Instrumental Variable Regression Research Articles

Persistent Agricultural Shocks and Child Poverty

This study shows how persistent agricultural shocks in Ethiopia affect education, health and labor outcomes through a time-use study of young people aged 5-22. Leveraging five rounds of the Young Lives Study from 2002-2016, we use dynamic panel instrumental variable regressions to account for the unobserved heterogeneity and serial correlation in the estimation. Agricultural shocks significantly reduce schooling participation and time spent in schooling, deteriorate health, and increase both labor force participation and labor time. Household wealth acts as a buffer and mitigates the adverse effects of shocks on schooling. Interestingly, children from wealthier households have a higher likelihood of joining agricultural labor during shocks, but their intensity of child labor is significantly lower compared to poorer households.

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).

Foreign institutional investors and the value of excess cash holdings: international evidence

Purpose Using a comprehensive sample from developed and emerging economies, this study aims to examine whether foreign institutional investors (FIIs) enhance the value of excess cash by constraining the potential self-appropriating managerial propensity related to its inefficient utilization. Design/methodology/approach This study uses a large panel data set of firms from 32 non-US countries from 2007 to 2018. Using data from COMPUSTAT Global and S&P Capital IQ, this study uses ordinary least squares regression with year- and firm-fixed effects for the baseline analysis. In addition, two-stage least squares with instrumental variable regression and propensity score matching approaches were used to address the potential endogeneity. Findings This study shows that FIIs significantly increase the value of excess cash holdings. The authors also found that the positive impact of FIIs is more significant when investors come from common-law countries with better governance and investor protection. Furthermore, in countries and firms with weaker governance controls, the relationship between FIIs and the value of excess cash is stronger, consistent with the institutional monitoring hypothesis. Collectively, the findings imply that FIIs are advantageous to investees because they effectively promote the efficient deployment of corporate resources. Practical implications Collectively, the findings of this study imply that FIIs are advantageous to investees because they effectively promote the efficient deployment of corporate resources. Originality/value This study offers new evidence on how FIIs impact the value of excess cash in an international setting. In addition, it highlights the significance of the legal origin of institutional investors’ home country and the governance quality of host countries and investee firms in influencing the effect of foreign institutional monitoring on the value of excess cash.

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.

Lipids, cholesterols, statins and liver cancer: a Mendelian randomization study.

To investigate the causal relationship of serum lipid indicators and lipid-lowering drugs with the risk of liver cancer using Mendelian randomization study. A two-sample Mendelian randomization (TSMR) study was performed to investigate the causal relationship between serum levels of lipid indicators and liver cancer, including low-density lipoprotein cholesterol (LDL-c), high-density lipoprotein cholesterol (HDL-c), triglycerides (TG), total cholesterol (TC), Apolipoprotein B (ApoB), and Apolipoprotein A1 (ApoA1).Furthermore, instrumental variable weighted regression (IVW) and summary data-based MR (SMR) analyses were performed to investigate the causal effects of lipid-lowering drugs, including statins and PCSK9 inhibitors, on the risk of liver cancer. Serum LDL-c and serum TC levels showed negatively associated with liver cancer (n = 22 SNPs, OR = 0.363, 95% CI = 0.231 - 0.570; p = 1.070E-5) (n = 83 SNPs; OR = 0.627, 95% CI = 0.413-0.952; p = 0.028). However, serum levels of TG, HDL-c, and ApoA1 did not show any significant correlation with liver cancer. In the drug target MR (DMR) analyses, HMGCR-mediated level of LDL-c showed an inverse relationship with the risk of liver cancer in the IVW-MR analysis (n = 5 SNPs, OR = 0.201, 95% CI = 0.064 - 0.631; p = 5.95E-03) and SMR analysis (n = 20 SNPs, OR = 0.245, 95% CI = 0.065 - 0.926; p = 0.038) However, PCSK9 did not show any significant association with liver cancer based on both the IVW-MR and SMR analyses. Our results demonstrated that reduced levels of LDL-c and TC were associated with an increased risk of liver cancer. Furthermore, lipid-lowering drugs targeting HMGCR such as statins were associated with increased risk of liver cancer.

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 .....

