Summary:
In the new stage of development, China faces the dual challenges of a shrinking demographic dividend and a transformation of investment structure. How to promote sustained growth of labor productivity through structural transformation in production has become a vital issue for China to advance high-quality development and achieve qualitative improvement and reasonable quantitative growth in economy. Over the past half-century, global economic development has provided a rich and diverse set of experience in catch-up with the productivity frontier. The success and failure of these economies offer important insights for China to promote steady economic growth and high-quality development. We develop a novel accounting framework for productivity growth, and quantify the contribution of structural transformation in production to the catch-up with the productivity frontier among the world's major economies from both global and long-term perspectives. We first calculate the industry-level Purchasing Power Parity indices based on micro survey data from the World Bank's International Comparison Program. We integrate these indices with the World Input-Output Database to apply double-deflation method on both nominal final outputs and intermediate inputs, through which value added measured by industry-level PPP is calculated yielding internationally comparable and additive measures of industry-level productivity. We incorporate the non-homothetic constant elasticity of substitution preference into productivity comparison study and employ a multi-sector general equilibrium model to characterize and estimate the mechanisms through which productivity drives structural transformation of industry. We calibrate the model with cross-country long-term panel data, allowing for a more accurate quantification of structural transformation. Compared to existing literature, this paper offers a novel theoretical framework from an international comparative perspective for understanding the process of catch-up to the productivity frontier and patterns of development. Prior research has seldom focused on the issue of catch-up. Besides, this paper improves on methodologies for analyzing productivity growth and structural transformation. Most previous studies either rely on aggregate PPP as industry-level price deflator for international productivity comparisons, or neglect the input-output structure and fail to employ accurate structural transformation models in their quantification, which may cause potential measurement errors. Key findings are as follows. First, we find that the ability of economies to catch-up with productivity frontier hinges critically on labor productivity in manufacturing and nontraditional services. These sectors constitute the primary distinction between successful and unsuccessful catch-up economies. Specifically, the catch-up in labor productivity within manufacturing and nontraditional services contributes the most to the overall labor productivity catch-up, with the contribution rates reaching 32.2% and 46.6%, respectively. Second, we find that nontraditional services exhibit the greatest contribution to overall catch-up, followed by manufacturing and traditional services, with agriculture contributing the least. Counterfactual analysis suggests that, if labor productivity in nontraditional services across all economies were to grow in tandem with that of the United States, the average productivity gap (relative to the U.S.) would narrow by 2.1 percentage points. Structural transformation plays a pivotal role in this process, as growth and catch-up in sectoral productivity alter the employment structure across sectors, thereby significantly influencing the dynamics of overall productivity growth and catch-up. Third, we find that dominant sectors contributing to overall catch-up vary across stages of economic development. In low-income economies, overall catch-up is mainly driven by agriculture and traditional services. Importance of manufacturing and nontraditional services increases with income. At the middle-and high-income stages, these two sectors become the central engines of catch-up. Notably, in high-income economies, the contribution of nontraditional services to overall catch-up exceeds 60%, underscoring its significance in the advanced stages of development. To further advance the upgrading of China's production structure and enhance labor productivity, thereby sustaining the catch-up toward the productivity frontier, we propose the following policy implications. First, the government should maintain the stability of manufacturing share and accelerate the development of modern services, supporting the modern industrial system anchored in the real economy. Second, the government should deepen market-oriented reforms to enhance the efficiency of factor and resource allocation and provide sustained momentum for productivity growth. Third, the government should integrate the strategy of expanding domestic demand with supply-side structural reform to realize economies of scale in the domestic market, and upgrade the demand structure to drive the structural transformation in production. Fourth, the government should promote coordinated regional development and optimize the spatial distribution of industries, to foster a complementary, synergistic regional economic structure and an integrated industrial spatial system.
罗章权, 郭凯明, 吴红晨. 生产结构转型与生产率——基于全球视角的分析[J]. 金融研究, 2025, 536(2): 1-19.
Luo Zhangquan, Guo Kaiming, Wu Hongchen. Structural Transformation in Production and Productivity: Analyses from a Global Perspective. Journal of Financial Research, 2025, 536(2): 1-19.
