Instrumental Variable Regression Model Research Articles

A Gendered Analysis of the Influence of Remittances and Democracy on Human Capital Accumulation via Educational Achievements

Although development experts acknowledge several development potentials of remittances, a clear understanding of the impacts of remittances and democracy on human capital accumulation regarding gender at the global level is still missing. In this research, we analyse the influences of remittances and democracy on human capital accumulation in terms of educational success, specifically primary, secondary and tertiary education, and average years of schooling with a gender focus at the global level through instrumental variables (IV) regression model. Our model using data from various valid international sources finds that (1) remittances have a significant positive impact on secondary and tertiary education and average years of schooling; (2) these have a higher significant effect on females’ education compared to their male counterparts; and (3) these are more instrumental for education in higher democratic developing countries rather than countries having no- or low-level of democracy. Next to remittances, the results find that (4) democracy has a significant positive influence on primary education and average schooling years; and (5) this is helpful for the educational advancement of both males and females but more effective for women compared to men. Based on our results, we suggest that remittances to developing countries and democratic practices in these countries can support investing and leveraging females’ education, which is a key mechanism for empowering women around the globe.

Interplay of Status Perception, Visible Inequality, Conspicuous Consumption, and Food Expenditure: Evidence from Consumer Pyramid Household Survey of Indian Households*

This study delves into the intricate interplay between visible inequality, conspicuous consumption, and food consumption in Indian households. Leveraging data from the Consumer Pyramids Household Survey (CPHS) provides significant insights. Through empirical analyses, including panel data analysis and instrumental variable panel data analysis, this study supports the hypothesis that there exists a relationship between visible inequality and conspicuous consumption among Indian households. The positive coefficients linked to conspicuous consumption variability reinforce established theories concerning the impact of status perception on spending behaviour. This study reveals a noteworthy adverse effect of visible inequality on essential expenditures, particularly food consumption, highlighting the delicate balancing act that households navigate between status‐driven spending and meeting fundamental needs. By employing instrumental variable regression models to address endogeneity concerns, this study robustly confirms the relationship between visible inequality and conspicuous consumption. This study emphasises the nuanced relationship between status‐oriented spending, visible inequality, and essential expenses in Indian households.

ESG performance and corporate fraudulence: Evidence from China

By adopting a large sample of Chinese public listed firms from 2014 to 2021, we examine whether firms' ESG performance inhibits corporate fraud. Using panel data regression techniques, we find that high ESG performance mitigates corporate fraudulence. After conducting a series of robustness tests, including propensity score matching (PSM) model, Heckman two-step sample selection model, instrumental variable (IV) and 2SLS regression model, and firm fixed effect model, the results remain unchanged. Further analyses suggest that this negative relationship is more pronounced in non-state-owned enterprise (non-SOE) firms and firms that voluntarily disclose ESG information. The mechanism analysis suggests that high-quality ESG engagement improves firms' governance performance and inhibits managerial myopia, which thereby mitigates corporate fraud. Overall, our findings provide incremental evidence on the role of ESG in filling institutional voids in emerging economies. Our findings also provide significant policy implications to regulators and policy makers who seek to promote fair information disclosure and mitigate corporate fraud risk.

An Analysis of Female Empowerment and Its Role in Mitigating Intimate Partner Violence in Ecuador

ABSTRACT This research article aims to analyze the effect of female empowerment on gender-based intimate partner violence against women in Ecuador, a country where levels of violence stand out in the region. We apply an instrumental variable regression model using official data from the 2019 National Survey on Family Relations and Gender Violence against Women. We found a negative association between women empowerment and intimate partner violence, that is, greater empowerment of women is associated with lower manifestations of intimate partner violence. We also find a positive reverse association between manifestations of intimate partner violence against women and empowerment. This means that a woman who has been a victim of intimate partner violence will be more willing to embrace ideals that empower women. From a public policy perspective, government engagement with promotion of female empowerment will reduce intimate partner violence against women and the costs associated with it.

Robots in action

Robots in action

Democracy, accountability, and forest loss: a cross-national analysis of low- and middle-income nations

ABSTRACT The existing cross-national research on democracy and forest loss has produced contradictory results. On the one hand, some studies find that democracy is related to less forest loss because of electoral accountability and guaranteeing political rights and civil liberties. On the other hand, studies find that democracy is related to increased forest loss in low- and middle-income nations because leaders promote policies that prioritize economic growth over protecting the natural environment. We use this research as a starting point for our study and build upon it in two ways. First, we examine how vertical, horizontal, and diagonal accountability – three different aspects of democracy – impacts forest loss in low- and middle-income nations. Second, we address the issue of endogeneity in the vertical, horizontal, and diagonal accountability. To do so, we analyze data for 80 low- and middle-income nations using a two-stage instrumental variable regression model. We find that higher levels of horizontal and diagonal accountability are related to less forest loss. We do not find that vertical accountability is related to forest loss in low- and middle-income nations. From the findings, we arrive at our theoretical implication, which support arguments concerning how actors at different scales work individually and together to promote conservation.

