Significant Marginal Effects Research Articles

Do two-wheeler riders propel towards autonomous driving? A path-based probabilistic study in Indian context

Regardless of the rational benefits of autonomous vehicle adoption towards mitigating mobility goals in urban and sub-urban areas of middle-income countries, adoption of such technology remains thought-provoking. Two wheeled vehicles are often utilized extensively all over the world for short distance trips in sub-urban areas. The present study investigates perceived risks of using four wheeled autonomous vehicles by captive two-wheeler riders for long and short distance trips in densely populated Indian cities. Theoretical autonomous vehicle technology acceptance models were modified considering Indian perceptions in this study. Offline stated preference responses were collected from various universities, open public spaces and governmental organizations of various cities within India. Structural equation models (SEM) and Random Forest (RF) were employed to generate meaningful insights from the surveys conducted. Random Forest (RF) analysis concluded that bicycle riders show medium to low levels of trust towards behavioural adoption intention of autonomous vehicles. According to proposed structural equation models, interest to adopt or willingness to buy autonomous vehicles for two wheeled vehicle users is mostly influenced by perceived trust and risk rather than perceived concerns/benefits for middle and old age groups in India. Perceived ease of use has the most significant marginal effects on two-wheeler riders' perceived risks towards autonomous vehicle adoption, which accounted for more than 20 % of unexplained variance. Results from this research may offer insightful diversity of attitudes towards adoption of autonomous vehicle technologies in India through the means of increased efficiency and reduced travel time and costs along with riders’ risks towards privacy and safety.

Do outgrower schemes enhance technology adoption and productivity? Evidence from maize farmers in Northern Ghana

AbstractNucleus outgrower schemes are contractual arrangements where well‐resourced large‐scale farmers (nucleus farmers) are empowered by development support agencies to take charge of smallholder farmers, by providing them with market access and the necessary training on agronomic practices and farm inputs for production. In this study, we examine the impact of participation in outgrower scheme on technology adoption and farm productivity, using data from 634 smallholder maize farmers in Northern Ghana. We use the linear regression with endogenous treatment effects model to account for both observable and unobservable selection bias. The results reveal positive and significant marginal effects of outgrower scheme participation on technology adoption and maize yields. Outgrower scheme participants applied 6% and 82% more inorganic fertilizer and weedicides, respectively, than nonparticipants. Maize yield increased by about 3% for the participants more than nonparticipants. The findings also show that factors such as distance to market, distance to nucleus farmers' satellite office, nucleus outgrower scheme awareness, input price, and farmer‐based organization significantly influence outgrower scheme participation decisions, as well as technology adoption and maize yields.

Community medical service construction: identifying factors that influence medical choice for patients with non-communicable chronic diseases in the Southwest China

BackgroundCommunity medical institutions play a vital role in China’s healthcare system. While the number of these institutions has increased in recent years, their construction contents remain insufficient. The potential of community medical institutions in preventing, screening, diagnosing, and treating non-communicable chronic diseases (NCDs) has not been fully utilized. This study aims to assess the status of construction contents in community medical institutions in Southwest China and examine how these contents influence the medical choices of NCD patients.MethodsDescriptive statistics were used to evaluate the construction content of community medical institutions. Multiple-sets of multinomial logistic regression were employed to analyze the associations and marginal impacts between construction content and medical choices. Shapley value analysis was applied to determine the contribution and ranking of these impacts.ResultsDescriptive statistics revealed satisfactory construction contents in community medical institutions. Notably, factors such as service attitude, nursing services, expert consultations, charging standards, medical equipment, medical examinations, privacy protection, and referrals significantly influenced medical choices. Among these, service attitude, charging standards, and privacy protection had the most significant marginal improvement effects on NCD patients’ choices, with improvements of 12.7%, 10.2%, and 5.9%, respectively. The combined contribution of privacy protection, medical examinations, service attitude, charging standards, and nursing services to medical choices exceeded 80%.ConclusionOptimizing the service contents of community institutions can encourage NCD patients to seek medical care at grassroots hospitals. This study addresses crucial gaps in existing literature and offers practical insights for implementing new medical reform policies, particularly in underdeveloped regions of Southwest China focusing on hierarchical diagnosis and treatment.

