Bivariate Probit Model Research Articles

Does agricultural cooperative membership influence off‐farm work decisions of farm couples?

AbstractMembership in agricultural cooperatives may influence intra‐household decisions regarding the division of household labor. However, the linkages between cooperative membership and labor allocation remain unexplored. To fill this gap, we examine the impact of cooperative membership on off‐farm work decisions of couples engaged in farming, using data collected from 595 banana farmers in China. The recursive bivariate probit model and endogenous‐treatment Poisson regression model are employed to address the self‐selection bias inherent in cooperative membership. The results show that cooperative membership increases the probability of participating in off‐farm work by 38% for husbands and 31% for wives. Having large households reduces the probability of husbands but increases that of wives working off‐farm. Cooperative membership is also associated with more time spent on off‐farm work and higher earnings for both husbands and wives. Our findings point to the potential of agricultural cooperatives to increase farm couples’ off‐farm employment, thus increasing household income and quality of life.

Testing identifying assumptions in bivariate probit models

SummaryThis paper considers the bivariate probit model's identifying assumptions: linear index specification, joint normality of errors, instrument exogeneity, and relevance. First, we develop sharp testable equalities that detect all possible observable violations of the assumptions. Second, we propose an easy‐to‐implement testing procedure for the model's validity using existing inference methods for intersection bounds. The test achieves correct empirical size and performs well in detecting violations of the conditions in simulations. Finally, we provide a road map on what to do when the bivariate probit model is rejected, including novel bounds for the average treatment effect that relax the normality assumption.

Receiving or not deemed necessary healthcare services

BackgroundAvoiding deemed necessary healthcare needs may worsen prognosis and treatment options, and damage people’s ability to perform their roles in society. Our study investigates why people avoid healthcare services in an upper-middle-income country, Türkiye.MethodsWe apply TurkStat’s 2012 Health Survey Data that includes a comprehensive health and social-demographic information of 28,055 survey participants who were 15 + aged. We use bivariate probit model to analyze the avoidance behavior in inpatient level in accordance with outpatient level because of the observed significant correlation between people’s avoidance behavior under tertiary and lower level health care.ResultsThe findings show that 2.6% of 15 + aged population avoided deemed necessary hospital services. Furthermore, we found that high cost (31%), organizational factors (21%) and fear (12%) are prominent reasons of avoiding tertiary care. Thereafter, in our bivariate probit model findings, we figure out that being covered by social security schemes decreases the probability of avoiding both outpatient and inpatient health services by 6.9%. Moreover, being female, living in rural area, having lower income increase the chance of being avoider in both stages of healthcare.ConclusionWe conclude that social inequalities are the main underlying determinants of the avoiding behavior.

SNAP Participation and Emergency Department Use.

To examine whether Supplemental Nutrition Assistance Program (SNAP) participation is associated with emergency department use among low-income children and whether any such association is mediated by household food hardship and child health status and/or moderated by special health care needs (SHCN) status. We hypothesized SNAP to be associated with reduced likelihoods of emergency department use, with greater effect sizes for children with SHCN and mediation by food hardship and health status. In this secondary analysis, we estimated a bivariate probit model (with state-level SNAP administrative policies as instruments) within a structural equation modeling framework using pooled cross-sectional samples of children in low-income households from the 2016 to 2019 iterations of the National Survey of Children's Health (n = 24 990). Among children with and without SHCN, respectively, SNAP was associated with: 22.0 percentage points (pp) (95% confidence interval [CI] 12.2-31.8pp) and 17.1pp (95% CI 7.2-27.0pp) reductions in the likelihood of household food hardship exposure (4.8pp difference-in-differences, 95% CI 2.3-7.4pp), 9.7pp (95% CI 3.9-15.5pp) and 7.9pp (95% CI 2.2-13.6) increases in the likelihood of excellent health status (1.9pp difference-in-differences, 95% CI 0.7-3.0pp), and 7.7pp (95% CI 2.9-12.5pp) and 4.3pp (95% CI 1.0-7.6pp) reductions in the likelihood of emergency department use (3.4pp difference-in-differences, 95% CI 1.8-5.1pp). We found SNAP participation was associated with lower likelihoods of emergency department use, that better food hardship and health statuses mediated this association, and that effect sizes were larger among children with SHCN. Food hardship relief may improve outcomes for vulnerable children and the health systems serving them.

