Ordered Probit Model Research Articles

Likert Scale Variables in Personal Finance Research: The Neutral Category Problem

Personal finance research often utilizes Likert-type items and Likert scales as dependent variables, frequently employing standard probit and ordered probit models. If inappropriately modeled, the “neutral” category of discrete dependent variables can bias estimates of the remaining categories. Through the utilization of hierarchical models, this paper demonstrates a methodology that accounts for the econometric issues of the neutral category. We then analyze the technique through an empirical exercise relevant to personal finance research using data from the National Financial Capability Study. We demonstrate that ignoring the “neutral” category bias can lead to incorrect inferences, hindering the progression of personal finance research. Our findings underscore the importance of refining statistical modeling techniques when dealing with Likert-type data. By accounting for the neutral category, we can enhance the reliability of personal finance research outcomes, fostering improved decision-relevant insights.

Drivers of corporate environmental policy at country, sector, and firm levels

Abstract This study provides a holistic approach to the potential drivers of corporate environmental policy. Institutional and/or stakeholder theories are used to explain any influence on this type of policy in situations with different characteristics. Specifically, the analysis considers country-, industry-, and firm-level determinants of an international sample of listed companies. Exploratory factor analysis was first applied to the variables at the country level because their underlying interrelationships were unknown. Using ordered probit models clustered at the firm level, we found that some environmental characteristics of a country and some macro-level variables considered together affect corporate environmental policy, along with pressure from industry peers. Moreover, we observed that companies with better policies for stakeholders, greater board independence, and greater gender diversity tended to develop better environmental policies. This study offers insight into fostering environmental responsibility through policy incentives and effective corporate governance structures.

Livelihood diversification and household welfare among farm households in the Philippines

AbstractDiversification of income sources is one of the most common strategies households employ to minimize household income variability and to ensure a minimum level of income that guarantee their food security. This study examines the impact of livelihood diversification on farm profits among smallholder rice farmers in the Central Luzon Region (CLR) of the Philippines using long‐term farm‐level panel data spanning from 1966 to 2016. We employed a random‐effects ordered probit model to investigate the drivers of livelihood diversification and then used the mixed Markov chain model to analyze the transition of households from less to more diversified livelihoods and its impact on farm profits over time. Our findings reveal substantial diversification among households over time. In particular, the elevation of the farm location is a key driver of rice farm households’ probability to diversify. The estimates show that an increase in the latitude of the farm location increases the probability of rice farmers in the CLR to diversify. We find that 64% of the rice farm households constitute farmers for whom diversification can be a strategy for survival. For medium‐ to high‐profit farm categories, diversification tends to protect farmers against farm profit losses arising from adverse climatic and weather variability.

Financial Literacy, Fintech, and Risky Financial Investment in Urban Households—An Analysis Based on CHFS Data

In recent years, China’s financial markets have come under increasing scrutiny. In order to explore the impact of financial literacy on urban household investment in the risk financial market, this paper used the micro-data of the 2019 China Household Finance Survey (CHFS) to start from two perspectives: household risk financial investment and the number of investment financial products, namely the breadth of investment. By constructing a probit model and ordered probit model for empirical analysis, the main conclusions are as follows. Benchmark regression results show that the improvement of financial literacy can significantly promote urban households to make risky financial investments and can significantly broaden the types of risky financial investments. Based on the IV-probit model and two-stage least square method, the endogeneity test using the economic and financial information attention degree as the instrumental variable showed that the model results were credible. The robustness test showed that the model results were basically correct. Furthermore, the mechanism analysis found that the use of fintech played an intermediary effect in the process of financial literacy affecting urban household risky financial investment and the amount of investment. This indicates that the improvement of financial literacy can improve the probability of using fintech, thus promoting the household risky financial investment behavior. Heterogeneity analysis based on risk attitude showed that financial literacy had a greater effect on the improvement in the risky financial investment behavior of risk-inclined families, followed by risk-neutral families, and had the least effect on risk-averse families. The research conclusions of this paper are of practical significance to solve the problems related to urban household financial market investment. Therefore, this paper puts forward some suggestions for reference, especially in terms of financial education and the digital economy.

Quantifying the strength of firearms comparisons based on error rate studies.

