Technology intensity and ownership in the Chinese manufacturing industry: A labor productivity decomposition approach

Ming He; Barnabé Walheer; Ming He; Barnabé Walheer

doi:10.3934/NAR.2020007

National Accounting Review

2020, Volume 2, Issue 2: 110-137. doi: 10.3934/NAR.2020007

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Technology intensity and ownership in the Chinese manufacturing industry: A labor productivity decomposition approach

Ming He ¹,
Barnabé Walheer ^{2
,
,}

1.
International Business School Suzhou, Xi’an Jiaotong-Liverpool University, China
2.
HEC Liège, Université de Liège, Belgium

Received: 12 January 2020 Accepted: 04 March 2020 Published: 09 March 2020
JEL Codes: C67, L60, O33, O47

China's manufacturing industry has registered phenomenal development in the past 40 years,which has become the most remarkable aspect of China's economic miracle. In this article,we interrogate labor productivity growth mechanisms in that industry during 1998–2007. Specifically,we assess the relative importance of efficiency,technology,and capital deepening changes in the growth process. Methodologically,we employ a nonparametric tripartite decomposition while controlling for technology and ownership heterogeneity using the concept of metafrontier. We find that most of the productivity growth was driven by capital deepening (125.60%),followed by technology progress (62.47%),and a small fraction (11.23%) was due to efficiency improvement. We also demonstrate strong productivity convergence in China's manufacturing industry,which was driven by technology change and capital deepening effects. These results suggest that China's overall industry development benefited from market mechanism in resource allocation and technology diffusion,but further improvement is possible. Finally,we point out that China's industry can still benefit from capital accumulation in the near future but long-term productivity growth must be based on technology progress.
- technology gap,
- technical efficiency,
- manufacturing industry,
- China,
- metafrontier
Citation: Ming He, Barnabé Walheer. Technology intensity and ownership in the Chinese manufacturing industry: A labor productivity decomposition approach[J]. National Accounting Review, 2020, 2(2): 110-137. doi: 10.3934/NAR.2020007

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Abstract

China's manufacturing industry has registered phenomenal development in the past 40 years,which has become the most remarkable aspect of China's economic miracle. In this article,we interrogate labor productivity growth mechanisms in that industry during 1998–2007. Specifically,we assess the relative importance of efficiency,technology,and capital deepening changes in the growth process. Methodologically,we employ a nonparametric tripartite decomposition while controlling for technology and ownership heterogeneity using the concept of metafrontier. We find that most of the productivity growth was driven by capital deepening (125.60%),followed by technology progress (62.47%),and a small fraction (11.23%) was due to efficiency improvement. We also demonstrate strong productivity convergence in China's manufacturing industry,which was driven by technology change and capital deepening effects. These results suggest that China's overall industry development benefited from market mechanism in resource allocation and technology diffusion,but further improvement is possible. Finally,we point out that China's industry can still benefit from capital accumulation in the near future but long-term productivity growth must be based on technology progress.