Searching for gene-gene interactions through variance quantitative trait loci of 29 continuous Taiwan Biobank phenotypes.

Introduction: After the era of genome-wide association studies (GWAS), thousands of genetic variants have been identified to exhibit main effects on human phenotypes. The next critical issue would be to explore the interplay between genes, the so-called "gene-gene interactions" (GxG) or epistasis. An exhaustive search for all single-nucleotide polymorphism (SNP) pairs is not recommended because this will induce a harsh penalty of multiple testing. Limiting the search of epistasis on SNPs reported by previous GWAS may miss essential interactions between SNPs without significant marginal effects. Moreover, most methods are computationally intensive and can be challenging to implement genome-wide. Methods: I here searched for GxG through variance quantitative trait loci (vQTLs) of 29 continuous Taiwan Biobank (TWB) phenotypes. A discovery cohort of 86,536 and a replication cohort of 25,460 TWB individuals were analyzed, respectively. Results: A total of 18 nearly independent vQTLs with linkage disequilibrium measure r 2 < 0.01 were identified and replicated from nine phenotypes. 15 significant GxG were found with p-values <1.1E-5 (in the discovery cohort) and false discovery rates <2% (in the replication cohort). Among these 15 GxG, 11 were detected for blood traits including red blood cells, hemoglobin, and hematocrit; 2 for total bilirubin; 1 for fasting glucose; and 1 for total cholesterol (TCHO). All GxG were observed for gene pairs on the same chromosome, except for the APOA5 (chromosome 11)-TOMM40 (chromosome 19) interaction for TCHO. Discussion: This study provided a computationally feasible way to search for GxG genome-wide and applied this approach to 29 phenotypes.

Assessing the predictive validity of pre-admission criteria on dental students’ academic performance: a cross-sectional study

BackgroundThis study examines the multifaceted factors influencing academic performance among dental students in Saudi Arabia, exploring the complex relationships between demographic, educational, and psychological variables and students' Grade Point Averages (GPAs) to enhance global dental education admission strategies.MethodsData on demographics, academic performance indicators (including GPA, high school grades, test scores), accommodation type, parental education, suspension history, and English proficiency were collected through an English-language electronic questionnaire from 900 dental students across multiple institutions in Riyadh. The study employed Pearson’s correlation analysis to examine relationships between GPA and various academic and demographic factors. A detailed regression analysis, using a stepwise selection based on Akaike’s information criteria (AIC), identified significant GPA predictors and evaluated the average marginal effects of pre-admission variables on GPA, alongside rigorous diagnostic checks to validate the model’s robustness.ResultsThe study revealed a complex interplay of factors impacting GPA among dental students. High school grades, achievement, and aptitude test scores showed moderate positive correlations with GPA, while negative correlations were observed with age and number of times suspended. Regression analysis highlighted age, marital status, high school grades, and test scores as key predictors, with complex interaction effects demonstrating the layered influences of these factors. For instance, the negative impact of age on GPA was moderated by high school grade and aptitude test score. The analysis also highlighted the significant marginal effects of various pre-admission variables on GPA, such as the negative average impact of age and the positive impact of high school grades.ConclusionsThis study provides valuable insights into the multifaceted determinants of academic success in dental education. Our findings underscore the significant roles of high school grades, achievement, and aptitude test scores, as well as the nuanced influence of age and marital status on GPA. These results advocate for a holistic approach in evaluating candidates for dental programs and have broader implications for global dental education, emphasizing the need for comprehensive admission strategies.

Genome-wide association studies for epistatic genetic effects on fertility and reproduction traits in Holstein cattle.

