The Empirical Analysis On Chinese Agricultural Food Processing Industry Productivity

Non-staple Food Processing, connecting primary industry and tertiary industry, is a field that is closed related to people’s survival and normal life. Accelerating the development of agricultural food processing industry is of great significance for the extension of the agricultural industry chain, optimizing the structure of agricultural industry, increasing the added value of agricultural products, increasing farmers’ income, promoting agricultural industrialization, and improving the overall level of agriculture. The technology and efficiency level of agricultural food processing industry is directly related to the industry’s competitiveness and development potential. In this paper, we’d like to study the total factor productivity of agricultural food processing industry, and analyze the main influence factors of it.Firstly, we summed up the related research of domestic and foreign scholars, and introduced the basic theory and method of measuring productivity. Then, based on the micro-data, we calculate and analyze quantity relation of technical progress, "pure" technical benefit, and scale benefit of TFP of agricultural food processing industry. Results showed that during the period of study samples, the productivity of agricultural food processing industry was declining. And the negative growth was mainly caused by the technical change. Thirdly, we calculated the TFP, technical change and technical efficiency with 13 division units. The study found that the TFP of "frozen processing of aquatic products" showed the positive growth; the rest of industries were characterized by negative growth. The results also showed that the technical change of the industries were less than 1; it meant that the industry failed to achieve the technical boundary moving forward. Correlation study showed that the correlation between technology change and TFP was larger. Finally, we analyzed the main influence factors of technical change, using panel data regression model. Through the results, we found that the human resource, the scale of enterprises and the foreign direct investment (FDI) acted significant positive roles in promoting the technical change.