Combined Agronomic and Economic Modeling in Farmers’ Determinants of Soil Fertility Management Practices: Case Study from the Semi-Arid Ethiopian Rift Valley

Studies on smallholders’ determinants of soil fertility management practices have become increasingly important for boosting agricultural productivity, particularly in cereal-based farming systems in sub-Saharan Africa. In these parts of Africa, farmers preferentially apply organic and inorganic fertilizers to the fields close to their housing compounds (infields). In addition, they prefer to use more fertilizers to grow cash crops rather than food crops. Many researchers suggested that farmers use limited nutrient resources in their hot-spot fields, e.g., infields and/or cash-crop fields. Recent econometric case studies have suggested using a model that considers a complementarity or substitutability between organic and inorganic fertilizers use. This study employed bivariate probit models to analyze 524 plot data collected from the northern semi-arid Ethiopian Rift Valley. A K-means cluster analysis divided the sample data into two subdatasets, representing food-crop-based cropping system (FCCS) and cash-crop-based cropping system (CCCS). Based on narrative inquiry interviews and the cluster analysis, this study considered reflecting the structure of the local farming system in modeling: a data segmentation approach and dummy variable method. Bivariate and univariate probit analyses showed that, first, the farmers’ determinants differed between the FCCS and CCCS. Second, the correlation between organic and inorganic fertilizers use was independent. Farmers’ determinants were primarily governed by the biophysical features of the plots (commuting distance to the plot, plot size, type of the plot, etc.), which narrowed down the feasible soil fertility management options in the plot to one or two; farmers’ more specific decisions on soil fertility management practices depend on individual farmers’ socioeconomic endowments (farm holding, livestock ownership, etc.).

On dose-response modeling for evaluation of drugs combinations

We introduce a framework of dose-response modeling for the evaluation of drug combinations. We focus on adaptive techniques in dose-finding studies when several endpoints can be observed simultaneously on each subject. This framework may fit well for clinical trials and we discuss its algorithmization. The generalized bivariate probit model is discussed in particular. Necessary conditions for plausible behavior of drug combinations are given from the theoretical stochastic perspective.

University-supported job search methods and educational mismatch in bachelor's and master's graduates

PurposeThis paper addresses the relevance of job search methods and strategies in determining vertical mismatch and the risk of underusing skills or knowledge in first jobs amongst graduates from bachelor's and master's programmes in Spain. Support from universities (via internships and career services) is compared to support from public institutions and informal strategies.Design/methodology/approachThe authors use the 2019 University Graduate Job Placement Survey. The dependent variables are estimated with a bivariate probit model with sample selection on a subsample of graduates who were not working at graduation.FindingsInternships and university career employment offices significantly improve the quality of first job matches. Job banks and public examinations also contribute to finding well-matched first positions, while for public employment services, results are mixed. When the job search is not supported by institutions, graduates generally do worse finding their first jobs, particularly when temporary employment agencies are involved. There are also large differences in mismatch risks across fields of study.Practical implicationsIf more graduates found their first jobs through internships and university job placement services, educational mismatch rates would decrease substantially. Further collaboration between universities and employers for the provision of high-quality internships may foster their conversion into regular, well-matched jobs. Industrial policies addressed to knowledge-based economic activities would enhance the creation of highly skilled positions. Further orientation towards STEM degrees is required to improve imbalances between supply and demand for graduate labour in Spain.Originality/valueEvidence about education mismatch among master's degree graduates is very scarce. This paper compares them to bachelor's degree graduates. It addresses two complementary types of education mismatch and takes into account potential self-selection into post-graduation job search.

Gender gap in travel behaviour and public opinion on proposed policy measures: Evidence from India

AbstractEmploying primary survey data collected from Jaipur city in India, this work attempts to evaluate inconsistencies in travel behaviour based on gender. It also intends to discuss the public opinion on a few proposed policy changes which can aid in bridging the established gender gap. Stratified random sampling approach is used to gather data on travel pattern measures and socioeconomic attributes. Descriptive statistics complemented with bivariate probit model and seemingly unrelated bivariate probit model is applied on the data acquired. The obtained results confirm the existence of a gender gap in all observed measures of travel behaviour. Compared to men, women travel shorter distances, use more of non‐motorised modes of transport, have lower frequency of travelling, and travel majorly for purposes other than work. Results of the study also highlight how a majority of the respondents are in favour of policy changes aimed at narrowing the observed gender disparities. The analysis demands infrastructural development of non‐motorised transportation and public transportation in the city in such a way which is both efficient and secured, so as to neither obstruct the objective of empowerment nor of sustainability.

