. Economics Letters, 204, 109873. https://doi.org/10.1016/j.econlet.2021.109873
Głodowska, A., Maciejewski, M., & Wach, K. (2019). How Entrepreneurial Orientation Stimulates Different Types of Knowledge in the Internationalisation Process of Firms from Poland? Entrepreneurial Business and Economics Review, 7, 61–73. https://doi.org/10.15678/EBER.2019.070104
Gu, J., Umar, M., Soran, S., & Yue, X.-G. (2020). Exacerbating effect of energy prices on resource curse: Can R&D be a mitigating factor? Resources Policy, 67, 101689. https://doi.org/10.1016/j.resourpol.2020.101689
Irshad, M. S., Xin, Q., Shahriar, S., & Arshad, H. (2017). A panel data analysis of China’s trade pattern with OPEC members: gravity model approach. Asian Economic and Financial Review, 8(1), 103–116. https://doi.org/10.18488/journal.aefr.2018.81.103.116
Malik, T. H., Xiang, T., & Huo, C. (2021). The transformation of national patents for high-technology export: Moderating effects of national cultures. International Business Review, 30(1), 101771. https://doi.org/10.1016/j.ibusrev.2020.101771
Martínez-Zarzoso, I., & Suárez-Burguet, C. (2005). Transport costs and trade: empirical evidence for Latin American imports from the European Union. Journal of International Trade & Economic Development, 14(3), 353-371. https://doi.org/10.1080/09638190500212121
Mehrara, M., Seijani, S., & Karsalari, A. R. (2017). Determinants of high-tech export in developing countries based on Bayesian model averaging. Zbornik Radova Ekonomskog Fakultet Au Rijeci, 35(1), 199–215. https://doi.org/10.18045/zbefri.2017.1.199
Mhuru, R. M., Daglish, T., & Geng, H. (2022). Oil discoveries and innovation. Energy Economics, 110, 105997. https://doi.org/10.1016/j.eneco.2022.105997
Nasrullah, M., Chang, L., Khan, K., Rizwanullah, M., Zulfiqar, F., & Ishfaq, M. (2020). Determinants of forest product group trade by gravity model approach: A case study of China. Forest Policy and Economics, 113, 102117. https://doi.org/10.1016/j.forpol.2020.102117
Natale, F., Borrello, A., & Motova, A. (2015). Analysis of the determinants of international seafood trade using a gravity model. Marine Policy, 60, 98–106. https://doi.org/10.1016/j.marpol.2015.05.016
Özsoy, S., Ergüzel, O. Ş., Ersoy, A. Y., & Saygılı, M. (2022). The impact of digitalization on export of high technology products: A panel data approach. The Journal of International Trade & Economic Development, 31(2), 277–298. https://doi.org/10.1080/09638199.2021.1965645
Sandu, S., & Ciocanel, B. (2014). Impact of R&D and Innovation on high-tech Export. Procedia Economics and Finance, 15(14), 80–90. https://doi.org/10.1016/s2212-5671(14)00450-x
Santos Silva, J. M. C., & Tenreyro, S. (2022). The log of gravity at 15. Portuguese Economic Journal, 21(3), 423-437. https://doi.org/10.1016/j.econlet.2010.02.020
Shao, Y., & Xiao, C. (2019). Corporate tax policy and heterogeneous firm innovation: Evidence from a developing country. Journal of Comparative Economics, 47(2), 470–486. https://doi.org/10.1016/j.jce.2019.02.005
Silva, J. M. C. S., & Tenreyro, S. (2006). The log of gravity. The Review of Economics and Statistics, 88(4), 641–658. https://doi.org/10.1162/rest.88.4.641
Silva, S. & Tenreyro, S. (2010). On the existence of the maximum likelihood estimates in Poisson regression. Economics Letters, 107(2), 310-312.
Tebaldi, E. (2011). The Determinants of High-Technology Export: A Panel Data Analysis. Atlantic Economic Journal, 39(4), 343–353. https://doi.org/10.1007/s11293-011-9288-9
Tinbergen, J. (1962). Shaping the world economy: Suggestions for an international economic policy. New York: The Twentieth Century Fund, 330.
Todshki, N. E., & Ranjbaraki, A. (2016). The Impact of Major Macroeconomic Variables on Iran’s Steel Import and Export. Procedia Economics and Finance, 36, 390–398. https://doi.org/10.1016/S2212-5671(16)30051-X
Vasilyeva, R. I., & Mariev, O. S. (2021). Determinants of foreign direct investment in developed and developing countries: impact of political stability. Economy of Region, 17(4), 1390–1404. https://doi.org/10.17059/ekon.reg.2021-4-24
Walter, J., Baek, J., & Koo, W. W. (2012). International trade and macroeconomic dynamics: The case of U.S. bilateral trade with G-7 countries. Research in Economics, 66(4), 398–405. https://doi.org/10.1016/j.rie.2012.06.003
Wan, Q., Chen, J., Yao, Z., & Yuan, L. (2022). Preferential tax policy and R&D personnel flow for technological innovation efficiency of China’s high-tech industry in an emerging economy. Technological Forecasting and Social Change, 121228. https://doi.org/10.1016/j.techfore.2021.121228
Wang, R., Tan, J., & Yao, S. (2021). Are natural resources a blessing or a curse for economic development? The importance of energy innovations. Resources Policy, 72, 102042. https://doi.org/10.1016/j.resourpol.2021.102042
Were, M. (2015). Differential effects of trade on economic growth and investment: A cross-country empirical investigation. Journal of African Trade, 2(1–2), 71–85, https://doi.org/10.1016/j.joat.2015.08.002
World Inequality Report. (2022). UNDP. 236 p.
Yang, Y., & Mallick, S. (2014). Explaining cross-country differences in exporting performance: The role of country-level macroeconomic environment. International Business Review, 23(1), 246–259. https://doi.org/10.1016/j.ibusrev.2013.04.004
Zhu, S., & Fu, X. (2013). Drivers of Export Upgrading. World Development, 51(C), 221–233. https://doi.org/10.1016/j.worlddev.2013.05.017
DOI: https://doi.org/10.15826/recon.2024.10.1.003
Copyright (c) 2024 Igor M. Drapkin, Rogneda I. Vasilyeva, Anastasya A. Kandalintseva
Сertificate of registration media Эл № ФС77-80764 от 23.04.2021
Online ISSN 2412-0731