Non-additive genetic effects are well known to play an important role in the phenotypic expression of complex traits, such as fertility and reproduction. In this study, a genome scan was performed using 41,640 single nucleotide polymorphism (SNP) markers to identify genomic regions associated with epistatic (additive-by-additive) effects in fertility and reproduction traits in Holstein cattle. Nine fertility and reproduction traits were analysed on 5825 and 6090 Holstein heifers and cows with phenotypes and genotypes, respectively. The Marginal Epistasis Test (MAPIT) was used to identify SNPs with significant marginal epistatic effects at a chromosome-wise 5% and 10% false discovery rate (FDR) level. The -log10 (p) values were adjusted by the genomic inflation factor (λ) to correct for the potential bias on the p-values and minimize the possible effects of population stratification. After adjustments, MAPIT enabled the identification of genomic regions with significant marginal epistatic effects for heifers on BTA5 for age at first insemination, BTA3 and BTA24 for non-return rate (NRR); BTA16 and BTA28 for gestation length (GL); BTA1, BTA4 and BTA17 for stillbirth (SB). For the cow traits, MAPIT enabled the identification of regions on BTA11 for GL, BTA11 and BTA16 for SB and BTA19 for calf size (CZ). An additional approach for mapping epistasis in a genome-wide association study was also proposed, in which the genome scan was performed using estimates of epistatic values as the input pseudo-phenotypes, computed using single-trait animal models. Significant SNPs were identified at the chromosome-wise 5% and 10% FDR levels for all traits. For the heifer traits, significant regions were found on BTA7 for AFS; BTA12 for NRR; BTA14 and BTA19 for GL; BTA19 for calving ease (CE); BTA5, BTA24, BTA25 and in the X chromosome for SB; BTA23 and in the X chromosome for CZ and in the X chromosome for the number of services (NS). For the cow traits, significant regions were found on BTA29 and in the X chromosome for NRR, BTA11, BTA16 and in the X chromosome for SB, BTA2 for GL, BTA28 for CZ, BTA19 for calving to first insemination, and in the X chromosome for NS and first insemination to conception. The results suggest that the epistatic genetic effects are likely due to many loci with a small effect rather than few loci with a large effect and/or a single SNP marker alone do not capture the epistatic effects well. The genomic architecture of fertility and reproduction traits is complex, and these results should be validated in independent dairy cattle populations and using alternative statistical models.

Social Determinants of the Non-Utilization of the Supplementary Feeding Program (PACAM) Aimed at Older Adults' Nutritional Support.

Chile has implemented the PACAM program to support older people with nutrition and for the prevention of malnutrition and frailty. This work aims to identify the social determinants of older persons not withdrawing PACAM food in order to obtain helpful knowledge for improving the program. First, the CASEN Survey 2017 was used (960,498 observations); the inclusion criterion was PACAM recipients (Yes/No). Next, a probit model was performed with a dichotomous response to determine the marginal effects of each independent variable (e.g., demographic, health, and social). The model shows a good fit (64.4%) with an explained variance between 10.5% to 14.1%. Those variables with more significant marginal effects are people aged 70-75, having tertiary and secondary education, urban living, not participating in social organizations, immigrants, and living in the austral zone. On the other hand, a higher likelihood of consumption was found among people of greater vulnerability (lowest income, lowest education, low health insurance, and aged over 80) and, therefore, in greater fragility. To conclude, the program achieves effective targeting, although improvement actions are required to expand coverage in some groups (indigenous people, immigrants, and people with disabilities). Moreover, authorities should evaluate and reinforce the program with tailored strategies for the older adults who actually withdraw food.

International Tourism and Poverty Alleviation: Cross-Country Evidence Using Panel Quantile Fixed Effects Approach

This paper evaluates the impact of tourism on poverty alleviation using a new panel quantile fixed effects method that allows regressors to affect the entire conditional distribution of the dependent variable providing substantial information gains. Our results show statistically significant negative marginal effects of tourism on both absolute poverty measures and Gini income inequality across all quantiles, including the poorest 10%. We also find evidence that international tourism can mitigate the slow improvement in domestic income level for poverty reduction. From a policy perspective, our findings can provide insights into developing targeted tourism policies and strategies to achieve better solutions on poverty alleviation. We also call for special attention to policymakers in developing countries to continue working on tourism product differentiation and targeting a smaller but reachable market in the post COVID-19 recovery era, to prevent the adverse effect of the worldwide income growth stagnation on their poverty rates.

