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The study aims to examine the patterns of time allocated to paid employment activities by women in India as well as change in time allocating pattern of women over the period 1998 to 2019. In doing so, it attempts to highlight gender-asymmetry of time use and heterogeneity in time use of women residing in urban and rural areas as well as variations in time use by marital status, motherhood and age.

Using unit-level data from two available Time Use Surveys (TUS) namely the Pilot Survey TUS 1998 and first nationally representative TUS 2019, the authors use Tobit model to estimate determinants of women’s time in employment. To explain the change in time spent on paid work by women over the two decades, the authors use counterfactual quantile regression decomposition.

The gender asymmetry in time allocation is stark, with women spending one fifth time compared to men paid employment activities. Over the two decades of interest, women’s time spent on employment activities in a day has reduced by half from around 4 h to 2 h, largely driven by rural women’s time. Regression results suggest the emergence of a “U-shaped” relationship between time spent on paid work and education of women. The counterfactual decomposition results suggest that women are spending lesser time on employment activities in 2019 than in 1998 across the time distribution.

This paper contributes to a novel understanding of time use by women in a developing country by analysing the changes in time use over two decades as well as distributional sensitivity to observed characteristics. The study informs about the intensive margins of female employment by incorporating dynamics of socio-economic development.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-03-2022-0164.

This article aims to analyze the workers' probabilities of following their parents’ occupational legacy and whether these individuals are paid differently compared to those who opted for occupations different from their parents, in Brazil.

To that end, the occupational legacy probability equation was estimated as the quantile wage equations with sample selection bias correction and the wage decomposition for Brazil from the microdata of the National Household Sample Survey (PNAD) of 2014. It was found that families have a strong influence on the process of choosing the careers of their children. The average probability of a young person following the occupational legacy of their parents was 41.63%. This percentage is different when analyzing different groups of individuals, such as being male or female, being in a traditional or single parent family, being in an income household lower or higher per capita.

The results also confirm the hypothesis that workers who tend to follow the occupational legacy have lower wages than individuals who choose other occupations and that this may cause a “poverty trap” since the lower the salary quantile, the stronger the “trap” as economically disadvantaged young people tend to follow in their parents' footsteps and to contribute to family income they face a tradeoff, opt between work or study, which ends up disrupting their education and forcing young people to entering the job market early, performing secondary occupations with lower income and arduous work, generating a “vicious cycle of poverty”.

Given the database, we are comprised to its most recent version.

This is the first work on Latin American problem of occupational legacy.

This is the first work on Latin American problem of occupational legacy.

The purpose of the paper is to analyse how the male-female pay gap in China varies across the pay distribution and to provide evidence on the factors that influence that gap.

The authors use the Recentered Influence Function modification of quantile regressions to estimate how the male-female pay gap varies across the pay distribution. The authors also decompose the pay gaps at different quantiles of the pay distribution into differences in endowments of wage determining characteristics and differences in the returns for the same characteristics. The analysis is based on data from the Life Histories and Social Change in Contemporary China survey.

The authors find evidence of a sticky floor (large pay gaps at the bottom of the pay distribution) and some limited and weaker evidence of a glass ceiling (large pay gaps at the top of the distribution). This pattern prevails based on the overall pay gap as well as on the adjusted or net gap that reflects differences in the pay that males and females receive when they have the same pay determining characteristics. The pattern largely reflects the coefficients or unexplained differences across the pay distribution. Factors influencing the pay gap and how they vary across the pay distribution are discussed. The variation highlights considerable heterogeneity in the Chinese labour market with respect to how pay is determined and different characteristics are rewarded, implying that the conventional Blinder-Oaxaca decompositions that focus only on the mean of the distribution can mask important differences across the full pay distribution.

At the bottom of the pay distribution most of the lower pay of females reflects their lower returns to job tenure, experience and a greater negative effect of family responsibilities on females’ wages, and to a lesser extent their lower level of education, less likelihood of being CPP members and their concentration in lower paying occupations. At the top of the pay distribution most of their lower pay reflects their lower returns on education, job tenure and work experience, and to a lesser extent their lower levels of experience and lower likelihood of being in managerial and leadership positions.

The paper systematically examines the male-female pay gap and its determinants throughout the pay distribution in China, highlighting that the conventional Blinder-Oaxaca decompositions that focus only on the mean of the distribution can mask important differences across the full pay distribution and not capture the considerable heterogeneity in that labour market.

This paper explores the wages of White, Black, Hispanic, Asian, Native American and “other race” women and men once differences in basic characteristics among these 12 groups are accounted for. The authors aim to extend comparisons beyond those of women and men of the same race or the various races within a given gender.

