Unconditional Quantile Regression Research Articles

Closing the gender wage gap in the boardroom: the role of compliance with governance codes

Purpose This paper aims to analyse the gender wage gap (GWG) in the board of directors at the executive-director level. The authors aim to answer two questions: (1) Is the GWG explained by differences between males and females, by discriminatory causes or by both? and (2) what are the main factors that cause or increase the existence of GWGs? Specifically, the authors pay special attention to compliance with good governance codes as a fundamental variable in explaining the GWG. Design/methodology/approach The study uses a sample of directors in Spanish companies listed on the continuous market from 2013 to 2021 and uses Blinder–Oaxaca decomposition and unconditional quantile regressions to analyse the GWG. Findings The findings demonstrate both discriminatory reasons and differences between individuals when explaining the GWG and showing that compliance with remuneration practices issued by good governance codes considerably reduces the GWG for all remuneration components. Practical implications The study confirms adequacy of regulator remuneration recommendations but highlights GWG persistence within boards. To counter this, enforcing pay transparency aids female directors’ advancement, reducing bonuses’ impact on wage disparity, necessitating monitored laws for fairer compensation systems and meeting 40% of women directors’ proposals. Social implications Primarily, this study significantly influences public attitudes towards GWG. Specifically, it calls for companies to not only increase female leadership representation but also to ensure equitable remuneration aligned with their male counterparts, conduct regular pay equity assessments, implement pay transparency policies and support work-life balance through flexible hours and parental leave. Furthermore, the work serves as a crucial resource for female directors, empowering them to advocate for their rights in the context of GWG. Originality/value This research offers nuanced insights into the GWG in corporate boards, corrects the main limitations of previous studies and calls for regulatory reinforcement and the active involvement of female directors and firms in creating equitable policies.

Global shocks and the dynamics of EU countries' specialisation

AbstractThis article empirically investigates the effects of global shocks on EU‐28 countries' patterns of specialisation by focusing on the global financial crisis of 2008. In particular, it addresses the following two research questions: Did the financial crisis change the patterns of specialisation of EU member states? Was the impact of the crisis homogenous across countries and manufacturing products? Answering these questions is important because changes in specialisation generate inequalities, given the shift of the demand from one factor to another. Using an unconditional quantile regression approach, this study demonstrates that the financial crisis had a positive effect which was larger on products in which countries were not specialised before the crisis. Some heterogeneity also emerged at both sectoral and geographical levels.

Mineral resource drivers in the global south: A case study of Australia

Mineral resource depletion directly restricts sustainable mineral development. This study investigates the drivers of sustainable mineral resource development via an evolutionary game model involving mineral firms, the Australian government, and financial institutions. The tripartite model provides a guide to strategies and interactions with external influences based on company liquidity. Leveraging panel data from Australian mining companies from 2015 to 2022, this study utilizes unconditional quantile regression techniques, culminating in three salient discoveries. First, despite financial limitations, small-to medium-sized enterprises (SMEs) can accumulate ample resources to enhance their green technology R&D and corporate social responsibility (CSR) expenditure through diverse financing methods, thereby creating an internal strategic impetus for CSR perpetuation. Second, by participating in CSR, mineral firms can transmit positive signals in an asymmetric market, which promotes their sustainable development. Finally, despite the Australian government's R&D tax refund policy incentivizing R&D investment, SMEs' lack of innovative capacity has led to the diversion of operational funds, which negatively impacts their sustainable development. These findings provide valuable insights for sustainable mineral resource development that extend beyond Australia to other Southern Hemisphere nations.