Digital Financial Services on Financial Performance of Commercial Banks in Nigeria

Since the introduction of information communication technology and the widespread use of the internet, the banking business has undergone considerable changes. Information and communication technology (ICT) is at the heart of Nigeria's current worldwide shift curve in the electronic banking system. In light of this, this study looked into the influence of digital financial services (DFS) on the financial performance of Nigeria's publicly traded commercial banks. The study aims to see if there is a link between the dependent variable, which is financial performance as assessed by banks' earnings-per-share (EPS), and the main independent variables, which are the volume of ATM and POS transactions as a proxy for digital financial services (DFS). Secondary data was employed in the study. The data was collected from the annual report of target banks and the Central Bank of Nigeria from 2012 to 2020. The study used both descriptive and inferential statistics in analysing the data. In general, the study revealed that digital financial services (DFS) have substantial and significant marginal effects on earnings per share in Nigeria’s banking sector. Thus, there exists a positive relationship between digital financial services (DFS) and bank financial performance. In conclusion, electronic banking has made banking transactions to be more accessible by bringing services closer to its customers hence improving banking industry performance. Thus, the study recommends that bank management should enhance digital banking to improve financial performance in commercial banks.

How does duplicate tweeting boost social media exposure to scholarly articles?

• Few studies disclose how duplicate tweeting strategy boosts social media exposure to online information, especially to scientific publications. • Several novel metrics are proposed to measure the behavior of duplicate tweeting. • Social media exposures to scholarly articles have significant marginal effects as the number of duplicate tweeting increases. • The interval of duplicate tweeting is negatively correlated with social media exposure to scholarly articles. • Posting non-duplicate content can bring more online exposure to articles, facilitating more discussion or conversations. Duplicate tweeting is a kind of behavior that a user posts the same or substantially similar original tweets to one or several topics multiple times in a row, which is commonly used to boost social media exposure to online information. However, how this behavior boosts social media exposure to online information, especially to scientific publications, is still unclear. In this study, we use the number of retweets an article received as a proxy for social media exposure to the article. Based on the duplicate tweeting records of 12,263 users on Twitter from 2011 to 2017, we find that social media exposure to scholarly articles has a significant marginal effect as the number of duplicate tweeting ( k ) increases. It ramps up a peak value when k is between 2 and 4 and goes down when k takes a greater value. We also find that a longer posting interval can sharply reduce social media exposure to scholarly articles, and posting non-duplicate content can significantly improve the exposure. Our findings not only help scientists and journal publishers effectively improve the social impact of their research outputs but also advance the understanding of the diffusion processes of scholarly articles.

The Impact of Environmental Policy on Innovation in Clean Technologies

This paper studies the effect of climate change mitigating policies on innovation in clean energy technologies. Results suggest that the tightening of environmental policies since the early 1990s have made a statistically and economically significant contribution to the increase in clean innovation. These effects generally materialized quickly, within 2 to 3 years of the policy change, and were driven by individually significant marginal effects of both market-based policies – such as feed-in tariffs and trading schemes – as well as non-market policies, such as R&D subsidies or emission limits. Looking at electricity innovation in particular, the paper finds that the estimated effect on total innovation is positive on net, meaning that increased innovation in clean and grey technologies is not offset by a decrease in innovation in dirty technologies. From a policy point of view, the paper’s results call for strong policy efforts to decisively shift innovation towards clean technologies.

The GDP-Temperature relationship: Implications for climate change damages

Econometric models of temperature impacts on GDP are increasingly used to inform global warming damage assessments. But theory does not prescribe estimable forms of this relationship. By estimating 800 plausible specifications of the temperature-GDP relationship, we demonstrate that a wide variety of models are statistically indistinguishable in their out-of-sample performance, including models that exclude any temperature effect. This full set of models, however, implies a wide range of climate change impacts by 2100, yielding considerable model uncertainty. The uncertainty is greatest for models that specify effects of temperature on GDP growth that accumulate over time; the 95% confidence interval that accounts for both sampling and model uncertainty across the best-performing models ranges from 84% GDP losses to 359% gains. Models of GDP levels effects yield a much narrower distribution of GDP impacts centered around 1–3% losses, consistent with damage functions of major integrated assessment models. Further, models that incorporate lagged temperature effects are indicative of impacts on GDP levels rather than GDP growth. We identify statistically significant marginal effects of temperature on poor country GDP and agricultural production, but not rich country GDP, non-agricultural production, or GDP growth.

