Search results

The purpose of this study is to explore the potential and challenges of biogas utilization as an alternative and sustainable energy source in the Gurage zone of Southern Ethiopia, where traditional energy sources such as firewood and charcoal are widely used.

The study adopts a mixed-methods approach to collect and analyze data from different sources and perspectives. The research collects quantitative data from structured interviews with 200 rural households who use biogas or other energy sources, and qualitative data from key informant interviews and focus group discussions with biogas experts, local authorities and community leaders. Socioeconomic analysis is conducted to assess the importance of biogas in terms of income, expenditure, health and environmental benefits, and a multivariate probit model is used to identify the factors influencing biogas energy adoption among rural households.

The findings indicate that biogas users are more likely to substitute traditional energy sources with biogas for cooking, lighting and heating purposes. The model reveals that age, sex, education level, land size and livestock quantity influence biogas energy adoption, whereas income, distance to market and access to credit do not have a significant effect. The findings also show that biogas users have higher income, lower expenditure, better health and lower greenhouse gas emissions than nonusers.

The study concludes that the socioeconomic impact of biogas varies among households based on location and lifestyle. The study also highlights the need for further research on the technical, institutional and behavioral aspects of biogas utilization in different contexts.

To address the challenges faced by biogas users and their energy choices, such as lack of awareness, maintenance, quality control and affordability, the study suggests exploring biogas energy to meet the diverse needs of cattle owners in different regions. The study also recommends enhancing the capacity of local stakeholders, promoting public–private partnerships, and developing supportive policies and regulations for biogas development in Ethiopia.

The study implies that biogas utilization can contribute to social development by improving the living standards, health status and gender equality of rural households. The study also suggests that biogas utilization can foster social cohesion and empowerment by creating opportunities for collective action, knowledge sharing and income generation among biogas users and their communities.

The study provides a comprehensive and empirical analysis of the socioeconomic landscape of biogas utilization and the determinants of energy choice in the Gurage zone of Southern Ethiopia. The study also offers valuable insights and recommendations for policymakers, practitioners, researchers and other stakeholders involved in biogas development in Ethiopia and other developing countries.

The purpose of this paper is to analyze the determinants of agricultural insurance adoption in Bulgaria, using a purpose-built survey of 224 farmers interviewed in 2011. The insurance decision is analyzed conjointly with other risk management decisions on the farm such as having contracts with retailers or processors, diversifying farm activities and using irrigation.

The agricultural insurance sector in Bulgaria is presented in the broader context of the transition to a market-oriented economy and integration of Bulgarian agriculture into the EU Common Agricultural Policy. The recent developments on the determinants of farm insurance adoption in the agricultural economics and finance literature are discussed. A multivariate probit model is used in order to determine the factors explaining the adoption or non-adoption of various risk management tools by the surveyed farmers, including farm insurance.

The authors find that farmers with diversified activities, using irrigation or having contracts with retailers or processors, are more likely to adopt insurance, after controlling for farms and farmers’ structural characteristics. Additionally, the authors find that the main characteristics distinguishing farmers who purchase agricultural insurance from non-users are farm size and farm location. The existence of strong regional effect suggests the importance of adapting the insurance products to the different regional contexts in Bulgaria.

This paper contributes to the (limited) literature on agricultural insurance adoption in transition countries, currently shifting from a system where compensation against natural hazards tended to come from a State damage mitigation fund, inherited from the centrally planned governments to private and voluntary agricultural insurance. This research provides a unique data source on the Bulgarian case study.

The objectives of this study are to offer cash based funds flow components as an alternative to financial ratios for classifying the financial performance of companies; to test empirically the ability of funds flow components to distinguish between failed and nonfailed companies with special emphasis on working capital components; to analyse the empirical results and make recommendations for future study.

This chapter reviews graphical modeling techniques for estimating large covariance matrices and their inverse. The chapter provides a selective survey of different models and estimators proposed by the graphical modeling literature and offers some practical examples where these methods could be applied in the area of health economics.

This study assesses the extent to which integrated extension services contribute to the adoption of climate-smart agriculture (CSA) innovations within the cotton value chain in Burkina Faso.

To address the research question, a probit multivariate econometric model with sample selection is utilized. The model is applied to a random sample of farmers (n = 510), and the endogeneity is addressed through a control function approach.

The study highlights the central role of value chains, particularly in the cotton sector, in overcoming resource scarcity through integrated extension services. Findings show that smallholder farmers who benefit from sound extension services are more willing to adopt and diversify CSA technologies. These include improved seeds, conservation techniques, adapted planting dates and mechanization. This study confirms the synergistic nature of these technologies and emphasizes that effective climate risk mitigation depends on the combined adoption of CSA technologies.

The use of cross-sectional data limits the analysis of long-term farmer behavior, and due to data limitations, the focus was primarily on the contributions of cotton companies and farmers to climate risk mitigation. Future research using panel data across the value chain could provide a more robust insights for policy decision-making.

The study contributes to the existing body of knowledge by emphasizing the crucial role of integrated extension services within the cotton value chain in developing countries. This highlights the critical benefits for farmers and emphasizes the need to diversify modern technologies to effectively combat climate change and its variability in agriculture.

