The study attempts to identify changes in the loan market for agribusiness enterprises, including farms in Poland, during the COVID-19 pandemic. The research used data from the Central Statistical Office and the Credit Information Bureau for 2017-2020. In the course of research, an econometric model was constructed explaining the volume of loans to the above-mentioned entities by commercial and cooperative banks in Poland during the pandemic. The program Statistica 13.3 was used. The analysis covers all loans granted in Poland on a monthly basis in 2017-2021. During this period, banks granted a total of 307 012 loans to individual farmers, and their volume amounted to almost PLN 30 billion. In the course of the research, it was found that in the years 2017-2021, the volume of loans for agribusiness entities, including farms, was decisively influenced by such factors as refinancing loan rate (stimulant), rediscount rate (destimulant), and general economic climate in manufacturing index (stimulant). The set of explanatory variables in the models may be a premise for the introduction of specific improvements in the credit policy of banks servicing agribusiness in the form of tightening or liberalizing credit requirements. The research results can also be used by banks to effectively plan future sales targets and interest income from these loans.
The study attempts to identify changes in the farm credit market in Poland during the Covid-19 pandemic. The research used the data of the Central Statistical Office and the Credit Information Bureau for the years 2017-2020. In the course of the research, three econometric models were constructed, explaining the number of loans to farms as well as the number of farmers’ credit inquiries, illustrating the interest in external capital of farms during the pandemic. The program Statistica 13.3 was used. An analysis of the normality of the distribution was performed using the Shapiro-Wilk test. The Pearson correlation method was used to establish the existence of a correlation relationship between the variables. In order to construct the predictive models, the correlation calculus and the forward step regression calculus were used. The analysis covered all loans granted on a monthly basis in 2017-2020. In total, in this period, banks granted 245,607 loans to individual farmers and their volume amounted to nearly PLN 24 billion. In the course of the research it was found, inter alia, that the set of explanatory variables in the models may be a premise to introduce improvements in the lending policy of banks servicing agriculture in the form of tightening or liberalizing credit requirements. The research results can also be used by banks to plan future sales targets and interest income from these loans.
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