Reducing Child Undernutrition through Dietary Diversification, Reduced Aflatoxin Exposure, and Improved Hygiene Practices: The Immediate Impacts in Central Tanzania

ABSTRACT The study aimed to quantify the immediate effects of dietary diversification, food safety, and hygiene interventions on child undernutrition in four rural villages in Kongwa district of central Tanzania. One hundred mothers with their children of less than 24 months old were recruited for this study. The difference-in-difference (DID) method was used to assess the effects of intensive intervention through a learning-by-doing process on the topic of aflatoxin free diversified food utilization and improved hygiene practices. Periodic anthropometric measurements were conducted on the 0th, 7th, 14th, and 21st days, and DID estimator showed the significant and positive average marginal effects of the intervention on Z-Scores being 0.459, 0.252, and 0.493 for wasting, stunting, and underweight, respectively. Notably, at the end of the study, the mean aflatoxin M1 level in urine samples decreased by 64% in the intervention group, while it decreased by 11% in the control group. The study provides quantitative evidence on intensive 21-day training for mothers incorporating integrated technologies yielded positive impacts on their children’s nutritional outcomes.

Household leverage and consumption during the Great Depression

PurposeThe purpose of this study is to explore the impact of household leverage on consumption in Denmark during the Great Depression in the 1930s.Design/methodology/approachA range of consumption functions are estimated on the basis of household-level data from the Expenditure and Saving Survey of 1931.FindingsThe estimations show significant negative marginal effects of various measures of leverage on homeowners’ non-durable consumption. The magnitude of the estimated effects suggests that leverage contributed significantly to the economic downturn during the Great Depression by depressing consumer spending of homeowners.Practical implicationsGross debt levels of homeowners are not only of direct importance for financial stability but also have implications for macroeconomic stability, which again might affect the stability of the financial system. These findings seem to be in line with the focus on household leverage in the macroprudential oversight performed by regulators and central banks in many countries.Originality/valueThis paper is the first study of the leverage channel in the private consumption function using household micro data from the Great Depression.

Technician Consistency in Specular Microscopy Measurements: A "Real-World" Retrospective Analysis of a United States Eye Bank.

To quantify consistency of endothelial cell density (ECD) measurements among technicians in a single US eye bank operating under typical operating conditions. In this retrospective analysis of 51 microscopy technicians using a semiautomated counting method on 35,067 eyes from July 2007 to May 2015, technician- and date-related marginal ECD effects were calculated using linear regression models. ECD variance was correlated with the number of specular microscopy technicians. Technician mean ECDs ranged from 2386 ± 431 to 3005 ± 560 cells/mm. Nine technicians had statistically and clinically significant marginal effects. Annual mean ECDs adjusted for changes in technicians ranged from 2422 ± 433 to 2644 ± 430 cells/mm. The period of 2007 to 2009 had statistically and clinically significant marginal effects. There was a nonstatistically significant association between the number of technicians and ECD standard deviation. There was significant ECD variability associated with specular microscopy technicians and with the date of measurement. We recommend that eye banks collect data related to laboratory factors that have been shown to influence ECD variability.

Local Logit Regression for Recovery Rate

We propose a flexible and robust non-parametric local logit regression for modelling and predicting defaulted loans' recovery rates that lie in [0,1]. Applying the model to the widely studied Moody's recovery dataset and estimating it by a data-driven method, the local logit regression uncovers the underlying nonlinear relationship between the recovery and covariates, which include loan/borrower characteristics and economic conditions. We find some significant nonlinear marginal and interaction effects of conditioning variables on recoveries of defaulted loans. The presence of such nonlinear economic effects enriches the local logit model specification that supports the improved recovery prediction. This paper is the first to study a non-parametric regression model that not only generates unbiased and improved recovery predictions of defaulted loans relative to the parametric counterparts, it also facilitates reliable inference on marginal and interaction effects of loan/borrower characteristics and economic conditions. Moreover, incorporating these nonlinear marginal and interaction effects, we improve the specification of parametric regression for fractional response variable, which we call a model, the predictive performance of which is comparable to that of local logit model. This calibrated parametric model will be attractive to applied researchers and industry professionals working in the risk management area and unfamiliar with non-parametric machinery.

