90th Quantile Research Articles

COVID-19 pandemic and financial market volatility: A quantile regression approach

The study examined the nexus between the COVID-19 pandemic and the market volatility of the global markets. For this purpose, a 30-country sample was used based on the most COVID-19 cases and deaths during the study period, from January 1 to December 12, 2020. We employed panel quantile regression and Panel Estimated Generalized Least Square (Panel-EGLS) frameworks to analyze the influence of COVID-19 on volatility in the whole sample and subsamples of emerging and developed markets. Our results of Panel-EGLS showed that the new cases and deaths positively impact volatility in the naïve and control models. The results from quantile regression also illustrated that new deaths and cases have positively influenced market volatility at the 50th and 75th quantiles. From the subsamples, our results demonstrate almost similar signs and significance for the impact of COVID-19 on market volatility in developed and emerging markets in both the naïve and control models. Both the results illustrate that any increase in COVID-19 positively caused volatility in the whole and subsamples at the mean and upper quantile levels. Our results necessitate coordinated global government actions to stabilize markets, mitigate volatility's impact by proactive policies in future health crises, and underscore a monetary policy for stability.

Natural resources rent and climate vulnerability: An inverted U-shaped relationship moderated by productive capacity, trade openness, and urbanization in resource-abundant countries

Natural resources play a pivotal role in the global economy, with numerous nations leveraging their extraction, utilization, and exportation as primary drivers for economic advancement. Nonetheless, an overreliance on these resources can expose countries to the adverse effects of climate change, including droughts, floods, and other extreme climatic events, thereby jeopardizing production and revenue streams. Paradoxically, the revenues derived from natural resource extraction can be channeled towards initiatives aimed at climate change mitigation and adaptation, underscoring the intricate interplay between natural resources and climate vulnerability. This research endeavors to elucidate the inverted U-shaped relationship between total natural resources rent and climate vulnerability. The study encompasses nineteen resource-rich countries over the period 2000–2021. Employing the panel quantile ARDL (Auto-Regressive Distributed Lag) methodology with a dynamic fixed effect specification, we delve into the moderating influence of overall productive capacity, trade openness and urbanization on the nexus between resource extraction and climate vulnerability. The panel QARDL estimations are segmented into the 25th, 50th, and 75th quantiles for both long-term and short-term outcomes. In the long-term perspective, our findings validate an inverted U-shaped association between total natural resources rent and climate vulnerability. Factors such as urbanization and trade openness exhibit a positive correlation with climate vulnerability, whereas economic growth demonstrates an inverse relationship. Significantly, the study reveals that productive capacity, when acting as a moderator for natural resources rent, holds the potential to attenuate climate vulnerability.

Modelling the impact of climate change and advanced agricultural technologies on grain output: Recent evidence from China

The adverse effect of rising temperatures on grain output is gradually spreading across China. On the other hand, technical developments have resulted in substantial changes in the agricultural production system over time. Hence, we assess the effect of temperature on grain yields in addition to the potential effect of some technological factors using a panel dataset spanning the period 1996 to 2020 for selected prominent grain-producing provinces in China: Anhui, Hebei, Heilongjiang, Henan, Hubei, Hunan, Jiangsu, Jiangxi, Jilin, Neimenggu, Shandong, Sichuan, and Liaoning. We apply a novel Method of Moments Quantile Regression (MM-QR) and second–generation estimation techniques, which generate consistent and robust results in the presence of cross–sectional dependency (CSD). The empirical findings from the MM-QR estimator reveal that climate change (via temperature) significantly decreases the grain yields in overall quantiles and the higher negative impact was observed in the 75th and 95th quantiles, while technical factors, irrigated area, and financial support play a substantial role in improving the grain yields in China. In addition, the findings from the D–H panel causality method show the various flows of causal links between the selected variables, considering the grain–producing regions of China: grain yields → temperature, pesticide usage → grain yields, and financial support → grain yields. A bidirectional causality association is observed to exist between fertilizer usage ↔ grain yields, pesticide usage ↔ grain yields, and irrigated area ↔ grain yields. To ensure food security, China's prominent grain–growing regions should strengthen their technological innovation efforts and invest in research and development to produce new varieties that can withstand heat and drought stress and produce better grain yields.

