China's Rural Labor Migration and Its Economic Development. Xiaoguang Liu

Чтение книги онлайн.

СКАЧАТЬ and labor transfer discovered by developmental economics. The group of the large-scale transfer of laborers constitutes an important supporting force for China’s economic growth, which helps expand the size of the labor market and increase the total factor productivity of the urban economy. The key to the long-term rapid growth of the Chinese economy will still lie in the continued transfer of surplus labor, which will bring about obvious benefits to China’s economic development in the next few years.¹²

      

      After more than 30 years of rapid economic growth, China’s economy has entered a critical stage of optimization of the economic growth rate and structural adjustment. On the one hand, China still has a lot of agricultural labor force to be transferred because the existing agricultural labor force accounts for more than 30%. On the other hand, a “labor short-age” has occurred frequently in the developed provinces along the east coast in recent years. Many enterprises face a labor shortage, despite the rapid rise in labor wages. Labor shortage has been an important factor in the declining international competitiveness of Chinese enterprises. In this context, how to promote the continued transfer of the surplus agricultural labor force is an important issue to be addressed urgently.

      To solve this practical problem, it is theoretically necessary to further clarify the determinants of labor transfer. In the past 30 years or so, why has the rural labor force shifted on a large scale and shown the extremely obvious characteristics of spatial agglomeration? What are the major factors that have affected this process and made it a turning point? How does the difference between urban and rural productivity form and act on the transfer of labor? In addition to the differences in productivity between urban and rural sectors, are there more specific factors that affect the transfer of labor in China? Only when these general and special factors are clarified can we truly grasp the internal laws of the historical process of the transfer of labor in China to bring forward pertinent suggestions and measures for the further promotion of the transfer of labor and for the reform of the labor factor market and economic growth in the next stage.

      

      Therefore, this section focuses on the driving factors of the transfer of agricultural labor by means of a theoretical and empirical analysis. Due to limitations of space, the theoretical analysis is limited and can be found in the “Appendix B: Driving Factors and Spillover Effects of the Transfer of Agricultural Labor”. The processes and results of the empirical analysis are described in the following sections.

1. Econometric model, regression variables and data description

      This section shows the empirical analysis of the determinants of the transfer of agricultural labor by the use of the panel data of China’s provinces and regions. Before the regression analysis, it is necessary to briefly introduce the methods of measuring to be used. In view of the fact that the core variables examined are likely to be affected by spatial correlation, the spatial econometric model is used for the regression analysis. The research by Xu Haiping and Wang Yuelong reveals that a significant autocorrelation exists in the urban–rural income gap in China’s provinces, municipalities and autonomous regions in terms of spatial distribution, and the studies by Luo Yongmin and Zhang Guangnan also indicate that infrastructure has spatial spillover effects.¹³ A spatial correlation may be derived from the system of economic variables under consideration or from the spatial correlation of the terms of error. Therefore, depending on the source of the effect of spatial correlation, the model of spatial measurement can be divided into the spatial autoregressive model (SAR) and the spatial error model (SEM). By reference to the practices in the above literature, both SAR and SEM models are used for analysis in this section to overcome the influence of potential spatial correlation and carry out maximum likelihood estimation. The same is also true for the setting of a spatial weight matrix. The weight coefficient of adjacent provinces is set as 1, and the weight coefficient of non-adjacent provinces is set as 0.¹⁴ The weight matrix is standardized in the specific measurement estimation. For purposes of comparison, the regression results under the two models are reported symmetrically in each table.

      

      The following sample interval analyzed in this section is from 1992 to 2010 out of the main considerations: (1) It is an ideal research interval because it is generally believed that China’s reform and opening-up has entered a new stage, and the economic system of a comprehensive market has gradually been established after Deng Xiaoping’s southern talks in 1992.¹⁵ (2) Because of strict governmental control over labor mobility, the real climax of the transfer of labor did not begin until after Deng Xiaoping’s southern talks in 1992, though the transfer of agricultural labor in China started in the early stages of reform and opening-up. In fact, since 1992, the government’s attitude toward the transfer of labor has also changed from “allowed” to “encouraged”.¹⁶ Therefore, this section uses China’s provincial panel data regarding the period 1992–2010 for quantitative analysis to examine the driving factors of the transfer of agricultural labor.

      The explained variable is the transfer of agricultural labor, and the key explanatory variables include the urban–rural income gap, the growth rate of the GDP, the level of infrastructure, total factor productivity and agricultural labor productivity (measured by the ratio of the total agricultural machinery power to the population employed in agriculture). In addition, a series of important variables are also introduced, including the degree of openness (measured by the ratio of the foreign direct investment (FDI) and the total volume of exports and imports to the GDP), the proportion of the total output of state-owned enterprises (measured by the proportion of state-owned and state-owned holding units in the value of the total output of the industrial sector), the scale and efficiency of financial development (using the ratio of total loans to GDP as an indicator of the scale of financial development, and the ratio of total loans to total deposits as a proxy variable for financial efficiency¹⁷) and the level of public education expenditure (measured by the public education expenditure per capita). In addition to these influence variables, the impact of other potential factors is also further considered, including the urban unemployment rate (measured by the registered urban unemployment rate and the surveyed urban unemployment rate estimated using urban household survey data), return on capital (measured by the ratio of the total profits of industrial enterprises to the net value of fixed assets of industrial enterprises) and the level of inflation (measured by consumer price indicator (CPI)). Theoretically, all these factors may affect the transfer of labor, so a regression analysis should be carried out to investigate the impact, with the following details.

      (1) Key variables

      (i) The transfer of agricultural labor

      The number of rural employees and the number of employees in the rural primary industry in various provinces and regions from 1978 to 2008 can be found in the Compilation of Agricultural Statistics Data of 60 Years in New China (the Compilation). These two groups of data measure the distribution of employment of the rural registered labor force in agricultural and non-agricultural sectors. The Compilation “directly collects and calculates the employees who have lived outside the household for more than half a year, but whose income is linked to the family economy in the statistical caliber of rural population and rural employees used in relevant proportions”. Therefore, it is possible to accurately measure the number of members of the agricultural labor force who have transferred by subtracting the number of employees in the rural primary industry from the number of rural employees. In addition, the provincial and regional data with the same statistical calibers in the Compilation for 2009 and 2010 can be found in the China Statistical Yearbook, which facilitates the extension of the data regarding the transfer of labor to 2010.¹⁸ Based on this, the indicator of the transfer of agricultural labor is constructed to reflect that transfer.

       СКАЧАТЬ