Wage Regressions Research Articles

Does information disclosure affect the gender gap in bidding behavior? Empirical evidence from a natural experiment on a large online labor platform

Exploiting an exogenous change in information disclosure on one of the largest online labor platforms worldwide, we assess how the provision of more information on the employers’ willingness to pay (WTP) and the required experience level of workers affects the gender gap in bidding behavior. We find that female workers make lower wage proposals than male workers if the employers’ WTP for a project, as given by its budget, is disclosed in addition to the (exogenously enforced) experience level of workers that employers deem necessary for the job, i.e., low, intermediate, or high. In addition, we do not find robust empirical support for the hypothesis that female workers’ under-confidence in their skills increases the gender gap in bidding behavior. Finally, we find a statistically significant gender wage gap of 16.8 %, which is reduced to 1.5 % when we control for employer, worker, and project characteristics. Once we include workers’ wage proposals in our agreed-upon wage regressions, the gender wage gap virtually disappears (0.2 %) and is statistically insignificant. This suggests that gender differences in wage expectations pertain to gender differences in wages.

Labor market effects of monetary policy across workers and firms

This paper uses Austrian social security records to analyze the effects of ECB monetary policy on the labor market. Our focus is on the role of worker and firm wage components, defined by an Abowd et al. (1999) wage regression. We find that monetary tightening causes the largest employment losses for low-paid workers who are employed in high-paying firms before the tightening. Monetary tightening further causes a reallocation of workers to lower-paying firms. In particular low-paid workers who were originally employed by low-paying firms are prone to falling down the firm wage ladder.

Commuting while Black: compensating differentials and Black–White wage gap in Canada

PurposeUsing the Canadian Census of 2016, the present study examines the Black and White gap in compensating differentials for their commute to work.Design/methodology/approachThe data are from the Canadian Census of 2016. The standard Mincerian wage regression, augmented by commute-related variables and their confounders, is estimated by OLS. The estimations use sample weights and heteroscedasticity robust standard errors.FindingsIn the standard Mincerian wage regressions, Black men are found to earn non-negligibly less than White men. No such gap is found among women. When the Mincerian wage equation is augmented by commute duration and its confounders, commute duration is revealed to positively predict wages of White men and negatively associate with wages of Black men. At the same time, in the specifications including commute duration and its confounders, the coefficient for the dummy variable identifying Black men is positive with a non-negligible size. The latter pattern indicates wage discrepancies among Black men by their commute duration. Again, no difference is found between Black and White women in these estimations.Research limitations/implicationsThe main caveat is that due to data limitations, causal estimates could not be produced.Practical implicationsFor the Canadian working men, the uncovered patterns indicate both between and within race gaps in the impact of commuting on wages. Particularly, Black men seem to commute longer towards relatively lower paying jobs, while the opposite holds for their White counterparts. However, Black men who reside close to their work earn substantially more than both otherwise identical White men and Black men who live far away from their jobs. The implications for research and policy are discussed.Originality/valueThis is the first paper focused on commute compensating differentials by race using Canadian data.

Do Higher State Minimum Wages Reduce the Racial Wage Gap for Men?

Using data from the 2019 Current Population Survey, we find that black, non-Hispanic men who reside in states with the highest minimum wages (above $10 in 2018) have a slightly smaller wage gap relative to white, non-Hispanic men. However, wage regressions show no appreciable improvement in the relative earnings of black men in states with minimum wages that exceed the federal level when accounting for other demographic determinants of earnings. Our results indicate that increasing a state’s minimum wage does not appear to be an effective policy tool to reduce racial wage inequality for men.

Heterogeneity in the US gender wage gap

Abstract As a measure of gender inequality, the gender wage gap has come to play an important role both in academic research and the public debate. In 2016, the majority of full-time employed women in the United States earned significantly less than comparable men. The extent to which women were affected by gender inequality in earnings, however, depended greatly on socio-economic characteristics, such as marital status or educational attainment. In this paper, we analyse data from the 2016 American Community Survey using a high-dimensional wage regression and applying double lasso to quantify heterogeneity in the gender wage gap. We find that the wage gap varied substantially across women and that the magnitude of the gap varied primarily by marital status, having children at home, race, occupation, industry, and educational attainment. These insights are helpful in designing policies that can reduce discrimination and unequal pay more effectively.

