Effects of knowledge production and knowledge spillovers on total factor productivity in China: A spatial econometric perspective

Thomas Scherngell (), Martin Borowiecki and Yuanjia Hu

ERSA conference papers from European Regional Science Association

Abstract: The transformation of China into a knowledge based economy is currently one of the most intensively debated research issues in Economic Geography and Regional Science. The focus of this study is on effects of knowledge production and knowledge spillovers on total factor productivity (TFP) in China - at the level of Chinese regions - through the lens of the regional knowledge capital model (KCM). The KCM has become the cornerstone of the productivity literature and has been applied in numerous empirical studies focusing on firm-level productivity, subsequently extended to the more aggregated industry and country levels, and recently also to the regional level. The objective is to estimate the impact of region-internal and region-external knowledge on TFP across Chinese regions, and, by this, providing evidence on the crucial question whether TFP in China is increasingly based on knowledge production and diffusion. Relying on the regional KCM as theoretical framework, we derive a Spatial Durbin Model (SDM) relationship that can be used for empirical testing. The Chinese coverage is achieved using regional data on 31 Chinese provinces for the years 1985-2010. The dependent variable denotes regional TFP, describing how efficiently each province transforms physical capital and labour into gross value added. We explain TFP - starting from the regional KCM - by region-internal and region-external knowledge stocks, the latter referred to as the inter-regional knowledge spillover pool. We measure regional knowledge stocks in terms of patents granted by the Chinese patent office. In estimating the effects, we implement a panel version of the standard SDM that controls for spatial autocorrelation as well as individual heterogeneity across regions. The specification incorporates a spatial lag of the dependent variable as well as spatial lags of the independent variables, allowing for the endogenous estimation of TFP effects resulting from region-external knowledge stocks. In order to identify the point in time of China shifting towards a knowledge-based economy, we employ panel LM unit root tests, providing empirical evidence for structural breaks in the time dimension of the data. By this, the study has the potential to break new ground in providing systematic statistical evidence on the transformation of China into a knowledge-based economy.

Keywords: China; knowledge-based economy; total factor productivity; knowledge spillovers (search for similar items in EconPapers)
Date: 2013-11
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