Abstract

Productivity is largely estimated ignoring the potential impact of spillovers and common shocks in the literature, and therefore, the estimates may be subject to the omitted variable bias and internal inconsistency. In this paper, we estimate a nonparametric production function, in which technology spillovers and common shocks have persistent effects on productivity and are controlled for through spatial networks and a factor structure in the productivity evolution process. We synthesize the proxy variable method to structurally identifying the production functions using the semiparametric common correlated effect estimator. The proposed model is then applied to the Chinese computer and peripheral equipment firms. We find that the annual productivity growth rate in this high-technology sector is about 15%. While firms are cross-sectionally dependent via both spatial and non-spatial connections, the productivity growth is largely explained by firms’ own effort, and mildly explained by the neighbors’ activities. Productivity is found to be higher in the areas of agglomeration, and the common shock effects on productivity are not necessarily correlated with the spatial variables.

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