To undertake the conditional analysis, first, the authors propose a simple re-weighing scheme that allows to build a counterfactual economy in which workers' attributes for all gender–race/ethnicity groups are the same. Second, the authors use a well-known re-weighting scheme that involves logit estimations.

Only Hispanic men, Native American men and Asian women have conditional wages around average. Black men and, especially, White, Black, Hispanic, Native American and “other race” women have conditional wages clearly below average, whereas those of Asian and White men are well above average. The wage differential between a privileged and a deprived group is disentangled into the premium of the former and the penalty of the latter, which brings a new perspective to what has been done in the literature based on pairwise comparisons. In this intersectional framework, the authors document that gender penalizes more than race.

This paper examines intergroup earnings differentials using a methodology that allows to examine 12 gender–race/ethnicity groups jointly, which is this work's distinctive feature. The authors' intersectional framework allows to picture the effect of gender and race/ethnicity more broadly than what the literature has shown thus far.

Economic theories on structural change focus on factors such as fluctuations in relative prices and income growth. In addition, China’s reform and opening up has also been accompanied by increasing openness, significant fluctuations in investment rates, and frictions in the labor market. Existing literature lacks a unified theoretical framework to assess the relative importance of all these determinants. The paper aims to discuss these issues.

To incorporate all of the potential determinants of China’s structural change, the authors build a two-country four-sector neoclassical growth model that embeds the multi-sector Eaton and Kortum (2002) model of international trade, complete input-output structure, non-homothetic preference and labor market frictions. The authors decompose the sectoral employment shares into six effects: the Baumol, Engel, investment, international trade, factor intensity and labor market friction effects. Using the data of Chinese economy from 1978 to 2011, the authors perform a quantitative investigation of the six determinants’ effects through the decomposition approach and counterfactual exercises.

Low-income elasticity of demand, high labor intensity, and the existence of the switching costs are the reasons for the high employment share in the agricultural sector. Technological progress, investment and international trade have comparatively less influence on the proportion difference of employment in the three sectors.

Therefore, to examine the impact on China’s structural change, in addition to Baumol effect and the Engel effect, it is also necessary to consider the impact of three more factors: international trade, investment and switching costs. Therefore, the authors decompose the factors that may influence China’s structural change into the Baumol, Engel, investment, international trade, factor intensity effect and switching cost effects. The authors evaluate these six effects using the decomposition approach and counterfactual exercises.

The purpose of this paper is to investigate the existence of sticky floor and glass ceiling effects in the gender wage gap (GWG) among Spanish managers. In addition, the paper determines if the pay gap at every quantile is a result of the gender characteristic differences, or the differences in returns to those characteristics.

The paper exploits a counterfactual decomposition analysis, using quantile regression, to decompose the GWG into one component that is based on differences in characteristics and one component that is based on differences in coefficients across the wage distribution.

A significant GWG over all the wage distribution is found. Such a gap exhibits a clear U-shaped pattern, thus pointing out both significant sticky floor and glass ceiling effects. Furthermore, the paper shows that such pattern is mainly determined by the coefficient effect, whose relative incidence is almost continuously increasing along the wage distribution.

While it is difficult to give a definitive explanation for the significant U-shaped pattern in the GWG and for the bigger incidence of the glass ceiling, the authors suggest two possible explanations that are consistent with these findings. The paper leaves the identification of these explanations to future research.

The pattern of rising coefficient effects at higher quantiles suggests that the glass ceiling is a more relevant question than the sticky floor. Indeed, at the highest wage quantiles, differences in characteristics make essentially no contribution to the overall wage gap. This suggests that upper-echelon female managers have the same characteristics as their male counterparts, which emphasizes the role of discrimination for these top-level jobs.

Despite the general GWG has been largely investigated, the analysis of a wage differential among managerial workers has certainly drawn much less attention. In particular just a few papers have investigated the existence of sticky floors and glass ceiling among managers. In addition, as to Spain, there is no empirical survey investigating and decomposing the gender pay gap among managers.

The purpose of this paper is to quantify the wage gap between native and immigrant women in Spain, taking into account differences in their characteristics and the need to control for common support. If immigrant women are segregated in occupations with few native women, it is important to take this into account to analyse wage differentials between both collectives.

Microdata from the Continuous Sample of Working Histories (Muestra Continua de Vidas Laborales) on wages and other personal characteristics such as gender, country of origin, and age were used to apply the matching procedure and the decomposition of the wage gap, along the lines of Ñopo, for the analysis of wage differentials between native and immigrant women. The advantage of this procedure is that one can simultaneously estimate the common support and the mean counterfactual wage for the women on the common support (i.e. comparing native and immigrant women with similar observable characteristics). In addition, differences not only at the mean but also along the entire wage distribution can be described.