Effect of Sustainable Development and Institutional Quality on Growth

The issue of compatibility of sustainable development policies, institutional quality, and economic growth gains on importance as the world races towards achieving the 2030 Agenda for Sustainable Development. This paper aims to examine the relationship between sustainable development, institutional quality, and economic growth between the years 2012 and 2021 in 116 countries. The quantile regression method has been employed in this study to capture various relationship nexuses in different quantiles of growth. The common 15th, 25th, 50th, 75th and 95th quantiles have been selected. The official Sustainable Development Goals (SDG) Index is applied to proxy the holistic conceptualization and policy achievement of the United Nation’s SDGs. The findings show a negative relationship between sustainable development and economic growth, indicating that achieving sustainable development goals will harm the economic growth. Increasing negative coefficient values from lower to higher quantiles imply increasing opportunity cost of degrowth towards increasing sustainable development. Besides, institutional quality did not affect economic growth, either directly or indirectly. The study suggests the necessity to review the existing policies, institutional structures, and strategies to foster compatibility between sustainable development, institutional quality, and growth.

A hedonic analysis of the determinants of hotel room rates in the Greater Gaborone Region (Botswana) using quantile regression

PurposeThe purpose of this study is to examine the influence of key hotel attributes on the room rates of selected hotels in the Greater Gaborone Region, Botswana.Design/methodology/approachUsing hedonic pricing analysis, the effect of eight attributes collected from 80 standard double rooms on Booking.com in the area was analysed using quantile regression.FindingsThe estimated results from quantile regression suggested the importance of the 10th quantile as the best predictor of hotel room price distribution. Overall, the presence of a fitness centre and the availability of meeting and conference facilities were positively significant for the lowest- and premium-priced hotels, respectively.Research limitations/implicationsThe study advanced the literature in hedonic pricing models by confirming the applicability of hotel room rate attribute research in unexplored environments.Practical implicationsHotel managers should be aware of the influence of key attributes, such as meeting and conference space availability and locational factors, on the pricing decisions of room rates in the Greater Gaborone Region. The study also presented opportunities for business-to-business marketing between hotel and tour operators in the region.Originality/valueThe study is one of the few that uses quantile regression in the hedonic pricing analysis of hotel room rates.

Global value chains and economic complexity index: Evidence from generalized panel quantile regression

This paper investigates the impact of global value chains (GVCs) participation on economic complexity for a sample of underdeveloped, moderately developed, and developed countries which includes 42 economies from 2000 to 2018. Our empirical analysis finds that the influence of GVC participation on economic complexity varies across quantiles as it has adverse and significant effects on economic complexity in the first five lower quantiles (5th - 25th). It indicates that GVC participation has adverse impacts on economic complexity except for the economy with higher economic complexity. Moreover, forward participation is negatively associated with economic complexity in all the quantiles except for the 90th quantile. In countries with lower and moderate economic complexity, forward participation has a negative impact on how complex the economy is. Alongside, backward participation has positive and significant impacts on economic complexity in the 85th, 90th, and 95th quantiles implying that in a more complex economy, backward participation is positively correlated with economic complexity.