Good Business Practices Improve Productivity in Myanmar’s Manufacturing Sector

We investigate the relationship between business practices and enterprise productivity using panel data with matched employer and employee information from Myanmar. The data show that micro, small, and medium-sized manufacturing enterprises in Myanmar typically adopt only a few modern business practices, and the persistence in the use is extremely low. Even so, we find a positive and economically important association between business practices and productivity. Specifically, the empirical results show that a one standard deviation difference in applied business practices (equivalent to applying an additional 4 to 5 of the 20 business practices in focus) is associated with an 8–10 per cent difference in labour productivity. Utilising the employer–employee information to estimate Mincer-type wage regressions, we find that workers receive about half to two-thirds of the productivity gain in higher wages. Overall, our findings support the notion of business practices as a production technology, and we find that workers and managers split the productivity gains evenly.

Legacy of the Czar: Complementarity between education and work in Russia

ABSTRACT Vocational school graduates enjoy a higher employment probability than other types of graduates across industrial economies. This may result from either the signaling effects of vocational school degrees or skill complementarity between vocational schooling and work experience. Regarding wage regressions, signaling effects should make the coefficient of the interaction term between years of schooling and work experience negative, whereas complementarity between education and work experience should increase this coefficient because the cross-derivative of output with respect to schooling and work experience is positive. Thus, the negativity of the interaction term between years of schooling and work experience decreases as schooling becomes more complementary to work. We find that the negativity of the interaction term is smaller for vocational track graduates than for general track graduates in Russia. This result is arguably because the Russian vocational track emphasizes complementarity between education and work to a greater degree than its general track.

Impact of Continuing Education on Stable Employment and Wages of Men and Women in Serbia

This paper examines whether continuing education and training contribute to overall job security and to narrowing the gender wage gap, thereby mitigating the potential effects of employer discrimination. Data from the Serbian Survey on Income and Living Conditions are used, focusing on 2020 and estimating wage regressions. The main results show that participation in continuing education and training has a positive effect on wages and contributes to reducing the wage gap, especially for individuals who were previously unemployed and participated in some form of additional training. This paper contributes to the understanding of the importance of training and its impact on employment stability and workers' wages in the post-transition economy. The findings presented in this paper are advisory to both policy makers and management. In general, it can be stated that trained employees are better suited to work tasks and, especially if they are satisfied with the knowledge acquired in the company, contribute to a stable environment that makes it easier for them to meet the demands of competition. On the other hand, this implies the empirically confirmed assumption that competition may be negatively correlated with employer discrimination. However, employee participation in continuing education and training in Serbia is still below the optimal level.

Sector specificity of training

ABSTRACT Human capital acquired through employer-provided training is pervasive in labour markets and an important determinant of post-schooling wage growth. The literature has focused on understanding under what conditions this training will lead to higher wages. Here I offer another aspect for consideration: Does the proximity of the current job to past jobs affect the return to training? In particular, I look at whether the wage return to training acquired at a previous employer depends upon the relative ‘proximity’ of the worker’s past employer to their current one, where proximity is measured by whether the worker received the training in the same industry or occupation as the current job. I investigate this using data from the British Household Panel Survey, with both fixed effects and instrumental variable estimation. The results suggest that both current and previous employer training spells are important determinants of wages, and both need to be included in wage regressions. Evidence further suggests that the return to formal training is highest if the training was received in a previous job that was in the same industry and occupation as the current one.

Expectation formation and learning in the labour market with on-the-job search and Nash bargaining

This paper develops a search and matching model with heterogeneous firms, on-the-job search by workers, Nash bargaining over wages and adaptive learning. We assume that workers are boundedly rational in the sense that they do not have perfect foresight about future bargaining outcomes. Instead workers rely on a recursive OLS learning mechanism and base their forecasts on a linear wage regression. We apply adaptive learning to a setting with generalized Nash bargaining and show analytically that the bargaining solution is unique. We use this solution to simulate the model and provide a numerical characterization of the Restricted Perceptions Equilibrium. We show that some job-to-job transitions are socially inefficient since workers can move to less productive employers. Output losses from these transitions decrease with workers’ bargaining power due to a more efficient allocation of workers to jobs. Finally, we find that bounded rationality taking form of adaptive learning can reduce wage inequality among heterogeneous worker groups if workers’ expectations are based on pooled statistical information.

