Recalculation of Manufacturing Industry Production Function with Trade Openness and Human Capital: Multi-Dimensional Panel Data Application

Year 2023, , 437 - 459, 28.11.2023

Ergün Aktürk , Yusuf Akan , Sena Gültekin

https://doi.org/10.26650/ibr.2023.52.1120652

Abstract

The manufacturing industry plays a key role in ensuring long-term and sustainable economic development. Although the impact of the service and information technology sectors on economic growth has increased recently, reindustrialization trends have appeared especially in developing and underdeveloped countries. Studies on the manufacturing industry have started to gain importance again within the scope of reindustrialization. In this context, the production functions of the manufacturing industry started to be recalculated and the factors affecting the manufacturing industry became the field of study again. In particular, global trade has become one of the dominant issues in terms of the manufacturing industry. This study aims to calculate the manufacturing industry production function of 40 countries for the period of 2000-2014. While making this calculation, it is aimed to see the effect of trade openness and human capital on manufacturing industry production. For this purpose, multidimensional panel data analysis was used and the Cobb-Douglas production function was calculated. As a result of the analysis, it has been found that labor, exchange rate, trade openness, and human capital have a positive effect on manufacturing industry production.

Keywords

Manufacturing Industry, Cobb-Douglas Production Function, Multidimensional Panel Data Analysis, Trade Openness, Human Capital

References

• Acemoglu, D., & Autor, D. (2010). Skills, tasks and technologies: implications for employment and earnings. Handbook of Labor Economics, 4(B), 1043-1171. https://doi.org/10.1016/S0169-7218(11)02410-5 google scholar
• Aiyar, S., & Dalgaard, C. J. (2009). Accounting for productivity: is it ok to assume that the world is Cobb-Douglas?. Journal of Macroeconomics, 31(2), 290-303. https://doi.org/10.1016/j.jmacro.2008.09.007 google scholar
• Aquino, J. C., & Ramnez-Rondan, N. R. (2020). Estimating factor shares from nonstationary panel data. Em-pirical Economics, 58(5), 2353-2380. https://doi.org/10.1007/s00181-019-01647-y google scholar
• Aslan, A., Menegaki, A. N., & Tugcu, C. T. (2016). Health and economic growth in high-income countries revisited: evidence from an augmented production function for the period 1980-2009. Quality & Quan-tity, 50(2), 937-953. https://doi.org/10.1007/s11135-015-0184-2 google scholar
• Aydın, E. (2018). Impact of capital intensity and R&D spending on manufacturing industry value added in industry 4.0 process: panel data analysis. Yönetim ve Ekonomi Araştırmaları Dergisi, 16(1), 303-314. https://doi.org/10.11611/yead.416806 google scholar
• Azolibe, C. B. (2020). Does foreign direct investment influence manufacturing sector growth in Middle East and North African region?. International Trade, Politics and Development, 5(1), 71-85. https://doi. org/10.1108/ITPD-04-2020-0010 google scholar
• Baldwin, R. E., Martin, P., & Ottaviano, G. I. (2001). Global income divergence, trade, and industrialization: The geography of growth take-offs. Journal of Economic Growth, 6(1), 5-37. Retrieved from https://link. springer.com/content/pdf/10.1023/A:1009876310544.pdf google scholar
• Baltagi B., Song S.H.,& Jung B. C., (2001).The unbalanced nested error component regression model. Jour-nal of Econometrics, 101 (2), 357-381. https://doi.org/10.1016/S0304-4076(00)00089-0 google scholar
• Banday, U. J., Murugan, S., & Maryam, J. (2021). Foreign direct investment, trade openness and economic growth in BRICS countries: evidences from panel data. Transnational Corporations Review, 13(2), 211221. https://doi.org/10.1080/19186444.2020.1851162 google scholar
• Böhringer, C., Moslener, U., Oberndorfer, U., & Ziegler, A. (2012). Clean and productive? empirical eviden-ce from the German manufacturing industry. Research Policy, 41(2), 442-451. https://doi.org/10.1016/j. respol.2011.10.004 google scholar
