Search results

The purpose of this paper is to explain the factors affecting crop insurance purchases by farmers in Inner Mongolia, China.

A survey of farmers in Inner Mongolia, China, is undertaken. Selected variables are used to explain crop insurance purchases, and a probit regression model is used for the analysis.

Results show that a number of variables explain crop insurance purchases by farmers in Inner Mongolia. Of the eight variables in the model, seven are statistically significant. The eight variables used to explain crop insurance purchases are: knowledge of crop insurance, previous purchases of crop insurance, trust of the crop insurance company, amount of risk taken on by the farmer, importance of low crop insurance premium, government as the main information source for crop insurance, role of head of village, and number of family members working in the city.

A possible limitation of the study is that data includes only one geographic area, Inner Mongolia, China, and so results may not always fully generalize to all regions of China, for all situations.

Crop insurance has been recently expanded in China, and the information from this study should be useful for insurance companies and government policy makers that are attempting to increase the adoption rate of crop insurance in China.

Crop insurance may be a useful approach for stabilizing the agricultural sector, and for increasing agricultural production and food security in China.

This is the first study to quantitatively model the factors affecting crop insurance purchases by farmers in Inner Mongolia, China.

This article analyzes farmers' preferences for different nonindexed crop insurance alternatives, using discrete choice experiment data on cocoa farmers from southern Ghana. We examine farmers' attendance to attributes by comparing self-reported attribute nonattendance (ANA) to the behavior inferred from the choices.

We utilize the latent class endogenous attribute attendance (EAA) model to address potential endogeneity by jointly modelling farmers' attribute processing strategies with their choice of attributes of the insurance products.

The results show that premium levels, mode and length of indemnity payouts tend to influence farmers' preferences for crop insurance products. The findings also reveal that credit-constrained farmers attend more to premium and payment mode attributes of the crop insurance products and that credit-constrained farmers tend to exhibit lower willingness-to-pay estimates for the crop insurance attributes.

The findings from the study suggest that credit constraints do not only limit input use, but also tend to have statistically significant impact on farmers' cocoa insurance participation decisions.

The study examines the impact of credit constraints on farmers' crop insurance preferences while accounting for ANA.

In Nepal, crop insurance is at initial phase. However, since its implementation seven years ago, the adoption rate has been fairly low even with the government's lucrative subsidy on premium. There have been very limited studies on specifics of insurance for different crops, and farmer's acceptability on insurance. This study examines WTP for tree-based insurance, a potential insurance scheme on fruit crops in hilly areas of Nepal.

The authors used a contingent valuation method to estimate farmer's willingness to pay (WTP) premium for insurance. They used a double-bounded dichotomous choice (DBDC) framework to elicit WTP and an interval regression method to estimate the WTP model.

The authors found that the farmers revealed WTP for tree-based insurance is three times higher than the premium they would pay under government's current subsidy plans of insurance. The authors’ result from interval regression also suggests that the factors such as farm size, farmer's adverse experience about invasive pest and weather, awareness of crop insurance, farming experience, and family involvement in agriculture significantly influence farmers' WTP.

A distinct modality of insurance, like tree-based insurance for fruit crops in mid and high hill areas, may enhance the adoption rate rather than a broad area-based plan generalized for all crops.

Only a few studies have examined specifics of insurance in fruit crop insurance in developing countries. The authors’ estimated WTP factors influencing WTP on citrus fruit-crop insurance in Nepal indicates that there is a scope for extending this insurance program. However, the authors also found that there is a gap in understanding of crop insurance and have limited awareness on the government's subsidy programs among farmers.

Farmers' adaptation strategies in agricultural production are required to minimise the negative impact of climate change on a nation's food production in developing countries. Based on the panel data of the provincial level in China from 2000 to 2017, this study aims to analyse the changing climate over recent years and farmers' adaptation strategy in terms of cropping in agricultural production.

This study uses Simpson's diversity index (SDI) to measure the degree of crop diversity planted by farmers and evaluate the influence of climate change on farmers' cropping strategy using the fixed-effect model. Further, the authors estimate the impact of farmers' cropping strategy on their economic performances in two aspects including yields and technical efficiency of crops.

The empirical results show that the overall climate appears a warming trend. Different from farmers in some other countries, Chinese farmers tend to adopt a more specialised cropping strategy which can significantly improve the technical efficiency and yields of crops in agriculture. In addition, as a moderating role, the specialised cropping can help farmers to alleviate the negative impact of climate change on technical efficiency of their crops.

