Are Chinese cities too big or too small?—A perspective of labor allocation efficiency

【Author】

PAN Shiyuan;ZHU Dandan;XU Kai

【Institution】

Zhejiang University;School of Economics, Zhejiang University;School of Economics, Zhejiang University;School of Economics, Zhejiang University

【Abstract】

This paper studied the labor allocation across Chinese cities and the implications for China’s economic growth. Our study is motivated by the increasing focus on the efficiency of Chinese resource allocation. In addition, the study of urban labor allocation provides an important theoretical basis for exploring the city size: the optimal urban size for achieving the efficient labor allocation. In addition, given that recent policies from various levels of the Chinese government have been biased toward limiting the expansion of large cities, the main results of this paper have important potential policy implications. Following the approach of Hsieh and Moretti (2018), we study the labor allocation across cities and its implications for economic growth by constructing a spatial equilibrium model. In the model, a city’s wage level depends on the city’s productivity, living amenities (e.g., traffic, environment, education, culture, medical services), and land supply. From this model setup, wage dispersion across cities can be used to measure the efficiency of labor allocation in the economy. Specifically, the smaller the wage dispersion is, the more efficient the labor allocation. Therefore, the sources of aggregate economic growth can be decomposed into two components: the increase in total factor productivity (TFP) and the improvement in labor allocation across cities. In our empirical study, we use city-level data, which include average annual wage, number of workers, value of gross domestic product (GDP), index of air quality, average worker characteristics (e.g., education, age, gender), land supply, road mileage, sales price of residential houses, and sales area of residential houses. Our empirical study includes 261 cities at the prefecture level or above in China, which account for more than 90% of the national GDP and more than 85% of the total population. All of the data used in our analysis come from China Statistical Yearbook, China Urban Statistical Yearbook, China Regional Economic Statistical Yearbook, and China Land and Resources Statistical Yearbook. As in Hsieh and Moretti (2018), to make labor wages comparable across cities, we estimate conditional city-level wages by controlling for differences in average worker characteristics and obtain the residual city-level wages. Based on empirical study and counterfactual calculations, this paper presents three key findings. First, the labor allocation across 261 cities in China improved substantially from 2000 to 2010, thus contributing positively to Chinese economic growth. Specifically, in terms of output per worker, the average annual growth rate caused by the improvement of labor allocation was about 2.34%, accounting for 19.78% of total annual growth in the period. In contrast, in the case of America, Hsieh and Moretti (2018) found that the labor allocation had worsened, generating losses in national output. Second, due to the improvement of the labor allocation, the actual contribution of first-tier cities in China to national output is larger than a simple accounting measure of local GDP growth. Third, the labor misallocation across cities is still serious. In particular, first-tier cities in China are still smaller than optimal, while second-, third-, and fourth-tier cities are larger than optimal. If all of the wages of Chinese cities were set as equal and thus labor was perfectly allocated in China, about 60.54% of the labor should be reallocated across our 261 sampled cities in 2010. The number of workers in first-tier cities in China would increase by about 365%. The gain to aggregate output would be about 17.52%. This finding suggests that there are still large potential gains to be realized from improving labor allocation in China’s economy. Finally, this paper provides some policy recommendations. Specifically, existing restrictions on the sizes of China’s first-tier cities should be further reduced, thus allowing them to expand. In terms of specific policies, the government can focus on improving traffic conditions in first-tier cities (represented by Shanghai and Shenzhen) and reducing air pollution (represented by Beijing) to enhance their attractiveness. To conclude, this paper makes two contributions to literature. First, by applying the approach of Hsieh and Moretti (2018) along with the careful consideration of the macro-economic characteristics of China, this paper studies the labor allocation across cities in China. Second, it discusses the optimal sizes of Chinese cities at various levels and analyzes how to improve labor allocation efficiency across Chinese cities, both qualitatively and quantitatively.

【Keywords】

labor allocation in China;optimal size of cities;economic growth of China

References

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Springer Journals Database

Total: 37 articles

  • [1] KUANG Weida (Institute of Finance and Trade Economics,CASS,100836), A Study on the Relationship Between Housing Pricing and Land Pricing:Basic Model and Evidence from China, Finance & Trade Economics,
  • [2] ZHAO Zi-fang,SHI Jin-chuan(College of Economics,Zhejiang University,Hangzhou 310027,China), Analysis on Industrial Efficiency Loss of China's Factors Market Distortion:An Empirical Study Based on DEA, China Industrial Economy,
  • [3] FENG Lei1,MIAO Tian2,JIANG Yan3(1.Department of Land and Real Estate Management,School of Public Administration, Renmin University of China,Beijing 100872,China;2.Bartlett School of Planning,University College London,London,UK,WC1E 6BT;3.School of Statistics,Renmin University of China,Beijing 100872,China), THE EFFECT OF LAND SUPPLY RESTRICTION ON HOUSING PRICE FLUCTUATION IN CHINA, Economic Theory and Business Management,
  • [4] YONGWEI CHEN(Peking University)WEIMIN HU(National Chengchi University), Distortions,Misallocation and Losses:Theory and Application, China Economic Quarterly,

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