The Spatial Analysis Of Chinese Agricultural Economic Growth

“Three rural issues” is an important issue in China’s modernization process. The2004and2009“No.1Document” directly pays attention to the problem of farmers’ income, but farmers’ income faces alot of difficulties, such as the low prices on agricultural products and difficulty finding jobs. So ourcounty increases incomes through the preferential agricultural policies such as the exemption ofagricultural tax and agricultural subsidies, agricultural economic policy from the global to the locality,such as the advantages of regional distribution, modern agriculture demonstration zones. Althoughmany scholars at home and abroad study Chinese agricultural economic growth, the quantitativeanalysis is less from the county perspective of the spatial factors of the agricultural economic growth.Therefore, this paper attempts to introduce spatial autocorrelation, and to study the spatial dependenceof the agricultural economic growth and space spillovers. According to this, our country needs to takeaccount of regional planning in the formulation of policies, and to break the restrictions ofadministrative division.This paper uses1590county-level panel data from1995to2011to explore the relationshipbetween the total agricultural machinery power, number of rural labors, agricultural consumption ofchemical fertilizer, agricultural fertilizer’s overuse, sown area, temperature and precipitation andAgricultural Economic Growth, and to add the spatial factors to the model, and to study the impact ofChina’s economic growth of agriculture, whether there is a convergence of economic growth inagricultural areas. The main contribution in this paper is to: based on China county data, analysizagricultural economic growth’s spatial aggregation, agricultural spatial growth spillover and factordecomposition, spatial growth convergence.Empirical results of this study display: Firstly, exploratory spatial agricultural economic growth indata analysis, respectively, use of global Moran’s I and Geary’s C, local Moran’s I and Getis and Ord’s Ganalysis, the results illustrate the presence of significant positive spatial autocorrelation and determineits location; Secondly, empirical analysis through the use of traditional econometric and spatialeconometrics, The residual Moran’s I test showed the presence of spatial dependencies that wasestimated by fixed effects model, re-estimate the model. The results show that the explanatory power tothe model increased, there is a significant and positive spatial spillovers, spatial Durbin model reflectscoefficient of0.931-0.939about the neighboring counties. Different weight matrix’s result is robust.The relationship between total agricultural machinery power, number of rural labors and agriculturaleconomic growth is a positive effect, and the excessive use of agricultural fertilizers and agriculturaleconomic growth is negative. Temperature and rainfall negatively affect agricultural Economic Growthbut not significantly, in addition to considering the regions agricultural economic growth, there areconsistent results; Thirdly, the time is divided into three sections. The absolute convergence andconditional convergence analysis are estimated. All the country, eastern and western regions’ resultsshow that there is no absolute convergence and conditional convergence, while in the central region, there is conditional convergence and in part-time segment, there is absolute convergence, the northeastpartly has the absolute convergence and conditional convergence, and calculates the correspondingconvergence rate and half-life.Based on the conclusions, made the following policy recommendations: to break the boundaries ofadministrative divisions, focusing on the area of economic development; continue to strengthen thedevelopment of agricultural mechanization, to support agricultural development; maintain anappropriate scale number of rural labors, promote agricultural growth; scientific and rational useagricultural fertilizers, to develop modern agriculture; steadily amplify crop sown areas, to protectagricultural development; great importance to climate change, to guide agricultural production.