Understanding China?s recent growth experience: A spatial econometric perspective

Abstract

This study reconsiders the question of China's recent growth experience from a spatial econometric perspective. An empirical model of Chinese output growth using cross provincial data over the 1978-1998 period is specified, but a spatial econometric analysis of the specification reveals strong evidence of misspecification due to ignored spatial lag dependence. The subsequent estimating using Anselin's spatial lag model determines the important sources of growth to be the growth of non-farm labor force, manufactured products, capital stock, and realized direct foreign investment. On the other hand, the estimated coefficient for the spatial lag variable suggests a polarizing process undergoing within the Chinese spatial economy, and the resulting change in the estimates of causal factors implies that as marketization progresses, a variety of spillover effects due to factor mobility, transfer payments and technological diffusion become operational, which actually improve the marginal productivity of factor inputs for labor (G L ) and capital (G K , G DFI ) and bring national output closer to its frontier of the Chinese economy.

The Spatial Dimension of Trade‐ andFDI‐driven Productivity Growth inChinese Provinces: A Global Cointegration Approach

“…Keller and Shuie (2007) investigate the expansion of inter-regional trade networks in China trough spatial explanatory data analysis and detect significant spatial interactions among provinces. Ying (2003) conducts a spatial analysis on Chinese output growth and reveals that previous studies which ignore spatial dependence generate unreliable results due to misspecification issues. Yet, these spatial econometric applications are essentially confined to the cross-sectional dimension and the integration of time dimension to spatial econometric analysis mostly remains a challenge ahead for researchers.…”

Regional Growth with Spatial Dependence: A Case Study on Early Italian Industrialization

“…Works such as Anselin and Rey (1991) provided then the statistical criteria to select the more appropriate model. 3 The need for more structural or theory-driven empirical growth models with spatial effects led to important contributions such as Niebuhr (2001), Ying (2003), , Dall'erba and Le Gallo (2008), Piras et al (2012). These studies are characterized by the inclusion of both the spatial lag of the dependent variable and control variables X within a conditional β-convergence framework.…”

Does Accounting for Spatial Effects Help Forecasting the Growth of Chinese Provinces?

“…In addition, over the whole 1985-2000 period, provinces other than direct neighbors are relatively isolated from each other. Ying (2003) finds that according to Moran's I test, the strongest pattern of spatial autocorrelation is manifest for a distance of 2000 kilometers. In line with Anselin and Rey (1991)'s criticism of Moran's test, he further distinguishes between spatially autocorrelated errors (often due to a mismatch between economic and administrative boundaries) and spatial lag dependence (due to spillovers across provinces).…”