The relationship between arable land and food production index as determinants of rural development: Turkey-European Union countries analysis

As economic organizations abroad and public institutions at home have created new paradigms about rural development, it is seen that expectations for rural development are gradually increasing. Due to the large number of factors affecting the concept of rural development, there is a need for holistic rural development plans. In addition, there is a need for financial support in incentives for rural areas. The EU provides financial support to member and candidate countries on the basis of rural development. Turkey is one of the countries to which the EU provides rural support. Turkey provides rural development subsidies to individual farmers or firms as well as rural development subsidies to farmers or firms with the EU. Therefore, the support provided by the EU is of great importance for the rural value added of countries. Although rural development studies in the literature are mostly foreign-based, academic studies on rural development have been conducted in Turkey in recent years. This study tests whether there is a relationship between rural value added, food production index and arable land in Turkey and 27 EU countries. The data in the study covers annual data for 2004 - 2022. Since N>T, Friedman Rank Correlation test was applied to test for horizontal cross-section dependence. According to the result, there is no horizontal cross-section dependence in the model. Since there is no horizontal cross-section dependence in the model, Breitung, Harris Tzavalis, Fisher ADF and PP unit root tests are applied as first generation panel unit root tests and it is revealed that the variables are stationary at the first difference level. Since there is no horizontal cross-section dependence in the study, Westerlund Cointegration Test is applied and there is a cointegration relationship between the variables. The homogeneity test reveals that the panels are homogeneous. According to the results of the GMM estimator, lag 1 of rural value added and lag 1 of food production index affect rural value added. Lag 1 of rural value added and lag 1 of food production index affect food production index. According to the results of Variance Decomposition, 95 percent of the forecast error variance of the rural value added variable is due to shocks of its own, while 4 percent is due to shocks to the food production index and 1 percent is due to shocks to arable land. According to the impulse-response function result, the shocks to the rural value added variable on arable land and food production index end within 5 years. According to the Eigenvalue Stability Condition, since all eigenvalues are less than one and within the unit circle, it is seen that the panel VAR meets the stability conditions. According to the Granger Causality test, there is a bidirectional causality relationship between rural value added and food production index. According to the results of the dynamic fixed effects estimator, there is a short and long-run relationship between the variables.