Unconditional Quantile Regression Models Research Articles

Heterogeneous Effects of Volunteering on Frailty in Later Life: A Panel Quantile Regression Approach.

Decades of research indicate that volunteering is associated with better health for the volunteer beyond the selection effects based on health. However, little is known about potential heterogeneity in health outcomes associated with volunteering in the context of good or poor health. This study addresses this gap by focusing on the frailty index (FI) to investigate the volunteering-health nexus across the population frailty distribution ranging from fit to frail. Using nationally representative data from the Health and Retirement Study (person N = 34,986; 198,218 person-wave observations), we estimated unconditional quantile regression models with panel fixed effects to estimate changes in FI associated with changes in the share of volunteers in the population across the frailty distribution observed across the study period (1998-2020). Our findings demonstrated that the volunteering-FI association was heterogeneous across the frailty distribution. The association was the most potent at the higher end of the frailty distribution, suggesting that efforts to promote volunteering may yield greater benefits for older adults experiencing high levels of frailty. The current study findings provide unique and compelling evidence in support of earlier calls for considering volunteering as a public health intervention. The study findings are discussed in the context of population health outcomes and health disparities.

ICTs Use, Agroforestry Technologies’ Adoption and Crop Farmers’ Welfare: An Empirical Evidence from Southwest, Nigeria

There is a glaring shortage of studies on the impact of ICTs use on the adoption of agroforestry technologies and combined effects of ICTs use and agroforestry technologies’ adoption on farmers’ welfare. To fill the information gap, this study examined the impact of ICTs use on agroforestry technologies’ adoption and their heterogenous impacts on crop farmers’ welfare in Southwest, Nigeria. Endogenous-treatment poisson regression (ETPR) model and unconditional quantile regression (UQR) model were used to analyse the data collected from 488 respondents. The results indicated that the use of ICTs improved the adoption of agroforestry technologies which facilitate friendly environment. Also, ICTs use and agroforestry technologies’ adoption statistically and heterogeneously influenced farm revenue and household food insecurity access scale (HFIAS). Precisely, ICTs use had the highest influence on farm revenue at the lowest quantile, while agroforestry technologies’ adoption had the highest effect on household food insecurity access scale (HFIAS) at the lowest quantile. Therefore, policies that promote crop farmers’ access to ICTs should be the priority of policy makers who are interested in the welfare of crop farmers and increased farmers’ level of agroforestry technologies’ adoption.

Trade-offs under pressure? Development of urban green space under economic growth and governance

Urban green space (UGS) is susceptible to shocks from multiple sources, including the economy and governance. It is now a global policy challenge to ensure the sustainability and livability of cities. Nevertheless, available studies have reached contradictory conclusions regarding the economic impact on UGS. Using statistical data, empirical studies in the Chinese context failed to differentiate between built-up areas and municipalities and neglected data matching within the study area. To address these gaps, this study explored the relationship between the economy and UGS at various quantiles by constructing unconditional quantile regression (UQR) models using panel data from 283 Chinese cities (2001–2019). The relationship between economic growth and the total area of UGS in the municipal zone (ugs_area) and UGS coverage of built-up areas (ugs_rate) was generally positive and statistically significant, according to the analysis. Furthermore, the study observed heterogeneity in the relationship between the economy and ugs_area and ugs_rate across different quantiles, indicating a growing presence of UGS appearing in the periphery of built-up areas. Cities strived to increase ugs_area and ugs_rate to meet the National Garden City (NGC) standards. After NGC designation, ugs_area and ugs_rate decreased significantly. Moreover, the positive correlation coefficient between the economy and UGS in provincial capital cities was considerably greater than in non-provincial capital cities. This study contributes to UGS research by revealing the nonlinear impact of driving factors. In addition to distinguishing between UGS in municipal districts and those specifically in built-up areas, this study quantifies the impact of governance variables. The study provides a valuable resource for planning UGS in China and promoting harmonious integration of economic growth, governance, and UGS in rapidly developing cities.

Household income and tourism expenditure: an unconditional quantile regression approach

ABSTRACT Although a growing number of studies have investigated the nexus between income and tourism demand, little is known about the heterogeneous income elasticity of tourism expenditure. This study fills this gap by analysing the 2018 China Family Panel Studies household survey data using an unconditional quantile regression model. The findings show that tourism expenditure is income inelastic regardless of the tourism expenditure quantile. Specifically, a 1% increase in per capita household income increases per capita tourism expenditure by 0.514–0.637%. In addition, household income affects tourism expenditure heterogeneously; the effects are larger for households at the higher tourism expenditure quantiles. Furthermore, the income elasticity of tourism expenditure is larger in relatively affluent and advanced regions – it is greater in urban areas relative to rural areas and in the eastern region of China relative to its western region.