• Brock, G., & German-Soto, V. (2013). Regional industrial growth in Mexico: Do human capital and infrastruc-ture matter?. Journal of Policy Modeling, 35(2), 228-242. https://doi.org/10.1016/j.jpolmod.2012.10.003 google scholar
• Brueckner, M., & Lederman, D. (2015). Trade openness and economic growth: Panel data evidence from Sub-Saharan Africa. Economica, 82, 1302-1323. https://doi.org/10.1111/ecca.12160 google scholar
• Chen, L. F., & Chien, C. F. (2011). Manufacturing intelligence for class prediction and rule generation to support human capital decisions for high-tech industries. Flexible services and manufacturing journal, 23(3), 263-289. https://doi.org/10.1007/s10696-010-9068-x google scholar
• Chikabwi, D., Chidoko, C., & Mudzingiri, C. (2017). Manufacturing sector productivity growth drivers: Evi-dence from SADC member states. African Journal of Science, Technology, Innovation and Development, 9(2), 163-171. https://doi.org/10.1080/20421338.2017.1299343 google scholar
• Ciccone, A., & Papaioannou, E. (2009). Human capital, the structure of production, and growth. Review of Economics andStatistics, 91 (1), 66-82. https://doi.Org/10.1162/rest.91.1.66 google scholar
• Cobb, C. W., & Douglas, P. H. (1928). A theory of production. The American Economic Review, 18(1), 139165. Retrieved from https://www.aeaweb.org/aer/top20/18.1.139-165.pdf google scholar
• Correa, N., & Kanatsouli, F. (2018). Industrial Development in Least Developed Countries. UNIDO Depart-ment of Policy, Research and Statistics Working Paper 26/2018. Retrieved from https://www.unido.org/ api/opentext/documents/download/12831761/unido-file-12831761 google scholar
• Correa, N., & Todorov, V. (2020). Competitive Industrial Performance Report 2020. UNIDO, Retrieved from https://stat.unido.org/content/publications/competitive-industrial-performance-report-2020 google scholar
• Dadush, U. (2015). Is Manufacturing Still A Key to Growth?. Morocco, PP-15/07, OCP Policy Centre. Ret-rieved from https://www.policycenter.ma/sites/default/files/2021-01/OCPPC-PP1507.pdf google scholar
• Das, D. K., & Kalita, G. (2009). Do Labor Intensive Industries Generate Employment? Evidence from firm level survey in India. Indian Councilfor Research on International Economic Relations, Working Paper, (237). Retrieved from https://icrier.org/pdf/WorkingPaper237.pdf google scholar
• Dasgupta, S., & Singh, A. (2007) Manufacturing, services and premature deindustrialization in developing countries: A Kaldorian analysis. In Mavrotas G. & Shorrocks A. (Eds), Advancing Development. Studies in Development Economics and Policy. London: Palgrave Macmillan. google scholar
• De Souza, J. P A., & Gomez-Ramırez, L. (2018). The paradox of Mexico’s export boom without growth: A demand-side explanation. Structural Change and Economic Dynamics, 47, 96-113. https://doi. org/10.1016/j.strueco.2018.08.001 google scholar
• Dietzenbacher, E., Los, B., Stehrer, R., Timmer, M., & De Vries, G. (2013). The construction of world in-put-output tables in the WIOD project. Economic Systems Research, 25(1), 71-98. https://doi.org/10.108 0/09535314.2012.761180 google scholar
• Dodzin, S., & Vamvakidis, A. (2004). Trade and industrialization in developing economies. Journal of Deve-lopment Economics, 75(1), 319-328. https://doi.org/10.1016/j.jdeveco.2003.08.006 google scholar
• Dumitrescu, E.I., & Hurlin, C. (2012). Testing for Granger non-causality in heterogeneous panels. Economic Modelling, 29, 1450-1460. https://doi.Org/10.1016/j.econmod.2012.02.014 google scholar
• Facevicova, K., & Kynclova, P. (2020). How Industrial development matters to the well-being of the po-pulation: Some statistical evidence. UNIDO, Retrieved from https://www.unido.org/sites/default/files/ files/2020-02/HOW%20INDUSTRIAL%20DEVELOPMENT%20MATTERS%20TO%20THE%20 WELL-BEING%20OF%20THE%20POPULATION%20FIN.pdf google scholar
