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The changes in women’s and men’s work lives have been considerable in recent decades. Yet much of the recent research on gender differences in employment and earnings has been of a more snapshot nature rather than taking a longer comparative look at evolving patterns. In this paper, we use 50 years (1964–2013) of US Census Annual Demographic Files (March Current Population Survey) to track the changing returns to human capital (measured as both educational attainment and potential work experience), estimating comparable earnings equations by gender at each point in time. We consider the effects of sample selection over time for both women and men and show the rising effect of selection for women in recent years. Returns to education diverge for women and men over this period in the selection-adjusted results but converge in the OLS results, while returns to potential experience converge in both sets of results. We also create annual calculations of synthetic lifetime labor force participation, hours, and earnings that indicate convergence by gender in worklife patterns, but less convergence in recent years in lifetime earnings. Thus, while some convergence has indeed occurred, the underlying mechanisms causing convergence differ for women and men, reflecting continued fundamental differences in women’s and men’s life experiences.

The purpose of this paper is to consider a new way of estimating the gender wage gap by introducing individual risk attitudes that is applied to representative Korean data.

The selection bias via risk attitudes results in the overestimation of this wage gap. Women are more risk averse and hence prefer not to be active in the labour market or, if they are active, prefer to work in the public sector, where wages are generally lower than in the private sector. This paper explains the reduced gender wage gap by developing an appropriate sample-selection model, with wage decompositions corrected for selection.

Self-selection based on risk attitudes is shown to partly explain the gap that is popularly perceived as reflecting gender discrimination.

It is the first attempt to explain the gender wage gap by looking at the individual risk preference through work status selection.

The purpose of this paper is to measure the effect that knowing the Catalan language has on individuals’ comparative advantage to perform certain jobs in Catalonia (Spain), where Catalan and Spanish coexist.

Using census data for 1991 and 1996, and for individuals born in Spain, the paper first estimates a Probit model for individuals’ level of Catalan proficiency in order to correct for the possible endogeneity of Catalan knowledge, as it may be jointly determined with occupational selection or be a reflection of unobserved human capital or innate ability. Then, it estimates a bivariate Probit model for the probability of choosing a given occupation conditional on a given Catalan proficiency level.

The paper finds that advanced proficiency in Catalan reinforces selection into being employed, being an entrepreneur, and into white‐collar occupations and communication‐intensive jobs. Being able to read and speak Catalan increases selection into white collar occupations by between 11 and 16 percentage points, while writing Catalan increases by 4 to 7 percentage points the probability of engaging in services, and government and educational activities.

Because census data are cross‐sectional panel effects on language selection cannot be analyzed. Nevertheless, the paper's results suggest that investing in learning the local language, at the firm and the government level, improves job matching and assimilation of workers to multilingual economies. The authors suggest a cost‐benefit analysis to assess the effectiveness of language policies for further research.

The results contribute to the scarce literature on the economic value of a language, i.e. on how much language knowledge as a form of human capital reinforces individuals’ comparative advantage to perform certain tasks.

The purpose of this paper is to investigate whether immigrants in the USA receive an earnings premium associated with marrying a native.

The raw premium revealed by the 2000 US Census data is suspect due to possible endogeneity and selection bias. Instrumental variables estimation, a sample selection model, and a counterfactual construction method are used to address these issues.

Results suggest a positive and modest intermarriage premium, although the magnitude varies with the estimation technique. The evidence is particularly strong for immigrants with high English proficiency, college graduates, and immigrants older than 12 upon arrival in the USA.

It is shown that the size of intermarriage premiums varies significantly across different immigrant groups. The empirical results provide insights into the economic assimilation process and mechanisms through which intermarriage influences the labor market outcomes of immigrants.

This study examines the impact of access to credit on the technical efficiency (TE) of maize-producing smallholder farmers in Ethiopia and explores factors determining credit utilization.

The study relies on nationally representative data collected in 2015/2016. The data are analyzed by combining the Propensity Score Matching technique with a stochastic frontier model that corrects selectivity bias arising from unobserved variables.

The result shows that credit service improves TE and helps smallholder farmers to achieve the maximum possible output level from a given set of inputs used.

