Preferences for crop insurance attributes among cocoa farmers in Ghana

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Victor Owusu ◽  
Awudu Abdulai ◽  
Williams Ali
Keyword(s):  
Latent Class ◽  
Credit Constraints ◽  
Crop Insurance ◽  
Content Type ◽  
Processing Strategies ◽  
Input Use ◽  
Cocoa Farmers ◽  
The Impact ◽  
Participation Decisions ◽  
Southern Ghana

PurposeThis 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.Design/methodology/approachWe 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.FindingsThe 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.Research limitations/implicationsThe 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.Originality/valueThe study examines the impact of credit constraints on farmers' crop insurance preferences while accounting for ANA.

Capital and credit constraints in the engagement of youth in Ghanaian agriculture

2019 ◽  
Vol 80 (1) ◽  
pp. 22-37 ◽  
Author(s):  
Martinson Ankrah Twumasi ◽  
Yuansheng Jiang ◽  
Monica Owusu Acheampong
Keyword(s):  
Positive Impact ◽  
Credit Constraints ◽  
Rural Youth ◽  
Unique Contribution ◽  
Switching Regression ◽  
Credit Constraint ◽  
Data Set ◽  
Content Type ◽  
Application Procedure ◽  
The Impact

Purpose The purpose of this paper is to determine the factors influencing rural youth farmers’ credit constraints status and the effect of credit constraint on the intensity of participation of these farmers in Ghana. Design/methodology/approach The econometric estimation is based on cross-sectional data collected in 2018 from the Brong Ahafo region in Ghana. The sample data set consists of 450 rural youth farmers. The collected data were analyzed through different econometric techniques, using the endogenous switching regression model (ERSM). Findings The direct elicitation approach employed in this study revealed that out of the 450 farmers, 211 (47 percent) of the respondents were credit constrained compared to 239 (53 percent) of their counterparts who were unconstrained. The ERSM indicated that youth farmers education, age, savings, parents occupation reduced the probability of the rural youth farmer to be credit constrained but cumbersome loan application procedure and loan disbursement time positively affect credit constraint. Moreover, farmers that are credit constrained have lower intensity of participation in agriculture activities than a random farmer from the sample. This suggests that access to credit has a positive impact on the intensity of participation in agriculture activities. Research limitations/implications In this study, only rural youth farmers in a particular region were considered. However, there are youths all over the nation. Therefore, future researchers could consider other youth’s farmers elsewhere in the country. Originality/value Although existing studies have examined rural youth farmers’ participation in agriculture and credit constraint separately, the unique contribution of this paper is the analysis of credit constraint of rural youth farmers as well as the impact of credit constraint on the intensity of participation in agriculture activities.

Consumer preference for wine from hand-harvested grapes

2019 ◽  
Vol 122 (8) ◽  
pp. 2551-2567 ◽  
Author(s):  
Andrea Dominici ◽  
Fabio Boncinelli ◽  
Francesca Gerini ◽  
Enrico Marone
Keyword(s):  
Latent Class ◽  
Consumer Preferences ◽  
Latent Class Model ◽  
Interactive Effect ◽  
Consumer Preference ◽  
Random Parameter ◽  
Content Type ◽  
Organic Certification ◽  
Taste Heterogeneity ◽  
The Impact

Purpose The purpose of this paper is to investigate preferences for wine made from hand-harvested grapes, and the interactive effect between this attribute and organic certification. Design/methodology/approach Data were collected via an online choice experiment involving a sample of 408 Italian wine consumers. A random parameter logit was performed to estimate consumer preferences for wine attributes: harvest type, organic and the interaction between these. The experiment also includes geographical indications and price. Furthermore, a latent class model (LCM) is performed to investigate taste heterogeneity for the included wine attributes. Findings On average, consumers prefer the wine produced with hand-harvested grapes. The hypothesis of an interaction between organic and hand-harvested attributes is rejected. Using the LCM, the authors identify three segments with significant taste heterogeneity in terms of the magnitude and the sign of the parameters. Moreover, consumer attitudes towards food naturalness differ according to their belonging to the segments. Originality/value The novelty of this article is twofold. First, this study investigates, for the first time, the impact of the hand-harvested method on consumer wine preferences. Second, hand-harvesting and organic have independent values.