The Role of Mobile Money Innovations in the Effect of Inequality on Poverty and Severity of Poverty in Sub-Saharan Africa

This study investigates the role of mobile money innovations in the incidence of income inequality on poverty and severity of poverty in 42 sub-Saharan African countries over the period 1980 to 2019. Mobile money innovations are understood as the mobile used to send money and the mobile used to pay bills online while income inequality is measured with the Gini index. Poverty is measured as the poverty headcount ratio while the severity of poverty is generated as the squared of the poverty gap index. The empirical evidence is based on interactive Quantile regressions. The following main findings are established. (i) Income inequality unconditionally reduces poverty and the severity of poverty though the significance is not throughout the conditional distributions of poverty and the severity of poverty. (ii) Mobile money innovations significantly moderate the positive incidence of income inequality on poverty and the severity of poverty in some quantiles. (iii) Positive net effects are apparent exclusively in the poverty regressions. (iv) Given the negative conditional effects, policy thresholds or minimum mobile money innovation levels needed to completely nullify the positive incidence of income inequality on poverty are provided: 27.666 (% age 15 +) and 24.000 (% age 15 +) of the mobile used to send money in the 50th and 75th quantiles, respectively and 16.272 (% age 15 +) and 13.666 (% age 15 +) of the mobile used to pay bills online in the 10th and 50th quantiles, respectively. Policy implications are discussed with respect of SDG1 on poverty reduction and SDG10 on inequality mitigation.

The impact of cryptocurrencies on the gold, WTI, VIX index, G7 and BRICS index before and during COVID-19: a quantile regression and NARDL analysis

PurposeThis study aims to explore the impact of cryptocurrencies (Bitcoin, Ethereum, Monero and Ripple) on the gold, WTI, VIX index, G7 and the BRICS index before and during COVID-19.Design/methodology/approachThis research analyzes the impact of cryptocurrencies (Bitcoin, Ethereum, Monero and Ripple) on the gold, WTI, VIX index, G7 and the BRICS index before and during COVID-19, using the quantile regression approach for the 2016–2020 period. In addition, to catch long- and short-run asymmetries of cryptocurrencies on aforementioned dependent variables, an asymmetric nonlinear co-integration (nonlinear autoregressive distributed lag [NARDL]) approach is applied.FindingsThe result of the quantile regression shows that in a high market, which corresponds to the 90th quantile, the FTSE MIB, CAC40, SSE, BSE 30, and BVSP stock market showed a statistically insignificant negative coefficient, on the Bitcoin price. In a middle and low markets, which correspond to the 0.2, 0.3 and 0.5th quantiles, the BVSP, FTSE MIB, S&P/TSX, SSE and Nikkei stock markets show statistically significant and positive on Bitcoin. Evidence from the NARDL shows a statistically significant positive impact of cryptocurrencies on the gold, WTI, VIX index, G7 and BRICS indices before and during COVID-19 pandemic.Originality/valueThese results can provide investors with valuable analysis and information and help them make the best decisions and adopt the best strategies. Therefore, future investigations may concentrate and examine the monetary and governmental policies to be adapted to face the COVID-19 pandemic’s dangerous effects on both the society and the economy. For this reason, investors should take this into account when making their asset allocation decisions. Moreover, the portfolio managers, such as index funds, may consider few eligible cryptocurrencies for their inclusion into the portfolio. However, the speculators present in both stock and crypto markets may opt for a spread strategy to improve their portfolio returns.

Beyond sleep duration: Sleep timing is associated with BMI among Brazilian adults

ObjectivesTo examine the association of sleep duration and timing with BMI among adults. Also, to identify obesogenic and unhealthy behaviors (e.g.diet/sleep quality, physical activity, screen time, smoking) associated with short sleep duration and late bedtime. ParticipantsParticipants (n=755) were part of exploratory, population-based research, with data collection in a virtual environment. MethodsFor purposes of characterizing the population we considered short sleepers<7h/night, and the population bedtime median was used to stratify participants into early and late sleepers (before and after 23:08). Student's t-test and chi-square test were performed to assess differences in characteristics between groups. Linear regression analyses were conducted to determine the association of sleep duration, bedtime, and wake-up time with BMI. Quantile regression was estimated for the 25th, 50th, and 75th quantiles to identify the distributional correlations between BMI and sleep variables. Restricted cubic splines were also used to study the shape of the association between sleep-BMI. Analyses were adjusted for potential confounding variables. ResultsBMI decreased by 0.40Kg/m2 for each additional hour of sleep duration [95%CI=-0.68,-0.12,p=0.005] and increased by 0.37 kg/m2 for each additional hour of bedtime [95%CI=0.12,0.61,p=0.003]. The association between bedtime and BMI remained even after adjustment for sleep duration. These effects were higher and stronger with higher BMI values (p75th). Wake-up time did not show statistically significant associations. ConclusionsBecause we found that beyond sleep duration, bedtime was significantly associated with BMI, our data reflect the pertinence of assessing sleep timing patterns in disentangling sleep-obesity association. Insights into the characteristics, obesogenic and unhealthy behaviors related to short and late sleep may support specific strategies to prevent and treat excess body adiposity and other negative health outcomes.