Does Working from Home Increase the Gender Wage Gap? Insights from an Italian Survey of Occupations

ABSTRACT This article investigates to what extent the working from home (WFH) feasibility of occupations can influence the gender wag gap (GWG) at the mean and along the wage distribution. Based on Oaxaca–Blinder decompositions and unconditional quantile regressions, results show that the GWG is greater among women working in an occupation with a high level of WFH feasibility. We find evidence of both sticky floor and glass ceiling effects for employees with high WFH feasibility and only a sticky floor effect for the group with low WFH feasibility. The positive association revealed between the level of WFH feasibility and the GWG appears particularly strong among older and married women employees. These results underscore that the WFH feasibility may play an important role in exacerbating future gender gaps in wages, as WFH is expected to remain a normal practice beyond the COVID-19 pandemic. HIGHLIGHTS Working from home (WFH) feasibility of occupations influences the gender wage gap (GWG) in Italy. GWG is overall wider among employees with high WFH feasibility than employees with low WFH feasibility. The GWG is higher among older and married women employees. A possible explanation is Italy’s ungenerous work–family policies and poor childcare availability. There is a need for policies aimed at regulating WFH from a gender-equality perspective.

Heterogeneous effects of a foreign buyer tax on house prices in New South Wales

Abstract This article combines unconditional quantile regressions with difference-in-differences to study the distributive effects of a foreign buyer tax (FBT) on home prices in New South Wales (NSW). The main results reveal that the FBT reduces house prices in NSW but only among the more expensive houses located in desirable neighborhoods of Sydney and with a relatively high share of foreign-born population. We find evidence that the FBT reduces transaction volumes in the same expensive Sydney neighborhoods and immigrant enclaves where house prices are observed to decline, in support of a direct mechanism that the FBT curbs foreign demand. Additional results suggest that more expensive homes are not substituted with less expensive housing, and that some foreign buyers respond to the FBT by divesting away from NSW locations. The main policy implication is that the FBT may help deter foreign buyers from accumulating higher-priced and luxury assets, but may fail to address broader housing affordability concerns facing the local population.

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.

Innovation Persistence and Firm Growth: Do They Go Hand in Hand?

AbstractThis study empirically examines the relationship between persistence in innovation and firm growth in Spanish manufacturing firms during the period 2005–2016. We include a number of input and output indicators for innovation persistence (R&D, product and process innovation, and patent filings) and use the changes in firms’ annual sales as a measure of firm growth. Differences in how innovation persistence affects firm growth are also explored for the subsets of small and large firms. We employ conditioned quantile regression (CQR) models to see how innovation persistence affects firms located at different quantiles of the firm growth distribution and unconditional quantile regression (UQR) which allow us to compare similar firms in terms of their propensity to innovate on a persistent basis. Our findings are sensitive to the choice of econometric approach. Overall, results indicate that the type of innovation persistence does influence growth. Persistence in R&D activities does not play any relevant role whereas persistence in innovation outputs (product, process, and patents) is a driver for growth only in firms with medium-to-low sales growth rates.

Could the minimum wage policy reduce food insecurity among households of formal workers in Indonesia?

BackgroundPrevious studies have concluded that minimum wages increase workers' wages. However, whether this effect will continue to improve households' food insecurity is an interesting question, especially in Indonesia, where food insecurity is still a public policy challenge. This study explores the ongoing impact of minimum wages on household food insecurity in Indonesia, leveraging data from the National Socioeconomic Survey (2017–2019) and provincial-level variations in minimum wages. The study employs unconditional quantile regression to provide nuanced insights by analyzing three food insecurity indicators: per capita calorie intake, per capita consumption of vegetables and fruits, and food diversity. We also investigate potential mechanisms driving the link between the minimum wage and food insecurity.ResultsThe study revealed that the real minimum wage reduced food insecurity, especially at specific distribution points. Significantly, the effect on per capita calorie intake was observed in lower deciles. The impact on dietary diversity was observed up to the seventh decile. However, the minimum wage increase did not significantly improve the consumption of nutritious foods like fruits and vegetables, except for the top deciles. The study confirmed that the minimum wage's impact on food insecurity operated through wage increases, particularly in the bottom-to-median wage distribution within the manufacturing sector.ConclusionsThe study concluded that the minimum wage policy ameliorated household food insecurity indicators in specific distribution segments. Our results support the effectiveness of government policies in increasing the minimum wage as a viable approach to mitigating food insecurity among formal worker households, especially within the manufacturing sector. However, additional policies targeting the lower end of the per capita calorie intake distribution are necessary, as the minimum wage was recognized to have no impact on this group.