Cognitive processing and affect predict negotiators’ post-adversity subjective and economic outcomes

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mara Olekalns ◽  
Philip Leigh Smith
Keyword(s):  
Cognitive Processing ◽  
Design Methodology ◽  
Economic Value ◽  
Economic Outcomes ◽  
Affective Processing ◽  
Processing Strategy ◽  
Content Type ◽  
Processing Strategies ◽  
And Coping ◽  
The Impact

Purpose Negotiators are offered limited advice on how to overcome adverse events. Drawing on resilience and coping literatures, this study aims to test the impact of three cognitive processing strategies on negotiators’ subjective and economic value following adversity. Design/methodology/approach Participants completed two negotiations with the same partner. The difficulty of the first negotiation was manipulated and tested how cognitive processing of this experience influenced subjective and economic outcomes in the second negotiation. Findings Subjective and economic outcomes were predicted by negotiators’ affect, their cognitive processing strategy and negotiation difficulty. In difficult negotiations, as positive affect increased, proactive processing decreased self-satisfaction. As negative affect increased, affective processing increased satisfaction with relationship and process. Research limitations/implications Cognitive processing of adversity is most effective when emotions are not running high and better able to protect relationship- and process-oriented satisfaction than outcome-oriented satisfaction. The findings apply to one specific type of adversity and to circumstances that do not generate strong emotions. Originality/value This research tests which of three cognitive processing strategies is best able to prevent the aftermath of a difficult negotiation from spilling over into subsequent negotiations. Two forms of proactive processing are more effective than immersive processing in mitigating the consequences.

scholarly journals The impact of enterprise unit policy change on the quantity demanded for crop insurance

2020 ◽  
Vol 80 (4) ◽  
pp. 507-527
Author(s):  
Harun Bulut
Keyword(s):  
Policy Change ◽  
Crop Insurance ◽  
Management Tools ◽  
High Coverage ◽  
Content Type ◽  
Time Path ◽  
Unit Structure ◽  
Catastrophic Coverage ◽  
Economic Regions ◽  
The Impact

PurposeThe article examines the impact of policy change on enterprise unit subsidies that took place in 2009 on the quantity demanded for crop insurance.Design/methodology/approachThe analysis covers corn, soybeans, and wheat that are grown in six economic regions and uses various measures of purchasing such as acres insured, unit structure, coverage levels, as well as crop hail use as proxies for the quantity demanded.The analysis first employs time series econometric tools to analyze whether the time path of the share of enterprise units within buyup acres is influenced by the policy change in enterprise unit subsidies. It then comparatively examines the insurance experience between 2008 (right before the change) and 2015 (well after the change).FindingsFor corn, soybean, and wheat, the analysis establishes that the time path of the share of enterprise units within buyup coverage acres is statistically and economically influenced by the intervention. The analysis further quantifies the intervention's immediate and long-term impacts and finds that farmers' unit choices are highly responsive (elastic) to subsidy rates in those units.Between 2008 and 2015, the insurance experience generally indicates that the share of enterprise units within buyup coverage surged, the share of acres under catastrophic coverage declined, and the share acres in high coverage levels increased. Meanwhile, growers have increasingly utilized crop-hail policies.Originality/valueThis appears to be the first study (1) quantifying the sensitivity of farmers' unit choices with respect to subsidy rates in those units and finding that such choices are actually highly responsive (elastic), and (2) pointing out the interaction between MPCI and crop-hail products and offering insights as to their combined use. The findings should be of considerable value to policymakers, academics, bankers, and producers in regards to the design and use of risk management tools.

