Raushan Bokusheva

Factors determining the adoption and impact of a postharvest storage technology

This paper evaluates the determinants and impact of adopting the metal silo—a postharvest storage technology for staple grains—which was disseminated by the Swiss Agency for Development and Cooperation (SDC) from 1983 to 2003 in four Central American countries. The aim of the SDC program was to diminish smallholder farmers’ postharvest losses by facilitating the manufacture and dissemination of metal silos and thereby to improve regional food security. Our empirical analysis is based on a unique data set obtained from a survey of 1,600 households from El Salvador, Guatemala, Honduras and Nicaragua. We employed a double-hurdle model to identify factors that contributed to the adoption of metal silos and used Tobit and standard regression models to assess the impact of adopting the silos on food security and well-being of households. Our results show that both the household demand for metal silos and the impact of their adoption varied across the four countries, demonstrating the relevance of regional policies for their adoption, as well as their impact. Furthermore, our results indicate that, in addition to achieving household self-sufficiency in maize, the main determinants of adoption were household socio-economic characteristics such as age, land ownership, completion of a training course and quality of basic infrastructure. Finally, when considering a group of economic and social indicators of household well-being, we found that, compared to the silo non-adopters, the adopter households experienced a significant improvement in their food security and well-being between 2005 and 2009.

Measuring dependence in joint distributions of yield and weather variables

Purpose - The design and pricing of weather-based insurance instruments is strongly based on an implicit assumption that the dependence structure between crop yields and weather variables remains unchanged over time. The purpose of this paper is to verify this critical assumption by employing historical time series of weather and farm yields from a semi-arid region. Design/methodology/approach - The analysis employs two different approaches to measure dependence in multivariate distributions – the regression analysis and copula approach. The estimations are done by employing Bayesian hierarchical model. Findings - The paper reveals statistically significant temporal changes in the joint distribution of weather variables and wheat yields for grain-producing farms in Kazakhstan over the period from 1961 to 2003. Research limitations/implications - By questioning its basic assumption the paper draws attention to serious limitations in the current methodology of the weather-based insurance design. Practical implications - The empirical results obtained indicate that the relationship between weather and crop yields is not fixed and can change over time. Accordingly, greater effort is required to capture potential temporal changes in the weather-yield-relationship and to consider them while developing and rating weather-based insurance instruments. Originality/value - The estimation of selected copula and regression models has been done by employing Bayesian hierarchical models.

Efficiency in Microfinance: Financial and Social Performance of Agricultural Credit Cooperatives in Bulgaria

Efficiency in microfinance requires accounting for a specific ambiguous production goal. Beyond financial performance, microfinance institutions are to be assessed with regard to their social impact. Based on a comprehensive data collection campaign on 15 Bulgarian agricultural credit cooperatives (ACCs), we compiled a database uniting financial (perennial data from 2000 to 2009) and social performance indicators (2009). The social performance assessment follows an internationally renowned methodology of social auditing. It provides the database for the construction of a social output, which, apart from outreach, evaluates social network quality, client benefits (protection from over-indebtedness) and other items that have not been assessed in efficiency analysis before. We develop a new analytical model for Data Envelopment Analysis and gain meaningful results for the sample of ACCs. Interestingly, the efficiency rankings revealed that only ACCs with sound financial performance can achieve a higher ranking in the specification including the social output.

Demand for Farm Insurance Under Financial Constraints

This article investigates the effect of the use of crop insurance on farms’ economic performance. The authors hypothesize the existence of reciprocal causation between crop insurance use and the economic performance of farms in an environment characterized by imperfect financial markets and farm budget constraints. The results confirm the reciprocal causation hypothesis. Economic performance is found to positively influence farms’ demand for insurance, confirming the significance of budget constraints. Moreover, insurance is found to have a negative effect on Hungarian farms’ economic performance, implying that the crop insurance system is inefficient.

Using copulas for rating weather index insurance contracts

ABSTRACT This study develops a methodology for a copula-based weather index insurance design. Because the copula approach is better suited for modeling tail dependence than the standard linear correlation approach, its use may increase the effectiveness of weather insurance contracts designed to provide protection against extreme weather events. In our study, we employ three selected Archimedean copulas to capture the left-tail dependence in the joint distribution of the farm yield and a specific weather index. A hierarchical Bayesian model is applied to obtain consistent estimates of tail dependence using relatively short time series. Our empirical results for 47 large grain-producing farms from Kazakhstan indicate that, given the choice of an appropriate weather index to signal catastrophic events, such as a severe drought, copula-based weather insurance contracts may provide significantly higher risk reductions than regression-based indemnification schemes.

Will climate change benefit or hurt Russian grain production? A statistical evidence from a panel approach

Using recent advances in statistical crop yield modelling and a unique dataset consisting of yield time series for Russian regions over the period from 1955 to 2012, the study investigates the potential impact of climate change (CC) on the productivity of the three most important grains. Holding current grain growing areas fixed, the aggregate productivity of the three grains is predicted to decrease by 6.7% in 2046–2065 and increase by 2.6% in 2081–2100 compared to 1971–2000 under the most optimistic representative emission concentration pathway (RCP). Based on the projections for the three other RCPs, the aggregate productivity of the three studied crops is assessed to decrease by 18.0, 7.9 and 26.0% in the medium term and by 31.2, 25.9 and 55.4% by the end of the century. Our results indicate that CC might have a positive effect on winter wheat, spring wheat and spring barley productivity in a number of regions in the Northern and Siberian parts of Russia. However, due to the highly damaging CC impact on grain production in the most productive regions located in the South of the country, the overall impact tends to be negative. Therefore, a shift of agricultural production to the Northern regions of the country could reduce the negative impact of CC on grain production only to a limited extent. More vigorous adaptation measures are required to maintain current grain production volumes in Russia under CC.

Confronto tra i prodotti assicurativi delle produzioni agricole e loro applicabilità nelle economie in transizione

The paper considers insurance as a potential instrument for farm income stabilization and compares several crop insurance products in terms of their applicability in a transition economy with reference to the case of Kazakhstan. The analysis is based on a qualitative evaluation as well as a quantitative assessment of selected insurance products. The qualitative analysis reviews the available literature on the topic. The quantitative assessment completes the comparison introducing the findings of a numerical analysis of farm and weather data.