First, previous studies showed that the changing climate influenced farmers' adaptation strategies, while most studies focussed on multiple adaptation strategies from the farm-level perspective rather than cropping strategy from the nation-level perspective. Second, the present study investigates how the cropping strategy affects the economic performance (in terms of the technical efficiency and crop yields) of agricultural production. Third, the stochastic frontier analysis method is used to estimate the technical efficiency. Fourth, this study explores the moderating effect between farmers' cropping strategy and technical efficiency by introducing an interaction item of SDI and accumulated temperature.

The aim of this paper is to identify the factors that influence rice farmers' decisions to adopt crop insurance and premium payments (willingness to pay [WTP] amounts). The paper also demonstrates the usefulness of the complementary log-log (cloglog) truncated Poisson double-hurdle model as an alternative hurdle model.

The study first investigated the nature of the dependent variable, which had non-normal residuals and was overdispersed. The probit truncated normal regression double-hurdle model was tried but it failed the normality and homoscedasticity tests; hence, the cloglog truncated Poisson double-hurdle model was employed in the study.

An estimated 61% of respondents would purchase crop insurance, despite farmers not having prior experience with this product. Amongst others, the factors that influence insurance adoption amongst rice farmers are the share of rice in total income, reliability perception of crop insurance schemes and the probability of failure to achieve target yields. The latter helps the authors to address adverse selection, a central issue to the viability of such an insurance programme. The determinants of farmers' WTP are also identified.

Sampling was limited to farmers using irrigation and living in one region of Ghana, which may limit the study’s wider applicability.

As far as the authors are aware, this study is the first to select the appropriate hurdle model based on established properties of the dependent variable on this topic – crop insurance decisions.

The purpose of this paper is to investigate the adoption of two categories of agricultural technologies among beginning farmers (10 years or less of experience) operating in the specialty crops industry. A secondary goal is to characterize the beginning farmers' population in the specialty crops industry and compare them to more experienced farmers (more than 10 years of farming experience).

Using a series of regressions, this paper tests the hypothesis that beginning farmers are more likely to adopt agricultural technologies such as growing technologies (i.e. hydroponics and hoop houses) and value-added (VA) technologies (drying and cutting produce into customer-ready portions) relative to counterparts. Using a unique primary collected dataset of specialty crops farmers, the dependent variable for each model is the binary decision to adopt each agricultural technology, while the main variables of interest are the dummy variables beginning farmers and the interaction terms created between beginning farmers and land farmed, percent of land rented, crop diversification, local sales, and part-time farming.

Farmers' characterization suggests that, on average, beginning farmers are more likely to adopt growing technologies than more experienced farmers. However, after controlling for other determinants of adoption, there is no significantly difference between the two groups. Lastly, results suggest that beginning farmers are more likely to adopt VA technologies relative to experienced farmers.

While the adoption of agricultural innovations can lead to increases in economic and environmental resilience, little is known about beginning farmers adopting agricultural technologies, and studies are even less common for specialty crops operations. As the world population continues to grow rapidly, the demand for agricultural food products is expected to increase up to 100% between 2010 and 2050. This growth places additional stress on the limited access to land and water for agricultural production. Farm profitability can be boosted by increasing economies of scope through the use of growing technologies that increase yield or by adding value to specialty crops. The increasing global demand for food makes it imperative to understand what influences the adoption of agricultural technologies among beginning farmers growing food crops.

The purpose of this paper is to analyze smallholder farmers’ perceptions of climate change and its adverse effects, identify major adaptation strategies used by farmers and analyze the factors that influence the choice of adaptation strategy by smallholder farmers in eastern Ethiopia.

The study was based on a cross-sectional survey of 296 sample households selected from three districts in east Ethiopia. Data were collected with the aid of a semi-structured questionnaire and review of literature, documents and databases.

The study provides empirical evidence that majority of farmers in the study area are aware of climate change patterns and their adverse effect on income, food security, diversity, forest resources, food prices and crop and livestock diseases. In response to these adverse effects, major adaptation strategies used by farmers include cultivating different crops, planting different crop varieties, changing planting dates, use of soil and water conservation techniques, conservation agriculture practices and engaging in non-farm income activities. Choice of adaptation strategies are influenced by gender of household head, household size, farm size, distance from market and number of farm plots.