Forensic firearms and tool mark examiners compare bullets and cartridge cases to assess whether they originate from the same source or different sources. To communicate their observations, they rely on predefined conclusion scales ranging from Identification to Elimination. However, these terms have not been calibrated against the actual strength of the evidence except indirectly through error rate studies. The present research reanalyzes the findings of firearms and cartridge case comparisons from error rate studies to generate a quantitative measure of the strength of the evidence for each comparison. We use an ordered probit model to summarize the distribution of responses of examiners and aggregate the data for all comparisons to produce a set of likelihood ratios. The likelihood ratios can be as low as less than 10, which does not seem to justify the current articulation scale that may imply a strength of evidence of 10,000 or greater. This suggests that examiners are using language that overstates the strength of the evidence by several orders of magnitude.

Socio-Economic Determinants of the Physical Activity Intensity in Russia

The study examines the socioeconomic, demographic and health determinants of physical activity intensity in Russia. Using RLMS-HSE (the Russia Longitudinal Monitoring Survey – Higher School of Economics) data for 2021 and indicators of six levels of physical activity intensity, the authors built ordered probit models and calculated average marginal effects for a set of covariates. The independent variables were selected based on the SLOTH microeconomic model describing individual preferences towards physical activity.The ordered probit regression provided empirical support for Meltzer and Jena's theoretical framework, stating that as income increases, with the pronounced substitution effect, the time spent on physical activity decreases, and the intensity of physical activity rises. In our study, the thesis about an increase in intensity with rising income was confirmed for a subsample of men but not women. For women, the intensity was determined by factors such as multiple morbidity and residing outside of Moscow or Saint Petersburg, which were not significant in the regressions for men.The study resulted in several important conclusions. The intensity analysis showed that physician recommendations regarding the type of physical activity should consider patients' workload. For individuals with a busy schedule, recommended types of exercise that require a long time (for example, walking) are not suitable. At the same time, intense workouts (such as tennis or gym classes) can be built into the schedule. There is a need to develop sports infrastructure at workplaces, allowing individuals to allocate time for classes without bearing additional time and monetary costs associated with travel to the location of workouts. As income increases, exercising near the workplace allows an individual to increase the intensity of physical activity without incurring additional time costs

Analysis of the Impact of Digital Inclusive Finance on the Well-being of Rural Residents

Improving the sense of well-being, gain, and security among rural residents has become one of the important tasks for promoting high-quality rural economic development and achieving rural revitalization. This paper, based on data from the China Household Finance Survey (CHFS) from 2015 to 2019, constructs an Ordered Probit model to study and analyze the impact and mechanism of digital inclusive finance on the well-being of rural residents. The results indicate that digital inclusive finance can enhance the well-being of rural residents, and the indices of coverage breadth, usage depth, and digitalization all have significant positive effects on the well-being of rural residents. In terms of the mechanism, digital inclusive finance improves the income of rural residents, promotes entrepreneurship among them, and enhances their financial literacy, thereby increasing their well-being. At the same time, digital inclusive finance has a greater impact on the well-being of samples from rural areas in the central and eastern regions, as well as among rural women and middle-aged and elderly groups.

Balance or Quality: Impact of Part-Time Farming on the Nutrition and Health of Rural Residents

The purpose of this paper is to explore the relationship between part-time farming and the nutrition and health of rural residents, test the possible effects through two potential pathways—income effect and time effect—and further analyze the family heterogeneity characteristic of downward intergenerational support. Using the ordered probit model and cross-sectional data from the China Rural Revitalization Comprehensive Survey (CRRS), which provide information on household income, health conditions, and nutritional caloric intake, this study estimates the relationship between part-time farming and the nutritional health of rural residents. The effects are decomposed into income (measured by dietary diversity scores and food consumption expenditures) and time effects (measured by excess caloric intake), with additional analysis on family heterogeneity concerning downward intergenerational support. Part-time farming positively correlates with rural residents’ nutritional health through two pathways: income effect (improved dietary diversity and increased food consumption) and time effect (negative impact of excessive caloric intake). Downward intergenerational support mitigates the negative time effect. This paper highlights the often-overlooked impact of part-time farming on rural nutrition and health, emphasizing non-linear effects and the significant role of downward intergenerational support, thus filling a gap in existing research.