Skill requirements in job advertisements: A comparison of skill-categorization methods based on wage regressions

In this paper, we compare different methods to extract skill demand from the text of job descriptions. We propose the fraction of wage variation explained by the extracted skills as a novel performance metric for the comparison of methods. Using this, we compare the performance of the word-counting method with three different dictionaries and that of three unsupervised topic-modeling techniques, the LDA, the PLSA and the BERTopic. We apply these methods to a U.K. job board dataset of 1,158,926 job advertisements from 35 industries collected in 2018. We find that each of the dictionary-based methods explain about 20% of the wage variation across jobs. The topic modeling techniques perform better as the PLSA is able to explain 36.5% of the wage variation, while BERTopic 32.6%. The best performing method is the LDA with 48.3% of the wage variation explained. Its disadvantage, however, is in the difficulty of interpretation of the skills extracted.

Sample selection models without exclusion restrictions: Parameter heterogeneity and partial identification

This paper studies semiparametric versions of the classical sample selection model (Heckman, 1976, 1979) without exclusion restrictions. We extend the analysis in Honoré and Hu (2020) by allowing for parameter heterogeneity and derive implications of this model. We also consider models that allow for heteroskedasticity and briefly discuss other extensions. The key ideas are illustrated in a simple wage regression for females. We find that the derived implications of a semiparametric version of Heckman’s classical sample selection model are consistent with the data for women with no college education, but strongly rejected for women with a college degree or more.

Shortage of Skilled Labor, Unions and the Wage Premium: A Regression Analysis with Establishment Panel Data for Germany

The author investigates the different influences of labor shortage on wages in firms with or without collective bargaining agreements. In addition to training, technological solutions, and organizational flexibility, employers can also offer higher wages at a constant employment level to fill vacancies if the current payments are lower than the marginal revenue of the workers. Firms with collective bargaining agreements probably already pay wages according to marginal revenue or, in the case of rent sharing, above it, and the remuneration is probably also not adjusted. Using wage regressions with panel data for German establishments, this paper shows that collective bargaining and a lack of skilled workers can lead to higher wages. However, the latter only applies to firms that are not bound by collective agreements. Hence, wage differentials between these firms decrease, providing further explanation for a countercyclical development of the wage premium from the collective bargaining agreement.

Regional differentiation of human capital – analysis based on the Mincer wage equation

The main objective of this paper was an attempt to assess the differentiation of human capital at the level of Polish regions (voivodeships, NUTS-2 level). For this purpose, we used unidentifiable unit data from a survey the Central Statistical Office conducted on the structure of wages and salaries in October 2016 (Z-12), data from the Labour Force Survey (LFS), and data on the life expectancy of women and men. The GUS microdata from the Z-12 study was used to estimate the parameters of the Mincer-type extended wage regression, separately for each voivodeship. In the next step, these estimates were used as weights to calculate the human capital index, taking into account the health condition, education, and professional experience of employees. The values of the aforementioned measure were estimated for 2016 and 2019 (the assumption of weight stability over a short time period was made). The analysis conducted made it possible to determine which regions are characterised by the highest and lowest levels of human capital. The highest levels of human capital were found in Mazowieckie, Pomorskie, and Małopolskie. The voivodeships with the lowest level of the considered measures were Lubuskie, Warmińsko-Mazurskie, Podlaskie, Podkarpackie, and Łódzkie. When comparing the values of the human capital index between 2016 and 2019, it can be concluded that the regions with the lowest value of this measure were also characterised by lower dynamics (the only exception was Lubelskie). Such a situation will probably favor the divergence of human capital between regions. This may, therefore, translate into the persistence (or deepening) of differences in the levels of development of these voivodeships, compared to more developed regions.

Health and Economic Growth: Reconciling the Micro and Macro Evidence

Micro-based and macro-based approaches have been used to assess the effects of health on economic growth. Micro-based approaches aggregate the return on individual health from Mincerian wage regressions to derive the macroeconomic effects of population health. Macro-based approaches estimate a generalized aggregate production function that decomposes output into its components. The microbased approach tends to find smaller effects than the macro-based approach, thus presenting a micromacro puzzle regarding the economic return on health. We reconcile these two strands of literature by showing that the point estimate of the macroeconomic effect of health is quantitatively close to that found by aggregating the microeconomic effects, controlling for potential spillovers of population health at the aggregate level. Our results justify using the micro-based approach to estimate the direct economic benefits of health interventions.