Being poor and being NEET in Europe: Are these two sides of the same coin?

The online version contains supplementary material available at 10.1007/s10888-022-09561-7.

Car versus motorcycle ride-hailing applications: User behaviors and adoption factors in Bangkok, Thailand

Ride-hailing applications (RHA) have surged in popularity in Southeast Asia, yet research comparing car and motorcycle RHA user characteristics, trip behaviors, and factors influencing adoption remain limited. To fill this gap, this study investigated motorcycle RHA use individually and in conjunction with use of car RHA by using the bivariate probit regression to analyze traveler intercept survey data from Bangkok, Thailand. Our findings revealed that car RHA has a higher market penetration rate than motorcycle RHA but that motorcycle RHA is used more frequently. Motorcycle RHA was adopted and used more frequently by individuals who have access to a private car and reside in areas with high urban rail accessibility. Notably, motorcycle RHA was used to connect to urban rail significantly more than car RHA, illustrating the need for policies that facilitate the connective role of motorcycle RHA in accessing public transportation. Overall, our results support the synergy hypothesis between car and motorcycle RHA based on the highly significant correlation between the two modes in the bivariate probit models.

Spatial distribution of stunting and wasting in 6-59 months children in Nepal: analysis using a Bayesian distributional bivariate probit model.

The combined burden of stunting and wasting in children under five years is a serious public health concern. The present study aimed to estimate the joint burden of stunting and wasting among children aged 6-59 months and explore its spatial variation across Nepal. The 2016 Nepal Demographic and Health Survey data was used to study acute and chronic childhood malnutrition. A Bayesian distributional bivariate probit geoadditive model was designed to study the linear association and geographical variation of stunting and wasting among 6-59 months, children. Child-related factors such as low birth weight, fever in the last 2 weeks preceding the survey and fourth or greater birth order were associated with a higher likelihood of stunting. The likelihood of a child being stunted was significantly less in the wealthiest households, having improved toilet facilities, and if mothers were overweight. Children from severely food insecure households were significantly more likely, and children from poorer households were significantly less likely to suffer both acute and chronic malnutrition simultaneously. Results from spatial effect showed that children from Lumbini and Karnali had a higher burden of stunting, and the likelihood that achild would have been wasted was significantly higher in Madhesh and Province 1. Immediate nutritional efforts are vital in low-income and severely food insecure households to lessen the risk of stunting and wasting in under children. Disproportionate geographic variations in stunting and wasting warrant sub-regional-specific nutrition intervention to achieve nutrition targets and reduce the burden of childhood malnutrition across the country.

Race Differentials in the Credit Market Experiences of Small Business Owners

AbstractSmall businesses employ more than half of the entire workforce, account for more than sixty percent of new jobs created in the United States, and are responsible for about fifty percent of private domestic gross product. It is noteworthy, however, that small business owners in credit markets, in particular minority owners, have difficulty in securing sources of capital for their business operation. The literature on credit market discrimination shows consistent results that can be interpreted as evidence that minority owners are discriminated against compared to their counterparts (i.e., White owners) in obtaining loans, which may be caused by lenders’ discrimination, although such behavior is prohibited under current fair-lending laws. This paper uses pooled cross-sectional data from the Survey of Small Business Finances (1993, 1998, and 2003) and a bivariate probit model based on James J. Heckman’s approach to deal with sample selection bias for those choosing to apply for loans. Those who didn’t apply for loans have been ignored in analyses of credit markets for small business owners. This paper adds to the small business lending market literature by 1) combining cross sectional data from the Survey of Small Business Finances (SSBF) for 1993, 1998, and 2003 to get more precise estimates and test statistics with more power; 2) conducting regression analyses with different model specifications to show the robustness of the empirical results; and 3) dealing directly with problems of sample selection based on Heckman’s approach with particular attention to the assumptions required to justify the identification of the effect (i.e., exclusion restrictions).The analysis confirms previous results, suggesting that minority owners are discriminated against in credit markets. These conclusions are supported in a variety of model specifications.

