Abstract
Agricultural activities are subjected to a wide range of risks because of the variable economic and biophysical environment in which farming operates. The uncertainties and risks in agriculture are diverse, ranging from weather conditions and animal diseases, changes in agricultural product prices to fertilizer and other inputs, and from financial uncertainties to policy and regulatory risks. The existence of risk in agriculture has long been observed as having a significant influence on farmers’ production and investment decisions.Farmers have many options to manage risk at the farm level, and many of them utilise these options. However, keeping in view different aspects of farmers’ behaviour, the present study is designed to investigate the impact of various factors on farmers’ risk management adoption decisions as to the main research objective. Two other research objectives were also included based on the importance and background of the study, i.e., identifying risk management strategies adopted by farmers in the study area, and identifying the correlation between the risk perception and risk attitude of farmers with the adoption of risk management strategies.
For this study, a well-refined questionnaire was designed and used to collect data. The study was conducted in the Khyber-Pakhtunkhwa (KP) province of Pakistan. Sampling weights were used in the analysis throughout the thesis to deal with the issue of non-random and unequal probability sampling. The variables used in this study were obtained based on relevant literature demonstrating their effect on farmers’ decision to adopt risk management strategies, and include age, education level, farming experience, the proximity of the farm to the river, access to credit, access to information, risk attitude, and risk perception of weather-related risks (flood, heavy rain, hail, storm, pests and disease, and drought). The risk attitude of farmers in the study area was measured using the Holt and Laury method, whereas risk perception of weather-related risks was identified using a risk matrix. The values for access to information were obtained using a composite index.
From the summary statistics, it was found that the majority of the farmers adopted diversification, credit reserve, and accumulated assets as risk management strategies. Farmers in the study area were mostly risk-averse, followed by those of risk-seeking and risk-neutral nature. Similarly, farmers in the study area highly perceived flood, heavy rain, storm, pests and disease, and hail, respectively, as the main threats to their farming activities. In the case of access to information, the farmers in the study area were found to use information sources less often than contacting friends and family to obtain information regarding agricultural activities. The farmers were also found to avoid obtaining credit for agricultural practices, particularly from formal institutions. Those who did obtain credit mostly sought it from local lenders, friends, and relatives.
Independence tests were used to answer the second research questions, where I found that risk perception and risk attitude influence farmers’ decision to adopt risk management strategies to cope with risks. The answer is split into two parts for the main research objective and presented across two empirical chapters.
To answer the first research objective in the first empirical chapter, I analysed the factors affecting farmers’ decision to adopt risk management strategies marginally, using probit and linear probability models. The multivariate probit model is used to answer the research objective from a different perspective, i.e., to analyse the factors affecting farmers’ decision to adopt one risk management strategy simultaneously and allow correlation between these strategies. From the results, I found a correlation between the unobserved factors of these risk management strategies, which the binary probit model fails to provide. Furthermore, a more sophisticated extension of the multivariate probit model, i.e., the recursive multivariate probit (RMVP) model, is used that can provide further value-added information from the data at hand. From the RMVP, we found the endogenous impact of one strategy on the adoption of another strategy along with the correlated error terms of these strategies.
Even though three different models were employed to describe different aspects of farmers’ decision-making behaviour during uncertainty, the results were robust. I found that the distance of the farm from the river, the risk perception of some weather-related risks, a risk-averse attitude, and access to credit and information have a positive and significant impact on farmers’ decision to adopt risk management strategies, irrespective of the model specification. However, the other variables, such as age, education, experience, farm size, and income, show a different impact when assessing farmers’ behaviour from a different perspective, depending on the model specification.
In this study, the endogenous impact of risk management strategies on the probability of adopting another risk management strategy in the recursive multivariate model provides an unprecedented approach while assessing farmers’ choices during uncertainty. From the recursive impact, we also determined whether the risk management strategies are complements or substitutes. We found that diversification and credit reserve are complements, whereas diversification and accumulated assets are substitutes.
Based on the study’s findings, it is recommended that there is a need to improve farmers’ understanding of the crop loan insurance scheme through better extension services and the use of other information sources. The government should improve farmers’ access to information to help them improve their risk adoption decisions in mitigating risks and other agricultural activities. The government should pay attention to enhancing farmers’ access to credit by shortening the credit processing period and simplifying the procedure considerably to increase their farm productivity and, hence, smoothening consumption during uncertainty. Agriculture departments should also arrange training programmes for farmers, guiding them through the process of obtaining a loan from institutional sources and encouraging the positive use of the credit. Moreover, it is important to take into account the factors that affect farmers’ decision to adopt risk management strategies when assessing farmers’ behaviour in risky situations, and to chart out policies to support farmers on the subject of managing risks.
| Date of Award | 2022 |
|---|---|
| Original language | English |
| Awarding Institution |
|
| Sponsors | Abdul Wali Khan University Mardan |
| Supervisor | Yu Zhu (Supervisor) & Andrzej Kwiatkowski (Supervisor) |