• Gajdzik, B. (2020). Conditions of steel industry in Poland after restructuring-the analysis by using C-D model. Multidisciplinary Aspects of Production Engineering, 3, 28-40. https://doi.org/10.2478/mape-2020-0003 google scholar
• Hajkova, D., & Hurnık, J. (2007). Cobb-Douglas production function: The case of a converging eco-nomy. Czech Journal of Economics and Finance, 57(9-10), 465-476. Retrieved from http://journal.fsv. cuni.cz/storage/1088_fau_9_10_2007_00000053.pdf google scholar
• Haraguchi, N., Cheng, C. F. C., & Smeets, E. (2017). The importance of manufacturing in economic de-velopment: Has this changed?. World Development, 93, 293-315. https://doi.org/10.1016/j.worl-ddev.2016.12.013 google scholar
• Hassine, B., H., Boudier, F., & Mathieu, C. (2017). The two ways of FDI R&D spillovers: Evidence from the French manufacturing industry. Applied Economics, 49(25), 2395-2408. http://dx.doi.org/10.1080/00 036846.2016.1240345 google scholar
• Hossain, M. Z., & Al-Amri, K. S. (2010). Use of Cobb-Douglas production model on some selected manu-facturing industries in Oman. Education, Business and Society: Contemporary Middle Eastern Issues. 3(2), 78-85. http://dx.doi.org/10.1108/17537981011047925 google scholar
• Hossain, M. M., Basak, T., & Majumder, A. K. (2013). Application of non-linear Cobb-Douglas production function with autocorrelation problem to selected manufacturing industries in Bangladesh. Open Journal of Statistics, 03(03), 173-178. http://dx.doi.org/10.4236/ojs.2013.33019 google scholar
• Hossain, Z., Bhatti, M. I., & Ali, M. Z. (2004). An econometric analysis of some major manufacturing in-dustries. Managerial Auditing Journal, 19(6), 790-795. http://dx.doi.org/10.1108/02686900410543895 google scholar
• Hsu, B. X., & Chen, Y. M. (2019). Industrial policy, social capital, human capital, and firm-level compe-titive advantage. International Entrepreneurship and Management Journal, 15(3), 883-903. https://doi. org/10.1007/s11365-019-00584-7 google scholar
• Hu, Z., & Hu, Z. (2013). Production function with electricity consumption and its applications. Energy Eco-nomics, 39, 313-321. https://doi.org/10.1016/j.eneco.2013.03.007 google scholar
• Ismail, R. (2006). Human capital attainment and performance of small and medium scale industries in Ma-laysia. Economic Journal of Emerging Markets, 11(1), 79-90. https://doi.org/10.20885/ejem.v11i1.578 google scholar
• İsabetli, İ., & Tunali, H. (2018). Toplam faktör verimliliği ve ekonomik büyüme ilişkisinin çok boyutlu panel veri modeli ile analizi [Analysis of total factor productivity and economic growth with multidimensional panel data model]. Akademik Araştırmalar ve Çalışmalar Dergisi, 10(18), 189-199. google scholar
• Jenkins, R., & Sen, K. (2006). International trade and manufacturing employment in the south: Four country case studies. Oxford Development Studies, 34(3), 299-322. http://dx.doi.org/10.1080/13600810600921802 google scholar
• Jungmittag, A., & Pesole, A. (2019). The impact of robots on labour productivity: A panel data approach covering 9 industries and 12 countries. JRC Working Papers Series on Labour, Education and Technology, No. 2019/08, European Commission, Joint Research Centre (JRC), Seville. Retrieved from https://joint-research-centre.ec.europa.eu/publications/impacts-robots-labour-productivity-panel-data-approach-cove ring-9-industries-and-12-countries_en google scholar
• Kaldor, N. (1966). Causes of the slow rate of economic growth of the United Kingdom: An inaugural lecture. Cambridge: Cambridge University Press. google scholar
• Karami, M., Elahinia, N., & Karami, S. (2019). The Effect of Manufacturing Value Added on Economic Growth: Empirical Evidence from Europe. Journal of Business Economics and Finance, 8(2), 133-146. https://doi.org/10.17261/Pressacademia.2019.1044 google scholar
• Kartal, Z., Zhumasheva, A., & Acaroglu, H. (2017). The effect of human capital on economic growth: A time series analysis for Turkey. In Bilgin, M. H., Danis, H., Demir, E. & Can, U. (Eds.), Regional Studies on Economic Growth, Financial Economics and Management (pp. 175-191). Springer, Cham. google scholar