Role of circular economy, energy transition, environmental policy stringency, and supply chain pressure on CO2 emissions in emerging economies

This paper investigates the effect of the circular economy on CO2 emissions growth by considering the role of energy transition, climate policy stringency, industrialization, and supply chain pressure from 1997 to 2020 using panel quantile Autoregressive Distributed Lags (QARDL) and the panel PMG. We employ cointegration association in the long run among the variables, and the results of the two models confirm this. Findings reveal that circular economy and climate policy stringency significantly negatively impact carbon emissions. On the other hand, the energy transition, industrialization, and supply chain pressures are crucial to determining CO2 emissions in the short and long run. The finding further explores that municipal waste generation recycling is considerable at the mean and upper 90th quantiles than the lower quantile. Therefore, the empirical results of the current study provide acumens for policymakers of advanced economies and emerging markets to maintain the balance among circular economy, energy transition, environmental policy stringency, and supply chain pressure for reducing CO2 emissions without halting economic growth and sustainable development. Furthermore, practical implications are reported through the lens of carbon neutrality and structural changes.

Does unemployment in sub-Saharan Africa have asymmetric effects on health? A panel quantile approach

This study examines the heterogeneous impact of unemployment on health (i.e., life expectancy and under-five mortality) using unbalanced panel data for 48 countries in sub-Saharan Africa (SSA) from 2000 to 2020. We applied Generalized Quantile Regression in an instrumental framework with multi-criteria MCMC (Markov Chain Monte Carlo) optimization to address the endogeneity (simultaneous bias, omitted variable bias) between unemployment and health. The quantile estimation findings show that the impact of unemployment is heterogeneous (i.e., non-linear/asymmetric) across health outcomes distributions. Unemployment significantly reduces life expectancy in the 10th, 20th, 30th, 50th, 60th, 80th, and 90th quantiles while increasing under-five mortality in the 10th, 50th, 60th, and 70th quantiles. The possible mechanism influencing the unemployed to have negative health effects could be the role of poverty associated with a lack of income. Meanwhile, the life expectancy of the unemployed in the 40th quantile is increasing significantly, which may be linked to the fact that more physical activity has a positive effect on their health. Similarly, unemployment significantly reduces under-five mortality in the 20th, 40th, 80th, and 90th quantiles, and the possible mechanism for the unemployed to reduce under-five mortality may be through financial support from family members who can help them buy nutritious food and provide medical care for children. Bayesian robustness tests support evidence prior to the COVID-19 outbreak that unemployment increases under-five mortality and creates uncertainty about life expectancy from 2000 to 2019. Overall, the findings for the period 2000–2020 confirm that unemployment has asymmetric (positive and negative) effects on health in SSA. The findings suggest two conclusions. First, unemployment is linked to poor health (lower life expectancy) and higher mortality in sub-Saharan Africa. Second, not all unemployment in the region is unhealthy. The policy implications for SSA countries are outlined.

Disparities in access to high-volume centers and in hospital discharge status following radical cystectomy in Florida.

