Abstract: [Objective] The direct and spillover effects of the agglomeration of wood processing industry on labor productivity were studied in order to improve the quality and efficiency of the industry and to provide a theoretical basis for optimizing its deployment in the region.[Method] Based on the inter-provincial panel data from 1998 to 2016, the global Moran index was used to measure the spatial autocorrelation of labor productivity in the wood processing industry. By controlling variables such as human capital, fixed asset investment and transportation conditions, the spatial econometrics model was used to examine empirically the direct effects and spillover effects of the wood processing industry agglomeration on industrial labor productivity.[Result] 1) The global Moran index of labor productivity fluctuated around 0.3, which was spatial dependence(P<0.05) in the wood processing industry. 2) The coefficient estimation of spatial econometric model showed that the wood processing industrial labor productivity had a spatial lag and spatial error autocorrelation (P<0.01). 3) The spatial effects decomposition showed that the direct and spillover effects of the wood processing industry agglomeration on industrial labor productivity were 0.260 6 and 0.029 2(P<0.01), respectively. For the control variables, the direct and spillover effects of human capital, per capita fixed asset investment, and inter-provincial transportation conditions on industrial labor productivity of the wood processing industry were 0.089 8(P<0.01) and 0.010 1(P<0.05), 0.843 4 and 0.094 6(P<0.01), and 0.771 8 and 0.085 1(P<0.01), respectively. The spillover effects of the wood processing industry agglomeration, human capital level, fixed assets per capita and transportation conditions on industrial labor productivity accounted for approximately 10% of the total effects, while the feedback effects were relatively small, accounting for less than 1% of the estimated coefficients of the model.[Conclusion] The labor productivity of the wood processing industry exhibits spatial dependence and spatial autocorrelation. The wood processing industry's agglomeration level, human capital level, fixed assets per capita and transportation conditions have positive direct effects (including small feedback effects) and spillover effects on industrial labor productivity. Suggestions were made to optimize deployment of the wood processing industries for agglomerated industrial development; to optimize the internal structure of the industries and increase the investment in fixed assets; to improve the quality of wood processing practitioners and strengthen training of professionals at different levels; and to increase the infrastructure investment in geographic areas rich in wood and bamboo resources and improve the business environment for the wood processing industry.

Key words: wood processing industry, industrial agglomeration, density of employment, labor productivity, direct effects, spillover effects