• Khalil, A. M. (2005). A cross section estimate of translog production function: Jordanian manufacturing industry. Topics in Middle Eastern and North African Economies, 7, 1-14. Retrieved from https://meea. sites.luc.edu/volume7/khalil.pdf google scholar
• Khatun, T., & Afroze, S. (2016). Relationship between real GDP and labour & capital by applying the Cobb-Douglas production function: A comparative analysis among selected Asian countries. Journal of Busi-ness, 37(1), 113-129. Retrieved from http://journal.library.du.ac.bd/index.php?journal=DUBS&page=art icle&op=view&path%5B%5D=2213&path%5B%5D=2053 google scholar
• Krawczynski, M., Czyzewski, P., & Bocian, K. (2016). Reindustrialization: A challenge to the economy in the first quarter of the twenty-first century. Foundations of Management, 8, 107-122. https://doi.org/10.1515/ fman-2016-0009 google scholar
• Kumar, S., Sankaran, A., Arjun, K., & Das, M. (2019). What types of economies of scale exist in the ma-nufacturing economy of India? A Cobb-Douglas production function approach for four decades. The Empirical Economics Letters, 18(6), 651-661. Retrieved from https://www.academia.edu/44936098/ What_Types_of_Economies_of_Scale_Exist_in_the_Manufacturing_Economy_of_India_A_Cobb_Do-uglas_Production_Function_Approach_for_Four_Decades google scholar
• Landesmann, M. A., & Stöllinger, R. (2019). Structural change, trade and global production networks: An ‘appropriate industrial policy’ for peripheral and catching-up economies. Structural Change and Econo-mic Dynamics, 48, 7-23. https://doi.org/10.1016/j.strueco.2018.04.001 google scholar
• Lee, J.-W., & McKibbin, W. J. (2014). Service sector productivity and economic growth in Asia. ADBI Wor-king Papers 490. Tokyo: Asian Development Bank Institute. Retrieved from https://www.adb.org/sites/ default/files/publication/156345/adbi-wp490.pdf google scholar
• Li, Z. (2020). Industrial agglomeration and regional economic growth—analysis of the threshold effect based on industrial upgrading. Open Journal of Business and Management, 8(2), 971-982. https://doi.org/10.4236/ojbm.2020.82061 google scholar
• Li, W., Xue, D., & Huang, X. (2018). The role of manufacturing in sustainable economic development: A case of Guangzhou, China. Sustainability, 10(9), 3039. https://doi.org/10.3390/su10093039 google scholar
• Li, H., & Wang, Y. (2016). Growth channels of human capital: A Chinese panel data study. China Economic Review, 51, 309-322. https://doi.org/10.1016/j.chieco.2016.11.002 google scholar
• Libanio, G., & Moro, S. (2006). Manufacturing industry and economic growth in Latin America: A Kaldorian approach. Proceedings of the 37th Brazilian Economics Meeting, 86, 1-14. Retrieved from http://www. anpec.org.br/encontro2009/inscricao.on/arquivos/000-98e6915698ae97aca03d8e866339ae4e.pdf google scholar
• Luken, R., & Castellanos-Silveria, F. (2011). Industrial transformation and sustainable development in deve-loping countries. Sustainable Development, 19(3), 167-175. http://dx.doi.org/10.1002/sd.434 google scholar
• Mahaboob, B., Ajmath, K. A., Venkateswarlu, B., Narayana, C., & Praveen, J. P. (2019). On Cobb-Douglas production function model. Proceedings of AIP Conference, 2177, No. 1, 020040. https://dx.doi. org/10.1063/1.5135215 google scholar
• Managi, S., Hibiki, A., & Tsurumi, T. (2009). Does trade openness improve environmental quality?. Journal of Environmental Economics and Management, 58(3), 346-363. https://doi.org/10.1016/j.jeem.2009.04.008 google scholar
• Maroto-Sanchez, A., & Cuadrado-Roura, J. R. (2009). Is growth of services an obstacle to productivity growth? A comparative analysis. Structural Change and Economic Dynamics, 20(4), 254-265. https:// doi.org/10.1016/j.strueco.2009.09.002 google scholar
• Mendoza Cota, J. E. (2016). US manufacturing imports from China and employment in the Mexican ma-nufacturing sector. Cuadernos de Economda, 35(69), 583-613. Retrieved from https://www.redalyc.org/ pdf/2821/282144830002.pdf google scholar
