<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>Progressive climate change triggers off phenomena that threaten agricultural production. Crop insurance makes it possible to mitigate their effects, but only a small percentage of crops in Poland is insured. Previous research into the determinants of farmers'participation in the production insurance system has mainly used the logit regression method. This paper presents the results of a study using a structural equation model (SEM) estimated for a sample of 600 farms in the FADN observation field, which aimed to identify factors influencing farmers’ purchase of production insurance. This research approach made it possible to describe the phenomenon in a way that has been little recognized so far, complementing the decision-making model under consideration with latent variables that could not be considered by the methods used so far. Based on the literature research, three unobservable variables were identified: willingness to purchase insurance, risk aversion and risk perception, and farming intensity, and then quantified using observable variables. The results show a directly proportional relationship between willingness to purchase insurance and risk aversion and risk perception and inversely proportional relationship with farming intensity.</p>
</abstract>

Progressive climate change triggers off phenomena that threaten agricultural production. Crop insurance makes it possible to mitigate their effects, but only a small percentage of crops in Poland is insured. Previous research into the determinants of farmers'participation in the production insurance system has mainly used the logit regression method. This paper presents the results of a study using a structural equation model (SEM) estimated for a sample of 600 farms in the FADN observation field, which aimed to identify factors influencing farmers’ purchase of production insurance. This research approach made it possible to describe the phenomenon in a way that has been little recognized so far, complementing the decision-making model under consideration with latent variables that could not be considered by the methods used so far. Based on the literature research, three unobservable variables were identified: willingness to purchase insurance, risk aversion and risk perception, and farming intensity, and then quantified using observable variables. The results show a directly proportional relationship between willingness to purchase insurance and risk aversion and risk perception and inversely proportional relationship with farming intensity.

Determinants of Farmers’ Participation in the Production Insurance System

Zagadnienia Ekonomiki Rolnej

This work is licensed under the Creative Commons Attribution 4.0 International License.

{"article-title":"Determinants of Farmers\u2019 Participation in the Production Insurance System"}

Progressive climate change triggers off phenomena that threaten agricultural production. Crop insurance makes it possible to mitigate their effects, but only a...

Determinants of Farmers’ Participation in the Production Insurance System

Online veröffentlicht: 30. Juni 2023

Seitenbereich: 51 - 67

Eingereicht: 20. März 2023

Akzeptiert: 30. Mai 2023

DOI: https://doi.org/10.30858/zer/166603

Schlüsselwörter
structural equation models (SEM), agricultural production insurance, agricultural sector

© 2023 Grzegorz Rawa, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Determinants of Farmers’ Participation in the Production Insurance System

Online veröffentlicht: 30. Juni 2023

Seitenbereich: 51 - 67

Eingereicht: 20. März 2023

Akzeptiert: 30. Mai 2023

DOI: https://doi.org/10.30858/zer/166603

Schlüsselwörterstructural equation models (SEM), agricultural production insurance, agricultural sector

© 2023 Grzegorz Rawa, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Schlüsselwörter
structural equation models (SEM), agricultural production insurance, agricultural sector