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We show how to quickly estimate spatial probit models for large data sets using maximum likelihood. Like Beron and Vijverberg (2004), we use the GHK (Geweke-Hajivassiliou-Keane) algorithm to perform maximum simulated likelihood estimation. However, using the GHK for large sample sizes has been viewed as extremely difficult (Wang, Iglesias, & Wooldridge, 2013). Nonetheless, for sparse covariance and precision matrices often encountered in spatial settings, the GHK can be applied to very large sample sizes as its operation counts and memory requirements increase almost linearly with n when using sparse matrix techniques.

The purpose of this paper is to examine the adoption of Islamic finance products (murabaha, musharakah, mudarabah, salam, ijara, istisna and Qard Hassan) by small and medium-sized enterprises (SMEs) in Cameroon, a non-Islamic Sub-Saharan African country.

It used primary data collected from a cross-section of 1,358 SMEs in eight regions of Cameroon using self-administered structured questionnaires. To facilitate the analyses and interpretation, these products are grouped into four groups based on certain characteristics. A multivariate probit model is estimated to take into account the interaction between these different Islamic finance products.

This study revealed that the desire to comply with Sharia law, awareness, attitude and intention were critical determinants of the decision to adopt Islamic finance products by Cameroonian SMEs. The least influential factors were perceived behavioral control, subjective norms, enterprise characteristics (size, age and location) and socio-demographic characteristics of the entrepreneur (gender, age and marital status). The extension of the multivariate approach permitted us to compute for predicted probabilities which revealed that there exists a synergy effect between the different Islamic finance products. That is, Cameroonian SMEs combine different Islamic finance products at the same time based on their needs. This is especially the case between the partnership-based products (musharakah and mudarabah) and manufacture/rent products (istisna and ijara).

Policymakers are encouraged to develop stakeholder-oriented strategies to promote effective consumer education in Islamic finance products which will boost awareness. Also, Islamic finance institutions should endeavor to develop innovative financial products that are Sharia-compliant and economically beneficial to the individual and business needs of SMEs. Moreover, policymakers and management of Islamic finance institutions should ensure the putting in place of effective governance structures to guide Islamic finance operations. Finally, policymakers should endeavor to take into account the possible synergy between the different Islamic finance products in their quest to develop this activity.

To the best of the authors’ knowledge, this is the first study that analyses the adoption of different Islamic finance products while taking into account the possible synergy that exists between these products.

This study aims to determine whether consumers are willing to pay a premium for locally produced hard apple cider and examine the factors influencing this premium. This study examines the influence of hard apple cider attributes and consumer characteristics on consumer preferences for local hard apple cider.

Data from a 2019 survey of 875 Tennessee consumers regarding their preferences for a local hard apple cider were obtained. Probit estimates were used to calculate the premium consumers were willing to pay for a locally made hard apple cider and factors influencing this premium. A multivariate probit was used to ascertain factors influencing the importance of attributes (e.g. heirloom apples, sweetness/dryness, sparking/still and no preservatives added) on local hard apple cider preference.

Consumers would pay a $3.22 premium for local hard apple cider compared with a $6.99 reference product. Local foods preferences, urbanization, weekly purchases of other alcoholic beverages and shopping venues influenced premium amounts. Other important attributes were sweetness/dryness and no preservatives. Influence of consumer demographics suggests targeted marketing of local ciders could be successful.

Few studies examine consumer preferences for hard apple ciders. This study represents a cross-sectional analysis of the premium consumers would pay for local hard apple ciders and the importance of other hard apple cider attributes.

Enabling decision-makers in Israel to better assess the prospects of government policies aimed at changing inter-generation income distribution for the benefit of the retirees.

Based on a comprehensive data set, the paper utilizes multivariate ordered-probit regression for empirical investigation of the motivations for support between parents and children in Israel.

The main finding is that child-parent support in Israel is usually driven by a combination of exchange and altruistic motives, rather than altruism alone.

Child-parent support will not reduce the impact of governmental policies aimed at redistributing income among different generations. If the Government of Israel raises the income level of its citizens aged 65 and over, the improvement in this population's condition will most probably be bigger than that caused directly by the amount the government has added to their income.

Empirical evaluation of the motivations for support given by children to their retired parents in Israel. Israel is a multicultural, immigrant country, home to people originating from all over the world, which provides an interesting cross-cultural perspective. In addition, the underlying database used in this study includes much more information than most databases utilized by earlier studies.