A Ridge-Regularized Jackknifed Anderson-Rubin Test

We consider hypothesis testing in instrumental variable regression models with few included exogenous covariates but many instruments—possibly more than the number of observations. We show that a ridge-regularized version of the jackknifed Anderson and Rubin (henceforth AR) test controls asymptotic size in the presence of heteroscedasticity, and when the instruments may be arbitrarily weak. Asymptotic size control is established under weaker assumptions than those imposed for recently proposed jackknifed AR tests in the literature. Furthermore, ridge-regularization extends the scope of jackknifed AR tests to situations in which there are more instruments than observations. Monte Carlo simulations indicate that our method has favorable finite-sample size and power properties compared to recently proposed alternative approaches in the literature. An empirical application on the elasticity of substitution between immigrants and natives in the United States illustrates the usefulness of the proposed method for practitioners.

Exploring the impact of social protest on mental health: A study of the 2019 “Social Uprising” in Chile

Socio-political conflicts, especially if accompanied by violent events, can affect the mental health of the population. This study aimed to estimate the causal effect of social protest-related violence on depressive symptoms during the 2019 social uprising in Chile. We collected population-representative data from a nationwide longitudinal survey (n = 2918), the fourth wave of which took place during the months of the social uprising in Chile (November 2019 and March 2020). Depressive symptoms were measured using the Patient Health Questionnaire-9, while violence related to social protest was measured as the perception of destruction at the neighbourhood level. To assess the casual relationship between destruction perception and depressive symptoms, we utilized an instrumental variable regression model. Our analysis controlled for relevant sociodemographic factors, participation in social protest, and history of mental health treatment. Results showed that perceived neighbourhood destruction during the 2019 social uprising significantly increased PHQ-9 score by 3.702 points, prevalence of moderate to severe depressive symptoms by 18.7%, and likelihood of having a Subthreshold or Major Depressive Episode by 15.2% (p < 0.01). The impact of perceived destruction on depressive symptoms varies by gender, with a significant effect found in men (an increase in depression indicators of 5.769 points, 26.8% and 23.0%, respectively, p < 0.05) but not in women. Stratified regression models by age demonstrate a positive association between the perception of neighbourhood destruction and depressive symptoms across all age groups, with a stronger effect observed among young adults. We found a casual effect of violence related to social protest on depressive symptoms. These findings have implications for the planning of social policies aimed at protecting the mental well-being of the population in times of increasing socio-political turmoil.

Analysing the drivers of ecological footprint in Africa with machine learning algorithm

Africa is largely confronted with varying issue of socioeconomic and insecurity, which is now increasingly linked with the mounting pressure on the continent's natural capital as glaring in the Sahel and Norther regions. As such, this study further probed the drivers of ecological footprint (EFP) by utilizing panel dataset of 39 African countries over the 1996 to 2018. Considering that several suspected drivers or covariates (which include the economy sectoral aspects, globalization aspects, governance and institutional aspects, energy types, and other socioeconomic aspects) of EFP were considered in the model, the feasibility of multicollinearity and other econometric drawbacks were accounted for by employing a two-step strategy. First, we used the least absolute shrinkage and selection operators (LASSOs) machine learning algorithms to predict the most important drivers of EFP. Second, we employed the Partialing-out LASSO instrumental variable regression (POIVLR) and Bayesian Model Averaging (BMA) techniques to obtain the variables marginal effects. The result found a more parsimonious regularization within the Adaptive LASSO (λ=0.0012), thus selecting 19 regressors out of the 26 covariates. Furthermore, the study found that Adaptive LASSO selection should be employed for inference since it performed better than the rest of the LASSOs and Elasticnet. As for the marginal effect of EFP, the partialing-out LASSO instrumental-variables regression (POIVLR) technique largely established expected impact of the selected covariates on EFP in Africa except for the impact of GDP and its square that shows negative and positive inference respectively. Combining these results and the sensitivity analysis, this study is poised to offer useful policy guide to environmentalist and decision-makers across Africa.

