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Studies on wage discrimination assume that independent observers are able to distinguish a priori which workers are suffering from discrimination. However, this may not be a good assumption when anti-discrimination laws mean that severe penalties can be imposed on discriminatory employers or when unobserved heterogeneity is significant. We develop a wage discrimination model in which workers are not classified a priori. It can be thought of as a generalization of the standard empirical framework, whereas the Oaxaca–Blinder model can be thought of as an extreme case. We propose a finite mixture model to explicitly model unobserved heterogeneity in individual characteristics and estimate the probabilities of being a discriminated or a non-discriminated worker. We illustrate this proposal by estimating wage discrimination in Germany and the UK.

This chapter tries to capture the disparity in expenditure on primary education based on gender among the religious groups (Hindu, Muslim, and Christian) in rural India. The gender gap in education expenditure for a certain demographic group is calculated using the Oaxaca–Blinder decomposition approach. Further, we tried to identify the various household-related factors which might influence the decision of spending on a child's education. We used the 75th-level National Sample Survey Office (NSSO) unit-level dataset of July 2017 to June 2018 (one academic year) to obtain data on education expenditure and other household factors which play a manifesting role in the gender gap in expenditure on education. Our finding suggests that the total differential (log mean boys education expenditure-log mean girls education expenditure) is positive among all religious groups signifying the gender bias in education expenditure. We also found that the magnitude of the “Unexplained Effect” component is higher compared to the “Explained Effect” component signifying that the treatment of characteristics by students differs by their sex at elementary education. Household size and if household members are employed on a casual basis, then their expenditure on education falls on the other hand income of the household, a household with computer availability and household member engaged in regular wage/salary earning plays a positive role in expenditure on primary education in rural India.

The gender pay gap is a well-documented phenomenon in labor economics. Based on the 2018 Structure of Earnings Survey (SES), the authors estimate the impact of observable characteristics on the gender pay gap in Visegrad Group countries and provide policy recommendations on reducing the gender pay gap.

The Oaxaca-Blinder decomposition is applied to estimate the values of explained and unexplained parts of the gender pay gap. Gender pay gap in unadjusted as well as adjusted form is estimated using data on the individual level.

The results show that unadjusted gender pay gap proved to be stable at more than 20%. The authors found evidence that education widens gender pay gap implying that men have higher returns on education than women. Tertiary education proved to be the highest contributor to widening of gender pay gap. Results also show that there is strong sectoral and occupational segregation. Decomposition proved that only 21% of gender pay gap could be explained by observed characteristics. The unexplained part showed negative values, meaning women would have higher wages, if they had characteristics like men.

Structure of Earnings Survey data are published every four years; therefore the authors’ dataset from year 2018 might not completely reflect today's reality. Unfortunately, newer data are note available yet. Second, Structure of Earning Survey data do not contain variables representing social factors of respondents like marital status, number of children or labour market absence due to birth or childcare. Third, data used for this study do not contain firms that have less than 10 employees; therefore, considerable portion of the labour market is omitted.

Results of this study will help policymakers understand the roots and causes of the gender pay gap in Visegrad Group countries but addressing this issue requires further research.

The purpose of this paper is to analyse the determinants of the survival of Spanish companies.

Two approaches are used and they are complementary. The first approach analyses the determinants of survival probability. For this purpose, a binary choice model is built and estimated using a sample of companies from the main economic sectors taken from the SABI database. Likewise, the Blinder–Oaxaca decomposition is applied to quantify the difference between companies with employees and without employees and the proportion of this difference that owes to observed factors or unobserved factors. Finally, the second approach is a survival analysis carried out through the Cox proportional hazard model that identifies the determinants of the duration of business activity.

The results of the empirical analysis show that companies without employees present less favourable conditions for survival at all stages of their evolution than companies with employees.

The contribution of this study to the empirical literature consists in analysing the difference between companies with and without employees. Due to the structure of Spanish companies, this aspect and the determinants of such difference are essential for policymakers to increase the survival for companies.

