Pakistan is an agrarian nation that is among the most vulnerable countries to climatic variations. Around 20% of its GDP is produced by agriculture, and livestock-related production contributes more than half of this value. However, few empirical studies have been conducted to determine the vulnerability and knowledge of livestock herders, and particularly the smaller herders. Comprehending individual perceptions of and vulnerabilities to climate change (CC) will enable effective formulation of CC mitigation strategies. This study intended to explore individual perceptions of and vulnerabilities to CC based on a primary dataset of 405 small livestock herders from three agro-ecological zones of Punjab. The results showed that livestock herders’ perceptions about temperature and rainfall variations/patterns coincide with the meteorological information of the study locations. The vulnerability indicators show that Dera Ghazi Khan district is more vulnerable than the other two zones because of high exposure and sensitivity to CC, and lower adaptive capacity. However, all zones experience regular livelihood risks due to livestock diseases and deaths resulting from extreme climatic conditions, lower economic status, and constrained institutional and human resource capabilities, thus leading to increased vulnerability. The results indicate that low-cost local approaches are needed, such as provision of improved veterinary services, increased availability of basic equipment, small-scale infrastructure projects, and reinforcement of informal social safety nets. These measures would support cost-effective and sustainable decisions to enable subsistence livestock herders to adopt climate smart practices.

Arable farming is an intrinsically risky enterprise. Therefore, managing risks and uncertainties in agriculture is very important as it affects all sectors of the economy of a developing country like Pakistan. To do so, a whole suite of options is available to the farming community to safeguard against any type of risk. However, farmers’ behavior of the concurrent adoption of multiple risk management tools is largely ignored in previous studies and has formed the rationale for this research. Thus, the current study is intended to investigate farmers’ decisions of adopting risk management strategies (contract farming, off-farm income diversification, and farm credit use) and to examine the impacts of a variety of factors on farmers’ risk management decisions. The present study is carried out in four districts of Punjab province, Pakistan with a focus on hybrid maize growers. A multivariate probit model is used to evaluate the impacts of independent variables on growers’ choices of adopting contract farming, off-farm income diversification, and farm credit use to manage farm risks keeping in view the potential for the concurrent adoption of these risk management strategies. Results show that 78% of farmers are risk-averse and hence ready to manage risks. The top risk faced by farmers is price risk followed by biological, climatic, and financial risks. Contract farming is the most popular strategy (61% farmers) followed by off-farm income diversification (49% farmers), and the use of farm credit (42% farmers). The findings also reveal that the decisions of adopting risk management strategies are interlinked while the adoption of one risk management tool complements farmers’ decision to adopt other risk management strategies. In addition, the risk management strategies’ adoption choices are affected by the number of factors including socioeconomic characteristics, farmers’ risk perceptions about risk sources, and their attitude towards risk. The study recommends the provision of timely information (climatic, extension) along with easy access to farm credit and the streamlining of contractual arrangements.

This study explored the multifaceted factors influencing the efficiency of hybrid maize production and investigated the possible implications for food security. The study adopted a comprehensive approach, examining personal, household, physical, and institutional factors that affect farmers’ productivity. Findings revealed the technical, allocative, and economic efficiencies through a combination of field surveys, data analysis, and econometric modeling. The mean technical, allocative, and economic efficiency scores for the sampled farms were 0.89, 0.66, and 0.59, respectively. Moreover, the result of Tobit regression analysis showed high significance of all three efficiencies. The significant factors associated with technical efficiency were farm size, age of farm household, maize farming experience, maize farming area, distance from the farm to the main market, number of visits by extension workers, credit access, and Okara district. In addition, the number of visits by extension workers, districts (Sahiwal and Okara), age of farmers, maize farming experience, and regional disparity (Sahiwal district) had substantial influences on allocative and economic inefficiencies in the hybrid maize-growing farms. Policymakers and agricultural stakeholders can develop focused strategies to improve farmers’ productivity and overall food security by identifying the key factors associated with hybrid maize production. Tailored interventions that address knowledge gaps, improve resource allocation, and provide improved institutional support can help make food systems more sustainable and resilient.

This paper is aimed at evaluating the factors affecting the concurrent adoption of two risk coping strategies among hybrid maize farmers, namely income diversification supplemented with off-farm work and contract farming in the wake of changing climatic conditions. Climatic changes and food insecurity at the national level have emerged as key risk elements for hybrid maize production due to varying economic conditions. The present paper addresses these risks by examining various sources of risks faced by hybrid maize farmers and develops ideas to tackle these risks. Bivariate and multinomial probit models were employed to analyze numerous factors that influence farmers’ choice of the simultaneous adoption of income diversification (both on and off the farm) and contract farming at the farm level. The results reveal that hybrid maize farmers’ socioeconomic attributes significantly affect their adoption of risk coping tools. Similarly, the climatic, economic (price-related), biological, and financial risk perceptions and risk preference significantly influence the utilization of risk coping strategies in maize production. These outcomes extend our understanding of farmers’ risk preferences and provide parameters for policymakers to forestall diverse risk sources associated with hybrid maize production.