Investigating Heterogeneity in the Relationship Between Marital Satisfaction and Cognitive Health by Gender and Across the Cognitive Function Distribution.

Marital satisfaction has been established as an essential factor for promoting health and well-being in older adults. However, it is unclear whether marital satisfaction is also associated with cognitive health in this population. This study aimed to investigate the longitudinal association between marital satisfaction and cognitive function, while also exploring variations in this relationship by gender and across the cognitive function distribution. This study used 6 waves of the Korean Longitudinal Study of Ageing (KLoSA) and employed gender-stratified unconditional quantile regression (UQR) models with fixed effects (FE) to estimate the association between marital satisfaction and cognitive function across different quantiles of the cognitive function distribution. FE models controlled for unobserved individual-level confounders such as genetics, cognitive and noncognitive skills, and early childhood social and cultural background. The results of this study revealed that marital satisfaction was positively associated with cognitive function (b = 0.305), and this association was stronger in older men than in older women (b = 0.392 for older men vs b = 0.181 for older women). The UQR-FE models suggested that stronger association between marital satisfaction and cognitive function was observed among older men with lower cognitive function (b = 0.817 for 10th percentile vs b = 0.118 for 90th percentile). Among older women, no clear patterns of heterogeneity were found across the cognitive function distribution. The findings of this study highlight a significant degree of heterogeneity in the relationship between marital satisfaction and cognitive function among older men, with stronger associations observed in the lower percentiles of the cognitive function distribution. Interventions aimed at improving marital quality could be an effective strategy for promoting cognitive health in older adults, with an approach tailored to the individual's characteristics.

Educational Disparities in Hypertension Prevalence and Blood Pressure Percentiles in the Health and Retirement Study.

Hypertension and uncontrolled high blood pressure (BP) are more prevalent among less-educated older adults than those with more schooling. However, these dichotomous indicators may fail to fully characterize educational disparities in BP, a continuous measure that predicts morbidity and mortality across much of its range. This study therefore focuses on the distribution of BP, assessing educational disparities across BP percentiles in addition to disparities in hypertension and uncontrolled BP. Data are from the 2014-2016 Health and Retirement Study, a nationally representative survey of older U.S. adults (n = 14,498, ages 51-89). To examine associations between education, hypertension, and uncontrolled BP, I estimate linear probability models. To assess relationships between education and BP, I fit linear and unconditional quantile regression models. Less-educated older adults are not only more likely to have hypertension and uncontrolled BP than those with more schooling, they also have higher systolic BP across nearly the entire BP distribution. Educational disparities in systolic BP increase in magnitude across BP percentiles and are largest at the highest levels of BP. This pattern is observed for those with and without diagnosed hypertension, is robust to early-life confounders, and is only partially explained by socioeconomic and health-related circumstances in adulthood. Among older U.S. adults, the distribution of BP is compressed at lower, healthier levels for those with more education, and skewed toward the highest, most harmful levels among those with less education. Educational inequities in hypertension awareness and treatment efficacy may underlie these patterns. Implications for fundamental cause theory are discussed.

Impact of digital technology on carbon emissions: Evidence from Chinese cities

IntroductionPromoting the development of digital technology is an important step in meeting the challenge of global climate change and achieving carbon peaking and carbon neutrality goals.MethodsBased on panel data of Chinese cities from 2006 to 2020, this paper used econometrics to investigate the impact and mechanism of digital technology on carbon emissions.ResultsThe results showed that digital technology can significantly reduce carbon emission intensity and improve carbon emission efficiency. These results remained robust after changing the estimation method, adding policy omission variables, replacing core variables, and solving the endogeneity problem. Digital technology can indirectly reduce carbon emissions by promoting green technological innovation and reducing energy intensity, and it plays a significant role in the carbon emission reduction practices of carbon emission trading policies and comprehensive national big data pilot zones. The replicability, non-exclusivity, and high mobility of digital technology help to accelerate the spread of knowledge and information between different cities, which leads to a spillover effect on carbon emission reductions. Our unconditional quantile regression model results showed that digital technology’s carbon emission reduction effect continuously decreases with increases in carbon dioxide emissions.DiscussionThe results of this paper provide evidence for the potential use of digital technology in achieving the goal of carbon neutrality, which is of great significance for achieving high-quality innovation and promoting the green transformation of the economy and society.

Understanding Heterogeneity in the Relationship Between Cancer and Hand Grip Strength: A Longitudinal Analysis.

