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Recent exchange rate experience of china

Par   •  13 Juin 2018  •  2 074 Mots (9 Pages)  •  348 Vues

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The data of the paper is from various years of the China Statistical Yearbook, Annual population change survey and China Data online. One important feature of this study is that our data are not only deflated over time but also by an index that accounts for living-cost differences across. Therefore, our data are comparable across provinces where living costs are quite different. GDP and capital-stock deflators are based on official price indexes (China Statistical Yearbook). The numbers of people with some college education or above and with some senior high school education or above are estimated based on the annual flow of college student enrolments and senior high school student enrolments. The infrastructural data are provided by Sylvie Demurger for the years 1978 through 1998 and from State Statistical Bureau for the years 1999 through 2003. Data on employed workers by education levels are obtained from the annual population change survey. Data for preferential tax policies are taken from the government official website for investment guidelines. For each province, we added those cities to get the number of cities in each SZ category in that province for that year.

The table 3 shows estimation results for provincial-level production function with two types or labor categorized according to educational attainment. As we can see, in the column 1, the estimated elasticity of less-educated worker is negative and marginally significant. And in the column 2 and 3, the estimated output elasticity of less-educated labor based on these commonly used treatments is positive. Then in the colunm4, the elasticity of capital, educated labor and less-educated labor reflect province-specific adjustments to the structural change in employment yield quite similar estimates of the inputs’ elasticities.

Between 1984 and 2003, MPL of educated labor calculated at existing factor quantities increased over fourfold and that of workers with elementary schooling or less increased more than tenfold in the coastal region. For workers in the lower schooling group, the regional ratios of MPL in the both interior and far west to that in the coast declined from about 0.6 to less than 0.4, reflecting substantial productivity divergence. MPK, which is an approximation of the rate of return to physical capital at existing factor quantities, started out high and has remained high (reaching over 0.3 in all regions except the far west in 2003).

TFP growth has important implications for regional disparity in China's economic development. Table 4 illustrates result which confirms that most of the instrument are significant, and the over identification test does not reject the null hypothesis. The estimated direct effect of human capital is positive and significant for both measures of the highly educated group. In Table 5, the education level above junior high school is used to measure human capital. When we use the variable defined as some college education or above, it is insignificant in all specifications.

In order to illustrate the economic importance of the estimation results, the paper calculate the impacts of possible policy interventions through human capital and infrastructure investments.

The returns to senior high school education or above and infrastructure are assumed to emanate from their impacts on TFP growth, while the return to junior high school education or above is postulated to arise from its direct impact as a factor of production. It is instructive to compare the estimated rates of return in Table 6 with the marginal products of educated labor shown in Fig. 5. It is clear that at existing factor quantities, the marginal product of educated labor is much higher in the coastal region and northeast regions than elsewhere, but so is the marginal product of less-educated labor. Hence the opportunity cost of sending a coastal or northeast worker to school is higher than it is in the interior or far west regions. The first line of each cell in Table 7 is the predicted ratio of percapita GDP in one of the other three regions to the coastal region if one of the three policy actions is undertaken. In the first row, we see that the impact of a policy focused on raising schooling levels education would have a larger impact on reducing regional inequality in the interior than in far west.

To conclude, China’s rapid economic growth was initiated by the complementarity betwee a solid base of medium-skill labor and a huge inflow of FDI. It has been sustained by rapid physical capital accumulation and human capital formation. But Chinese policy makers face a dilemma, because continued economic transformation has not been equally beneficial across China's major regions. The interior region (near west) and far western regions lag far behind the coastal and northeast regions in economic progress.

My point of view, China is now facing serious challenges in the areas of education, the quality of its labor force, and in sustaining its economic growth. And China tries to reduce economic inequality between near west and far western regions, for example China’s on-going Go-West policy.

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