This paper formulates and analyzes Bayesian model variants for the analysis of systems of spatial panel data with binary-dependent variables. The paper focuses on cases where latent variables of cross-sectional units in an equation of the system contemporaneously depend on the values of the same and, eventually, other latent variables of other cross-sectional units. Moreover, the paper discusses cases where time-invariant effects are exogenous versus endogenous. Such models may have numerous applications in industrial economics, public economics, or international economics. The paper illustrates that the performance of Bayesian estimation methods for such models is supportive of their use with even relatively small panel data sets.

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.

Drought-related climate risk and access to credit are among the major risks to agricultural productivity for smallholder farmers in Kenya. Farmers are usually credit-constrained due to either involuntary quantity rationing or voluntary risk rationing. By exploiting randomized distribution of weather risk-contingent credit (RCC) and traditional credit, the authors estimate the causal effect of bundling weather index insurance to credit on uptake of agricultural credits among rural smallholders in Eastern Kenya. Further, the authors assess farmers' credit rationing, its determinants and effects on credit uptake.

The study design was a randomized controlled trial (RCT) conducted in Machakos County, Kenya. 1,170 sample households were randomly assigned to one of three research groups, namely control, RCC and traditional credit. This paper is based on baseline household survey data and the first phase of loan implementation data.

The authors find that 48% of the households were price-rationed, 41% were risk-rationed and 11% were quantity-rationed. The average credit uptake rate was 33% with the uptake of bundled credit being significantly higher than that of traditional credit. Risk rationing seems to influence the credit uptake negatively, whereas premium subsidies do not have any significant association with credit uptake. Among the socio-economic variables, training attendance, crop production being the main household head occupation, expenditure on food, maize labour requirement, hired labour, livestock revenue and access to credit are found to influence the credit uptake positively, whereas the expenditure on non-food items is negatively related with credit uptake.

The study findings provide important insights on the factors of credit demand. Empirical results suggest that risk rationing is pervasive and discourages farmers to take up credit. The study results also imply that credit demand is inelastic although relatively small sample size for RCC premium subsidy groups may be a limiting factor to the authors’ estimation.

By implementing a multi-arm RCT, the authors estimate the factors affecting the uptake of insurance bundled agricultural credits along with eliciting credit rationing among rural smallholders in Eastern Kenya. This paper provides key empirical findings on the uptake of RCC and the effect of credit rationing on uptake of agricultural credits, a field which has been majorly theoretical.

The purpose of this paper is to examine whether people who engage in religious activities are more generous in terms of both religious and secular giving.

Bivariate probit (BVP) and bivariate tobit (BVT) analyses show that religious people have a greater propensity to give and higher levels of giving to both religious and secular charitable organizations. The bivariate systems permit a test of the correlation across the different giving decisions, and the correlation between religious and secular giving is found to be highly significant.

Religiosity positively influences both religious and secular donations. After controlling for this correlation, the impacts of religiosity on religious and secular giving are more efficient estimates but smaller than expected.

As a result of these methodological shortcomings, the causal relationship between religiosity and charitable giving is far from clear. To overcome those problems, this study uses BVP and BVT models to control for the potential correlation between religious giving and secular giving by the same individual and then draws appropriate interpretations. This study adds a firmer theoretical foundation to the existing literature.

The main purpose of this study was to assess constraints and determinants of pineapple farmers' choice of certification schemes in Ghana.

A multistage sampling method was used to solicit data from 345 pineapple farmers from Eastern and Central regions of Ghana. Analytical techniques including descriptive statistics, four-point Likert scale index and multinomial logistic regression model (MNL) were used to analyze the data.

The four-point scale index shows that high renewal fee for certification schemes is the most important constraint facing certified farmers before high labor cost of production. The MNL model shows that both off-farm income and age negatively influenced farmers' choice of GlobalG.A.P scheme. However, household size had significant positive influence on farmers' choice of GlobalG.A.P and Organic schemes. Likewise, formal education had significant positive relationship with the choice of Fairtrade and Organic certification schemes while farming experience positively influenced organic scheme choice. On the other hand, premium price and extension services positively influenced the likelihood of choosing all the three certification schemes. Lastly, regional dummy only negatively influences the choice of organic certification schemes.

This study contributes to the literature on certification schemes adopted by smallholder by analyzing the determinants and constraints of choice of scheme(s).

The study brings to bear the issues confronting smallholder pineapple farmers in the employment of certification schemes in developing countries, specifically Ghana.

In this article we propose a multivariate dynamic probit model. Our model can be viewed as a nonlinear VAR model for the latent variables associated with correlated binary time-series data. To estimate it, we implement an exact maximum likelihood approach, hence providing a solution to the problem generally encountered in the formulation of multivariate probit models. Our framework allows us to study the predictive relationships among the binary processes under analysis. Finally, an empirical study of three financial crises is conducted.