The effect of internet use on the health of middle-aged and older adults: evidences from China general social survey

BackgroundAccording to the United Nations classification of aging societies, China is rapidly transitioning into a moderately aging society, facing significant challenges related to population aging. Concurrently, China is actively implementing the Internet Power Strategy and the Internet Plus action plan, which are profoundly transforming the daily lives of individuals, including their health status. However, research on the impact of internet use on the health of middle-aged and older adults has not reached a consensus. This study aims to investigate the effects of internet use on the health of middle-aged and older adults, as well as the mechanisms and heterogeneity of these effects.MethodsThis study utilized data from the China General Social Survey conducted in 2018, which includes a sample of 6470 individuals. Self-rated health, mental health, and objective health were used as key health indicators, with internet use identified as the primary independent variable. The study aims to analyze the impact of internet use on the health status of middle-aged and older adults through the application of an ordered probit model and instrumental variable methods.ResultsThe results indicate that internet use has a significant positive impact on the health of middle-aged and older adults, with significance at the 1% level. This finding has passed a series of robustness tests. Mechanism analysis reveals that information acquisition is a crucial mediating mechanism between internet use and the health of middle-aged and older adults. This suggests that increased internet use enhances information access, thereby improving health outcomes. Furthermore, heterogeneity analysis shows that the impact of internet use on health is more pronounced among individuals living in rural areas, western regions, low-income groups, and those aged under 60, compared to their counterparts in urban areas, eastern regions, higher-income brackets, and those aged 60 and above.ConclusionInternet use can improve the health of middle-aged and older adults. Therefore, government departments, senior universities, communities, and families should collaborate to actively conduct digital skills training for older adults. Additionally, efforts should be accelerated to adapt electronic products to be more elder-friendly, helping older adults overcome the digital divide and thereby reducing health inequalities among middle-aged and older groups.

Prevalence of depression and associated factors among adolescents in Uttar Pradesh, India: insights from UDAYA wave-1

ABSTRACT Mental health issues, especially depression among adolescents is a global concern. This study focuses on understanding the prevalence and factors influencing depression among adolescents in Uttar Pradesh (UP), India. The study was utilized data from the Understanding the Lives of Adolescents and Young Adults (UDAYA) survey (Wave-1) conducted in 2015–16 among adolescents (aged 10–19 years). Bi-variate analysis, t-test, ANOVA, and ordered probit regression were employed for statistical analysis (N = 8,363). The ordered probit model demonstrated significant associations with higher depression among older adolescents (coef. = 0.16; 95% CI: 0.09, 0.24), females (coef. = 0.19; 95% CI: 0.13, 0.26), those with higher schooling (coef. = 0.19; 95% CI: 0.05, 0.33), and non-Hindu individuals (coef. = 0.08; 95% CI: 0.01, 0.15). Additionally, depression was notably higher in the richest households (coef. = 0.14; 95% CI: 0.05, 0.23), with high parental interaction (coef. = 0.11; 95% CI: 0.02, 0.21), and high peer interaction (coef. = 0.23; 95% CI: 0.16, 0.31). Conversely, lower depression was linked to good academic performance (coef. = -0.10; 95% CI: −0.18, −0.02), belonging to OBC (coef. = -0.11; 95% CI: −0.18, −0.05), and general (coef. = -0.09; 95% CI: −0.17, −0.01) categories. The study concludes that addressing adolescent depression in UP requires a nuanced approach considering demographic, socio-economic, and interpersonal factors. Interventions should target vulnerable groups while addressing academic stress, promoting positive social interactions, and providing mental health support. Further research is needed to explore underlying mechanisms and develop effective strategies for improving adolescent mental well-being in the region.

Exploring the Impact of Digital Literacy and Policy Cognition on Rural Residents' Eco-friendly Behaviors.