This study examined whether the relationship between cancer and hand grip strength differs by sex and along the hand grip strength distribution. Using six waves of the Korean Longitudinal Study of Ageing (KLoSA) (N = 9735), sex-stratified unconditional quantile regression models with fixed effects were used to assess sex-specific effects of cancer for patients in different quantiles of the hand grip strength distribution. Cancer diagnosis was negatively associated with hand grip strength for males, but not females, and this sex difference was statistically significant. Quantile regression models showed that the stronger association between cancer and hand grip strength is observed among males with weaker hand grip strength. No statistically significant association was found between hand grip strength and cancer in females across the entire distribution of hand grip strength. This study provided evidence of the heterogeneity in the relationship between cancer and hand grip strength.

Dairy cow longevity: Impact of animal health and farmers' investment decisions

A dairy farmer's decision to cull or keep dairy cows is likely a complex decision based on animal health and farm management practices. The present paper investigated the relationship between cow longevity and animal health, and between longevity and farm investments, while controlling for farm-specific characteristics and animal management practices, by using Swedish dairy farm and production data for the period 2009 to 2018. We used the ordinary least square and unconditional quantile regression model to perform mean-based and heterogeneous-based analysis, respectively. Findings from the study indicate that, on average, animal health has a negative but insignificant effect on dairy herd longevity. This implies that culling is predominantly done for other reasons than poor health status. Investment in farm infrastructure has a positive and significant effect on dairy herd longevity. The investment in farm infrastructure creates room for new or superior recruitment heifers without the need to cull existing dairy cows. Production variables that prolong dairy cow longevity include higher milk yield and an extended calving interval. Findings from this study imply that the relatively short longevity of dairy cows in Sweden compared with some dairy producing countries is not a result of problems with health and welfare. Rather, dairy cow longevity in Sweden hinges on the farmers' investment decisions, farm-specific characteristics and animal management practices.

Migration and wage inequality: a detailed analysis for German metropolitan and non-metropolitan regions

This study presents new evidence on immigrant-native wage gaps considering regional-specific differences between 2000 and 2019 in Germany. Using linked employer-employee-data, unconditional quantile regression models are estimated in order to assess the degree of labor market integration of foreign workers. The applied extended version of the Oaxaca-Blinder decomposition method provides evidence on driving factors behind wage gaps along the entire wage distribution. Estimated results are presented not only for the whole of West Germany but also differentiated between metropolitan and non-metropolitan areas. On average, larger wage differentials are identified in metropolitan areas with at the same time a higher presence of foreign population. Detailed decompositions show that there are not only changes in the relative importance of explanatory factors over time, but also possible sources of wage differentials shift between different points of the wage distribution. Decisive explanatory variables in this context are the practised profession and the economic sector affiliation. Distinguishing between metropolitan and non-metropolitan areas, provides evidence that especially differences in educational attainment impact wage gaps in urban areas. Regarding the size of overall estimated wage gaps, after 2012 a reversal in trend and particular increasing tendencies around median wages are revealed.

Impacto empírico do acesso a serviços financeiros na renda dos agricultores em Gana

ABSTRACT: The impact of access to financial services (AFS) and access to informal financial services (AIFS) on farmer income is examined in this study. After a multi-stage random sampling procedure, the study used a sample size of 478 people from two regions in Ghana. The endogenous treatment regression (ETR) model was used to account for selection bias while the unconditional quantile regression (UQR) model was used for a heterogenous analysis. The findings showed that education, financial literacy, IT access, farm size, and distance were all factors of access to financial services. Similarly, the findings revealed a positive and statistically significant link between household income and access to formal financial services. Similarly, there was a positive and significant association between access to informal financial services and household income. The findings showed that access to formal and informal financial services has different effects on household income. As a result, the effects of access to financial services on income varied by quantile. Based on the findings of the study, we developed policies to boost financial services accessibility as a means of increasing household income.

Stroke in women between 2006 and 2018: Demographic, socioeconomic, and age disparities.