Supporting older workers to work: a systematic review

2019 ◽  
Vol 48 (5) ◽  
pp. 1318-1335 ◽  
Author(s):  
Mego Kuan-Lun Chen ◽  
Elliroma Gardiner
Keyword(s):  
Older Workers ◽  
Systematic Evaluation ◽  
Workforce Participation ◽  
Related Factors ◽  
Cross Sectional ◽  
Content Type ◽  
Work Arrangements ◽  
Work Related ◽  
The Impact ◽  
Participation Decisions

PurposeThe purpose of this paper is to identify what work-related factors influence the continued participation of older workers in the workforce.Design/methodology/approachA systematic quantitative literature review of the workforce participation literature identified 27 publications from 1995 to 2016 that examined the impact of work-related factors on older workers’ intention to continue working.FindingsResults show that work demands, learning and development opportunities, job autonomy, recognition and respect, mentoring opportunities, supportive organisational climate and social support were significant factors that predicted older workers’ workforce participation decisions. Interestingly, less evidence was found to support flexible work arrangements or salary as inducers of workforce participation. Results also show an overrepresentation of cross-sectional studies involving participants from western countries employed in healthcare and social assistance sectors.Practical implicationsOrganisations should adjust their policies and practices to accommodate the needs of older workers, focusing specifically on increasing factors that encourage participation and removing obstacles to participation.Social implicationsIncreasing the participation rates of older workers is a key goal for governments and organisations worldwide. This research identifies some specific factors that are likely to encourage continued participation.Originality/valueA systematic evaluation of the extant research draws new conclusions and insights as to what work factors are more likely to influence the participation decisions of older workers.

Does federal crop insurance lead to higher farm debt use? Evidence from the Agricultural Resource Management Survey (ARMS)

2015 ◽  
Vol 75 (3) ◽  
pp. 349-367 ◽  
Author(s):  
Jennifer E Ifft ◽  
Todd Kuethe ◽  
Mitch Morehart
Keyword(s):  
Resource Management ◽  
Crop Insurance ◽  
Future Research ◽  
Short Term ◽  
Farm Sector ◽  
Content Type ◽  
Financial Decisions ◽  
Farm Debt ◽  
The Impact ◽  
Agricultural Resource Management Survey

Purpose – The purpose of this paper is to consider how the federal crop insurance (FCI) program influences farm debt use, one of the key financial decisions made by farm operators. Design/methodology/approach – Using data from the nationally representative Agricultural Resource Management Survey, the paper implements a propensity score matching model of the impact of FCI participation on various measures of farm business debt use. To account for the simultaneity of financial decisions, the paper further tests this relationship using a seemingly unrelated regression model. Findings – FCI participation is associated with an increase in use of short-term farm debt, but not long-term debt, consistent with risk balancing behavior and current trends in the farm sector. Research limitations/implications – In addition to risk balancing, the results are also consistent with credit constraints or lender preferences. The paper cannot fully establish causality between crop insurance participation and short-term debt levels. Future research should address these limitations. Practical implications – Agricultural lending standards are generally conservative and the farm sector as a whole currently has historically low leverage, which implies that an increase in debt use may not be a threat to the financial health of the farm sector. Social implications – The results indicate that the reduction in total risk facing the farm sector is significantly less than the decline in risk provided by FCI, which is an important consideration for policymakers. Originality/value – This is the first paper to use an econometric model to analyze the relationship between FCI and farm debt use decisions. This paper can inform future research on the FCI program and farm financial decisions.

Agricultural labour productivity and credit constraints: implications for consumption in rural Ghana

2020 ◽  
Vol 11 (2) ◽  
pp. 331-351
Author(s):  
Haruna Issahaku ◽  
Ishaque Mahama ◽  
Reginald Addy–Morton
Keyword(s):  
Quantitative Estimation ◽  
Credit Constraints ◽  
Labour Productivity ◽  
Rural Households ◽  
Farm Size ◽  
Living Standard ◽  
Content Type ◽  
Wide Range ◽  
Agricultural Labour Productivity ◽  
The Impact

