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The authors would like to thank Jim Gordon for comments, and Aasim Husain for providing much of the data used in the paper.
Throughout this paper, references to China are to the Mainland and the term “provinces” refers to the set of 28 provinces, autonomous regions and municipalities listed in Table 1.
In the growth literature, the phenomenon of initially poorer economies—measured in terms of their per capita incomes—growing faster than those that are initially richer is referred to as absolute (or unconditional) beta-convergence.
This phenomenon is referred to as conditional beta-convergence.
The decline in the dispersion of relative income across a set of economies is referred to as sigma-convergence.
Some observers believe that China’s GDP growth rates are overstated by as much as 2 percentage points. This issue is not relevant to the present study, which focuses on relative provincial GDP levels and growth rates, under the assumption that there is no systematic tendency for growth in certain provinces to be overstated more than in others.
Convergence in this case arises from the assumption of diminishing returns to capital. Since the rate of return on capital is lower in economies with more capital per worker, there are incentives for capital to flow from rich to poor economies, boosting growth in the latter relative to the former, and thus causing convergence.
In comparison, estimates of the rate of convergence for other economies center around 2 percent. See Mankiw, Romer, Weil (1992), for example.
The window width was chosen following the suggestion in Silverman (1986) to be given by 0.9AN1/5, where A=min(standard deviation, interquartile range/1.34).
The choice of Shanghai as the numeraire is arbitrary and has little impact on the analysis.
Note that Hainan and Tibet Autonomous Region were excluded from the sample since data on per capita income are not available before 1985. Data for Chongqing, which became a municipality in 1997, were included in the data for Sichuan.
For these exercises, the interval [0,1] was divided into equally spaced 50 sub-intervals.
In the remainder of this chapter the terms kernel and distribution will be used interchangeably. In the charts, the income distribution is referred to as the Gaussian kernel since the weights used were drawn from a Gaussian distribution. Weights drawn from a Epanechnikov distribution, which is the other frequently used weighting method, did not seem to make any material difference to the shape of the estimated kernels.
Quah (1997) termed this bimodality “twin peaks” in the context of cross-country growth experience. In that study, the twin peaks lay along the north-south diagonal implying little mobility in relative rankings. In the case of China’s provincial growth, the emergent twin peaks would lie across the north-south diagonal, implying significant mobility in rankings. This is a specific example of what Baumol (1986) termed “club convergence”.
Except for population growth, all the other variables were chosen on the basis of results in Dayal-Gulati and Husain (2000).
The major factors, however, are mainly structural since the coefficients of the structural variables in regressions 4 and 6 in Table 3 are statistically significant while those on the policy variables are not.
During the Sixth Five-Year Plan (1981–85), a pro-coastal policy program was adopted, and this orientation became even more pronounced in the Seventh Five-Year Plan (1986–90).The idea was that reforms should be conducted on an experimental basis in certain regions first. If such experiments were successful, their influence would eventually spread to other regions (see Wang and Hu (1999)).
Excluding the even more affluent but largely metropolitan areas of Shanghai, Beijing, and Tianjin.
The household responsibility system allowed peasant households to operate their own plots and to have greater freedom to choose which crops to plant.
About two-thirds of the expenditure under the fiscal stimulus packages in 1998 and 1999 has been targeted at the central and western provinces.