To the best of author’s knowledge, no study has yet measured the impact of access to credit on TE by controlling for both observed and unobserved heterogeneities. Existing research relied on a single production frontier model, assuming that credit users and non-users have similar production characteristics or ignored selection bias due to observable and unobservable characteristics.

This paper aims to determine the characteristics of board certification among US physicians and to test whether accounting for the expected gains to certification alters the pattern of the determinants of board certification.

Splitting the sample into sub‐samples by characteristics associated with certification/non‐certification identified in a probit, the incremental gain to certification from log‐earnings equations is identified. Realizing that these methods are susceptible to sample selection, correction is made for it using the Heckman approach. Using the sample selection corrected equations, the expected gain to certification among those who certify is then predicted and those who do not certify is then predicted and this difference is included as a proxy for the expected gain in the original probit to ascertain whether including the expected gain alters the determinants of certification.

Accounting for the expected gain alters the pattern of the determinants of certification. Although some groups such as blacks appear less likely to certify, after accounting for their expected return to certification, they are not as less likely. This is explained in terms of the expected marginal return to certification, market structure and practice setting.

The data used in the analysis apply only to young physicians in the USA. Also, these results may be applicable only to the particular cohort used in this analysis.

The findings help to explain the absence of minority board certified physicians within the USA.

This paper is the first to simultaneously estimate the returns to physician board certification and the decision to obtain certification.

This paper analyzes the age pay gap in Italy (22%), particularly as it is of interest in an aging society and as it may affect social cohesion. Instead of the traditional approach for model selection, we use a machine-learning approach (post double robust Least Absolute Shrinkage Operator [LASSO]). This approach allows us to reduce Omitted Variable Bias (OVB), given data restrictions, and to obtain a robust estimate of the conditional age pay gap. We then decompose the conditional gap and analyze the impact of four further potential sources of heterogeneity (workers', sectors', and occupations' permanent heterogeneity as well as sample selection bias). The results suggest that age discrimination in pay is only perceived but not real in Italy for both men and women.

This work examines the returns to education for workers who pursue additional education after time out of the labor force. It compares those who remain in the labor force during additional education with those who drop out of the labor force during additional education. It compares two cohorts of the National Longitudinal Survey of Youth (NLSY).

This work utilizes a difference equation to estimate the returns to education for workers who pursue additional education after time spent out of school and in the labor force.

The results indicate a sheepskin return of approximately 14% for those who remain in the labor force and a return of approximately 9% to years of additional education for those who drop out of the labor force. This contrasting pattern of returns is robust to sample selection correction and a variety of checks.

This work does not fully account for all threats to causation. Further research could pursue these and make use of data from more clearly defined periods of education.

This work finds key differences between the internal labor market faced by those remaining in the labor force and the external labor market faced by those dropping out of the labor force. A policy focused on re-training workers should account for these differences.

This is the first work to compare workers who pursue additional education while remaining in the labor force to workers who pursue additional education and drop out of the labor force.

A case study of the analysis of operator reponse times following an abnormal event is presented. A number of timings of operator responses on a full‐scale nuclear plant simulator have been taken. These timings are compared with the human cognitive reliability (HCR) model. Agreement with the basic framework of the model is shown. Based on the data collected and on operators′ judgements on behaviour differences on simulators and the plant, criticisms of some aspects of the model are raised. The principal findings are: (1) the technique relies on the judgement of the analyst in the correct selection of behaviour type. The results of the analysis are very sensitive to this behaviour type; (2) the methods proposed for estimating the median response time are questioned, particularly when applying data from simulator measurements to the plant.

A very wide variety of alloy types are available for selection to combat the potential corrosion problems posed in a diverse range of industries. Although in today's climate cost reduction is an important goal, the price of unexpected failure of equipment is often measured as risk to human life, and materials selection must always be given a prime place in design, engineering and construction. Material selection should not be based simply on low installed cost of equipment — the need to maintain safety standards and effective long‐term utilization of a production asset, with minimum costly maintenance and downtime, mandate the selection of materials which can be justified on the basis of life‐cycle cost and risk analysis. The material chosen should provide the lowest cost viable, and if possible, “fit and forget” solution. In the Offshore Oil and Gas industry in the North Sea the solution adopted would need to address the CRINE cost reduction strategy.