• Miller, E. (2008). An assessment of CES and Cobb-Douglas production functions. Working Paper Was-hington, DC: Congressional Budget Office. Retrieved from https://www.cbo.gov/sites/default/files/110th-congress-2007-2008/workingpaper/2008-05_0.pdf google scholar
• Moore, J., & Shute, T. (2012). How to get positioned for America’s reindustrialization, The hidden cleantech revolution. New York: Energy Publishers of America. google scholar
• Ndikumana, L. (2000). Financial determinants of domestic investment in Sub-Saharan Africa: Evidence from panel data. World development, 28(2), 381-400. https://doi.org/10.1016/S0305-750X(99)00129-1 google scholar
• Novotna, M., Leitmanova, I. F., Alina, J., & Volek, T. (2020). Capital intensity and labour productivity in waste companies. Sustainability, 12(24), 10300. https://doi.org/10.3390/su122410300 google scholar
• Peter, P. (2017). Indian manufacturing industry in the era of globalization: A Cobb-Douglas production func-tion analysis. Indian Journal of Economics and Development, 5(1), 1-11. Retrieved from https://ijed.in/ articles/indian-manufacturing-industry-in-the-era-of-globalization-a-cobb-douglas-production-function-analysis google scholar
• Rjiesh, R. (2018). Trade liberalisation, technology import and industrial productivity: Evidence from Indian manufacturing firms. Institute for Studies in Industrial Development Working Paper 203. Retrieved from https://isid.org.in/wp-content/uploads/2019/05/WP203.pdf google scholar
• Rodrik, D. (2013). Unconditional convergence in manufacturing. The Quarterly Journal of Economics, 128(1), 165-204. https://doi.org/10.1093/qje/qjs047 google scholar
• Rodrik, D., (2015). Premature Deindustrialization. NBER Working Paper No. 20935. https://doi.org/10.3386/ w20935 google scholar
• Sade, A. T., Esther, A. B., Oladipo, A. D., & Adedokun, D. (2021). Trade openness and manufacturing sector performance in some selected West African countries: A panel study approach. Acta Universitatis Danu-bius OEconomica, 17(3), 286-300. Retrieved from https://dj.univ-danubius.ro/index.php/AUDOE/article/ view/1040/1369 google scholar
• Saygili, S., Cihan, C., Yalcin, C., & Hamsici, T. (2010). Türkiye imalat sanayiin ithalat yapısı [Import struc-ture of Turkish manufacturing industry]. Türkiye Cumhuriyet Merkez Bankası Çalışma Tebliği No: 10/02. Retrieved from https://www.tcmb.gov.tr/wps/wcm/connect/16e81cc5-44d8-4d2b-a7d4-b61cedb0b4c1/ WP1002.pdf?MOD=AJPERES&CACHEID=ROOTWORKSPACE-16e81cc5-44d8-4d2b-a7d4-b61cedb0b4c1-m3fB8Ud google scholar
• Scott, A. J. (2006). The changing global geography of low-technology, labor-intensive industry: clot-hing, footwear, and furniture. World Development, 34(9), 1517-1536. https://doi.org/10.1016/j.worl-ddev.2006.01.003 google scholar
• Sipikal, M., Siranova, M., & Nemethova, V (2017). Evaluation of innovation support from EU funds in the manufacturing of wood and wood products in The Slovak Republic. Acta Facultatis Xylologiae Zvolen res Publica Slovaca, 59(2), 167-180. https://doi.org/10.17423/afx.2017.59.2.16 google scholar
• Song, Y. C., & Son, S. H. (2020). Identifying the impact of geographical proximity on spillover effect of FDI: The evidence from Indian local firms’ performance gains. The North American Journal of Economics and Finance, 52, 101138. http://doi.org/10.1016/j.najef.2019.101138 google scholar
• Su, D., & Yao, Y. (2016). Manufacturing as the key engine of economic growth for middle-income economi-es. Journal of the Asia Pacific Economy, 22(1), 47-70. https://doi.org/10.1080/13547860.2016.1261481 google scholar
• Sutikno, S., & Suliswanto, M. S. W. (2017). The impact of industrialization on the regional economic develop-ment and community welfare. Signifikan-Jurnal Ilmu Ekonomi, 6(2), 231-246. https://doi.org/10.15408/ sjie.v6i2.5334 google scholar Szirmai, A. (2009). Industrialisation as an Engine of Growth in Developing Countries, 1950 - 2005. google scholar