Government revenue composition and forest loss: A cross‐national study of low‐ and middle‐income nations

AbstractIntroductionWe draw on social contract theory and resource curse literatures to assess the relationship between government revenue composition and forest loss in low‐ and middle‐income nations that collect higher levels of revenues from a broad base of individuals and companies should have less forest loss.MethodsWe use two‐stage instrumental variable regression models to test how a government's revenue source impacts forest loss for a sample of 83 low‐ and middle‐income nations.ResultsWe find support that low‐ and middle‐income nations that collect more revenue from broad‐based taxes tend to have less forest loss.ConclusionWe move the cross‐national research frontier forward by applying insights from the fiscal contract and resource curse literatures to forest loss. We find that a government's revenue source is related to forest loss with low‐ and middle‐income nations that rely more on broad‐based taxes having lower levels of forest loss than revenues collected from other sources including natural resource rents and foreign aid.

Heterogeneity in price elasticity of vehicle kilometers traveled: Evidence from micro-level panel data

This article presents an empirical estimation of the effect of fuel prices on vehicle kilometers traveled (VKT) using a panel dataset of 1560 Swiss households over the period 2018–2021. Elasticities are estimated for different segments of households, based on their socio-demographic and vehicle characteristics, as well as on their driving intensity. Our results, based on fixed-effect, instrumental variable, and quantile regression models, indicate relatively large price elasticities and reveal heterogeneity in price sensitivity. Single-member households appear significantly more responsive to price than multiple-member households. Travel-intensive households do respond to changes in gasoline price, while less intensive drivers do not exhibit statistically significant price elasticities. For household segments who do not react to price, tailored non-price measures would be a useful complement to fuel taxes in order to reduce distance traveled and/or avoid imposing too strong a financial burden.

Thinking of the children: Energy poverty and acute respiratory infections among young children in South Asia

Energy poverty has been extensively studied in the literature regarding its impact on physical, mental, and maternity health as well as the social well-being of adults. However, there is still a research gap in understanding how energy poverty specifically affects the health of young children under the age of five, particularly toward the occurrence of acute respiratory infections (ARIs). To address this gap, this paper aims to clarify the link between energy poverty and acute respiratory illness among young children in South Asia. We utilized data from five demographic and health surveys conducted between 2015 and 2018, encompassing 292,196 young children. Employing the multidimensional energy poverty index and principal component analysis, we assessed energy poverty at the household level, considering indicators such as lack of electricity, clean cooking fuels, indoor smoke, and lifestyle-sustaining devices. Applying multilevel logistic and probit instrumental variable regression models, this study revealed that multidimensional energy poverty significantly triggers the risk of ARI among young children. Specifically, a 1 % increase in energy poverty leads to a 48 % increase in the odds of developing ARI among young children in South Asian households. Furthermore, regional disparities in the impact of energy poverty on respiratory infections were identified. Our findings remain robust across different methods and measures of energy poverty. The findings of this research work have a significant policy implication for ensuring sustainable energy services to improve children's health, contributing to sustainable development goals 3 (good health and well-being) and 7 (affordable and clean energy).

A Mere Fan Effect on Home-Court Advantage

The existence of a home-court advantage is one of the most durable empirical patterns in all of sports. Yet, the mechanisms explaining its strength and persistence remain a mystery in large part because of well-known challenges with statistical identification. We use attendance restrictions in place during the 2020–2021 National Basketball Association regular season as an instrument in order to identify the effect of fans and crowd size on home-court advantage. We show that home teams win by [Formula: see text] points, on average, when fans are present at games compared with [Formula: see text] points when no fans are present. This equates to winning approximately 2.2 additional home games over the course of a regular season. In fixed effects instrumental variables regression models, we estimate that the marginal effect of an additional one thousand fans on home-court advantage is [Formula: see text] points. We conclude that the mere presence of home fans, on its own, explains a larger share of home-court advantage than previously thought.

Hemiarthroplasty Versus Total Hip Arthroplasty for Femoral Neck Fracture in Elderly Patients: Twelve-Month Risk of Revision and Dislocation in an Instrumental Variable Analysis of Medicare Data.