The purpose of this paper is to draw on recent developments in the open innovation literature to explore whether the openness of SMEs to the four categories of external sources of information (ESI) is complementary, substitute or independent, while assessing the determinants of SMEs’ openness to these ESI.

This research is based on data from a survey of 451 manufacturing SMEs in the province of Québec, Canada. Data have been elaborated through a multivariate probit model to empirically show that SMEs are considered to be simultaneously open to different ESI. The results of this study show significant heterogeneity in the determinants of SMEs’ openness to these ESI.

The study found that the SMEs’ openness to different ESI seems to be complementary rather than substitute; and not all variables included in the model explain the SMEs’ openness to the different ESI.

The paper provides practical implications for managers and policy makers including the SMEs’ managers’ role to recognize the consolidation of different ESI jointly instead of separately. Furthermore, managers and policy makers should attempt to provide a fair context to SMEs to manage their openness ecosystem.

This study is virtually the first to investigate both the complementarity and the determinants of SMEs’ openness to different ESI using a sophisticated econometric model.

Simulation-based methods and simulation-assisted estimators have greatly increased the reach of empirical applications in econometrics. The received literature includes a thick layer of theoretical studies, including landmark works by Gourieroux and Monfort (1996), McFadden and Ruud (1994), and Train (2003), and hundreds of applications. An early and still influential application of the method is Berry, Levinsohn, and Pakes's (1995) (BLP) application to the U.S. automobile market in which a market equilibrium model is cleared of latent heterogeneity by integrating the heterogeneity out of the moments in a GMM setting. BLP's methodology is a baseline technique for studying market equilibrium in empirical industrial organization. Contemporary applications involving multilayered models of heterogeneity in individual behavior such as that in Riphahn, Wambach, and Million's (2003) study of moral hazard in health insurance are also common. Computation of multivariate probabilities by using simulation methods is now a standard technique in estimating discrete choice models. The mixed logit model for modeling preferences (McFadden & Train, 2000) is now the leading edge of research in multinomial choice modeling. Finally, perhaps the most prominent application in the entire arena of simulation-based estimation is the current generation of Bayesian econometrics based on Markov Chain Monte Carlo (MCMC) methods. In this area, heretofore intractable estimators of posterior means are routinely estimated with the assistance of simulation and the Gibbs sampler.

The agricultural sector in the USA has experienced significant structural changes. For accommodating farm business, households have diversified their operations adopting various strategies—agricultural, structural, environmental, and income strategies. The purpose of this study is to analyze the factors influencing farmer’s diversification strategies while taking into account the simultaneous decision-making process.

This study uses a nation-wide farm household data from the US. The diversification decisions are analyzed using multivariate probit regressions.

The study suggests that agricultural, structural, environmental, and income diversification strategies are interlinked. Specifically, results indicate that, on one hand, environmental and income diversification strategies are positively interlinked. On the other hand, agricultural and structural diversification strategies are positively interlinked. Additionally, the factors representing location, farm, and farmer characteristics, farm type, and financial condition of the farm are major determinants in the choice of farm diversification strategies.

In this paper, diversification activities are broadly classified under four strategies: agricultural, structural, environmental, and income. Depending on the context and country, the definition and strategy set may need revision.

Strong complementary between diversification strategies suggests that studies analyzing farm household decisions and strategies need to account for the simultaneous decision-making process. As decisions are interlinked, separately analyzing one specific strategy may lead to biased estimates. Farm business households need to develop multiple skills and flexible capacities to tackle farming-related issues, including structural changes, risk management, and income enhancing activities. Improving employment opportunities for the rural farming population can stimulate structural diversification.

This paper contributes to limited literature about diversification by analyzing factors influencing different diversification decisions and finds interlinkage between decisions.

This chapter deals with the estimation of the effect of exchange rate flexibility on financial account openness. The purpose of our analysis is twofold: On the one hand, we try to quantify the differences in the estimated parameters when exchange rate flexibility is treated as an exogenous regressor. On the other hand, we try to identify how two different degrees of exchange rate flexibility (intermediate vs floating regimes) affect the propensity of opening the financial account. We argue that a simultaneous determination of exchange rate and financial account policies must be acknowledged in order to obtain reliable estimates of their interaction and determinants. Using a panel data set of advanced countries and emerging markets, a trivariate probit model is estimated via a maximum simulated likelihood approach. In line with the monetary policy trilemma, our results show that countries switching from an intermediate regime to a floating arrangement are more likely to remove capital controls. In addition, the estimated coefficients exhibit important differences when exchange rate flexibility is treated as an exogenous regressor relative to the case when it is treated as endogenous.

This paper analyzes county-level firm births across the United States using a spatial count model that permits spatial dependence, cross-correlation among different industry types, and over-dispersion commonly found in empirical count data. Results confirm the presence of spatial autocorrelation (which can arise from agglomeration effects and missing variables), industry-specific over-dispersion, and positive, significant cross-correlations. After controlling for existing-firm counts in 2008 (as an exposure term), parameter estimates and inference suggest that a younger work force and/or clientele (as quantified using each county’s median-age values) is associated with more firm births (in 2009). Higher population densities is associated with more new basic-sector firms, while reducing retail-firm starts. The modeling framework demonstrated here can be adopted for a variety of settings, harnessing very local, detailed data to evaluate the effectiveness of investments and policies, in terms of generating business establishments and promoting economic gains.