The present study delves into the health inequalities between the two most socially deprived groups namely Scheduled Tribes (STs) and Scheduled Castes (SCs) in rural India.

This study used health-specific three rounds of National Sample Survey Office (NSSO) unit-level data for analyses. Probit model has been used to predict the differences in access to maternal healthcare services. Blinder–Oaxaca decomposition method is used to explore the inequality in health of rural population in India and assess the estimated relative contribution of socioeconomic and demographic factors to inequalities in maternal health.

The study establishes that STs women often perform poorly compared to SCs in terms of maternal health such as antenatal care, postnatal care and institutional delivery. Blinder–Oaxaca decomposition method shows that there exist health inequalities between STs and SCs women. Difference in household income contributes 21–34 percent and women's education 19–24 percent in the gap of utilization of maternal healthcare services between SCs and STs women. A substantial part of this difference is contributed by availability of water at home and geographical region. Finally, the study offers some policy suggestions in order to mitigate the health inequalities among socially marginalized groups of SCs and STs women in rural areas.

This study measures and explains inequalities in maternal health variables such as antenatal care, postnatal care and institutional delivery in rural India. Research on access to maternal healthcare facilities is needed to improve the health of deprived sections such as STs and SCs in India. The results of this study pinpoint the need for public health decision-makers in India to concentrate on the most deprived and vulnerable sections of the society. This study thus makes a detailed and tangible contribution to the current knowledge of health inequalities between the two most deprived social groups, i.e., SCs and STs.

This study compares the performance of female majority-owned new ventures (FNV) vs. male majority-owned new ventures (MNV). It analyzes the differences in levels of variables such as education, the same industry work experience of owners, and other venture level attributes between FNVs and MNVs. More importantly, this study employs decomposition techniques to determine the individual contribution from the intergender difference of each attribute on the performance of the new venture. For example, the study finds that, on average, the owners of an MNV possessed 3.4 years more of the same industry work experience than their FNV counterparts. This difference in work experience accounted for 47% of the “explained” gap [1] in Net Profits between the FNVs and MNVs.

This paper utilizes the Kauffman Firm Survey, a longitudinal dataset of 4,928 new ventures started in the USA in 2004. It employs Blinder-Oaxaca and Fairlie decomposition techniques in conjunction with OLS and Logit regressions. Both methods provide point estimates of contributions to the performance gap due to the heterogeneity in each attribute across the groups (FNV and MNV). This approach has a significant advantage over OLS or mediation analysis, which can only provide a directional analysis of the contributions of differences in attributes to performance.

The paper finds no performance gap between MNVs and FNVs. It further investigates whether the heterogeneous characteristics of MNVs vs FNVs are related to different effects on survival and performance. It finds that characteristics such as owners’ work experience in the same industry, average hours worked by owners in the new venture, the technology level of the venture, and its incorporation status are related with a differential impact on new venture survival and performance.

All firms in the dataset belonged to a single cohort (2004) of new ventures started in the US. Future studies are encouraged to develop a dataset from multiple geographies and founding over several years so that the results may be more generalizable.

The paper provides crucial practical guidance to policymakers, investors, and entrepreneurs. In general, policies that enhance the work experience of women entrepreneurs and provide access to infrastructure such as daycares, which may allow them to work more hours, would probably improve the performance of FNVs.

The paper furthers the literature on women entrepreneurship by analyzing point estimates of differential contribution of disparate variables to performance. From a methodological perspective, the study reconciles the results between regression and decomposition analyses.

This study aims to assess the effects of microfinance institution (MFI) services on the productivity of family farms in Cameroon, in the region of Mbam and Kim. It will be a question, therefore, of determining the level and determiners of the outputs of family farms, in particular those concerned by the cultures of cocoa, beneficiaries of the agricultural services of MFIs.

