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It is widely believed that the acceleration of growth since reforms began in 1978 has increased regional disparities in China. This paper examines whether this is the case for GDP per capita, labour productivity and technical efficiency in industry in 30 regions from 1978 to 2005. The unexpected conclusion is that over the whole period, there has been convergence rather than divergence: more backward regions have caught up with leading regions. The process of regional convergence was especially strong from 1978 to 1990. In the 1990s, there was divergence, but convergence resumed after 2000, leaving regional inequalities in 2005 much smaller than in 1978. Possible theoretical and policy explanations for the observed pattern are considered.
Notes
1. It is important to note that periods distinguished in the different papers are not identical.
2. As fixed assets age, the decline in their productive capability is represented by their age–efficiency profiles. The decline in the market value of assets is represented by their age–price profiles. The age–efficiency profile is used in estimates of capital stocks in productivity analysis. The age–price profile is relevant to the measurement of the net capital stock and consumption of fixed capital in wealth accounting (see more details also in OECD, 2001).
3. The coefficient of variation (CV) is the ratio of the standard deviation to the mean. The main advantage of the coefficient of variation is that it utilises the standard deviation in the context of mean of the data.
4. The time span covered by this paper is 1978–2005. In the case of regional GDP per capita, it was possible to update the figures to 2008. We include these updated figures because they indicate that the decline in regional inequality after 2004 was not a single-year fluke.
5. First, we calculated the average of regional growth rates for each given year. In order to smooth the graphs, we subsequently calculated moving five-year averages.
6. 1996 refers to the original annual growth rates, rather than the smoothed five-year averages. In Figure 3, with the smoothed data, the exception year is 1998.
7. Var(ln (y)) = Var(ln (A))+α2Var(ln (k))+γ2Var( ln (L))+2αCov( ln (a), ln (k))+2γCov( ln (A), ln (L))+2αγCov( ln (k), ln (L)).
8. See Färe et al. (1994) for more comparisons between MPI and other index approaches.
9. There has been some criticism on further decomposition of the technical efficiency change into pure technical efficiency change and scale efficiency change. Namely, the first step of such decomposition (on technology progress and change of technology efficiency) is taken under the assumption of constant returns to scale (CRS). However, in the second step, the technical efficiency is decomposed under the condition of variable returns to scale (VRS). In this paper, to avoid this inconsistency, we assume only CRS, and do not take consideration of the scale efficiency change.