The aim of this article is to investigate the relationship between size and farm growth. The existing theories of the association between size and farm growth give mixed results by countries and over time. This paper pursues a twofold objective: on one hand, to test the validity of Gibrat’s Law for French, Hungarian and Slovenian specialized dairy and crop farms during the pre- and post-accession period to the European Union membership. Dairy and crops farms are prevailing in the farming structure of these countries. Using Farm Accountancy Data Network datasets makes it necessary to avoid biases due to heterogeneous structures across the farming systems. Thus we use quantile regressions to control for farm size related heterogeneity in the samples. On the other hand, the main novelty of this paper is the comparative analysis of the relationship between farm size and farm growth between transition Hungarian and Slovenian and non-transition French farming sectors, characterized by rather different farm structures. The results reject the validity of Gibrat’s Law for crop farms in Hungary and to a lesser extent in France, and for French and Slovenian dairy farms. We provide evidence that smaller farms grew faster than larger ones over the studied period 2001-2007 for France, 2001-2008 for Hungary, and 2004-2008 for Slovenia. Conversely, the results for Slovenia suggest that the rate of growth of crop farms in terms of its land is independent from its size.

Hungarian agriculture is expected to experience greater risks due to more variability in crop productivity due to increasing yearly average temperatures and extreme precipitation patterns. This study investigates the effect of changing climatic conditions on productivity, using a Hungarian sample of crop producers for a 12-year time period. Our empirical analysis employs True Fixed Effects frontier models of Farm Accountancy Data Network data that are merged with specific meteorological data representatively maintained for seeding, vegetative, and generative periods for cereals, oil seed and protein crops, along with soil quality and usage-related data. Estimations indicate that climate variables have significant impacts on technical efficiency. In addition, calculation suggest that an increase in temperature during seeding and vegetative periods, combined with higher precipitation levels in May and June, will reduce crop farmers’ production frontier. Estimations explain the variance, while the technical efficiency (TE) scores emphasize the impact of the difference in soil quality and its water absorption capacity.

Since the collapse of the communist system, regional inequalities have increased in Central European Countries. This paper describes an assessment of the impacts of regional development programmes on the development of Hungarian regions at a highly disaggregated level between 2002 and 2008. We construct a multi-dimensional composite indicator to estimate the overall development of rural regions and capture social, economic and environmental dimensions. The impacts of rural development programmes were investigated through counterfactual analysis in combination with Propensity Score Matching and Difference-in-Differences approaches. There has been considerable variation with increasing concentration in the level of subsidies distributed during the analysed period. From a policy perspective, the results are disappointing. Irrespective of the subsidy measures or methodology employed, the impact of the former is very close to zero or non-significant. Our findings cast serious doubt on the effectiveness of development policy and the long-run convergence of European regions.

The effectiveness of support directed to less developed regions is a timely question more than halfway through the 2014–2020 programming period. We present an analysis of the impact of rural development support on the well-being of Hungarian LAU1 regions between 2008 and 2013. The aim was to measure the overall impact of all of the Rural Development Funds, covering all measures within the program. Two indices of local well-being were used: the multi-dimensional, local-variables-based Regional Development Index that measures the overall level of regional development and a simple, migration-based index as a proxy for perceived quality of life. Generalized propensity score matching, and difference-in-differences estimation techniques were employed to evaluate the impact of subsidies. Irrespective of how the amount of support was calculated, the measure of local well-being, or the methodology employed, the impact was not significant, and was sometimes even negative. This casts doubt on the effectiveness of Rural Development Policy in Hungary.

Growth in the craft beer sector has been unevenly distributed over time and in terms of geographical area. While the spatial drivers of craft breweries in the United States are well documented, research on the situation in European countries is still limited. This paper investigates the locational determinants of the Hungarian craft brewing industry between 2005 and 2018 at the level of small regions. We employ negative binominal models to determine the relationship between the number of microbreweries and locational factors. We find that demand-side factors, including income, level of education, proportion of youth in a region and population density, positively affect the number of craft breweries. We emphasize that general local economic characteristics may be less important, whilst industry-specific local conditions (e.g., craft brewing traditions and market saturation) significantly impact the location choice of craft breweries. Our estimations highlight the role of transport costs in location decisions. Finally, we demonstrate the relevance of the availability of water, one of most important inputs in beer production.