There is practice variation in the selection of a total hip arthroplasty (THA) or a hemiarthroplasty (HA) for the treatment of displaced femoral neck fractures in elderly patients. Large data sets are needed to compare the rates of rare complications following these procedures. We sought to examine the relationship between surgery type and secondary hip surgery (revision or conversion arthroplasty) at 12 months following the index arthroplasty, and that between surgery type and dislocation at 12 months, among elderly Medicare beneficiaries who underwent THA or HA for a femoral neck fracture, taking into account the potential for selection bias. We performed a population-based, retrospective study of elderly (>65 years of age) Medicare beneficiaries who underwent THA or HA following a femoral neck fracture. Two-stage, instrumental variable regression models were applied to nationally representative Medicare medical claims data from 2017 to 2019. Of the 61,695 elderly patients who met the inclusion criteria, of whom 74.1% were female and 92.2% were non-Hispanic White, 10,268 patients (16.6%) underwent THA and 51,427 (83.4%) underwent HA. The findings from the multivariable, instrumental variable analyses indicated that treatment of displaced femoral neck fractures with THA was associated with a significantly higher risk of dislocation at 12 months compared with treatment with HA (2.9% for the THA group versus 1.9% for the HA group; p = 0.001). There was no significant difference in the likelihood of 12-month revision/conversion between THA and HA. The use of THA to treat femoral neck fractures in elderly patients is associated with a significantly higher risk of 12-month dislocation, as compared with the use of HA, although the difference may not be clinically important. A low overall rate of dislocation was found in both groups. The risk of revision/conversion at 12 months did not differ between the groups. Therapeutic Level III. See Instructions for Authors for a complete description of levels of evidence.

Financial Integration, Trade Integration and Economic Growth in the East African Community

This study sought to investigate the influence of macroeconomic volatility and trade integration on the relationship between financial integration and economic growth in the EAC member states. Specifically, the study aimed at determining the influence of trade integration on the relationship between financial integration and economic growth in the EAC. To achieve this objective, the following hypothesis was developed: There is no significant intervening effect of trade integration on the relationship between financial integration and economic growth. The study adopted a positivistic research philosophy and casual research design. Diagnostic tests were carried out to meet the requirements for conducting correlation and regression analysis on panel data. These include; Multicollinearity tests, Im- Pesaran-Shit Test (IPS) panel unit root test and Hausman test for fixed effects and random effects models. Descriptive statistics such as the mean, standard deviation, coefficient of variation as well as correlation analysis were conducted as the preliminary statistical analysis. Generalized-two stage least squares instrumental variable regression model (G2SLSIV) was then conducted to test the hypotheses. The findings of the study showed that: there is no significant intervening effect of trade integration on the relationship between financial integration and economic growth. These findings contribute to knowledge in the sense that, the positive and significant correlation between financial integration and economic growth confirms that, an increase in gross capital flows is accompanied by increase in economic growth. It also contributes to knowledge by revealing that, financial deepening contributes positively to financial integration which further contributes to accelerating economic growth. Therefore, the study is useful to the governments of respective member states in formulating policies aimed at achieving similarity in economic structures and ensuring the quality .....

Pandemics, economy and health in Asia-A scenario of post 2020

Utilizing a daily data of 29 Asian Economies from June 2021 to June 2022, this study investigates the impacts of economic growth, health infrastructures and Government measures on COVID-19 cases. Our results demonstrate that GDP, Government intervention, testing and vaccination exert positive impacts on COVID-19 cases. We incorporate factors like weather to know how temperature impacts COVID-19 Cases. Our results demonstrate that magnitude of COVID-19 cases goes on upward fashion in winter days more. With reference to co-morbid conditions like diabetes, we notice that people with diabetes are more vulnerable to the infections, however due to the greater behavioral response, we obtain a negative association between co-morbid conditions and new COVID-19 cases. However, the intensity of COVID-19 cases is decimated with the improvement in health facilities and behavioral changes. Besides basic regression estimates, our instrumental variable estimates hold true in the line of regression results while underlying the relation with the COVID-19 cases. Interestingly, our results from alternate specification ensures that high human development with greater openness has resulted in more COVID-19 cases. Overall, our study belies the fact that vaccination and higher govt intervention can prevent COVID-19. Rather, a comprehensive policy is recommended on cross-country basis to overcome such challenge.•The Study analyzes the relation among COVID-19, economic growth and health infrastructure on a daily basis from June 2021 to June 2022 for 29 Asian Economies•Our empirical strategy involves regression followed by robustness tests of instrumental variable regression model.•Results show that higher growth, human development, lesser vaccination and trivial govt intervention post 2020 have resulted in more COVID-19 cases.