• UNU-MERIT Working Paper no 2009-010. Retrieved from https://www.merit.unu.edu/publications/ wppdf/2009/wp2009-010.pdf google scholar
• Tahir, M., Estrada, M. R., Khan, I., & Afridi, M. A. (2016). The role of trade openness for industrial sector development: panel data evidence from SAARC region. Journal of Asia Business Studies, 10(1), 93-103. https://doi.org/10.1108/JABS-01-2015-0007 google scholar
• Tatoğlu Yerdelen, F. (2016). Various Approaches for the Estimation of the Three-Dimensional Fixed and Random Effect Models. Eurasian Academy of Sciences Eurasian Econometrics, Statistics&Emprical Economics Journal, 5, 60-70. http://dx.doi.org/10.17740/eas.stat.2016-V5-05 google scholar
• Tatoğlu Yerdelen, F. (2017). Avrupa ülkelerinde Okun Yasasının çok boyutlu panel veri modelleri ile analizi [Analysis of Okun’s Law in European countries with multidimensional panel data models]. Yönetim ve Çalışma Dergisi, 1(1), 43-56. google scholar
• Tatoğlu Yerdelen, F. (2018). Panel veri ekonometrisi: Stata uygulamalı (4th ed.) [Panel data econometrics: Applied to stata]. İstanbul, Turkey: Beta Yayınları. google scholar
• Tregenna, F. (2011). Manufacturing productivity, deindustrialization, and reindustrialization. WIDER Wor-king Paper, No. 2011/57, ISBN 978-92-9230-424-9, The United Nations University World Institute for Development Economics Research (UNU-WIDER), Helsinki. Retrieved from https://www.wider.unu. edu/sites/default/files/wp2011-057.pdf google scholar
• Tripathi, M., & Inani, S. K. (2020). does information and communications technology affect economic growth? Empirical evidence from SAARC Countries. Information Technology for Development, 26(4),773-787. https://doi.org/10.1080/02681102.2020.1785827 google scholar
• Tüzemen, D., & Willis, J. (2013). The vanishing middle: Job polarization and workers’ response to the decli-ne in middle-skill jobs. Economic Review, 39(1), 5-32. Retrieved from https://www.proquest.com/docvie w/1353335157?parentSessionId=OxyXKyQrj7Lc4g2DTu24ORrOcocNHnobGyC4c0o6Ywo%3D google scholar
• Ughulu, S.E. (2021). Industrial output and economic growth in emerging economies: Evidence from Nigeria. Applied Finance and Accounting, 7(1), 32-43. https://doi.org/10.11114/afa.v7i1.5175 google scholar
• UNIDO (2021). MVA 2021 Database. Retrieved from https://stat.unido.org/database/MVA%202021,%20 Manufacturing google scholar
• Wang, C., Wang, L., & Dai, S. (2018). An indicator approach to industrial sustainability assessment: The case of China’s capital economic circle. Journal of Cleaner Production, 194, 473-482. https://doi. org/10.1016/j.jclepro.2018.05.125 google scholar
• Willman, A. (2002). Euro Area production function and potential output: A supply side system approach. ECB Working Paper, No. 153, European Central Bank (ECB), Frankfurt a. M. https://dx.doi.org/10.2139/ ssrn.357941 google scholar
• WIOD (2016). Socio economic accounts release 2016. Retrieved from http://www.wiod.org/database/ seas16 google scholar
• Wong, S. (2006). Productivity and trade openness: Micro-level evidence from manufacturing industries in google scholar
• Ecuador, 1997-2003. Andean Development Corporation (CAF) Working Paper, Quito, Ecuador. Retrie-ved from https://www.caf.com/media/29875/sarawong-productivityandtradeopenness.pdf google scholar
• World Data Bank (2021). Employment in industry (% of total employment) (modeled ILO estimate). Retrie-ved from https://data.worldbank.org/indicator/SL.IND.EMPL.ZS google scholar
• World Economic Forum (2013). The human capital report. Retrieved from https://www3.weforum.org/docs/ WEF_HumanCapitalReport_2013.pdf google scholar
• Yang, W., & Zhao, J. (2020). Study on China’s economic development from the perspective of strong sustaina-bility. The Singapore Economic Review, 65(01), 161-192. http://dx.doi.org/10.1142/S021759081746002X google scholar
• Zhou, Y. (2018). Human capital, institutional quality and industrial upgrading: global insights from industrial data. Economic Change and Restructuring, 51(1), 1-27. https://doi.org/10.1007/s10644-016-9194-x google scholar