Unconditional Quantile Regression for Streaming Datasets

The Unconditional Quantile Regression (UQR) method, initially introduced by Firpo et al. has gained significant traction as a popular approach for modeling and analyzing data. However, much like Conditional Quantile Regression (CQR), UQR encounters computational challenges when it comes to obtaining parameter estimates for streaming datasets. This is attributed to the involvement of unknown parameters in the logistic regression loss function used in UQR, which presents obstacles in both computational execution and theoretical development. To address this, we present a novel approach involving smoothing logistic regression estimation. Subsequently, we propose a renewable estimator tailored for UQR with streaming data, relying exclusively on current data and summary statistics derived from historical data. Theoretically, our proposed estimators exhibit equivalent asymptotic properties to the standard version computed directly on the entire dataset, without any additional constraints. Both simulations and real data analysis are conducted to illustrate the finite sample performance of the proposed methods.

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.

Exploring the determinants of the evolution of urban and rural household carbon footprints inequality in China

Households are key actors in mitigating climate change and their carbon footprints are unequally distributed due to differences in the scale and patterns of consumption. This study separately estimates household carbon footprints inequality in urban and rural areas of China from 2012 to 2018 and identifies the factors contributing to the evolution of the inequality by applying environmentally extended multiregional input-output analysis, unconditional quantile regression and Oaxaca-Blinder decomposition. The results show that the largest emission growth occurred among the 50th–80th percentile of urban emitters and the highest rural emitters. The Gini coefficient of urban household carbon footprints decreased from 0.463 to 0.439, whereas that of rural household carbon footprints increased from 0.447 to 0.459. Notably, the changes of household characteristics exacerbated carbon inequality, with income growth, increased car ownership, and smaller household size being the three primary factors, while the changes in consumption preferences and technological advancements reduced carbon inequality. The latter are dominant in urban households and the former are dominant in rural households. To mitigate climate change and reduce inequality, the government should not only encourage high-emitting households to adopt greener low-carbon consumption and lifestyles, but also promote low-carbon technology innovation to reduce carbon intensity.

Sales performance of direct food marketers: African American‐led operations

AbstractThis paper examines the impact of participation in direct marketing on the entire distribution of farm sales for African American (AA) operations using the unconditional quantile regression (UQR) estimator. Our analysis yields unbiased estimates of the unconditional impact of direct marketing on farm sales and reveals the heterogeneous effects that occur across the distribution of farm sales. The sales gap for AA‐led operations is about 11% across all quantiles when we control for farming and marketing experience along with key features of the farm operation such as crop choice and geographic location. The relative sales gap for AA operations declines across the distribution of farm sales and actually disappears for the largest operations. The network effect that we identify is associated with a sales premium for AA‐led operations relative to other operations engaged in direct marketing. Marketing experts and extension professionals can use this information to guide farmers who are considering initiating or expanding direct marketing activities.

Does Gender Equality in Managerial Positions Improve the Gender Wage Gap? Comparative Evidence from Europe

In this paper, we analyse the impact of gender equality in managerial positions on wages and the gender wage gap in 22 European countries. We draw on the employer–employee microdata from the European Structure of Earnings Survey (E-SES) for the year 2018, which allows us to include firm fixed effects in our econometric specifications, thus controlling for both observed and unobserved heterogeneity at the firm level. The analysis is carried out not only at the mean but also across the wage distribution through unconditional quantile regressions. The results on the impact of gender equality in management on wages are mixed. However, we find that gender equality has a predominantly positive effect in the upper part of the wage distribution, and a negative effect in the middle and lower parts. The results on the impact on the gender wage gap show that in many cases, a more gender-equal management reduces the gender wage gap. Furthermore, gender equality in management reduces the gender wage gap mainly in the middle and lower part of the wage distribution.

Job satisfaction in Europe: a gender analysis

PurposeThe main aim of this study was to examine gender differences in job satisfaction in Europe.Design/methodology/approachFor the empirical analysis, data from the Sixth European Working Conditions Survey were used. Oaxaca–Blinder decomposition with a principal component analysis (PCA) aggregated variable, after unconditional quantile regressions in a multiple imputation background, was implemented.FindingsWomen report higher job satisfaction than men do. Women were significantly more satisfied than men for the middle levels of the job satisfaction distribution.Originality/valueThis study expands the evidence on the determinants of job satisfaction in the European labour market by applying a recent form of decomposition that invests in unconditional quantile regression (UQR). To the best of this study knowledge, this is the first time that the Oaxaca–Blinder decomposition with a PCA aggregated variable after unconditional quantile regression has been employed to study gender-based differences in job satisfaction.