The active participation of rural residents in ecological protection is crucial for preserving the rural environment and advancing ecological civilization. However, existing literature often neglects the impact of rural residents' digital literacy and policy cognition on their adoption of eco-friendly behaviors. In the digital age, rural residents can efficiently access and utilize ecological information, deepen their policy cognition, and consequently, become more actively involved in ecological protection through enhancing their digital literacy. This enhancement is crucial for ensuring the smooth implementation of rural ecological policies at the grassroots level, thereby providing a strong impetus for the further development of rural ecological protection. Therefore, based on survey data from 851 respondents in four counties and cities in Hainan Province, this paper uses the Ordered Probit model to analyze the impact of digital literacy on rural residents' adoption of eco-friendly behaviors, supported by theoretical mechanism analysis. The results indicate that: (1) Digital literacy enhances the adoption of eco-friendly behaviors among rural residents; (2) The mechanism analysis shows that digital literacy promotes such adoption through improved policy cognition. Consequently, the government should actively promote digital technology education and training to improve rural residents' digital literacy. Therefore, targeted digital skills training policies should be developed according to the individual characteristics of rural residents. Additionally, promoting digital literacy to improve policy cognition will likely lead to greater engagement in eco-friendly behaviors.

AI-induced job impact: Complementary or substitution? Empirical insights and sustainable technology considerations

This study utilizes 3,682 full-time workers to examine perceptions of AI-induced job displacement risk and evaluate AI's potential complementary effects on labor. By distinguishing between these variables, the research identifies which worker characteristics and industries are most affected by AI. Employing an extended ordered probit model, the results show that those with higher perceived risks are mainly female, older, and more educated. Workers with frequent internet usage and remote work are more concerned about AI-induced job risks. Sector-wise, entry-level employees perceive the least risk, whereas manufacturing professionals and senior service sector employees are more apprehensive. Contrary to the mainstream assumption that AI causes unemployment, this study identifies a potential complementary effect on job tasks, suggesting that AI can enhance and support human labor rather than replace it. This inference is based on observed worker perceptions and the increased use of AI tools in tasks that complement human skills. Moreover, AI's integration contributes to sustainable practices and entrepreneurial opportunities, enhancing business innovation and environmental efficiency. Workers increasingly view AI as a value-added element in their jobs rather than a threat, particularly in sectors focusing on sustainable development and green technologies.

Climate-smart agriculture and food security in climate-vulnerable coastal areas of Bangladesh

The issue of global climate change is increasingly worrisome, particularly for countries heavily reliant on agriculture. To reduce the negative impact of climate change on agriculture, farmers of Bangladesh started adopting different climate smart agriculture (CSA) practices. The CSA sustainably increases productivity, resilience, and food security, which can contribute to the achievement of a number of sustainable development goals (SDGs). However, the adoption of CSA is low especially in the climate-vulnerable coastal areas of Bangladesh. Therefore, this study was conducted to identify the factors affecting the adoption of CSA and its influence on coastal household’s food security. A total of 327 sample farmers from three coastal districts of Bangladesh were interviewed. The collected data were then analyzed by using the binary probit and ordered probit model. The findings indicated that highest 65% of farmers adopted early planting of rice as one of CSA practices. The adoption of CSA practices positively affected by the household annual income, extension services and awareness regarding CSA practices. Moreover, the adopters of CSA were more food secure than non-adopters. For instance, adoption of one additional CSA practice leads to an increase in the likelihood of being food secure by 4.3%. In terms of policy perspective, the adoption of CSA in the coastal areas can be increased through creation of employment opportunities, increasing access to extension services, and broadcasting of CSA-related programs on mass media.

공공기관 상임감사와 감사조직의 특성이 청렴 수준 평가에 미치는 영향

The government has been evaluating the overall integrity levels of public institutions to promote and support anti-corruption efforts at all levels, including improving vulnerable areas and spreading integrity awareness and culture. However, despite these integrity assessments, recent corruption cases in public institutions have become a social issue, and the appointment of unprofessional executive auditors continues to be controversial regardless of the administration. The primary objective of this study is to analyze the impact of the characteristics of executive auditors and audit office organizations in public institutions on the results of integrity assessments. To this end, a panel data set was constructed using the integrity evaluation results from the Anti-Corruption and Civil Rights Commission and the performance reports of executive auditors in public institutions from 2019 to 2023. An ordered probit model was employed to empirically analyze the impact of the characteristics of executive auditors and audit office organizations on the integrity evaluation results. The analysis results showed that the personal characteristics of the executive auditor, such as experience, age, and education, did not have a statistically significant impact on the integrity evaluation results. On the other hand, among the characteristics variables of the audit organization, it was found that the higher the budget ratio of the audit office to the total budget of the institution and the larger the number of staff in the audit office, the more likely the institution is to receive a higher comprehensive integrity grade. Additionally, while the professionalism of the executive auditor and the audit department did not affect integrity, high ethics and independence had a positive impact on integrity. In other words, it was estimated that the budget ratio of the audit office to the total budget of the institution, the number of staff in the audit office, and the ethics and independence of the audit department have a more important impact on integrity than the personal characteristics of the executive auditor.