College majors and wages in Turkey: OLS and quantile regression with sample selection correction

PurposeThis study aims to analyze the wage differentials of the majors in college education in Turkey, which is a country implementing an ongoing expansion in college education in recent years.Design/methodology/approachThe study implements Mincreian wage regression using ordinary least squares, Heckman two-step estimation and quantile regression with sample selection correction by using household labor force surveys of TurkStat from the years 2014–2017.FindingsThe findings indicate one of the highest heterogeneity, close to 0.50 log points, between majors in the literature. The within-heterogeneity created by majors is highest among the graduates of social-behavioral sciences, law, biology, physics, mathematics, statistics, computer, engineering and manufacturing, as shown by a 90–10 difference, which is almost 700% for some of these majors. This study shows that the natural science and technical majors that are expected to be more productive and to be paid more fall behind in the wage distribution.Research limitations/implicationsEstimation results show that natural science majors, except for subjects allied to medicine and engineering, are paid lower than law and service-sector-related majors. This indicates that the predictions of the skill-biased technical change hypothesis are not valid in the wage profiles in Turkey and that some majors supply more than the sectoral needs. This casts doubts on the effectiveness of the ongoing higher education expansion process of the country.Originality/valueThis study contributes to the literature on wage differentials of college majors, an area with limited studies. This is the first study analyzing wage differentials of the field of studies by correcting sample selection bias for the Turkish case.

Bounding Omitted Variable Bias Using Auxiliary Data

This paper proposes a new estimator that bound omitted variable bias using proxies for omitted variables with an asymptotically valid bootstrap procedure. I provide open-source software to implement the estimator and to compute the confidence interval. The estimator is useful in many applications because it uses proxies that do not need to appear in the same dataset as the outcome variable. Many surveys include rich proxy variables for a diverse set of unobservable characteristics including abilities, beliefs, and preferences; such surveys can be used as auxiliary datasets in computing my estimator. I provide Monte Carlo simulation results that compare my estimator to the alternative estimator proposed by Pacini (2017) and to the Altonji et al. (2005) - Oster (2019) bound estimator. I show from a simulation that my estimator is robust when proxy variables are contaminated with a large amount of measurement error. Last, I illustrate the application of my estimator in the context of a Mincerian wage regression

The federal-private wage differential: how has it evolved?

ABSTRACT This paper is the first to document and analyse the variation of the federal-private pay differential over time. We estimate the evolution of the federal-private pay differential from 1995 to 2017 using Current Population Survey data, enabling us to examine the current pay gap and how it has changed. To do so, wage regressions are estimated by year and used to calculate the yearly federal-private wage differential. To deal with unobserved heterogeneity, we adopt control function methods. We also estimate the probability of receiving employer-provided health insurance and a pension plan each year for each sector. The findings imply that the federal pay differential is invariably positive, but has varied substantially. We examine the reasons for this variation and find that the most robust result is the positive effect of federal spending as a share of GDP, ipromplying that a 1 percentage point increase in federal spending as a share of GDP raises the federal pay differential by 1.3 to 1.75 percentage points.

The Gender Gap: Looking at the Entire Distribution

We propose a new method of estimating wage differences among individuals from different populations, which is based on looking at the distribution of fixed effects from a wage regression. We use this method to compare males’ and females’ wage distribution at different levels of education and at different ages. In most cases, unobserved, time-constant factors increase the wage of males, compared to that of females, by a constant share. But this is not true when looking at the tails of the distribution. We also discuss the advantages of our method. JEL: J71, J31

Education–Occupation Mismatch and Dispersion in Returns to Education: Evidence from India

Using a national level sample survey on labour market in India, we analyze the role of education–occupation (mis-)match (EOM) in explaining within-group dispersion in returns to education. Applying a double sample selection bias correction and Mincerian quantile wage regression estimation, the analysis reveals interesting findings. First, on average, overeducated workers suffer a wage penalty of 7% and undereducated workers do not receive a wage reward as compared to their adequately educated counterparts. Second, the inclusion of match status reduces within-education group dispersion in returns. The finding highlights that ignoring EOM and thus, adopting a restrictive view of similarity across workers may lead to overestimation of the within-education group dispersion in returns. This study argues for focusing on EOM to increase both pecuniary and social benefits of education in terms of productivity gains and wages as well as to reduce wage dispersion.