Centralization of radical cystectomy (RC) improves outcomes but may unintentionally exacerbate existing disparities in care. Our objective was to assess disparities in access to high-volume RC centers and in postoperative recovery. We identified RC patients in the Florida Inpatient Data File from 2013 to 2019. Hospital annual cystectomy volume was categorized as low, medium, or high using data-derived 75th and 90th quantiles: <5, 5 to 13, and >13 RC/year. Outcomes included inpatient mortality, non-home discharge, in-hospital complications, length of stay (LOS) and surgery in a low-volume hospital. Mixed-effects regression models accounting for clustering within centers were utilized. Among 4,396 patients treated at 105 centers, RC at a high-volume center was associated with lower odds of mortality, non-home discharge, shorter length of stay and fewer complications (all P ≤ 0.001). Characteristics associated with receiving care in a low-volume hospital included Black race (OR 1.67, 95% CI 1.14-2.39), Hispanic/Latino ethnicity (OR 1.74, 95% CI 1.32-2.00), and residing in northeast (OR 2.11, 95% CI 1.58-2.80) or west Florida (OR 1.34, 95% CI 1.05-1.71). Black patients had increased odds of non-home discharge (OR 1.91, 95% CI 1.27-2.86) and longer LOS (IRR 1.17, 95% CI 1.08-1.27), but no difference in the rate or number of postoperative complications (P > 0.2). In Florida, we observed racial and geographic disparities in likelihood of undergoing RC at a high-volume hospital, and that Black patients experienced longer LOS and lower odds of home discharge despite similar rates of complications. Efforts to increase access to high-value RC care for these vulnerable populations are needed.

Health performance and economic growth in sub-Saharan Africa: new evidence based on quantile regressions

PurposeThe present study investigates the nexus between health performance dynamics and economic growth in 43 countries in sub-Saharan Africa for the period 2004–2018.Design/methodology/approachFour health performance dynamics are used, notably: total life expectancy, male life expectancy, female life expectancy and risk of maternal death. The empirical evidence is based on quantile regressions (QRs) in order to put into perspective the conditional distribution of economic growth.FindingsThe following findings are established: (1) total life expectancy and male life expectancy increase economic growth exclusively in the 10th and 90th quantiles of economic growth; (2) female life expectancy boosts economic growth in the 90th quantile of economic growth and (3) the risk of maternal death reduces economic growth in the 75th and 90th quantiles of economic growth. Policy implications are discussed.Originality/valueThe study complements the literature on the nexus between health performance and economic growth by assessing the nexuses throughout the conditional distribution of economic growth.

Breaking down the complexity of sustainable development: A focus on resources, economic complexity, and innovation

The escalating global concern regarding climate change has necessitated the adoption of green innovation and pollution mitigation as crucial steps toward realizing sustainable economic development. This research fills a gap in the literature by studying the impacts of economic complexity, green innovation, and natural resource rent on trade-adjusted carbon emissions in G-7 economies. Our empirical findings suggest that there has been a substantial decline in the carbon emissions of the G-7 nations, largely attributable to the increasing complexity of their economies. The results also reveal a significant inverse relationship between CO2 emissions and green innovation. Interestingly, the impact of natural resource rent on CO2 emissions is positive at the 25th quantile but significantly negative at the 75th and 90th quantiles. In addition, economic growth was found to exert a positive influence on carbon emissions, whereas environmental taxes and energy productivity were found to have a negative effect on carbon emissions, thereby aiding in the attainment of carbon neutrality. These findings suggest that regulators and policymakers should prioritize economic complexity, natural resources, energy productivity, and green innovation to meet G-7's environmental sustainability goals.

Renewable energy R&D and natural resources: A success story of environmentally friendly financing in OECD economies

Sustainable development is increasingly important in today's world as it combines social and economic progress with environmental protection, and few studies have examined renewable energy R&D and natural resources rent as important components of achieving a sustainable future. Therefore, this study addresses the gap in the literature by exploring the influence of renewable energy R&D, and natural resources rent on consumption-based carbon emissions for OECD economies from 1990 to 2020. The results obtained using the method of moment quantile regression indicate that renewable energy R&D plays a crucial role in mitigating carbon emissions, with its impact being more pronounced at higher quantiles. The results for natural resources rent show an adverse effect on environmental pollution at the 25th and 50th quantiles, whereas, at the 75th and 90th quantiles, the impact is positive but insignificant. The results for imports and economic growth have a significant positive influence on environmental pollution, while exports have a negative relationship with carbon emissions. Policymakers can decrease carbon emissions to improve environmental quality and enhance economic development in OECD economies by investing in renewable energy R&D and sustainable management of natural resource rent.

