Evaluation Of Efficiency And Influencing Factors Of Agricultural Science And Technology Resource Allocation In Anhui Province

The 2023 Central Document No.1 states that efforts will be made to strengthen agricultural infrastructure development and agricultural science and technology,improve the rural governance system led by the Party organization,strengthen policy protection and institutional mechanism innovation,and several other efforts.The most difficult task remains in the countryside and the comprehensive construction of a modern socialist country.As the world’s unprecedented changes accelerate,it is vital to safeguard the "three rural areas".The Central Committee of the Communist Party of China has proposed to promote the revitalization of the countryside with the efforts of the whole society and the whole Party,always putting the "three rural issues" at the forefront of the work of the whole Party and modernizing agriculture and the countryside at a faster pace.We will work hard to do the key work in 2023 and complete the set targets without compromise,so that we can make new progress in promoting rural revitalization and make a good start in building a strong agricultural country.In summary,it is important to analyse the efficiency of agricultural science and technology resource allocation and its influencing factors in Anhui Province.This study uses the literature analysis method combined with domestic and foreign scholars’ research on the efficiency of agricultural science and technology resources allocation,guided by input-output and other related theories,to firstly conduct a preliminary analysis of the current situation and problems of agricultural science and technology resources allocation in 16 prefecture-level cities in Anhui Province.Secondly,an input-output index system was established,and the BCC model and ML index model were used to measure and analyse the efficiency of agricultural science and technology resources allocation in Anhui Province from 2011 to 2020,The results show that: statically,there are differences in the overall development level of Anhui Province,the overall productivity needs to be improved and the industrial structure needs to be optimized;dynamically,Anhui Province has the characteristics of high in the east and low in the west,which requires rational allocation of resources to optimize the overall resource allocation efficiency.Then,the combined technical efficiency value of the BCC model is taken as the dependent variable and the factors affecting various other aspects of agricultural science and technology resource allocation are taken as independent variables,Further empirical analysis of the factors influencing the efficiency of agricultural science and technology resource allocation in Anhui Province by constructing a tobit panel regression model revealed that:The level of rural economic development and agricultural fertilizer application have a positive contribution to the efficiency of agricultural science and technology resource allocation;the level of industrial modernization and the degree of marketization have a negative inhibitory effect;the size of government has no significant effect.Finally,it is concluded that the allocation structure of agricultural science and technology resources in Anhui Province is unreasonable,the allocation efficiency of agricultural science and technology resources is low,the investment in agricultural science and technology human resources is insufficient,and the allocation of agricultural science and technology resources is unevenly distributed,etc.It also put forward countermeasure suggestions such as optimising the allocation structure of agricultural science and technology resources to promote industrial development;reasonably allocating agricultural science and technology resources to promote balanced development in the east and west;accelerating investment in agricultural science and technology talents to promote high-quality agricultural development;and scientifically and reasonably using chemical fertilisers to improve farmers’ income.