Black Americans have a higher prevalence of stroke and stroke-related deaths than any other racial group. Racial disparities in stroke outcomes are even wider among women than men. Conventional studies have cited differences in lifestyle (i.e. smoking, alcohol consumption, etc.) and vascular risk factors between races as the source of these disparities. However, these studies fail to account for the higher prevalence of minoritized populations at the lower end of the socioeconomic distribution. This study explores differences in stroke risk factors across age and socioeconomic cohorts to determine whether comorbidities can sufficiently explain disparities at all ages and income levels. Using the 2006-2018 National Health Interview Survey data, statistical analysis evaluated differences in risk factors among a full sample cohort (aged 18-85 years; n = 131,091) and a "young" subsample cohort (aged 18-59 years; n = 6183) of women. Logistics and unconditional quantile regression models assessed the relationship between stroke and comorbid, demographic, and behavioral characteristics across socioeconomic classes. Results suggest that Black women had a 1.415-fold (confidence interval = 1.259, 1.591) higher likelihood of stroke compared with White women after controlling for age, behavior, and comorbidities. Racial disparities were not statistically significant at the higher income ranges for either the full (odds ratio = 1.404, p = 0.3114) or young samples (odds ratio = 1.576, p = 0.7718). However, Blacks had significantly higher odds of stroke in the lower quartiles (lower odds ratio: 1.329, p = 0.0242; lower middle odds ratio: 1.233, p = 0.0486; and upper middle odds ratio: 1.994, p = 0.0005). Disparities were larger among young women (odds ratio = 1.449, confidence interval = 1.211, 1.734). While comorbidities were highly associated with stroke prevalence in all socioeconomic cohorts, Blacks only had higher relative odds in the lower income classes. Lack of biological or behavioral explanations for these findings suggests that unobserved or uncontrolled factors such as systemic racism, prejudicial institutions, or differential treatment may contribute to this.

Does income diversity really stimulate household consumption expenditure diversity? Evidence from mean-based and unconditional quantile regressions

ABSTRACT Although both income diversity and household consumption expenditure diversity are positively correlated with income, little is known about how the former affects the latter. This study investigates how and to what extent income diversity stimulates household consumption expenditure diversity, utilizing data collected by the China Social Survey. We estimate a standard mean-based linear regression model and an unconditional quantile regression (UQR) model to explore mean-based and quantile-specific effects, respectively. The results of the linear regression show that income diversity significantly increases household consumption expenditure diversity. The UQR estimates provide more granular insights, revealing that income diversity improves consumption expenditure diversity at the lower quantiles (5th and 25th), with the largest effect occurring at the lowest 5th quantile; for the higher quantiles, income diversity has no effect on consumption expenditure diversity. Our findings highlight that policies aimed at improving consumption expenditure diversity and the quality of life of people in China should create an economic environment that allows people to diversify their income sources. From a methodological standpoint, we show that mean-based approaches may overlook the finer details of the linkages between income and consumption and thus should be applied cautiously.

Is Contract Farming with Modern Distributors Partnership for Higher Returns? Analysis of Rice Farm Households in Taiwan

This study provides empirical evidence of the economic effect of contract farming for the agriculture sector dominated by smallholder farms. In light of the association between contract farming and modern food distribution channels, we categorize the adoption decisions of contract farming and modern marketing channels into four mutually exclusive choices and investigate their economic effects through the simulated maximum likelihood estimation of the multinomial treatment effects model. The results provide empirical evidence supporting higher returns from the dual partnerships as choosing modern distributors generates more revenues for the those participating in contract farming than for those with no contract farming, and contract farming is more likely to help generate more revenues for those who have taken modern distributors as their major marketing channel compared with those relying on traditional channels. Moreover, we examine whether any distributional pattern of marginal economic effects, of either contract farming or modern marketing channel, is present among farmers at various scales by using the conditional and unconditional quantile regression models. Our findings suggest that the marginal treatment effects are generally in an increasing trend as the quantile increases, implying that the economic effects of contract farming or partnership with modern distributors are more pronounced for higher returns among rice farmers in Taiwan. This finding has great policy implications for developing sustainable agriculture and food supply when facing greater uncertainties due to global warming in the future, especially in an agriculture sector with most smallholder farmers.

Quantile regression estimands and models: revisiting the motherhood wage penalty debate

AbstractThis paper discusses the crucial but sometimes neglected differences between unconditional quantile regression (UQR) models and quantile treatment effects (QTE) models. We argue that there is a frequent mismatch between the aim of the quantile regression analysis and the quantitative toolkit used in much of the applied literature, including the motherhood wage penalty literature. This mismatch may result in wrong conclusions being drawn from the data, and in the end, misguided theories. In this paper, we clarify the crucial conceptual distinction between influences on quantiles of the overall distributions, which we term population-level influences, and individual-level QTEs. Further, we use data simulations to illustrate that various classes of quantile regression models may, in some instances, give entirely different conclusions (to different questions). Finally, we compare quantile regression estimates using real data examples, showing that UQR and QTE models differ sometimes but not always. Still, the conceptual and empirical distinctions between quantile regression models underline the need to match the correct model to the specific research questions. We conclude the paper with a few practical guidelines for researchers.