The results obtained indicate that, on average, immigrant women earn less than native women in the Spanish labour market. This wage gap is bigger when immigrant women from developing countries are considered, but the authors’ main finding is that an important part of this wage gap is related to differences in common support (i.e. immigrant women are segregated in certain jobs with low wages different from those occupied by native women). If the need to control for common support is neglected, estimates of the wage gap will be biased.

Studying the case of Spain is particularly interesting because it is a country with abundant and recent immigration. Immigrant women account for more than half of the total immigrants in Spain, and unlike other host countries, they come from a highly varied range of countries, with origins as diverse as Latin America, the Maghreb and Eastern Europe. To the authors’ knowledge, no other study has explicitly focused on the analysis of the wage differential of immigrant women in the Spanish labour market by taking into account the need to control for common support. Moreover, published papers illustrating the potentiality of Ñopo's methodology are also very scarce.

The purpose of this paper is to examine the effects of changes in the relative composition and in the segmentation between formal and informal labour on earnings differentials among women over the last decade in Brazil.

The authors follow Machado and Mata’s method to decompose the changes along the earnings distribution, with correction for sample selection and using microdata from the Demographic Census of 2000 and 2010. Informal labour was divided into informal salaried labour and self-employment, and both groups were compared with the formal labour separately.

The results indicate that, in both cases, an increase in earnings differentials in the bottom of the earnings distribution due to segmentation, suggesting that the returns to formal labour have grown relatively to informal labour during the period. On the other hand, earnings differentials decrease as one moves up the earnings distribution due to the composition effect, which is stronger on the top of the distribution relatively to the bottom. Furthermore, there are compensating differentials for self-employed women above the 30th quantile, which contributed to reduce the inequality between this group and formal workers.

The paper contributes to a better understanding of the changes taking place in female labour, shedding some light on how they affect different points along the earnings distribution. Furthermore, the adopted approach proposes a new application for the correction of sample bias in the context of quantile regression by employing a logit multinomial, and using the Demographic Census data.

The purpose of this paper is to examine the correlation between childhood poverty and its influence on adulthood wage distribution, where childhood poverty refers to the experience of poverty or poor family background during one’s childhood.

With data from the Korean Labor and Income Panel Study, a quantile regression technique and a decomposition method are conducted to identify and decompose the wage gap between low (poor) and middle class income groups along the whole current wage distribution, based on a simulated counterfactual distribution.

The results show that those who had been less fortunate during their childhood were also less likely to have the opportunity to gain labor market favored characteristics, such as a higher level of education, and even earn lower returns to their labor market characteristics in the current labor market. This leads to a discount of about 15 percentage points in the wage, on average, in total for those with underprivileged backgrounds during childhood compared to those with a middle class background. This disadvantage is observed heterogeneously, with a greater effect at the lower quantiles compared to the higher quantiles of the current wage distribution.

This research contributes to the literature by providing a partial understanding of poverty in Korea along with possible causes, including poor family background or childhood poverty, with which the implication of an intergenerational effect is considered.

The determinants of income of rural and urban farm households, with emphasis on the role of off-farm employment by farm household members and of farm size, are examined using data from the 2016 Agricultural Resource Management Survey (ARMS) and quantile regression procedure. The implemented quantile regression technique is extended to allow for the decomposition of the income gap between the two groups of farm households. Findings indicate, regardless of the location of the farm, a positive and significant impact of a previous year's participation in off-farm work by household members on the distribution of current household income. Having operated a larger-sized farm in the previous year is shown with a similar effect in the upper range of the income distribution for urban households and with a comparable impact but across the whole income distribution for rural farm households.

Data from the 2016 ARMS are used in conjunction with quantile regression in order for decomposition of the income gap between the two groups of farm households.

Findings show that urban farm households who in a previous year have participated in off-farm work and operated larger-sized farms tend to earn higher incomes. Results further indicate higher rates of return to education for “urban” farm households in comparison to “rural” farm households, particularly for those with a college education and beyond who are at the lower portion of the income distribution.

To the extent that the ARMS is an annual cross-sectional data, the temporal impacts of factors that potentially may influence the incomes of farm households in urban and rural areas cannot be measured.

Findings from this research indirectly support previous published research where higher earnings by urban US population were documented in comparison to rural population and where earnings tend to rise as a result of participation in off-farm work and in expanding the size of the farming operation; this is in addition to the procurement of higher education.

The results of a higher rate of return to education for “urban” farm households in comparison to “rural” farm households have important policy implications for policymakers.

This is the first paper in the agricultural economic literature that implements a method of assessing the rural–urban divide across all of the quantiles of income distribution.