China's regional convergence in panels with multiple structural breaks

Abstract

This study investigates the existence of regional convergence of per capita outputs in China from 1952-2004, particularly focusing on considering the presence of multiple structural breaks in the provincial-level panel data. First, the panel-based unit root test that allows for occurrence of multiple breaks at various break dates across provinces is developed; this test is based on the p-value combination approach suggested by Fisher (1932). Next, the test is applied to China's provincial real per capita outputs to examine the regional convergence in China. To obtain the p-values of unit root tests for each province, which are combined to construct the panel unit root test, this study assumes three data generating processes: a driftless random walk process, an ARMA process, and an AR process with cross-sectionally dependent errors in Monte Carlo simulation.The results obtained from this study reveal that the convergence of the provincial per capita outputs exists in each of the three geographically classified regions-the Eastern, Central, and Western regions-of China.

Spatial Econometric Analysis of Urban and County-level Economic Growth Convergence in China

“…Wang and Ge (2004) showed that while absolute β convergence does not exist in China, conditional β convergence does exist, concluding that differences between the eastern area and other areas are growing, while those between central and western regions are becoming less distinct. At the province level, Herrerias, Orts, and Tortosa-Ausina (2011) and Matsuki and Usami (2011) confirmed the existence of regional economic convergence in China. Other scholars applied a unit root test, unbalanced index, cross-sectional data model, and panel data model, further confirming the existence of β convergence in provinces (Yao and Zhang 2001a, 2001b).…”

“…However, so far the spatial autoregressive model (SAR) and spatial error model (SEM) are the most established and commonly used methods of econometric analysis. In data aspect, given scholarly doubts concerning the use of the cross-sectional data for analyzing economic growth, most scholars recommend using the panel data (Matsuki and Usami 2011; Tselios 2009). It is widely believed that the panel data model offers more information, a lower degree of collinearity and superior estimate efficiency (Tselios 2009).…”

Regional disparity, transitional dynamics and convergence in China

“…In general it is found that economic reforms have led to divergence of regional income (Zhang et al, 2001, Pedroni and Yao, 2006, Lau, 2010, Westerlund et al, 2010. The existing literature also presented evidence of club convergence (Zhang et al, 2001, Liu and Wang, 2010, Matsuki and Usami, 2011. There is also a large pool of literature which adopts the concepts of σ-convergence and β-convergence.…”

Regional disparities in Sri Lanka: An empirical analysis

“…As per the endogenous growth theory, the smart use of resources owned by a region can provide the key to its economic success. However, many authors have observed that disparities may persistent due to differences in resource endowment among regions and lagging regions inadequate capacity to benefit from agglomeration in the leading regions (Marques and Soukiazis, 1998;Matsuki and Usami, 2011;Barro and Sala-i-Martin, 1997). Myrdal (1957) argues that while the leading region will have a favourable effect on the other regions due to "spread effects" of trade and modernization of institutions (as discussed above), this will normally be outweighed by adverse backwash effects with movements of factors of production and other resources favouring the leading region at the expense of the lagging regions.…”