The Impact of Agricultural Credit on Agricultural Productivity, in Case of Kazakhstan

Abstract

The strategy regarding developing agricultural production is one of the priorities of Kazakhstan. In order to improve it, the state conducts range of financing programs, one of which is lending of agricultural sector. This study will consider the impact of loan on productivity in the agricultural sector. There is a new method for solving the problems of endogeneity and collinearity in the production function using OLS and GMM estimators. This paper explores alternative identification assessments using farm-level strategies. Dynamic panel regression with fixed effects is evaluated by using the GMM System method. The sample is based on annual reporting forms of the National Bank of Kazakhstan and the Statistics Department under the Ministry of National Economy of the Republic for the period 2007–2017. The main purpose of the study is to verify the impact of credit on the level of productivity of the agricultural sector, and to identify other factors affecting the productivity of the sector.