Trayectorias de inicio laboral y desigualdad en Uruguay. Un análisis con base en el estudio longitudinal PISA-L 2003-2012

Este trabajo se propone primero identificar y luego explicar, las trayectorias laborales iniciales de jóvenes uruguayos haciendo énfasis en tres elementos: la protección social, el calendario y la cualificación en el contexto de la nueva incertidumbre generada por la globalización y los filtros institucionales provistos por los sistemas laboral y educativo. Utiliza datos del proyecto PISA longitudinal 2003-2012. Una solución óptima de siete clusters evidencia un mediano nivel de heterogeneidad en la transición. La regresión sobre clase social, género y capital humano informa modestos, aunque significativos efectos marginales para los dos últimos. Es notorio la reproducción de la desigualdad de género en este “período denso”, en especial que afecta a la mujer con hijos. El capital humano tiene un nítido efecto protector respecto de trayectorias vulnerables, pero no genera ventajas respecto de seguir trayectorias ascendentes de cualificación del empleo.

The Effect of Publicized Quality Information on Home Health Agency Choice.

We examine consumers' use of publicized quality information in Medicare home health care markets, where consumer cost sharing and travel costs are absent. We report two findings. First, agencies with high quality scores are more likely to be preferred by consumers after the introduction of a public reporting program than before. Second, consumers' use of publicized quality information differs by patient group. Community-based patients have slightly larger responses to public reporting than hospital-discharged patients. Patients with functional limitations at the start of their care, at least among hospital-discharged patients, have a larger response to the reported functional outcome measure than those without functional limitations. In all cases of significant marginal effects, magnitudes are small. We conclude that the current public reporting approach is unlikely to have critical impacts on home health agency choice. Identifying and releasing quality information that is meaningful to consumers may help increase consumers' use of public reports.

Using edge-preserving algorithm with non-local mean for significantly improved image-domain material decomposition in dual-energy CT

Increased noise is a general concern for dual-energy material decomposition. Here, we develop an image-domain material decomposition algorithm for dual-energy CT (DECT) by incorporating an edge-preserving filter into the Local HighlY constrained backPRojection reconstruction (HYPR-LR) framework. With effective use of the non-local mean, the proposed algorithm, which is referred to as HYPR-NLM, reduces the noise in dual-energy decomposition while preserving the accuracy of quantitative measurement and spatial resolution of the material-specific dual-energy images. We demonstrate the noise reduction and resolution preservation of the algorithm with an iodine concentrate numerical phantom by comparing the HYPR-NLM algorithm to the direct matrix inversion, HYPR-LR and iterative image-domain material decomposition (Iter-DECT). We also show the superior performance of the HYPR-NLM over the existing methods by using two sets of cardiac perfusing imaging data. The DECT material decomposition comparison study shows that all four algorithms yield acceptable quantitative measurements of iodine concentrate. Direct matrix inversion yields the highest noise level, followed by HYPR-LR and Iter-DECT. HYPR-NLM in an iterative formulation significantly reduces image noise and the image noise is comparable to or even lower than that generated using Iter-DECT. For the HYPR-NLM method, there are marginal edge effects in the difference image, suggesting the high-frequency details are well preserved. In addition, when the search window size increases from to , there are no significant changes or marginal edge effects in the HYPR-NLM difference images. The reference drawn from the comparison study includes: (1) HYPR-NLM significantly reduces the DECT material decomposition noise while preserving quantitative measurements and high-frequency edge information, and (2) HYPR-NLM is robust with respect to parameter selection.

Regularized machine learning in the genetic prediction of complex traits.

Regularized machine learning in the genetic prediction of complex traits.