References

[1]	Afsharian M, Podinovski VV (2018) A linear programming approach to efficiency evaluation in nonconvex metatechnologies. Eur J Oper Res 268: 268-280. doi: 10.1016/j.ejor.2018.01.013
[2]	Amsler C, O'Donnell CJ, Schmidt P (2017) Stochastic metafrontiers. Econometric Rev 36: 1007-1020. doi: 10.1080/07474938.2017.1308345
[3]	Atkinson AB, Stiglitz JE (1969) A new view of technological change. Econ J 79: 573-578. doi: 10.2307/2230384
[4]	Badunenko O, Kumbhakar SC (2017) Economies of scale, technical change and persistent and time-varying cost efficiency in Indian banking: Do ownership, regulation and heterogeneity matter? Eur J Oper Res 260: 789-803. doi: 10.1016/j.ejor.2017.01.025
[5]	Badunenko O, Romero-Ávila D (2013) Financial development and the sources of growth and convergence. Int Econ Rev 54: 629-663. doi: 10.1111/iere.12009
[6]	Badunenko O, Tochkov K (2010) Soaring dragons, roaring tigers, growling bears: Determinants of regional growth and convergence in China, India and Russia. Econ Transition 18: 539-570. doi: 10.1111/j.1468-0351.2009.00387.x
[7]	Banker RD, Charnes A, Cooper WW (1984) Some models for estimating technical and scale inefficiencies in data envelopment analysis. Manage Sci 30: 1078-1092. doi: 10.1287/mnsc.30.9.1078
[8]	Barro R, Sala-i-Martin X (1991) Convergence across states and regions. Brookings Pap Econ Act 1991:107-182. doi: 10.2307/2534639
[9]	Basu S, Weil DN (1998) Appropriate technology and growth. Q J Econ 113: 1025-1054. doi: 10.1162/003355398555829
[10]	Battese GE, Rao DSP (2002) Technology gap, efficiency, and a stochastic metafrontier function. Int J Bus Econ 1: 87-93.
[11]	Battese GE, Rao DSP, O'Donnell CJ (2004) A metafrontier production function for estimation of technical efficiencies and technology gaps for firms operating under different technologies. J Prod Anal 21: 91-103. doi: 10.1023/B:PROD.0000012454.06094.29
[12]	Baumol WJ (1986) Productivity growth, convergence, and welfare: What the long-run data show. Am Econ Rev 76: 1072-1085.
[13]	Berkowitz D, Ma H, Nishioka S (2017) Recasting the iron rice bowl: The reform of China's state-owned enterprises. Rev Econ Stat 99: 735-747. doi: 10.1162/REST_a_00637
[14]	Bos JWB, Economidou C, Koetter M (2010a) Technology clubs, R&D and growth patterns: Evidence from EU manufacturing. Eur Econ Rev 54: 60-79.
[15]	Bos JWB, Economidou C, Koetter M, et al. (2010b) Do all countries grow alike? J Dev Econ 91:113-127.
[16]	Brandt L, Van Biesebroeck J, Zhang Y (2012) Creative accounting or creative destruction? Firm-level productivity growth in Chinese manufacturing. J Dev Econ 97: 339-351.
[17]	Brandt L, Van Biesebroeck J, Zhang Y (2014) Challenges of working with the Chinese NBS firm-level data. China Econ Rev 30: 339-352. doi: 10.1016/j.chieco.2014.04.008
[18]	Brandt L, Zhu X (2010) Accounting for China's growth Working Paper 394. Department of Economics, University of Toronto.
[19]	Charnes A, Cooper WW, Rhodes E (1978) Measuring the efficiency of decision making units. Eur J Oper Res 2: 429-444. doi: 10.1016/0377-2217(78)90138-8
[20]	Chen KH, Huang YJ, Yang CH (2009) Analysis of regional productivity growth in China: A generalized metafrontier MPI approach. China Econ Rev 20: 777-792. doi: 10.1016/j.chieco.2009.05.003
[21]	Chen M, Guariglia A (2013) Internal financial constraints and firm productivity in China: Do liquidity and export behavior make a difference? J Comp Econ 41: 1123-1140. doi: 10.1016/j.jce.2013.05.003
[22]	Chen S, Jefferson GH, Zhang J (2011) Structural change, productivity growth and industrial transformation in China. China Econ Rev 22: 133-150. doi: 10.1016/j.chieco.2010.10.003
[23]	Daraio C, Simar L (2007) Advanced robust and nonparametric methods in efficiency analysis: Methodology and applications, New York, NYSpringer.
[24]	Debreu G (1951) The coefficient of resource utilization. Econometrica 19: 273-292. doi: 10.2307/1906814
[25]	Deng PD, Jefferson GH (2011) Explaining spatial convergence of China's industrial productivity. Oxford Bulletin Econ Stati 73: 818-832. doi: 10.1111/j.1468-0084.2011.00675.x
[26]	Ding S, Guariglia A, Harris R (2016) The determinants of productivity in Chinese large and medium-sized industrial firms, 1998-2007. J Prod Anal 45: 131-155. doi: 10.1007/s11123-015-0460-0
[27]	Elyasiani E, Rezvanian R (2002) A comparative multiproduct cost study of foreign-owned and domestic-owned US banks. Appl Financ Econ 12: 271-284. doi: 10.1080/09603100110090136
[28]	Färe R, Grosskopf S, Norris M, et al. (1994) Productivity growth, technical progress, and efficiency change in industrialized countries. Am Econ Rev 84: 66-83.
[29]	Färe R, Primont D (1995) Multi-output production and duality: Theory and applications, Kluwer, Boston, MA.
[30]	Farrell MJ (1957) The measurement of productive efficiency The measurement of productive efficiency. J Royal Stat Society Series A (General) 120: 253-281. doi: 10.2307/2343100
[31]	Fei R, Lin B (2016) Energy efficiency and production technology heterogeneity in China's agricultural sector: A meta-frontier approach. Technol Forecasting Social Change 109: 25-34. doi: 10.1016/j.techfore.2016.05.012