Climate shocks, vulnerability, resilience and livelihoods in rural Zambia

ABSTRACT Climate and weather shocks pose risks to livelihoods in Southern Africa. We assess the extent to which smallholders are exposed to climate shocks in Zambia and how behavioural choices influence the negative effects of these shocks on vulnerability and resilience. We use household data from the nationally representative Rural Agricultural Livelihoods Survey and employ an instrumental variable probit regression model to control for the endogeneity of key choice variables. There are four main findings. First, droughts are the most prevalent climate shock faced by rural smallholder farmers in Zambia, but the extent of exposure differs spatially, with the Southern and Western Provinces being the hardest hit. Nationally, 76% of all smallholder farmers are vulnerable and only 24% are resilient, with female households most vulnerable. Second, increased climate shocks correlate with both increased vulnerability and reduced resilience, with short- and long-term deviations in seasonal rainfall worsening vulnerability and resilience. Third, higher asset endowments and education are correlated with reduced vulnerability and increased resilience. And last, climate-smart agricultural practices significantly improve household resilience. These findings imply a need to support scaling of climate-smart agricultural technologies and to invest in risk mitigation strategies such as weather-indexed insurance and targeted social cash transfers.

Can geopolitical risk improve energy efficiency in European countries?

The European countries are highly dependent on energy imports, making them vulnerable to international geopolitical threats. In this context, improving energy efficiency emerges as a cost-effective solution. The primary purpose of this study is to investigate the impact of geopolitical risk (GPR) on energy efficiency for 18 European countries during 1991–2020 using the Dumitrescu Hurlin Panel Causality test, instrumental variable quantile regression (IVQR) model, and Data Envelopment Analysis (DEA). The study found that GPR has a positive impact on energy efficiency in higher quantities. This trend might be due to the fact that countries with high energy efficiency are better equipped to face GPR, thanks to their investments in infrastructure, particularly renewable energy technology.

Metropolitan area heterogeneity and the impact of road infrastructure improvements on VMT

Past studies have found that the average elasticity of vehicle miles traveled (VMT) to the stock of highways is close to one. This result is often interpreted to mean that an increase in the stock of highway miles is likely to be accompanied by a commensurate increase in VMT, leaving congestion unaffected. In this study, we explore the heterogeneity in this elasticity due to both observed and unobserved city characteristics. We begin by using a simple model to demonstrate how cities with different initial congestion levels may respond differently to added road capacity. These differences give rise to heterogeneity in the elasticity of VMT to highway capacity. We then conduct an empirical analysis using the instrumental variable quantile regression (IVQR) model to incorporate variation in the elasticity due to the presence of unobserved differences across metropolitan statistical areas (MSAs). The IVQR results imply that expanding road capacities has a greater impact on MSAs with low levels of VMT than on MSAs with high VMT. Estimates of the elasticity using generalized quantile regression (GQR) mirror the IVQR estimates. We further simulate the mechanisms using a spatial equilibrium model with an extensive road network calibrated to the Greater Los Angeles region by treating commuting and shopping trips, mode, and route choices. We find that the elasticity of VMT to capacity—which decreases with initial VMT—in LA is 0.32. One important policy implication is that, when building more roads, the mean or median congestion level across cities remains unchanged, although it can reduce the number of cities experiencing high congestion levels.

Outcomes of thymoglobulin versus basiliximab induction therapies in living donor kidney transplant recipients with mild to moderate immunological risk – a retrospective analysis of UNOS database

Introduction The aim of this study is to assess the outcomes of different induction therapies among mild to moderate immunological risk kidney transplants in the era tacrolimus and mycophenolate-derivate based maintenance. Methods This was a retrospective cohort study using data from the United States Organ Procurement and Transplantation Network among mild to moderate immunological risk living-donor KTRs, defined as having first transplant and panel reactive antibodies less than 20% but with two HLA-DR mismatches. KTRs were divided into two groups based on induction therapy with either thymoglobulin or basiliximab. Instrumental variable regression models were used to assess the effect of induction therapy on acute rejection episodes, serum creatinine levels and graft survival. Results Of the entire cohort, 788 patients received basiliximab while 1727 patients received thymoglobulin induction. There were no significant differences between basiliximab versus thymoglobulin induction in acute rejection episodes at one-year post-transplant (coefficient= −0.229, p value = .106), serum creatinine levels at one-year post-transplant (coefficient= −0.024, p value = .128) or death-censored graft survival (coefficient: − <0.001, p value = .201). Conclusion This study showed no significant difference in acute rejection episodes or graft survival when using thymoglobulin or basiliximab in mild to moderate immunological risk living donor KTRs, maintained on tacrolimus and mycophenolate-based immunosuppressive regimen.