Can a firm's hierarchical complexity affect its stock price behavior? Evidence from stock price crash risk

PurposeThis paper examines how a firm's hierarchical complexity, which is determined by the way it organizes its subsidiaries across the hierarchical levels, can impact its stock price crash risk.Design/methodology/approachThe authors employ a measure of hierarchical complexity that captures the depth and breadth of how subsidiaries are organized within a firm. This measure is calculated using information about firms' subsidiaries extracted from the Bureau van Dijk (BvD) database that allows the authors to construct each firm's hierarchical structure. The data sample includes 2,461 USA firms for the period from 2012 to 2017 (11,006 firm-year observations). Univariate tests and panel regression are used for the main analysis. Two-stage-least-squares (2SLS) instrumental variable regression and various other tests are employed for robustness check.FindingsThe results show a positive relationship between hierarchical complexity and stock price crash risk. This relationship is amplified in firms with a greater number of subsidiaries that are hierarchically distanced from the parent company as well as in firms with a greater number of foreign subsidiaries in countries with weaker rule of law.Originality/valueThis paper is the first to investigate the impact hierarchical complexity has on crash risk. The results highlight the role that a firm's organizational structure can have on asset pricing behavior.

Urban Economic Efficiency, Environmental Factors, and Digital Finance: Impacts on Sustainable Development in Chinese Cities

This study investigates the potential of digital finance to mitigate the environmental impact of economic development. Utilizing panel data from 290 Chinese cities between 2011 and 2019, we employ a two-way fixed effects model to control for unobservable city characteristics and time-invariant macro factors. Our findings reveal that cities with higher proportions of value-added tax and secondary industries (mainly for manufacturing) tend to experience increased air pollution. Conversely, cities characterized by higher economic efficiency exhibit better air quality, underscoring the significance of prioritizing technology-intensive sectors during economic development. Pollution control technologies, such as centralized wastewater treatment systems and harmless treatment systems for household waste, also play positive roles. Moreover, technological and educational investments correlate with increased urban green coverage and lower air pollution, highlighting the pivotal role of technology development and residents’ literacy in fostering sustainable practices. Although we initially observed a positive association between the index of digital financial technology and air pollution, which could be attributed to the influence of economic growth, our study employs instrumental variable regression to unveil their true correlation. The results suggest the application of digital financial technology may enhance environmental awareness, contributing to the mitigation of air pollution.

Digital “is” Strategy: The Role of Digital Technology Adoption in Strategy Renewal

As digital technologies emerge and improve rapidly, firms face changing tradeoffs in terms of their technology infrastructure and strategic direction. Hence, many of them adopt new digital technology and develop new business models and strategies. The literature on strategic alignment of IT suggests that firms need to synchronize these different domains of choice. We therefore, ask how far firms renew their strategy as they adopt new technologies. In this article, we study this question empirically by assessing if the adoption of new digital technologies is associated with, or even leads to, changes to firm strategy using a detailed survey-based dataset on firms’ strategy renewal and their adoption of digital technologies. We observe a strong positive association between the extent of strategy change and the stage of adoption of advanced digital technologies overall, suggesting a tight coupling between (technological) structure and strategy. Further, using instrumental variable regressions to disentangle the two effects, we find that the adoption of new technologies may lead to a large and robust effect on strategy change: the more extensive the adoption, the larger the change in strategy. This result is robust to various specifications and across industries. However, we notice substantial differences across technologies, potentially pointing at heterogeneity in their strategic nature or maturity level.

The Impact of Subjective Poverty on the Mental Health of the Elderly in China: The Mediating Role of Social Capital.

Reducing subjective poverty among the elderly is an important aspect of poverty governance and is a necessary part of implementing the healthy aging strategy in China. In both China and the majority of low- and middle-income countries, systematic research on the relationship between subjective poverty and the mental health of the elderly needs to be expanded. In this study, we aimed to examine how social capital, including bonding and bridging social capital, mediate the relationship between subjective poverty and mental health among the elderly in China. Relying on the 2018 Chinese Longitudinal Healthy Longevity Survey (CLHLS) data, we used ordered probit (oprobit) regression, propensity score matching (PSM), and instrumental variable (IV) regression to estimate the effects of subjective poverty on mental health. The results indicate that subjective poverty has a significant negative impact on the mental health of the elderly in China. More importantly, social capital, including bonding and bridging social capital, partially mediates the relationship between subjective poverty and mental health. We believe that, in the process of implementing the government's healthy aging strategy in China, society and government should recognize the importance and value of subjective poverty governance for the elderly. In particular, the construction of a social relationship network that centers on bonding and bridging social capital could be instrumental in dealing with subjective poverty among the elderly and safeguarding their mental health and wellbeing.

