Tag: Agricultural Productivity

This study analyses the relationship among carbon dioxide emissions, energy consumption, agricultural labour productivity, agricultural land productivity and agricultural raw material exports using a time series for the period 1960-2015. In this article, some theroretical hypotheses are formulated, aiming to explain the bidirectional causality between agricultural productivity and climate change. These hypotheses are tested by using Vector Autoregression (VAR), Granger causality and Vector Error Correction Models (VECM). Results confirm revelant theoretical hypotheses between agricultural productivity and climate change and show that the variables used are stationary. Agricultural labour and land productivity as well as agricultural raw material exports are positively related to CO2 emissions, meaning that these variables stimulate environmental pollution. Empirical results presented in the paper might be of interest to the academic community and also to policymakers.

The paper analyses targeting and spatial impacts of investment support on agricultural holdings in Slovenia within the national Rural Development Plan for the period 2007-2013. The measure Modernisation of agricultural holdings primarily tackles the problem of low labour productivity in Slovenian agriculture. Achievement of the stated objective of productivity enhancement in agriculture is monitored by the relevant Common Monitoring and Evaluation Framework indicator, standard output (i.e. approximated revenue) per annual work unit SO/AWU. Municipalities (LAU2) are the territorial units of the analysis. Non-spatial and spatial econometric models are developed in order to determine to what extent the estimated labour productivity is affected by intensity of investment support and other factors (measure-specific variables, agricultural structures, socio-economic conditions and geographical conditions). Effectiveness of spatial targeting has been analysed by testing the assumption of a positive relationship between the intensity of implementation of the analysed measure and the productivity. The presence of spatial effects (spatial autocorrelation and spatial heterogeneity) has been examined by including the spatial weight matrix to the ordinary least squares regression. The results confirm a positive relationship between farm investment support and agricultural labour productivity and spatial spillovers in agricultural labour productivity.