The role of time preferences in contract breach: Evidence from Chinese poultry farmers participating in contract farming

Farmers’ contract breach behavior is cited as one of the major stumbling blocks in the sustainable expansion of contract farming in many developing countries. This paper examines farmers’ contract breach decisions from the perspective of time preferences. The empirical analysis is based on a household survey and economic field experiments of poultry households participating in contract farming conducted in Jiangsu Province, China. A discounted utility model and a maximum likelihood technique are applied to estimate farmers’ time preferences and the effect of time preferences on contract breach in the production and sales phases are explored with a bivariate probit model. The results show that, on average, the poultry farmers in the sample are generally present biased and impatient regarding future utility. The regression results show that farmers with a higher preference for the present and a higher discount rate are more likely to breach contracts, and time preferences play a greater role in the production phase than in the sales phase. When considering heterogeneity, specific investments and transaction costs promote contract stability only for farmers with a low degree of impatience. Moreover, compared with large-scale farmers, small-scale farmers’ contract breach decisions are more significantly affected by their time preferences. These results have implications for contract stability policies and other issues that are impacted by the linking of behavioral preferences to agricultural decisions.

Live and digital engagement with the visual arts.

The cluster of innovations brought about by information and communication technology (ICT) is dramatically changing the ways in which the visual arts can be produced and consumed. By using the USA 2012 Survey of Public Participation in the Arts, we explore visual arts consumption through both onsite attendance at museums and electronic and digital media. To disentangle the complexity of the relationship of different forms of museums attendance, both a multinomial logit and a recursive bivariate probit model are estimated to obtain direct and indirect effects of the alternative forms of participation. Results demonstrate that there are no age consumer differences in the form they consume visual arts. Noticeable differences concern race, gender, families with children attending arts school, and type of occupation. In addition, results show that there is a trade-off between online and onsite visits. Visiting museums and art galleries have a positive correlation with the digital access to visual arts, both through handheld and mobile devices and via the internet, whilst the same correlation is not found for internet access on museum attendance. This means that for many consumers, online attendance is the only way to overcome time constraints and other costs involved in an onsite visit.

A Bivariate Probit Model of Attitudes Toward the Preferential Hiring and Promotion of Women and Black People

A Bivariate Probit Model of Attitudes Toward the Preferential Hiring and Promotion of Women and Black People

The Importance of Separating the Probability of Committing and Detecting Misstatements in the Restatement Setting

This study demonstrates the importance of separating the probabilities of misstatement occurrence and detection when examining financial statement restatements. Despite the many benefits of examining the probability of restatements using traditional logistic models, interpretations of these models are clouded by partial observability—only subsequently detected misstatements are observable. We propose addressing this often overlooked issue by implementing a bivariate probit model with partial observability. We demonstrate the importance of separating these latent probabilities by re-examining three prior restatement studies and show the importance of separating the occurrence and detection probabilities. Our evidence suggests that future studies interested in restatements as a measure of accounting quality should consider implementing bivariate probit models as one way to address the partial observability inherent in this setting. This paper was accepted by Brian Bushee, accounting. Funding: B. P. Miller gratefully acknowledges financial support from the Sam Frumer Professorship. Supplemental Material: Data and the internet appendix are available at https://doi.org/10.1287/mnsc.2022.4627 .

Organic soil amendments and food security: Evidence from Cameroon

AbstractFood insecurity remains a persistent policy issue in many developing countries. While socio‐political, epidemiological, climatic, and productivity‐related factors have received attention regarding food insecurity, a rarely considered factor is the changing quality of the soil, a natural resource base that has the potential of increasing or reducing vulnerability to food insecurity. The use of organic soil amendments may be socioeconomically and environmentally advantageous. This study examines the inherent relationship between the use of organic soil amendments and food security among smallholder farming households. Using the seemingly unrelated bivariate probit model and the recursive bivariate probit (RBP) model on nationally representative household‐level data from Cameroon, we find evidence that the use of organic soil amendments is positively associated with household food security. We also find the use of organic soil amendments to be associated with reduced levels of mild, moderate, and severe food insecurity. Empirical evidence is also suggestive of a positive association between crop diversification and food security. The results further show that households with larger farm sizes tend to use more organic soil amendments than households with smaller farms. Taken together, our findings confirm another pathway of improving food security with implications for the broad path toward achieving the UN Sustainable Development Goals (SDGs), particularly SDG 2 of ending hunger.