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.

Inference under covariate-adaptive randomization with imperfect compliance

This paper studies inference in a randomized controlled trial (RCT) with covariate-adaptive randomization (CAR) and imperfect compliance of a binary treatment. In this context, we study inference on the local average treatment effect (LATE), i.e., the average treatment effect conditional on individuals that always comply with the assigned treatment. As in Bugni et al. (2018, 2019), CAR refers to randomization schemes that first stratify according to baseline covariates and then assign treatment status so as to achieve “balance” within each stratum. In contrast to these papers, however, we allow participants of the RCT to endogenously decide to comply or not with the assigned treatment status.We study the properties of an estimator of the LATE derived from a “fully saturated” instrumental variable (IV) linear regression, i.e., a linear regression of the outcome on all indicators for all strata and their interaction with the treatment decision, with the latter instrumented with the treatment assignment. We show that the proposed LATE estimator is asymptotically normal, and we characterize its asymptotic variance in terms of primitives of the problem. We provide consistent estimators of the standard errors and asymptotically exact hypothesis tests. In the special case when the target proportion of units assigned to each treatment does not vary across strata, we can also consider two other estimators of the LATE, including the one based on the “strata fixed effects” IV linear regression, i.e., a linear regression of the outcome on indicators for all strata and the treatment decision, with the latter instrumented with the treatment assignment.Our characterization of the asymptotic variance of the LATE estimators in terms of the primitives of the problem allows us to understand the influence of the parameters of the RCT. We use this to propose strategies to minimize their asymptotic variance in a hypothetical RCT based on data from a pilot study. We illustrate the practical relevance of these results using a simulation study and an empirical application based on Dupas et al. (2018).

How does Financial Development Affect Regional Economic Growth in China? A Mediating Role of Industrial Structure Optimization

<p style="text-align: justify;">Financial development and industrial structure optimization are two-wheeled engines for promoting high-quality development, but the causal identification of the two is still poorly understood. This paper addresses this research gap by comprehensively analyzing the relationship between them. Regional economic growth is a necessary condition for achieving high-quality development. Taking China as an example, this study empirically examines the role of financial development and industrial structure optimization in high-quality development using the entropy method, fixed effects, mediation effects and instrumental variable regression. The study results show that (i) financial development has actively promoted regional economic growth. (ii) The driving effect on the central and western regions is greater than that on the eastern region. (iii) There are differences in the mediating effect of industrial structure optimization and rationalization between different levels of financial development and economic growth. (iv) In addition, the mediating effect of industrial structure optimization is larger in the eastern region than in the central and western regions. (v) The mediating effect of industrial structure rationalization is not obvious in the eastern region, but has a masking effect in the central and western regions. Our findings provide new strategies for financial development and industrial structure optimization in developing countries.</p>

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.

Diverse Hedge Funds

Abstract Hedge fund teams with heterogeneous educational backgrounds, academic specializations, work experiences, genders, and races, outperform homogeneous teams after adjusting for risk and fund characteristics. An event study of manager team transitions, instrumental variable regressions, and an analysis of managers who simultaneously operate solo- and team-managed funds address endogeneity concerns. Diverse teams deliver superior returns by arbitraging more stock anomalies, avoiding behavioral biases, and minimizing downside risks. Moreover, diversity allows hedge funds to circumvent capacity constraints and generate persistent performance. Our results suggest that diversity adds value in asset management. Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online