The Relationship Between Iodine Excess and Thyroid Function During Pregnancy and Infantile Neurodevelopment at 18–24 Months

BackgroundThyroid disease is a prevalent condition during pregnancy, and excessive iodine intake can lead to changes in thyroid function. However, research on the relationship between maternal iodine excess, thyroid hormones during pregnancy, and infantile neurodevelopment is limited. ObjectivesThis study aimed to explore the relationship between maternal iodine excess and thyroid hormones during pregnancy and infantile neurodevelopment. The objective was to provide evidence to support and enhance the prevention of neurodevelopmental retardation in infants. MethodsFrom 2016 to 2018, a prospective study was conducted from pregnancy to 18–24 mo postpartum. Maternal urinary iodine concentration (UIC), thyroid-stimulating hormone (TSH), total serum iodine (TSI), and nonprotein-bound serum iodine during pregnancy were determined. The Gesell Development Scale was used to assess neurodevelopment of infants aged 18–24 mo. The iodine status of pregnant females was divided into following 4 groups on the basis of the distribution of maternal UIC: <100 μg/L (moderate deficiency), 100–149 μg/L (mild deficiency), 150–249 μg/L (sufficiency), and >250 μg/L (above requirement). ResultsOur study included 469 mother-infant pairs. Compared with the maternal UIC of 150–249 μg/L during pregnancy, risk of adaptive developmental delay was increased in infants with maternal UIC ≥250 μg/L (OR: 2.38; 95% CI: 1.06, 5.35). Pregnant females with TSI >90th quantiles were more likely to have offspring with language developmental delay than those with lower TSI in 10th–90th quantiles (OR: 3.06; 95% CI: 1.09, 8.58). Risk of fine motor developmental delay was increased in infants with maternal TSH ≥2.5 mIU/L during pregnancy (OR: 4.32; 95% CI: 1.43, 13.0). ConclusionsMaternal iodine nutritional status above requirement (UIC ≥250 μg/L or TSI >90th quantiles) during pregnancy negatively affects infantile neurodevelopment. Maternal TSH ≥2.5 mIU/L during pregnancy was an independent risk factor for infantile neurodevelopment. This trial was registered at clinicaltrials.gov as NCT03710148.

Microfinance institutions and female entrepreneurship in Sub-Saharan Africa: avoidable female unemployment thresholds

PurposeThis study aims to contribute to the extant literature by assessing how microfinance institutions (MFIs) affect female entrepreneurship, contingent on female unemployment levels.Design/methodology/approachThe study focuses on 44 countries in sub-Saharan Africa for the period 2004–2018. The empirical evidence is based on interactive quantile regressions, which put emphasis on nations with high, low and intermediate levels of business constraints. The analysis is tailored to provide avoidable female unemployment levels in the implementation of policies designed for MFIs to promote female business ownership.FindingsThe hypotheses that MFIs are favorable for female business owners and some critical rates of female unemployment should be avoided in order for the favorable incidence to be maintained is exclusively valid in the 10th quantiles of the cost of business by females and time to start-up a business by females. Policy implications are discussed.Originality/valueThis study has complemented the extant literature by providing actionable female unemployment critical masses that governments can act upon in tailoring the relevance of MFIs in the doing of business by females.