Multifaceted Social and Environmental Disruptions Impact on Smallholder Plantations' Resilience in Indonesia.

As one of the most productive plantation producers in the world, Indonesia also faces rapid change in both social and environmental systems. These conditions are predicted to become more disruptive to the agricultural sector in the future. Therefore, understanding the impact of social and environmental disruption on smallholder plantations' resilience is vital to formulate a strategy for the sustainability of farmers' livelihoods in this country. Using survey data from 360 smallholding farmers in six villages from three districts in Bengkulu Province, Indonesia, the study deployed a multidimensional approach to assess smallholders' resilience to social and environmental disruption as well as towards economic dynamics. There are four dimensions of smallholder resilience, namely, the ability of adaptation, recoverability, anticipation, and farmers' innovation level. Social disruption was indicated by farmers' demography, epidemic/family health, social conflict, culture clash, and intention on land conversion. Meanwhile, environmental disruption was shown by natural catastrophe incidents, climate variations, environmentally unfriendly cultivation activities, and land fires. Since the resilience level was classified as binary, bivariate probit model was used in the analysis. The result shows that smallholder plantations in Bengkulu Indonesia are categorized as innovative, and recoverable, but less adaptive, and less anticipatory farmers. Overall, more than 50% of smallholder plantations are classified as less resilient smallholders. The statistical result empirically uncovers that the intentions of land conversion, climate change, and environmentally unfriendly farming activities statistically have a significant contribution to the reduction of smallholder plantations' resilience. Furthermore, the economic dynamisms such as lack of input availability, price volatility, demand uncertainty, and capital limitation have a significant negative impact on smallholder plantation resilience.

The “Double Trap” in China—Multiple Equilibria in Institutions and Income and their Causal Relationship

While institutions are said to be poor in China in cross-country comparison, recent research indicates that at the provincial level, institutional quality plays in fact an important role for the economic success of a province, municipality, or autonomous region in China. Our paper aims to add further arguments to this discussion by focusing on the concept of club convergence. In particular, we analyze whether institutional quality in low-income provincial level administrative divisions converges to the level experienced by relatively highly developed ones or whether there exist multiple institutional clubs over the period 1997–2007 by using the log t test proposed by Phillips and Sul (Econometrica 75(6):1771–1855, 2007). Our findings indicate that there exist multiple institutional clubs within China, three rather small clubs which follow an above-average high institutional quality path and two clubs which find themselves on a relatively low institutional quality path and which together account for the majority of provinces and autonomous regions. Using the same methodology, we find that various members of the poor institutional clubs are additionally caught in a low-income trap. In a next step, we analyze the causal relationship between poor institutional traps and low-income traps in China by using a recursive bivariate probit model. We find evidence that institutional traps are important determinants of income traps, giving rise to the recently identified phenomenon of a ‘double trap’. Finally, our findings indicate that human capital and urbanization are additional important determinants of income traps, while globalization is decisive for avoiding poor institutional traps.

Innovation and the Financial Performance of Firms during the Great Recession and Recovery Period

This study analyzes the relationship between innovation and financial constraints. To this end, a database extracted from the Community Innovation Survey (CIS) and the System of Business Accounts (SCIE) was used. The sample consisted of 24,679 active companies operating in Portugal in the manufacturing and service industry between 2008 and 2016. A Recursive Bivariate Probit Model (RPBM) was used for making estimates. When analyzing the relationship between innovation and financial constraints, the results reveal a negative relationship between the two, confirming that firms that are financially constrained are more limited in their investments in R&D, and innovation is less accessible to them. The severity of the effects of financial constraints is heterogeneous across economic activities, strongly affecting innovative industries, while service industries appear to be the least affected. It was also observed that larger companies are better able to innovate. There was a positive relationship between innovation and the variables sales and exports, indicating that innovation will positively affect the financial results of companies.