The study suggests that developing more effective climate change adaptation strategies need support from the government. Such an effort needs provision of the necessary resources such as credit, information and extension services on climate change adaptation strategies and technologies, and investing in climate smart and resilient projects.

The study adopts multivariate probit model that models farmers’ simultaneous adaptation choice behavior which has been rarely addressed by previous researches.

This work examines the impact of institutional agricultural credit on crop productivity of some major crops such as paddy, cotton, wheat and pulses for small and marginal farmers across various social groups.

The cross-sectional field data on socio economic variables was collected from three Indian states from about 400 small and marginal farmers across various social groups using multi-stage stratified random and purposive sampling through a structured questionnaire by interviewing. The method of propensity score matching (PSM) was employed to calculate average treatment effect (ATE) and average treatment effect on the treated (ATET) by categorising sample farmers as treatment group and control group where crop productivity was considered as outcome variable and access to institutional credit was considered as treatment variable.

The PSM estimates reveal that ATE and ATET for all the selected crops are found to be significantly higher for the treated group vis-à-vis non-treated group suggesting that institutional agricultural credit has a statistically and significant positive impact on the crop productivity.

Similar study can be extended for more crops and across regions in India for a universal coverage.

The agricultural credit policy of India has been to increase the access and availability of institutional farm credit. This has led to in general increase in the flow of formal farm credit to agricultural sector. However, the impact of institutional credit and crop productivity especially for small and marginal farmers across social groups is not well recognized in India using field data. Accordingly, this field data study contributes to the existing research by providing fresh evidence from field across social groups for both kharif and rabi crops using recent survey data from small and marginal farmers which has important policy implications.

The purpose of this paper is to assess farmers’ willingness to participate and pay for weather-based index insurance in the Upper East Region of Ghana, and what factors influence the participation and purchase of crop insurance schemes.

A survey of 200 farmers in the region was carried out in 2018 to measure demographic information, farm characteristics, risks and risk-management practices and attitudes to crop insurance programs. The survey also captured maximum willingness to pay (WTP) for crop insurance. The double-bounded contingent valuation technique was used to estimate the WTP for crop insurance and the variables that affected WTP.

Farmers, in general, had an indifferent attitude to crop insurance in the region, but were willing to participate in the crop insurance programme, and were willing to pay between 7.5 and 12.5 per cent of the cost of growing maize as a premium for crop insurance. Demographic and economic variables did not impact WTP, but attitude towards crop insurance, farm diversification and frequency of drought negatively impacted on the WTP for crop insurance.

Education programs could be undertaken to improve the attitude and understanding towards crop insurance, as some farmers perceived the programme as not trustworthy, and others did not truly understand the operation of the programme.

Drought can have a significant impact on household welfare, particularly in food insecure countries or regions. Crop insurance can provide a method of securing income for farmers allowing them to purchase food rather than other choices, such as removing children from education to reduce household expenses, improving the long-term welfare of the farm household.

This paper considers willingness to participate and WTP for a crop insurance programme in Ghana, it is one of a small number of papers that consider attitude to, and willingness to participate and WTP for crop insurance in developing countries. The value of the research is the expanded understanding of farmer attitude to crop insurance and their lack of knowledge of crop insurance operations.

Regional differences in crop insurance uptake have persisted over time. To partly explain this phenomenon, the purpose of this paper is to propose and evaluate a budget constraint (heuristic) effect within the standard expected utility theory (EUT) framework through simulation methods.

Within the EUT framework, a standard simulation model is used to gain insights into farm insurance decisions when a budget constraint is in effect. The budget constraint is modeled as it has been revealed through the data on farmers’ insurance expenditures. In the simulation analysis, certainty equivalent values are used to rank farm options subject to the revealed budget constraint.

A budget constraint effect within the EUT framework stands out in explaining the observed regional differences. The proposed explanation is consistent with the historical trends on the ratio of crop insurance expenditure to expected crop value, higher premium rates in regions with lower crop insurance uptake, and the limited turnout for the 2014 Farm Bill’s supplemental area-based crop insurance products. Farmers’ crop insurance choices are found to be mostly constrained-optimal.

This appears to be the first study taking the revealed preferences approach to farmers’ crop insurance choices in a simulation analysis. Some policy implications are drawn and future research avenues are suggested. The findings should be of considerable value to policymakers, academics, bankers, and producers in regard to the design and use of risk management tools.