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Este artículo analiza la influencia de la educación en el comportamiento ambiental de los habitantes del municipio de Sabaneta. Con datos de la Encuesta de Percepción Ciudadana de Calidad de Vida de 2018 se emplea un modelo probit para analizar los efectos de la educación considerando características sociodemográficas. Los resultados muestran comportamientos más favorables con el medio ambiente a medida que aumenta la escolaridad, aunque existen diferencias significativas entre personas: es más favorable entre menores de 55 años y habitantes rurales que entre miembros de sus grupos de control. Estos resultados son de interés para las iniciativas educativas que buscan mejorar la actitud hacia el medio ambiente.

Applying analytic approximations for computing multivariate normal cumulative distribution functions has led to a substantial improvement in the estimability of mixed multinomial probit models, both in terms of accuracy and especially in terms of computation time. This paper makes a contribution by presenting a possible way to improve the accuracy of estimating mixed multinomial probit model covariances based on the idea of parameter selection using cross-validation. Comparisons to the MACML approach indicate that the proposed parameter selection approach is able to recover covariance parameters more accurately, even when there is a moderate degree of independence between the random coefficients. The approach also estimates parameters efficiently, with standard errors tending to be smaller than those of the MACML approach, which can be observed by means of a real data case.

Background As the amount of solid waste generated by households in Ghana continues to grow, policy makers are preoccupied with finding better means of managing these solid wastes. To this end, a number of studies have been conducted on the factors that determine the choice of solid waste disposal method among households in Ghana. Notwithstanding, while financial inclusion is deemed as an effective tool for improved solid waste management, none of these studies paid attention to it. This study therefore, investigates the effect of financial inclusion on the choice of solid waste disposal method among households in Ghana. Methods The study uses data from the Ghana Living Standards Survey round 7 (GLSS7). The multinomial probit regression is used as the empirical estimation technique. Results Our results show that financial inclusion increases the likelihood of households opting for the collection method of solid waste disposal relative to burning, public dumping and indiscriminate disposal of solid waste. Conclusion Financial inclusion enables households to opt for a healthy solid waste disposal method (collection method), hence, in policy makers’ attempts to improve solid waste disposal, paying attention to financial inclusion can be a very useful strategy.

Farmers have number of options available in managing disaster risks at farm and many of them utilize these risk management tools simultaneously. However, previous studies have ignored the correlation among the risk management adoption decisions. This study, therefore, aimed at investigating factors affecting the adoption of off-farm diversification and agricultural credit to manage catastrophic risks while taking into account the contemporaneous correlation in the decisions to adopt the two risk management tools simultaneously. Bivariate and multinomial probit approaches are applied to data collected from four districts of Khyber Pakhtunkhwa Province in Pakistan. Findings revealed a strong correlation between the decisions to adopt the two risk management tools and conclude that adopting one risk management tool may induce farmers to adopt the other tool at the same time. Moreover, socioeconomic characteristics, losses due to natural disasters, farmers’ risk perceptions and their risk attitude play significant role in shaping their decisions of adopting risk management tools.

Purpose Youth unemployment is one of the major problems that the economic systems face. Given this issue, the purpose of this paper is to assess whether school-to-work transition is easier for individuals with secondary vocational education compared to general secondary education. The authors want to explore which vocational systems across Europe produce better effects. Design/methodology/approach The authors use data from a module on “Entry of young people into the labour market” from the 2009 and 2014 European Labour Survey and they estimate multinomial probit models, allowing for violation of the irrelevance of the alternative assumption. Findings The authors find that in countries with the dual vocational system, vocational education improves employability both in the short and medium run, whereas in countries with a school-based vocational system, results are mixed and, only in some cases, the effect of vocational studies is significantly positive. Research limitations/implications Sample size for short-run analysis is a bit small in a few countries (Austria and Germany). Moreover, even if the authors have reason to believe that the methods adopted are mitigating the omitted heterogeneity issues and robustness checks are run on these aspects, these issues cannot be fully excluded. Practical implications The authors provide policy implications, showing that dual vocational systems can improve school-to-work transitions and that vocational structure is particularly effective in this case. Social implications The authors provide information on which education model may offer better chance in terms of labour outcomes. Originality/value Given the relevance of youth unemployment, the authors provide valuable information on how to mitigate this problem. The use of cross-country comparisons offers great insights on which vocational systems appear to be well-suited to enhance employability.

Commute trips account for a large portion of travel demand in peak hours and significantly influence the operation of urban transportation systems. In this paper, we apply a fully flexible multinomial probit (MNP) model for the analysis of commute mode choice behavior, and compare this MNP model with more traditional discrete choice models, including the multinomial logit (MNL), the cross-nested logit (CNL), the heteroscedastic independent MNP (HI-MNP), and the homoscedastic non-independent MNP (HONI-MNP). The two-variate bivariate screening (TVBS) approach, a recently developed analytical evaluation for the multivariate normal cumulative distribution (MVNCD) function, is employed. The sample for analysis is drawn from a web-based travel survey conducted in Shanghai. Overall, from a data fit perspective at, both the disaggregate and aggregate levels, the MNP clearly outperforms all the other four models, underscoring the importance of considering both heteroscedasticity as well as correlated error terms when estimating mode choice models. Policy implications are also examined and discussed.

The seaweed market in France is expanding. French consumers were surveyed regarding their perceptions and purchase intentions of seaweed products. Based on the survey results, we explore the determinants of seaweed consumption and preferences for this new, sustainable food in France. The survey database includes the results of over 495 in-person interviews. Two types of consumers are identified. Some consumers maintain a traditional attitude toward seaweed consumption, while others are willing to consume more innovative products. Attitude strongly influences seaweed consumption. The acceptance of claims (natural, eco-label, health, and fair-trade) is studied, using a multinomial probit model with random intercept. The purchase location is an important factor in the choice of product claims, and there is more heterogeneity at the individual level than the collective level. These results are important to understand the scope for increased seaweed consumption in order to help improve the sustainability of food consumption for future generations.

While Saudi coffee (SC) holds deep cultural and historical significance within the Kingdom, rising global exposure and modern coffee shops are driving domestic consumers toward other coffee (OC) varieties. In this context, this study has two objectives: First, to segment the coffee market and analyze how consumer characteristics vary among its components, and second, to estimate the coffee expenditure function. The study data were collected through our custom online survey. We employed a multinomial probit model to estimate choices within the identified market segments of individuals consuming: (1) SC, (2) OC varieties, such as American or Turkish coffee and (3) Both Saudi and OC types. Additionally, we applied an ordered probit model to estimate coffee-related expenditure. The results offer valuable insights for marketing and policy considerations relevant to the concurrent government’s efforts as consumers are increasing their consumption of OC types.

Applying analytic approximations for computing multivariate normal cumulative distribution functions has led to a substantial improvement in the estimability of mixed multinomial probit models, both in terms of accuracy and especially in terms of computation time. This paper makes a contribution by presenting a possible way to improve the accuracy of estimating mixed multinomial probit model covariances based on the idea of parameter selection using cross-validation. Comparisons to the MACML approach indicate that the proposed parameter selection approach is able to recover covariance parameters more accurately, even when there is a moderate degree of independence between the random coefficients. The approach also estimates parameters efficiently, with standard errors tending to be smaller than those of the MACML approach, which can be observed by means of a real data case.