Sustainable financial risk, resources abundance and technological innovation: Evidence from resources abundance economies

The present study explores the intricate relationship between financial risk and various economic factors in the BRICS economies from 1989 to 2021. This research looks at the effects of resource abundance (RA), technological innovation (TI), energy efficiency (ENEF), and GDP on the financial risk index (FRI) to provide valuable insights into the underlying mechanisms that drive financial risk in these rapidly developing economies. Sophisticated panel data methodologies were employed to analyze the chosen panel's cross-section dependence and residual heterogeneity. Moment's quantile regression (MMQR) was used because the normality tests divulged that all covariates follow non-normal or non-parametric distributions. The study's findings revealed that RA has a symmetrical and significantly detrimental impact on FRI across all quantiles for the BRICS nations. Furthermore, it was found that at the 25th quantile, RA has a more damaging impact on FRI than at the 90th quantile. The study also discovered that TI and ENEF are positively related to FRI. Except for TI at the 25th quintile, which was not statistically significant, these results were all statistically significant at 1%. Additionally, the empirical results revealed that ENEF positively affects FRI, but the relationship does not become more pronounced as one moves up the quantile scale. The inverse relationship between GDP and FRI refutes the demand-side theory. The robustness of the findings was confirmed through the use of Bootstrap quantile regression. Based on the study findings, pertinent policies were recommended to decision-makers about the efficient use of RA, encouragement of ENEF, and developments in technological innovation. Overall, this study represents a rigorous and cutting-edge examination of a critical issue with far-reaching implications for the global economy.

Sustainability and firm performance: the role of environmental, social and governance disclosure and green innovation

PurposeThis paper aims to determine whether financial performance is affected in firms adopting separately or jointly two sustainability tools (green innovation and environmental, social and governance reporting (ESG)).Design/methodology/approachThe empirical study examines a sample of 211 S&P 500 firms over the 2011 to 2019 period and uses the quantile estimation method.FindingsThe results show that two dimensions of ESG disclosure (the social and governance dimensions) and green innovation positively affect financial performance. This result suggests that sustainability tools have a strong financial impact. The positive relationship between green innovation and financial performance is detected at the 10th quantile up to the 70th quantile. This finding suggests that financial performance needs a moderate investment in green innovation. When considering the joint effect of ESG disclosure and green innovation, our findings show that the positive impact of some ESG disclosure dimensions (social and governance) on financial performance is more observable with a moderate investment in green innovation.Originality/valueThis study highlights the prominent role of sustainability tools in financial performance. Despite the contributions of the literature, to our knowledge, the relationship between these tools and financial performance is not yet comprehensively investigated. Sustainability is less studied from the social movement perspective. This paper is among the few to study the effect of ESG reporting on financial performance in a world of green innovation.

Prevalence and risk factors of underweight among under-5 children in Bangladesh: Evidence from a countrywide cross-sectional study.

Underweight is one of the important anthropometric components of malnutrition among under-five children and is a major public health concern in Bangladesh because it contributes to mortality as well as morbidity. In designing suitable health programs and policies with the goal of attaining UN SDG Goals, it is necessary to identify the critical risk factors of under-five malnutrition. It is evident that the quantile regression produces robust estimates in the presence of outliers. However, in the context of Bangladesh, no study has been conducted considering the sequential quantile regression on this topic. Therefore, the authors aimed to find the determinants of underweight among under-5 children in Bangladesh considering the latest country representative dataset. The paper considers a weighted sample of size 7762 children are used and data were extracted from the latest Bangladesh Demographic and Health Survey (BDHS) 2017-18 data. Multivariable simultaneous quantile regression models were used to fulfill the objectives of this study. Findings depict that undernutrition affects the majority of children in the population as compared to the reference population. The WAZ-score of the child increases by 0.202 points at the 10th quantile of the conditional distribution, and by 0.565 points at the 90th quantile as we move from children of underweight to overweight women. Moreover, the WAZ scores of children from the richest families in the 10th, 50th, and 75th quantiles, respectively, are increased by 0.171, 0.016, and 0.084 points. Quantile regression revealed the results of several socioeconomic and demographic factors acting differently across the WAZ distribution. Therefore, policymakers may consider the identified risk factors to lessen malnutrition among under-5 children in Bangladesh.