Research On Agricultural Productivity In China Under Low Carbon Emission Constraints

For a long time,the agricultural carbon emission is high in China.Report of the 19th National Congress of the Communist Party of China points out that it is necessary to form a spatial pattern,industrial structure,mode of production and way of life to save resources and protect environment.Therefore,agricultural resources should be motivated to transfer from extensive pattern to saving pattern,and take low-carbon and energy-saving as the strategic orientation for the transformation of agricultural development mode.Although agricultural carbon emission is lower than that of other industries,the positive externalities of agricultural"carbon emission reduction" can not be underestimated.On the one hand,the potential of agricultural "carbon emission reduction" in China is huge;on the other hand,"carbon emission reduction" means efficient utilization of agricultural productions and widespread low-carbon technology for the disposal of agricultural waste.Therefore,it is indispensable and urgent to re-examine and evaluate agricultural productivity of our country at present from the perspective of carbon emission constraint.But,the questions are:what is the level of low carbon agricultural productivity in China?What about its trajectory and future trend?What are the spatial distribution characteristics of low carbon agricultural productivity among provinces?Is there any convergence in spatial difference?What are the key factors that lead to the difference in low carbon agricultural productivity in China?From the perspective of "low carbon emission constraint" and "spatial metrics",this paper makes relevant exploration.The main conclusions are as follows:(1)Agricultural carbon emission in China is characterized by stage,with wide fluctuation range and obvious heterogeneity among provinces and regions,and also spatial dependence exists.First,in the whole sample interval,carbon emission fluctuation trend of agriculture in our country presents an evolutionary characteristic of "fluctuant rising-fast falling-slow rising" and the proportion of agricultural production input to agricultural carbon emission increases gradually in its internal structure.The intensity of agricultural carbon emission presents a downward trend,showing a "steady-fluctuant-steady" trajectory and its growth rate fluctuates greatly.Second,eight regions whose agricultural carbon emission tops the country emit over 13 million tons.Their total carbon emission accounts for 48.23 percent of the country's;the lowest eight carbon-emission regions emit basically below 2 million tons,and their total carbon emission accounts for 5.93%of the whole country's,which forms the distribution pattern of "the highest in the west,then in the central area and the lowest in the east".Third,from the Moran scatter plot and LISA map,it can be seen that the low-low agglomeration area is expanding,and the overall trend is good,but the clustering effect is very limited.(2)After controlling individual heterogeneity,the efficiency of agricultural technology is higher than that of traditional SFA.Considering the difference between agricultural TFP with carbon emission constraint and that without it down first and then up,the agricultural TFP growth belongs to the "single wheel" driving mode relying on advanced technology,which has obvious periodicity and relatively big spatial difference.Firstly,the annual average value of agricultural technical efficiency in China is 0.562,which is higher than the traditional SFA model estimate,after regional individual effect removed from the non-efficiency of agricultural technology.It shows a declining trend overall.The agricultural technology efficiency in the east is significantly higher than that in the middle and west.Differences between the three clubs have widened.Secondly,considering difference between TFP with carbon emission constraint and TFP without constraint shows an overall trend of declining first and rising later,with great fluctuations during the process,TFP of carbon-emission-constrained agriculture has exceeded traditional TFP without carbon emission constraint since 2012.Under carbon emission constraint,TFP of agriculture in the east increases more,while the overall TFP in the central and western China increases slightly.Thirdly,there are obvious differences in TFP among different provinces in China,showing a decreasing trend from the east to the west to central China and the distribution pattern is clear.The average annual growth rate of agricultural TFP is 4.31%,while agricultural technological advancement has contributed 6.85%of its growth,becoming the main driving force of agricultural TFP growth.Fourthly,agricultural TFP growth coincides with Chinese present agricultural development.In the sample period,agricultural TFP growth has experienced declining,then stagnant stage,recovery stage to rapid growth stage.Fifthly,there is spatial correlation between agricultural technical efficiency and agricultural TFP growth rate,and the spatial correlation effect between them fluctuates greatly and fails to develop in a coordinated way.(3)The whole nation and the three major clubs have conditional ? convergence;there is no universal convergence trend,but there are random convergence clubs within regions;the transfer of agricultural technology efficiency in China is affected by regional background.Firstly,agricultural productivity of each province is advancing towards balanced and steady state,but the speed of catch-up effect within regions is different.Secondly,from the conclusion of CA analysis,there is no universal convergence trend,but there are stable random convergence clubs in the east,midland and west.Thirdly,through nuclear density curve,the agricultural technology efficiency under low carbon emission constraint shows a trend of convergence overall,but with obvious decline.The agglomeration trend of TFP growth in agriculture is further strengthened,and the trend towards high value agglomeration is obvious.Fourthly,the probability of transfer of agricultural technology efficiency in each province is small,and there is a phenomenon of "club convergence".The evolution of agricultural technology efficiency in China is affected by regional conditions.Provinces with low-level agricultural productivity in the sample are more likely to accumulate,thus the "lag-behind club" formed has a tendency to expand.(4)The geospatial factor is an important factor affecting the low carbon agricultural productivity.The spillover effect is obvious,and the influence factors of the three clubs are different.Firstly,with the improvement of agricultural market system,the spatial mobility of agricultural production factors is increasing gradually,and the spatial dependence of low-carbon agricultural productivity in adjacent areas is becoming stronger and stronger.Secondly,the direct impact of per capita income of rural residents on agricultural productivity stays at the right half of the inverted "u" type,while the overall effect stays at the left half of the inverted "U" type.Thirdly,the implementation of rural fiscal policies will lead to a decline in the low-carbon agricultural productivity in our province and our neighboring provinces;the rural price policy has no significant impact on the low-carbon agricultural productivity in our province,but has a significant positive impact on it in our neighboring provinces;the promotion of agricultural openness and the increasing proportion of planting industry have led to a drop in the low-carbon agricultural productivity in our province,yet a rise in our neighboring provinces' low-carbon agricultural productivity.Fourthly,various factors that influence low-carbon agricultural productivity have different significance and functions in the nation and among the three clubs.To sum up,compared with existing literature,possible innovations of this paper are as follows:first,a new perspective.This paper expands research on agricultural productivity from the perspectives of low-carbon emission constrant and spatial measurement,and conforms to the current background.Second,a new approach.By using SFA-Malmquist model,the original agricultural productivity estimation and decomposition method are expended and a new framework for agricultural productivity analysis is formed.The method of confirmatory analysis(CA)is used to test the stochastic convergence of the overall and the clubs.The long-term evolution trend and dynamic change of low-carbon emission agricultural productivity are analyzed by using weighted spatial Markov chain.Meanwhile,geospatial factors are added to the analysis of P convergence and influence factors.Third,a new conclusion.New low-carbon agricultural productivity has been obtained due to the consideration of individual heterogeneity in the calculation.On this basis,spatial spillover effect is considered by using Spatial Dubin Model(SDM),and the conclusion includes spatial interaction effect.A more specific convergence club is obtained in the stochastic convergence analysis.The trend of regional background to low carbon agricultural productivity transfer status and the influence of dynamic changes of clubs are considered in the dynamic distribution of growth.