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Dr. Geng XIAO The University of Hong Kong xiaogeng@hku.hk econ.hku.hk/~xiaogeng Dr. Zhengge TU

Productivity Growth in China's Large and Medium Industrial Firms: Patterns, Causes, and Implications. Dr. Geng XIAO The University of Hong Kong xiaogeng@hku.hk www.econ.hku.hk/~xiaogeng Dr. Zhengge TU Peking University tuzg@szpku.edu.cn

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Dr. Geng XIAO The University of Hong Kong xiaogeng@hku.hk econ.hku.hk/~xiaogeng Dr. Zhengge TU

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  1. Productivity Growthin China's Large and Medium Industrial Firms: Patterns, Causes, and Implications Dr. Geng XIAO The University of Hong Kong xiaogeng@hku.hk www.econ.hku.hk/~xiaogeng Dr. Zhengge TU Peking University tuzg@szpku.edu.cn International Workshop on Competition, Innovation and Productivity: Empirical Evidence from Firm Level Data Nice, Sophia-Antipolis, France, 19-20 December 2005

  2. TFP Growth • y: actual output • Sj: share of costs by input xj • Growth accounting equation:

  3. TFP Growth = FTP + change in TE + AE + SE • Frontier Production Function with Technical Inefficiency: • Total Factor Productivity (TFP) Growth due to: • Frontier Technology Progress (FTP) • Changes in Technical Efficiency (TE) Relative to the Frontier • Allocating Efficiency (AE) • Scale Economy (SE)

  4. FTP and TE: An Illustration

  5. Frontier Technology Progress (FTP) • f(x, t): frontier production function • X: vector of inputs • t: time trend • FTP: output increase over time due to broa • dly defined technology progress such as the use of new technology, new management, new institutions, etc., given the same levels of inputs

  6. Technical Efficiency (TE）Relative to Frontier and its Change • TE: Ratio of actual output to frontier output: • Change of TE:

  7. Allocative Efficiency (AE)in the Employment of Inputs • j: normalized output elasticity of input j • Sj: share of costs by input j • xj: input j • AE: Allocative Efficiency due to more cost-effective employment of inputs (e.g. marginal return greater than marginal costs of inputs)

  8. Scale Economy (SE) • RTS: total return to scale, sum of output elasticity of all inputs. • j: output elasticity of input j • xj: input j • Scale Economy:

  9. Time-Varying Log Stochastic Frontier Production Function

  10. Data Sources • National Bureau of Statistics annual survey on large and medium industrial enterprises during 1995-2002 with about 22,000 firms each year • After data cleaning the total observations for the imbalanced panel data set is 177,086 with about 21,000 for each year over 8 years • The significance of sample enterprises in the Chinese economy: • Number of enterprises is about 12% of all industrial enterprises with sales above 5 million RMB • About 16.7% of the total industrial employment • About 40% of the total industrial value added • Total value added is about 14% to 19% of GDP • Price deflators • Estimated output deflator • Estimated fixed capital deflator

  11. Variables Used in Estimation y: deflated industrial value added K: deflated net value of fixed capital L: average number of employees SK: interest expenses and current depreciation SL: wages, bonuses, expenses on labor welfare and insurances

  12. TFP Growth by Sector

  13. TFP Growth due to FTP

  14. TE: Actual to Frontier Output

  15. TE by Ownership

  16. TFP Growth due to Change in TE

  17. TFP Growth due to AE

  18. Return to Scale (RTS) by Sector

  19. TFP Growth due to SE

  20. Dynamics of TFP Growth Unit: Average Annual TFP Growth during 1996-2002 (= 6.8%)

  21. Patterns of Productivity Revolution • Average annual growth of TFP in China’s large and medium industrial enterprises sector is as high as 6.8% with a rising trend during 1996-2002. • The contribution to TFP growth by Frontier Technology Progress reached as much as 14 percentage points a year on average. • The decline in Technical Efficiency (Relative to the Frontier) reduced the growth of TFP by 7.1 percentage points a year on average. • Allocative Efficiency contributed on average only 0.02 percentage points a year to the growth of TFP. • Scale Dis-Economy slowed the growth of TFP by 0.33 percentage points a year. • At the turn of the century, the most important part of China’s industry is in the middle of an industrial productivity revolution driven by both frontier technological catching up and expanding gaps of technical efficiency among enterprises.

  22. Factors Driving China’s Industrial Productivity Revolution • Privatization • Financial sector development • Competition • FDI and globalization • Urbanization & industrialization • Business cycle

  23. Privatization and Capital Markets

  24. Explaining Technical Efficiency • Finance (liability/asset) • Firm size (market share) • Competition/concentration (hfindex3) • Ownership and privatization (type) • Industry effect (Ind2) • Region effect (place2)

  25. Explaining Technical Efficiency

  26. Ownership-Specific Impact on TE

  27. Industry-Specific Impact on TE

  28. Region-Specific Impact on TE

  29. Implications • Clear evidences of rapid industrial productivity growth driven by technological progress • Clear evidences of large productivity gaps across ownership, region, and industry • Clear evidences that privatization, competition and globalization contributed to China’s industrial productivity revolution. • The evidences uncovered here support the view that China’s economic growth is sustainable as it is based on productivity catch-up

  30. Thank you

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