Financial efficiency analysis of Hungarian agriculture, fisheries and forestry sector

Abstract

In this study, we examine the efficiency of companies in Hungary's agriculture, fisheries and forestry sector. We analysed corporate efficiency by using stochastic frontier analysis (SFA). We used two methods to perform the SFA calculations – the Cobb-Douglas and translog functions. The result variable for the SFA calculation was gross value added (GVA), and the explanatory variables were tangibles, material costs, employee costs and other costs. The original database contained cross-sectional and time series data and was transformed into a panel database. We used the maximum log-likelihood method for parameter estimation. We performed the efficiency analysis in the case of the Cobb-Douglas and translog functions in two ways – first, without z variables (factor effects) and second, considering different factors (subsectors, workforce categories, ranking by total assets and ranking by total sales). Taking z variables into account increased the value of the efficiency coefficients. The latter model's results show that the companies' average performance in the sector examined was more than 70%. Further calculations also showed that the subsectors of the agriculture, fisheries and forestry sector differed in efficiency scores. The larger companies operated more efficiently than the smaller ones in the sector examined.