ESG ratings and corporate financial performance in South Africa

PurposeThis paper examines the effect of ESG ratings and its dimensions (environmental, social and governance) on the financial performance of JSE-listed firms included in FTSE/JSE Responsible Investment Index.Design/methodology/approachThe paper employs panel data covering 40 JSE-listed firms included in FTSE/JSE Responsible Investment Index between 2015 and 2019. The paper employs the two-stage least squares (2SLS) instrumental variable regression technique to estimate the effect of ESG ratings and its dimensions (environmental, social and governance) on both accounting- and market-based performance indicators.FindingsThe results of the two-stage least squares instrumental estimation analysis reveal that investment in ESG initiatives improves both accounting- and market-based indicators of financial performance. Of the ESG pillars, the paper finds environmental initiatives improves firms' financial bottom line and market performance, while a firm's social and governance practices are observed to have no effect on a firm's accounting and market performance measures.Practical implicationsThe insights from this study proffers policy implications for firms' management, investors and regulatory authorities.Originality/valueAs far as the authors are concerned, this paper presents the first empirical analysis on the contribution of ESG ratings on financial performance in South Africa.

A New Instrumental-Type Estimator for Quantile Regression Models

This paper proposes a new instrumental-type estimator of quantile regression models for panel data with fixed effects. The estimator is built upon the minimum distance, which is defined as the weighted average of the conventional individual instrumental variable quantile regression slope estimators. The weights assigned to each estimator are determined by the inverses of their corresponding individual variance–covariance matrices. The implementation of the estimation has many advantages in terms of computational efforts and simplifies the asymptotic distribution. Furthermore, the paper shows consistency and asymptotic normality for sequential and simultaneous asymptotics. Additionally, it presents an empirical application that investigates the income elasticity of health expenditures.

Sensitivity analysis of G-estimators to invalid instrumental variables.

Instrumental variables regression is a tool that is commonly used in the analysis of observational data. The instrumental variables are used to make causal inference about the effect of a certain exposure in the presence of unmeasured confounders. A valid instrumental variable is a variable that is associated with the exposure, affects the outcome only through the exposure (exclusion), and is not confounded with the outcome (exogeneity). Unlike the first assumption, the other two are generally untestable and rely on subject-matter knowledge. Therefore, a sensitivity analysis is desirable to assess the impact of assumptions' violation on the estimated parameters. In this paper, we propose and demonstrate a new method of sensitivity analysis for G-estimators in causal linear and non-linear models. We introduce two novel aspects of sensitivity analysis in instrumental variables studies. The first is a single sensitivity parameter that captures violations of exclusion and exogeneity assumptions. The second is an application of the method to non-linear models. The introduced framework is theoretically justified and is illustrated via a simulation study. Finally, we illustrate the method by application to real-world data and provide guidelines on conducting sensitivity analysis.

The effects of amended sustainability reporting requirements on corporate social responsibility reporting and firm value: the moderating role of assurance

Purpose To assist Malaysian public-listed companies (PLCs) in preparing corporate social responsibility (CSR) reports, Bursa Malaysia Berhad (BMB) launched the second edition of the Sustainability Reporting Guide (SRG) in 2018. This new SRG edition has several additional requirements for CSR reporting (CSRR), the most important of which is a chapter on assurance which provides detailed guidance on how it may be carried out. This study aims to determine whether the new SRG edition influences the extent of CSRR, and whether such effect is moderated by the provision of assurance on CSRR. It also aims to identify whether amending CSRR regulations and providing assurance on such reporting indirectly influences firm value through the possible improvement in the extent of CSRR. Design/methodology/approach This study performed a content analysis of the CSRR of a sample of Malaysian PLCs that maintained their positions among the top 100 companies by market capitalization between 2017 and 2020 to determine the extent of CSRR for the two years before and two years after the implementation of the new edition of SRG. This study conducted different statistical analyses to indicate whether the implementation of the second edition of SRG has an effect on enhancing the extent of CSRR, and whether the provision of assurance on such reporting moderates such an effect. This study then used instrumental variable regressions to examine the influence of the predicted extent of CSRR on firms’ value measured by Tobin’s Q. Findings This study found that the implementation of the second edition of SRG has a positive and significant influence on the extent of CSRR. This effect is strengthened by the provision of assurance on CSRR. Instrumental variable regressions also indicate that enhancing the extent of CSRR affected by the second edition of SRG is linked to higher firm value. Originality/value To the best of the authors’ knowledge, this study is one of the first to assess the determinants and implications of CSRR among Malaysian companies after adopting the second edition of SRG.