Total factor productivity and convergence of China’s textile industry

Abstract

The scale of China’s textile industry has grown to be the largest in the world with massive factor input. There is a strong demand China’s textile industry, and as a traditional industry, should improve total factor productivity (TFP) to realize technology-driven and sustainable development. TFP is a commonly used indicator to measure the level of technological progress. But regional textile industry development in China is seriously unbalanced and regional TFP is quite different from each other. It is worthwhile to estimate the textile industry TFP of China and different regions, analyse the changing trend and test for their convergences. This paper firstly uses the nonparametric DEA-Malmquist index method to measure and analyse the TFP and its evolution of China’s textile industry during 2007–2018 at the nation, region and province levels. Then it uses the coefficient of variation to test for σ-convergence of China’s and regional textile industry TFP. It also constructs an absolute β-convergence regression equation and panel data model, respectively to test for absolute β-convergence and conditional β-convergence and determine whether the TFP of each region will also converge to its own steady-state or not. The research results help explore the future development model of China’s textile industry and provide corresponding policy suggestions for the upgrading and sustainable development of the industry.