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Purpose The purpose of this paper is to identify the factors that determine demand for crop insurance in Poland. Design/methodology/approach To examine the determinants of decisions regarding crop insurance, the authors used logistic regression. The base source of data for the analysis was the 2013 FADN sample. The scale of yield losses, the indemnities received and the Arrow-Pratt risk aversion coefficient were examined in a representative sample of farms in consecutive years in the period 2004-2013. Findings Losses are the major determinants of crop insurance uptake. Additionally, it was observed that the economic determinants are in line with the expected utility theory, while contrary to expectations, farmer’s characteristics such as education level, age or even risk aversion did not prove to have any influence on crop insurance uptake. Research limitations/implications The FADN sample is representative as regards the type of farming, economic size of farm and location of the farm. Every farm in the sample represents a specific number of similar farms in the population. However, it must be emphasised that the representativeness of the sample with respect to other determinants, e.g., yield losses in previous years, using crop insurance or the farmers’ age and education has not been verified due to lack of data characterizing the general population with regard to these factors. Practical implications It could be argued that the system of crop insurance subsidies should be targeted to encourage the farmers who previously had not used insurance to join the system. Originality/value The paper presents the analysis of crop insurance uptake in a country with a strongly polarised agriculture. The Polish farm sector consists of 1.4 million farms with sizes ranging from 1 ha to over a few thousands hectares. The research is based on a data set of 5,202 farms which contains data from ten years (2004-2013). The novelty of the methodological approach is that it includes information on the number of farms represented by every farm in the FADN sample in the Horvitz-Thompson estimator in order to achieve results which are valid for the general population of Polish farms.

Risk aversion is an important research area in the field of agricultural economics in the last years. Creating effective and efficient risk management tools in an increasingly volatile economic and natural environment requires proper recognition of farmers’ behavior and attitudes towards risk. In this context, the main aim of the paper was to estimate farmers’ attitudes towards risk and identification of farm’s and farmer’s characteristics in dependency on risk aversion level. The assessment of farmers’ preferences towards risk was based on hypothetical games in a representative sample of 600 Polish farms—participants of Farm Accountancy Data Network (FADN). Based on the interviews with farmers, a relative risk aversion coefficient has been estimated. Results revealed that on average Polish farmers have quite a strong risk aversion. Their attitudes towards risk are strongly linked with their self-assessment regarding their way of making decisions under risk. Some relations between farmers’ risk aversion and perception of selected risk factors could also be observed. The results revealed that the application of specified risk management tools by farmers and their potential reaction to a significant income drop are related to risk aversion level.

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Climate neutrality achievement in the European Union assumes the necessity of efforts and transformations in most economic sectors of its member-states. The farm sector in Poland, being the second largest contributor to the country’s greenhouse gas (GHG) emissions and in the top fifth of farm sectors in the EU-27 countries, needs to undergo structural and technological transformations to contribute to the climate action goals. The article assesses the potential impacts of Poland’s climate neutrality achievement path on the domestic farm sector in terms of its structure, output, income, and prices of agricultural products. The approach is based on complex economic modelling combining computable general equilibrium (CGE) and optimisation modelling, with the farm sector model consisting of farm, structural, and market modules. While the modelling results cover three GHG emission-reduction scenarios up to 2050, to understand the transformation impact within varying policy approaches, the study for each scenario of farm sector development also outlines three policy options: carbon pricing, forced emission limit, and carbon subsidies. Results in all scenarios and policy options indicate a strong foreseeable impact on agricultural output and prices (mainly livestock production), shifts in the production structure toward crops, as well as changes in farm income along the analysed timeframe.

Farming sectors’ resilience has been built over decades with the aid of policies and institutions. However, its actual standing can be assessed in times of crises when farms have to overcome particular challenges. We use a large-scale farming sectors dataset FADN spanning 2006–2015 in which two major economic crises occurred—the global economic crisis of 2008 and the Russian embargo of 2014—to exemplify our approach to resilience’s assessment based on the Polish farming sectors. We introduce a distinction between “potential resilience” versus “revealed resilience” where the former is assessed based on resilience capacities (robustness, adaptability and transformability), while the latter is assessed based on the observed decomposition of total factor productivity (TFP) changes in response to the adverse economic shocks. Hence, the proposed framework directly links productivity with the two types of resilience. We applied the Färe-Primont method of TFP decomposition, into technological change and various types of efficiency changes and a detailed farm survey to distinguish between the drivers of technological changes in each farming sector such as specific innovations and ecosystem services. Our findings show that farms differ in their revealed resilience both among the sectors and between two different shock events. Only field crop farms and granivores farms (pig and poultry) maintained their resilience to both crises, staying robust and/or adaptable. The former had the most productive technology and were leaders in applying innovations while the latter were second best in innovations and fairly good in their application of ecosystem-based services into their technology. Other farm types failed to be resilient to the first crisis but proved robust during the second. The outcomes of the study have implications for sustainability oriented policies.

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