Income Inequality, Human Capital and Institutional Quality in Sub-Saharan Africa

AbstractThis paper aligns with Sustainable Development Goal 10 to investigate the role of quality institutions in the human capital-income inequality nexus. It uses an unbalanced panel data on the Gini index (measure of income inequality), human capital index and institutional quality index on 46 sub-Saharan African countries from 2010 to 2019. The Driscoll and Kraay (Rev Econ Stat 80:549–560, 1998) panel spatial correlation consistent (PSCC) and Firpo et al. (Unconditional quantile regressions. National Bureau of Economic Research Working Paper, No. 339, pp 1–54, 2007. https://doi.org/10.3982/ECTA6822) bootstrap unconditional quantile regression (UQR) techniques are deployed. Among others, findings reveal that: (1) human capital and institutions aggravate inequality; (2) the interaction of human capital and institution reduce inequality; (3) UQR reveals that the interaction effect is negative at lower quantiles of 0.10, 0.25 and 0.50; and (4) results across the sub-regions are mixed. In addition, evidence from the margin plots reveals that the conditional effect of human capital on income inequality is negative as institutions are strengthened. The downward trend of the plot within the 95% confidence interval shows that institutional quality enhances the impact of human capital on income inequality. These are novel contributions to the literature as it suggests that quality institutions matter in the drive towards reducing the menace of income inequality. Policy recommendations include strengthening institutions and making basic education affordable.

The over-education wage penalty among PhD holders: a European perspective

ABSTRACT Using a unique pan-European dataset, we rely on two alternative measures of over-education and control stepwise for four groups of covariates in order to interpret the over-education wage penalty in light of theoretical models. Firstly, it appears that a significant fraction (i.e. between 1/5 and 1/3) of PhD holders in Europe are genuinely over-educated. Secondly, these genuinely over-educated PhD holders are found to face a substantial wage penalty (ranging from 15 to almost 30%) with respect to their well-matched counterparts. Finally, unconditional quantile regressions highlight that the over-education wage penalty among PhD holders increases greatly along the wage distribution.

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.

Youth, Crime, and the Potential Cost Offset to Housing First Programs

Housing First (HF) is an approach that emphasizes providing housing as a precondition for assisting people experiencing homelessness. To the extent that housing reduces contacts with police, HF may reduce criminal behaviour and so reduce costs borne by the justice system. This may be particularly true for youth whose homelessness often forces them to adopt survival behaviour that exposes them to police and bylaw enforcement officers. Using regression analysis, we employ linked administrative data sets from police and from HF programs to examine how interactions of youth with police change following admission to a HF program. An important contribution of our study is the use of administrative police records rather than self-reported data on the number of criminal incidents and their severity. Unconditional quantile regression is used to observe HF’s effect on changes in both the number and severity of criminal incidents. Controlling for demographic characteristics of youth and for type of housing program and using administrative police records as opposed to self-reported police interactions, we find only weak evidence to suggest that the number of criminal incidents falls following admission to a HF program and only weak evidence of a fall in the seriousness of crimes.

Asymmetry in Hedges, Safe Havens, Flights and Contagion: Unconditional Quantile Regression Approach

We examine the hedging/safe-haven ability of gold, the US dollar, bonds, crude oil, and Bitcoin against stocks using the unconditional quantile regression (UQR). We reveal that hedging (safe-haven) effect generally decreases (increases) with the quantiles of asset returns and find an asymmetric flight from stocks to the US dollar as well as asymmetric stock-gold, stock-bond, and stock-oil contagion. Finally, we find a connection between the asymmetric safe haven and asymmetric cross-asset flights/contagion. Therefore, investors seeking hedging and safe-haven assets and investigating flights or contagion should consider the feature of extremes of assets returns.JEL: C13; G11; G14