The authors use the Blinder (1973) and Oaxaca (1973) model of decomposition of the productivity differential between beneficiaries and non-beneficiaries of agricultural credits on a sample of 130 cocoa farming households and four MFIs of the same area between 2008 and 2011.

The yield gap between beneficiaries and non-beneficiaries of agricultural credits is estimated at 0.19 tons per hectare. This gap is explained positively by the financial aid variable, the farm size variable, which is significant in the explanation of the beneficiaries' level of returns and the constant term. On the other hand, all the socio-economic variables of the farmers contribute to reduce this gap of productivity.

This financial assistance from CVECA is essential to increase agricultural yields because it helps to cancel out some structural barriers. However, as this improvement in yields is only possible for large farms, the services of the MFIs would rather favor extensification policies. Nevertheless, the study results are limited by the negative effects of the socio-economic characteristics of the farmers on these yields, the study having been revealed without any selectivity bias.

This study seeks to reverse the trend that in rural areas, MFIs are financing agriculture to increase extensification rather than enhancing intensification in sub-Saharan Africa by challenging the role of MFI services in intensification.

The purpose of this study is to understand the factors that contribute to the number of reported coronavirus (COVID-19) deaths among low-income and high-income countries, and to understand the sources of differences between these two groups of countries.

Multiple linear regression models evaluate the socio-economic factors that determine COVID-19 deaths in the two groups of countries. The Oaxaca–Blinder decomposition is used to examine sources of differences between these two groups.

Low-income countries report a significantly lower average number of COVID-19 deaths compared to high-income countries. Community mobility and the easiness of carrying the virus from one place to another are significant factors affecting the number of deaths, while life expectancy is only significant in high-income countries. Higher health expenditure is associated with more reported deaths in both high- and low-income countries. Factors such as the transport infrastructure system, life expectancy and the percent of expenditure on health lead to the differences in the number of deaths between high- and low-income countries.

Our study shows that mobility measures taken by individuals to limit the spread of the virus are important to prevent deaths in both high- and low-income countries. Additionally, our results suggest that countries with weak health institutions underestimate the number of deaths from COVID-19, especially low-income countries. The underestimation of COVID-19 deaths could be affecting a great number of people in poverty in low-income economies.

This paper contributes to the emerging literature on COVID-19 and its relation to socio-economic factors by examining the differences in reported between deaths between rates in low-income and high-income countries.

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.

The purpose of this paper is to quantify the labor market outcomes of people with disabilities (PwD) in Indonesia and compares them to people without disabilities. It first studies the labor force participation of PwD before examining the large and persistent wage gaps they face. It explores whether these wage gaps are explained by differences in productivity, a distinction which has important implications for policies addressing these gaps.

The analysis is based on the Indonesian Family Life Survey Wave 5, which includes unique questions allowing for several definitions of disability. Multinomial logistic regression is used to study differences in type of employment for PwD. Wage gaps are estimated and corrected for selection using propensity score matching, supported by a Heckman selection model and Oaxaca–Blinder decomposition. Comparisons with other physically disadvantaged subgroups and the analysis of heterogeneity by job requirements and sector of work explore whether productivity gaps help explain wage gaps.

PwD generally have lower unconditional labor force participation, but disparities largely disappear when controlling for characteristics. Moreover, patterns vary depending on whether the measure of disability used depends on prior medical diagnosis. PwD that do not require prior diagnosis tend to work in more vulnerable employment. When they are employed for wages, people with these types of disabilities face lower wages, up to 22% lower. Meanwhile, (surprisingly) those with medically diagnosed conditions face no difference or a wage premium. This paper finds compelling evidence that, where a wage penalty exists, a substantial part is unexplained by observable characteristics.

Previous literature on disability has been mostly based on studies of high-income economies. This paper extends the literature to Indonesia, which differs from high-income contexts due to lack of mental healthcare resources and assistive technologies, as well as weaker rule of law. It provides unique insights based on types of disability and the salient dimensions of disability in the workplace. It also provides evidence that productivity differences do not explain the wage gap.