Household carbon footprints inequality in China: Drivers, components and dynamics

The significant achievements in economic growth and urbanization in China have recently led to substantial increases of and great inequality in household carbon footprints (HCFs). To achieve efficiency and justice in emissions reduction, policymakers need to fully understand the sources of HCFs and identify the major causes of carbon inequality. By applying the Unconditional Quantile Regression (UQR) model and decomposition method to the Chinese household survey data, this paper investigates the distributional features of HCFs and their determinants. We find that HCFs are unevenly distributed due to differences in the volume and pattern of consumption, which are further determined by household characteristics and lifestyles. The intertemporal lifestyle changes have played a major role in the rise of HCFs inequality measured by various quantile emissions differentials. In addition, considerable increases in HCFs come from the high carbon emission groups, and most of the HCFs inequality stems from the 90–50 emissions differential. To transform the current carbon-intensive economy, policies are required to enhance environmental equity and encourage low-carbon lifestyles.

Conditional vs Unconditional Quantile Regression Models: A Guide to Practitioners

This paper analyzes two econometric tools that are used to evaluate distributional effects, conditional quantile regression (CQR) and unconditional quantile regression (UQR). Our main objective is to shed light on the similarities and differences between these methodologies. An interesting theoretical derivation to connect CQR and UQR is that, for the effect of a continuous covariate, the UQR is a weighted average of the CQR. This imposes clear bounds on the values that UQR coefficients can take and provides a way to detect misspecification. The key here is a match between CQR whose predicted values are the closest to the unconditional quantile. For a binary covariate, however, we derive a new analytical relationship. We illustrate these models using age returns and gender gap in Argentina for 2019 and 2020.

Does the Level of Financial Cognition Affect the Income of Rural Households? Based on the Moderating Effect of the Digital Financial Inclusion Index

Financial cognitive ability is an important part of human capital, which has a direct impact on household income. The dual differences composed by rural residents’ cognition level and residents’ income make the relationship between the two complicated. Based on the analysis of the impact of financial cognitive level on rural household income, this paper takes into account the individual heterogeneity of financial cognition to build an unconditional quantile regression (UQR) model through the micro data of the China Household Financial Survey Project (CHFS). Incorporating the background of the rapid development of digital finance, this paper also studies the impact of rural residents’ financial cognition on household income. The empirical results of the article have the following conclusions: First, on the whole, the improvement of financial cognitive level promotes the increase of rural household income, but this promotion has significant differences at different quantile levels of household income. Second, the digital financial inclusion index in the region has a positive moderating effect on the impact of financial cognition on the income of rural households. Third, the heterogeneity of the impact of financial cognition on the income of rural households is reflected in the two aspects of regions and household assets.

The role of resource reallocation in promoting total factor productivity growth: Insights from China’s agricultural sector

AbstractThis study investigates the contribution of resource reallocation to aggregate total factor productivity (TFP) in China's agricultural sector using unique county‐level panel data for the period 2002–2016. The factors affecting resource reallocation are also investigated by estimating an unconditional quantile regression (UQR) model. Our results show that there exists an “N‐shaped” contribution of resource reallocation to aggregate TFP over time, and on average, resource reallocation increases aggregate TFP by 4.84% annually. The results of the UQR model indicate that government intervention and financial and labor market development affect resource reallocation heterogeneously. In particular, we show that government intervention significantly decreases resource reallocation at the selected quantiles (except for the 70th quantile), with the largest effect occurring at the lowest 10th quantile. Financial market development significantly increases resource reallocation at all the selected quantiles, whereas labor market development significantly increases resource reallocation exclusively at the 10th, 50th, and 70th quantiles.

The immigrant-native wage gap in Germany revisited

This study provides new evidence on the levels of economic integration experienced by foreigners and naturalised immigrants relative to native Germans from 1994 to 2015. We decompose the wage gap using the method for unconditional quantile regression models by employing a regression of the (recentered) influence function (RIF) of the gross hourly wage on a rich set of explanatory variables. This approach enables us to estimate contributions made across the whole wage distribution. To allow for a detailed characterisation of labour market conditions, we consider a comprehensive set of socio-economic and labour-related aspects capturing influences of, e.g., human capital quality, cultural background, and the personalities of immigrants. The decomposition results clearly indicate a significant growing gap with higher wages for both foreigners (13.6 to 17.6%) and naturalised immigrants (10.0 to 16.4%). The findings further display a low explanation for the wage gap in low wage deciles that is even more pronounced within immigrant subgroups. Cultural and economic distances each correlate strongly with wages. A different appreciation of foreign educational qualifications, however, widens the wage gap substantially by 4.5%points on average. Moreover, we observe an indication of deterioration of immigrants’ human capital endowments over time relative to those of native Germans.