[1]陈梦根、侯园园,2021,《中国行业劳动投入和劳动生产率:2000—2018》,《经济研究》第5期,第109~126页。 [2]干春晖、郑若谷,2009,《改革开放以来产业结构演进与生产率增长研究——对中国1978~2007年“结构红利假说”的检验》,《中国工业经济》第2期,第55~65页。 [3]郭凯明、余靖雯、吴泽雄,2018,《投资、结构转型与劳动生产率增长》,《金融研究》第8期,第1~16页。 [4]郭凯明、罗章权、杭静,2023:《中国劳动生产率的国际比较与远景展望(1992—2035)》,《经济学(季刊)》第6期,第2194~2212页。 [5]郭凯明、王钰冰、杭静,2024:《数据要素规模效应、产业结构转型与生产率提升》,《中国工业经济》第8期,第5~23页。 [6]鲁晓东、连玉君,2012,《中国工业企业全要素生产率估计:1999—2007》,《经济学(季刊)》第2期,第541~558页。 [7]倪红福,2022:《扭曲因子、进口中间品价格与全要素生产率——基于非竞争型投入产出网络结构一般均衡模型事后核算方法》,《金融研究》第2期,第21~39页。 [8]颜色、郭凯明、杭静,2018,《需求结构变迁、产业结构转型和生产率提高》,《经济研究》第12期,第83~96页。 [9]Acemoglu, D.and V.Guerrieri, 2008, “Capital Deepening and Nonbalanced Economic Growth”, Journal of Political Economy, 116(3), pp.467~498 [10]Bernard, A.B.and C.I.Jones, 1996, “Comparing Apples to Oranges: Productivity Convergence and Measurement Across Industries and Countries”, American Economic Review, 86(5), pp.1216~1238. [11]Cai, W., 2015, “Structural Change Accounting with Labor Market Distortions”, Journal of Economic Dynamics and Control, 57, pp.54~64. [12]Comin, D., D.Lashkari, and M.Mestieri, 2021, “Structural Change with Long-run Income and Price Effects”, Econometrica, 89(1), pp.311~374. [13]Duarte, M.and D.Restuccia, 2010, “The Role of the Structural Transformation in Aggregate Productivity”, The Quarterly Journal of Economics, 125(1), pp.129~173. [14]Duarte, M.and D.Restuccia, 2020, “Relative Prices and Sectoral Productivity”, Journal of the European Economic Association, 18(3), pp.1400~1443. [15]Fujiwara, I., and K.Matsuyama, 2024, “A Technology-Gap Model of ‘Premature' Deindustrialization”, American Economic Review, 114(11), pp.3714~3745. [16]Gollin, D., S.L.Parente, and R.Rogerson, 2004, “Farm Work, Home Work and International Productivity Differences”, Review of Economic Dynamics, 7(4), pp.827~850. [17]Herrendorf, B., R.Rogerson, and Á.Valentinyi, 2022, “New Evidence on Sectoral Labor Productivity: Implications for Industrialization and Development”, NBER Working Paper, No.29834. [18]Herrendorf, B.and Á.Valentinyi, 2012, “Which Sectors Make Poor Countries So Unproductive?”, Journal of the European Economic Association, 10(2), pp.323~341. [19]Hsieh, C.T.and P.J.Klenow, 2007, “Relative Prices and Relative Prosperity”, American Economic Review, 97(3), pp.562~585. [20]Inklaar, R., and M.P.Timmer, 2014, “The Relative Price of Services”, Review of Income and Wealth, 60(4), pp.727~746. [21]Lee, B.L., D.S.P.Rao, and W.Shepherd, 2007, “Comparisons of Real Output and Productivity of Chinese and Indian Manufacturing, 1980-2002”, Journal of Development Economics, 84(1), pp.378~416. [22]Ngai, L.R.and C.A.Pissarides, 2007, “Structural Change in a Multisector Model of Growth”, American Economic Review, 97(1), pp.429~443. [23]Restuccia, D., D.T.Yang, and X.Zhu, 2008, “Agriculture and Aggregate Productivity: A Quantitative Cross-country Analysis”, Journal of Monetary Economics, 55(2), pp.234~250. [24]Rodrik, D., 2013, “Unconditional Convergence in Manufacturing”, Quarterly Journal of Economics, 128(1), pp.165~204. [25]Üngör, M., 2017, “Productivity Growth and Labor Reallocation: Latin America Versus East Asia”, Review of Economic Dynamics, 24(2017), pp.25~42. [26]Young, A., 2003, “Gold into Base Metals: Productivity Growth in the People's Republic of China During the Reform Period”, Journal of Political Economy, 111(6), pp.1220~1261.