Investigation into the effects of COVID-19 on the Mobility Preferences and Challenges amongst Senior U.S. Citizens: Insights from a Nationwide Survey Study

Seniors’ mobility decreases as they age as a result of deteriorating health and restricted travel alternatives. Consequently, it is imperative that their transportation needs be met, particularly when they are at risk because of pandemics like COVID-19. This study aims to examine older U.S. citizens’ (65 years and older) travel behavior and challenges before and during COVID-19 through conducting a nationwide online survey that collected responses from 1,507 senior U.S. citizens. The McNemar-Bowker test and Ordered Probit Modeling were employed to assess the differences in their travel behavior and factors determining their mobility satisfaction during COVID-19. The findings indicate that there was a considerable reduction in the frequency of work-related, shopping, medical, leisure, and social/religious trips during COVID-19. In addition, the frequency of all travel modes usages declined significantly except for paratransit and motorcycle. Senior U.S. citizens’ travel choices during COVID-19 were largely influenced by their safety and security, virus infection concern, and comfort and convenience. Seniors mostly preferred to use their private vehicles during COVID-19. Accessibility, reliability, and flexibility were the greatest concerns of seniors about using public transit. Moreover, seniors’ satisfaction with their mobility depended on their physical mobility challenges, family size, subregional locations, length of driving, decline in their driving skills and abilities as they aged, preference to use private cars as the most affordable and reliable modes, and extra expenditure they made on their travels during COVID-19. Finally, several actionable countermeasures have been suggested in this study to improve the mobility of seniors.

Debunking the One-size-fits-all Approach: Synergistic and Trade-off Effects of Collective Action on Household Food Security Among the Smallholder Farmers in Central Kenya

Collective action is important in ameliorating the negative externalities in agriculture to promote household food security (HFS). This study explored the effects of efficiency and livelihood collective action initiatives (CAIs) on HFS along the pathways of production and income. The efficiency CAIs pursue efficiency-enhancing collective activities including input sourcing and output marketing. The livelihood CAIs engage in household livelihood and resilience enhancing collective activities such as provision of credit and informal insurance, pooling savings and acquisition of assets. A multinomial endogenous treatment effects (METE) model and an ordered probit model were employed on cross-sectional data drawn from 532 households from Murang’a County in central Kenya. The results revealed significant differences in HFS between the efficiency and livelihood CAIs. The differences were accounted for by the variations in household and organizational characteristics that determine the capacity to leverage HFS benefits along the pathways of production and income. Both efficiency and livelihood CAIs showed a positive significant effect on HFS through production. The results further showed that income positively influenced HFS among the livelihood members contrary to efficiency CAIs that showed negative HFS effects. The HFS across the combined pathways of income and production was lower for the efficiency CAIs than the livelihood CAIs. This was mainly due to the trade-off income effects exhibited by the former and the synergies accrued from income and production on the latter. The findings suggest that the overall performance of both efficiency and livelihood CAIs in leveraging HFS from joint income and production remains tentative. Therefore, a one-size-fits-all collective action promotional policy and program design approaches for improved HFS outcomes are inadequate. The study suggests a portfolio of context-specific collective action policies and interventions that match the differences between the efficiency and livelihood CAIs and their links to HFS. The policies would confer potential synergies, spillover effects and complementarities in strengthening the synergies while mitigating the trade-offs along the income and production pathways between the efficiency and livelihood CAIs. There is a need to enhance access to information, extension and advisory services and ICT among the members of the livelihood CAIs to improve production. It is important to incentivize the non-farm livelihood-enhancing economic activities among the livelihood members to fill the household food gaps arising from low production. It is also important to establish collective action funds and micro-credit schemes with affordable interest rates. This would help to tap the opportunities for credit sourcing and pooling savings among the livelihood members while promoting collective input sourcing and output marketing among the efficiency CAIs.