PurposeThe purpose of this study is to assess the impact of credit constraints on agricultural labour productivity as well as the impact of credit constraints and agricultural labour productivity on rural households' consumption in Ghana.Design/methodology/approachThis study uses the Ghana Living Standard Survey round six (GLSS 6) as the main source of data, which happens to be one of the most comprehensive household datasets in Ghana. Quantitative estimation techniques (namely: Endogenous Switching Regression and Two Stage Least Squares) are used to address possible endogeneity and selection into credit markets.FindingsFirst, large households are prone to credit constraints while age (experience) and compliance with extension advice reduce credit constraints. Second, the determinants of agricultural labour productivity for both constrained and unconstrained households are age, sex, farm equipment, herbicide and farm size. Third, household size, education and livestock rearing influence agricultural labour productivity of constrained households. Fourth, credit constraints, irrespective of how they are measured, impede agricultural labour productivity while access to credit fosters labour productivity. Lastly, credit constraints robustly reduce consumption while agricultural labour productivity strongly enhances rural households' consumption.Originality/valueThe first contribution is that, unlike most previous studies, we do not focus on the widely used measure of productivity – output per unit land, but on agriculture labour productivity in particular. Secondly, unlike most previous studies which examine the effect of credit constraints either on productivity alone or consumption alone, our study examines the impact of credit constraints on both. Thirdly, unlike the existing literature which uses one or two measures of credit constraints, we use a wide range of measures of credit constraints – seven different measures of credit constraints. Lastly, our empirical strategy solves at least two critical econometric problems – sample selection bias and endogeneity.

Duration analyses of precision agriculture technology adoption: what's influencing farmers' time-to-adoption decisions?

2020 ◽  
Vol 80 (5) ◽  
pp. 647-664 ◽  
Author(s):  
Eric Ofori ◽  
Terry Griffin ◽  
Elizabeth Yeager
Keyword(s):  
Precision Agriculture ◽  
Crop Insurance ◽  
Farm Income ◽  
Embodied Knowledge ◽  
Content Type ◽  
Farm Level ◽  
Adoption Decisions ◽  
The Difference ◽  
The Cost ◽  
The Impact

PurposePrecision technologies have been available at the farm level for decades. Some technologies have been readily adopted, while the adoption of other technologies has been slower. The purpose of this study is to examine the factors influencing farmers' time-to-adoption decisions as duration between year of commercialization of precision agriculture (PA) technologies and year of adoption, at the farm level.Design/methodology/approachTime-to-adoption, which is the difference in years between technologies becoming commercially available and the year of adoption was determined using non-parametric duration analysis, and the impact of specific farm/farmer characteristics on time-to-adoption were estimated using a semi-parametric Cox proportional-hazard (CPH) model, based on a panel dataset of 316 Kansas farms from 2002 to 2018.FindingsThe findings indicate that, time-to-adoption for embodied-knowledge technologies such as automated guidance and section control were statistically shorter than for information-intensive technologies such as yield monitors, precision soil sampling and variable rate fertility. Duration was indirectly (directly) proportional to commercialization date of embodied-knowledge (information-intensive) technology. More so, time-to-adoption statistically differed among technologies within these two broad categories. Time-to-adoption varies across farm location and between both types of technologies. Millennial farmers are more likely to adopt both types of technologies sooner compared to baby boomers. Net farm income, percentage changes in debt-to-asset ratio, corn to total crop acres and machinery investment had no significant impact on the time-to-adoption for both information-intensive and embodied-knowledge technologies. On the other hand, while variations exist, time-to-adoption of PA technologies is mainly driven by location of farm, generation of farmer, number of workers, years of farming experience, total acres cropped and the cost of crop insurance.Originality/valueThis study investigates how the financial position of farms, amongst other important factors might influence time-to-adoption of PA technologies. Results are useful to extension personnel and retailers for planning marketing or farm outreach programs taking into consideration that, time-to-adoption differs across regions and by specific characteristics, key amongst them: generation of farmer, number of workers, years of farming experience, total acres cropped and the cost of crop insurance.

