Productivity Convergence in Vietnamese Manufacturing Industry: Evidence Using a Spatial Durbin Model
This paper applies the \(\beta \)-convergence regression model in order to assess convergence of total factor productivity among Vietnamese provinces for manufacturing industries. Specifically, we express this model in the form of a Spatial Durbin Model (SDM), which allows us to take into account the presence of omitted variables that can be spatially correlated and correlated with the initial level of productivity. We calculate the annual total factor productivity (TFP) of 63 Vietnamese provinces and 6 manufacturing industries, using the results of the structural estimation of a value-added production function from firm data over the period from 2000 to 2012. The regression of growth rates of TFP over this period on the initial levels of productivity using SDM shows that there is convergence in most industries, i.e. the gap between lower-productivity and higher-productivity provinces decreases. These results also show the importance of modeling the indirect effect of the initial level of productivity of a province on its TFP growth rate, through its effect on neighboring provinces. The inclusion of these indirect effects is made possible by SDM and increases the speed of convergence for most considered manufacturing industries, except for metal and machinery, and transportation and telecommunication.
KeywordsTotal Factor Productivity Manufacturing Industry Spatial Weight Matrix Spatial Error Model Food Processing Industry
This research was partially funded by Vietnam National Foundation for Science and Technology Development, grant number II 2.2-2012-18.
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