Using Sensory Analysis and Stated Preference Valuation to Assess the Willingness to Pay for Fresh Tomato Attributes

ABSTRACTThis study combines sensory analysis and stated preference valuation techniques to assess the monetary value of organoleptic attributes of new tomato varieties. The tomatoes evaluated included two new varieties adapted to South Texas growing conditions, a commercial check, and tomatoes imported from Mexico. In a blind sensory test, participants sampled, rated, and valued the attributes of all tomato varieties. Willingness to pay responses were collected using a payment card elicitation approach and jointly analyzed with a multivariate ordered probit model. Price premiums were associated with males, smaller households, younger consumers, higher income, and the liking of different organoleptic attributes.

How Farm Machinery Rental Services and Off-Farm Work Affect Household Income in China

(1) Background: Most nations struggle to close significant income gaps between high and low earners. While the adoption of farm machinery rental services and off-farm employment may be beneficial, it is unclear whether jointly applying both approaches can raise income levels in rural households or help narrow the income gap within the farm sector. This study investigated scenarios involving both participation in farm machinery rental markets and in off-farm work, analyzing their varied impacts on household incomes based on survey data from 1027 rice producers in rural China. (2) Methods: We employed a two-stage econometric procedure encompassing a bivariate ordered probit model with an endogeneity-corrected unconditional quantile regression model. (3) Results: Rice farmers often simultaneously rent farm machinery services and engage in off-farm work. Both activities positively affect their household incomes; however, these effects vary across different income levels. Renting farm machinery provides greater marginal benefits for lower-income households, while off-farm employment has a stronger impact on higher-income households. Farm machinery rental services appear to benefit disadvantaged households more than off-farm employment opportunities do. (4) Suggestions: To enhance the welfare of lower-income households, policymakers should focus on expanding access to farm machinery rental services.

Personality traits and participation in holiday trips for people without and with moderate and severe disabilities

ABSTRACT This study examines the relationship between personality traits (using the Big Five-Factor model, BFF), and participation and its intensity in holiday trips for German people without and with moderate and severe disabilities. Namely, this study investigates the contribution of the BFF model to understanding this relationship among travellers with different degrees of disability, and fills a gap in the literature on tourism and disability. Data from the 2013 and 2019 German Socioeconomic Panel surveys were used. To consider the particular nature of our dependent variable we run three different regression models (i.e. binary and ordered probit models for panel data, and a zero-inflated ordered probit model). Overall, there are significant differences in the impact of personality traits on participation in holiday trips by disability status but not in all dimensions and directions. For example, the dimension ‘consciousness’ positively affects the participation in holiday trips of people with disabilities (greater if the individual has a severe disability). The impact of ‘agreeableness’ on the likelihood to participate in holiday trips is lower for those people having a moderate/severe disability. Public programmes and policies for people with different degrees of disabilities must consider their personality traits to promote and increase their travel opportunities.

Boosting domestic rice production in Ghana: Analysis of consumer opinions, purchasing behavior and determinants among different income strata

Despite the fact that domestic rice production contributes significantly to the livelihood of millions of people in Ghana, it has been observed that consumers show a strong preference for expensive and imported rice over locally produced rice. The purpose of this study was to investigate the perception, purchasing behaviour and determinants of local rice consumption across three income households in the Kumasi Metropolis, Ghana. A total of 414 rice consumers were selected through a multi-stage sampling technique. Descriptive and inferential techniques, including perception analysis and ordered probit model, were used to analyse the data. The overall perception index of 3.61 denotes that consumers generally have a positive perception of local rice regarding health benefits (index = 4.44), affordability (index = 3.86), and cooking attributes (index = 3.48), despite its poor appearance (index = 2.80). The ordered probit model depicted heterogeneity of covariates as determinants of local rice consumption-based income strata of the household. For instance, various factors, including gender, age, occupation, and attributes of local rice such as affordability, nutrition, cooking attributes, and appearance, have a notable impact on the consumption of local rice among low-income households. In contrast, education, household decision-making, the place of purchasing local rice, and three perception attributes, namely affordability, nutrition, and cooking attributes, were found to be significant determinants of local rice consumption among middle-income households. According to the data, local rice consumption among high-income families was significantly predicted by gender, occupation, household size, and two perception attributes—affordability and nutrition. The study has practical implications for improving the competitiveness of local rice to increase its acceptance and consumption among consumers in the country.