Credit constraints and their impact on farm household welfare

2016 ◽  
Vol 43 (8) ◽  
pp. 782-803 ◽  
Author(s):  
Minh Chau Tran ◽  
Christopher E.C. Gan ◽  
Baiding Hu
Keyword(s):  
Transaction Cost ◽  
Credit Constraints ◽  
Credit Rationing ◽  
Farm Households ◽  
Farm Income ◽  
Farm Household ◽  
Household Welfare ◽  
Switching Regression ◽  
Content Type ◽  
The Impact

Purpose – The purpose of this paper is to identify factors affecting formal credit constraint status of rural farm households in Vietnam’s North Central Coast (NCC) region. Design/methodology/approach – Using the direct elicitation method (DEM), the authors consider both internal and external credit rationing. Findings – Empirical evidences confirm the importance of household head’s age, gender and education to household’s likelihood of being credit constrained. In addition, households who have advantages in farm land size, labour resources and non-farm income are less likely to be credit constrained. Poor households are observed to remain restricted by formal credit institutions. Results from the endogenous switching regression model suggest that credit constraints negatively impact household’s consumption per capita and informal credit can act as a substitute to mitigate the negative influence of formal credit constraints. Research limitations/implications – One limitation arises from the usage of the DEM to identify credit constrained households. The method cannot detect effective and ineffective constraints. Another limitation is the inability of cross-section data to capture long-term impacts of credit constraints on household welfare. Finally, causes of credit constraints from the lender’s view cannot be observed. Practical implications – The results suggest that it is necessary to enhance the credit allocation regime to reduce the transaction cost and provide target households with sufficient credit. It should be emphasized that high transaction cost and the mismatch between credit demand and supply stemming from information asymmetry. The government can help formal financial institutions to reduce information cost by encouraging the active role of social organizations such as Women Unions, Youth Unions and Veteran Unions in bridging rural farm households with formal lenders. Originality/value – There are limited studies focusing on determinants of credit constraints and their impacts on rural farm households. To the best of the knowledge, there is no study evaluating the impact of credit constraints on rural farm household welfare particularly in Vietnam. In addition, the studies related to credit constraints only considered full quantity rationing (households applied for the loan but were rejected), omitting the case of partly quantity rationing (loan obtained by the borrowers is less than their demand) and self-rationing.

How important is the transitional yield (t-yield)? An analysis of reforms to organic crop insurance

2019 ◽  
Vol 79 (2) ◽  
pp. 234-254 ◽  
Author(s):  
Timothy A. Delbridge ◽  
Robert P. King
Keyword(s):  
Crop Yield ◽  
Crop Insurance ◽  
Yield Potential ◽  
Yield Data ◽  
Data Set ◽  
Content Type ◽  
Insurance Program ◽  
Before And After ◽  
Production History ◽  
The Impact

PurposeThe USDA’s Risk Management Agency (RMA) made several changes to the crop insurance products available to organic growers for the 2014 crop year. Most notably, a 5 percent premium surcharge was removed and organic-specific transitional yields (t-yields) were issued for the first time. The purpose of this paper is to use farm-level organic crop yield data to analyze the impact of these reforms on producer insurance outcomes and compare the insurance options for new organic growers.Design/methodology/approachThis study uses a unique panel data set of organic corn and soybean yields to analyze the impact of organic crop insurance reforms. Actual Production History values and premium rates are calculated for each farm and crop yield sequence. Producer loss ratios and subsidized premium wedges are compared for yield, revenue and area-risk products before and after the instituted reforms.FindingsResults indicate that RMA succeeded in improving the actuarial soundness of the organic insurance program, though further refinement of organic t-yields may be necessary to accurately reflect the yield potential of organic producers and avoid reductions in program participation.Originality/valueThis paper provides insight into the effectiveness of reforms intended to improve the actuarial soundness of organic crop insurance and demonstrates the effect that the reforms are likely to have on new and existing organic farms. Because this analysis uses data collected independently of RMA and includes farms that may or may not have purchased crop insurance, it avoids the self-selection problems that might affect analyses using crop insurance program data.

Sign in / Sign up

Export Citation Format

Share Document