[32]	Filippetti A, Peyrache A (2015) Labour productivity and technology gap in European regions: A conditional frontier approach. Reg Stud 49: 532-554. doi: 10.1080/00343404.2013.799768
[33]	Guariglia A, Liu X, Song L (2011) Internal finance and growth: Microeconometric evidence on Chinese firms. J Dev Econ 96: 79-94. doi: 10.1016/j.jdeveco.2010.07.003
[34]	Hayami Y, Ruttan VW (1970) Agricultural productivity differences among countries Agricultural productivity differences among countries. Am Econ Rev 60: 895-911.
[35]	He M, Walheer B (2019) Spillovers and path dependences in the Chinese manufacturing industry: A firm-level analysis. J Dev Stud.
[36]	Henderson DJ, Russell RR (2005) Human capital and convergence: A production-frontier approach. Int Econ Rev 46: 1167-1205. doi: 10.1111/j.1468-2354.2005.00364.x
[37]	Henderson DJ, Tochkov K, Badunenko O (2007) A drive up the capital coast? Contributions to post-reform growth across Chinese provinces. J Macroecon 29: 569-594.
[38]	Hsieh CT, Klenow PJ (2009) Misallocation and manufacturing TFP in China and India. Q J Econo 124: 1403-1448. doi: 10.1162/qjec.2009.124.4.1403
[39]	Hsieh CT, Song ZM (2015) Grasp the large, let go of the small: The transformation of the state sector in China. Brookings Pap Econ Act 2015: 295-346.
[40]	Huang CW, Ting CT, Lin CH, et al. (2013) Measuring non-convex metafrontier efficiency in international tourist hotels. J Oper Res Society 64:250-259. doi: 10.1057/jors.2012.52
[41]	Jefferson GH, Rawski TG, Zhang Y (2008) Productivity growth and convergence across China's industrial economy. J Chinese Econo Bus Stud 6: 121-140. doi: 10.1080/14765280802028237
[42]	Kerstens K, O'Donnell C, Van de Woestyne I (2019) Metatechnology frontier and convexity: A restatement. Eur J Oper Res 275: 780-792. doi: 10.1016/j.ejor.2018.11.064
[43]	Kumar S, Russell RR (2002) Technological change, technological catch-up, and capital deepening:Relative contributions to growth and convergence. Am Econ Rev 92: 527-548.
[44]	Lemoine F, Poncet S, Ünal D (2015) Spatial rebalancing and industrial convergence in China. China Econ Rev 34: 39-63. doi: 10.1016/j.chieco.2015.03.007
[45]	Molinos-Senante M, Maziotis A, Sala-Garrido R (2017) Assessing the productivity change of water companies in England and Wales: A dynamic metafrontier approach. J Environ Manage 197: 1-9. doi: 10.1016/j.jenvman.2017.03.023
[46]	O'Donnell CJ, Rao DSP, Battese GE (2008). Metafrontier frameworks for the study of firm-level efficiencies and technology ratios. Empirical Econ 34: 231-255. doi: 10.1007/s00181-007-0119-4
[47]	Rodrik D (2013) Unconditional convergence in manufacturing. Q J Econ 128: 165-204. doi: 10.1093/qje/qjs047
[48]	Solow RM (1956) A contribution to the theory of economic growth. Q J Econ 70: 65-94. doi: 10.2307/1884513
[49]	Unel B, Zebregs H (2009) The dynamics of provincial growth in China: A nonparametric approach. IMF Staff Pap 56: 239-262. doi: 10.1057/imfsp.2008.1
[50]	Walheer B (2016a) Growth and convergence of the OECD countries: A multi-sector production-frontier approach. Eur Jo Oper Rese 252: 665-675.
[51]	Walheer B (2016b) Multi-sector nonparametric production-frontier analysis of the economic growth and the convergence of the European countries. Pac Econ Rev 21: 498-524.
[52]	Walheer B (2018a) Aggregation of metafrontier technology gap ratios: The case of European sectors in 1995-2015. Eur J Oper Res 269: 1013-1026.
[53]	Walheer B (2018b) Economic growth and greenhouse gases in Europe: A non-radial multi-sector nonparametric production-frontier analysis. Energy Econ 74: 51-62.
[54]	Walheer B (2018c) Labour productivity growth and energy in Europe: A production-frontier approach. Energy 152: 129-143.
[55]	Walheer B (2019a) Disentangling heterogeneity gaps and pure performance differences in composite indexes over time: The case of the Europe 2020 strategy. Social Indicators Res 143: 25-45.
[56]	Walheer B (2019b) How foreign investments contribute to economic growth of industrial parks in China: A production-frontier decomposition approach. Appl Econ Lett 26: 281-285.
[57]	Walheer B (2019c) Scale, congestion, and technical efficiency of European countries: A sector-based nonparametric approach. Empirical Econ 56: 2025-2078.
[58]	Walheer B, He M (2018) Technical efficiency and technology gap of the manufacturing industry in china: Does firm ownership matter? World Dev.
[59]	Xu X, Sheng Y (2012) Productivity spillovers from foreign direct investment: Firm-level evidence from China. World Dev 40: 62-74. doi: 10.1016/j.worlddev.2011.05.006
[60]	Yu M (2015) Processing trade, tariff reductions and firm productivity: Evidence from Chinese firms. Econ J 125: 943-988. doi: 10.1111/ecoj.12127
[61]	Zhang KH, Song S (2001) Promoting exports: The role of inward FDI in China. China Econ Rev 11:385-396. doi: 10.1016/S1043-951X(01)00033-5
[62]	Zhang N, Choi Y (2013) Total-factor carbon emission performance of fossil fuel power plants in China:A metafrontier non-radial Malmquist index analysis. Energy Econ 40: 549-559. doi: 10.1016/j.eneco.2013.08.012

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