Explore the vast range of titles available.

This article considers generalized linear models in the presence of many controls. We lay out a general methodology to estimate an effect of interest based on the construction of an instrument that immunizes against model selection mistakes and apply it to the case of logistic binary choice model. More specifically we propose new methods for estimating and constructing confidence regions for a regression parameter of primary interest α 0 , a parameter in front of the regressor of interest, such as the treatment variable or a policy variable. These methods allow to estimate α 0 at the root-n rate when the total number p of other regressors, called controls, potentially exceeds the sample size n using sparsity assumptions. The sparsity assumption means that there is a subset of s < n controls, which suffices to accurately approximate the nuisance part of the regression function. Importantly, the estimators and these resulting confidence regions are valid uniformly over s-sparse models satisfying s 2 log  2 p = o(n) and other technical conditions. These procedures do not rely on traditional consistent model selection arguments for their validity. In fact, they are robust with respect to moderate model selection mistakes in variable selection. Under suitable conditions, the estimators are semi-parametrically efficient in the sense of attaining the semi-parametric efficiency bounds for the class of models in this article.

This study aims to analyze the education-job mismatch effect on the return to education in Cameroon, by using data on employment provided by the National Institute of Statistics. Based on Verdugo and Verdugo’s model estimate, we use several types of regression models to examine both the heterogeneity in returns to education derived from education-job mismatch and the choice of different types of selection model. Results show that overeducation is associated with a wage penalty while undereducation leads to a wage premium. With each year of schooling, differences in earning are significant between overeducated, undereducated, and well-matched people. They also show a substantial difference in the magnitude of coefficients with respect to the control variables for different types of selection model. This difference observed across different models implies that the estimation of returns to schooling is highly sensitive to the model’s specification. Beyond other contributions, this study highlights the need to exercise a fair degree of care in the choice of an appropriate model for analysis.

Climate Information (CI) services play a critical role in enhancing smallholder farmers' adaptive capacity to climate change. However, the effective uptake of CI in rural areas remains limited, and few studies have examined the underlying challenges. This study investigates the drivers and barriers to CI adoption among smallholder farmers in Migori County (Kenya) and the determinants of access, demand, and willingness to pay (WTP) for CI. Data from 318 households were analysed using descriptive statistics, chi-square, and a double-selection probit model, which examined the sequential decision-making process influencing farmers' engagement with CI. The study finds that while 52% accessed CI, 61.1% of them expressed dissatisfaction with its adequacy for decision-making. Farmers mainly accessed seasonal forecasts and weather warnings, primarily via radio. However, they prioritize information on rainfall timing and a combination of either seasonal or early warnings with production impact data as the most critical CI. Enhancing household food security was a primary motivation for CI adoption, reported by 92.8% of all CI users, with a significantly higher proportion among upstream farmers (100%) compared to midstream (93.4%) and downstream (85.5%) farmers (X 2  = 8.46, p  = 0.015). Soil preparation, weeding, and cropping were the three operations most influenced by CI, with no significant differences among the zones ( p  > 0.05). The double-selection probit model revealed that age, education, farm size, and watershed section significantly influence farmers' engagement with CI, i.e., access to CI, desire for additional CI, and WTP for it. Older farmers showed a negative association with access to and desire for additional CI, while education and farm size were strong positive predictors of all stages of CI adoption.

In the rapidly evolving business landscape of Thailand, the design and facilities of office buildings play a crucial role in enhancing employee satisfaction and productivity. This study seeks to answer the question: “How can office building facilities be optimized to meet the diverse preferences of occupants in Thailand, thereby improving their satisfaction and productivity”? This study employs a copula-based ordinal regression model combined with machine learning techniques to investigate the determinants of facility preferences in office buildings in Thailand. By analyzing data from 372 office workers in Bangkok, we identify the factors influencing facility needs and preferences, and measure the correlation between these preferences. Our findings reveal that safety and security are the highest-rated amenities, indicating their importance in the workplace. The findings reveal distinct preferences across demographic groups: age negatively influences the demand for certain amenities like lounges, while higher education levels increase the preference for cafeteria services. Employees in smaller firms show a higher preference for lounges and fitness centers but lower for restaurants and cafeterias. Interestingly, the size of the enterprise does not significantly affect preferences for fundamental facilities like security and cleaning. The study also uncovers the significant role of gender and income in shaping preferences for certain facilities. These results suggest that while basic amenities are universally valued, luxury or leisure-oriented facilities are more appreciated in smaller, possibly more community-focused work environments. This study highlights the need for tailored facility management in office buildings, considering the diverse needs of different employee groups, which has significant implications for enhancing workplace satisfaction and productivity.

Purpose The purpose of this paper is to highlight the pivotal role of overeducation in explaining the unexplained part of the gender pay gap (GPG), i.e. the component usually attributed to gender discrimination in the Oaxaca-Blinder decomposition. Design/methodology/approach The study uses a large Italian data set (ISFOL PLUS 2005–2014) to estimate the GPG among properly educated and overeducated workers. The model simultaneously accounts for both participation bias and endogeneity bias by applying an extension of the Heckman’s two-stage procedure. Findings Estimates show that the GPG is significantly higher among overeducated than among properly educated workers because women’s unobservable characteristics driving female employment into overeducation also drag down female wages more than men’s unobservable characteristics drag down male wages. Correcting for the participation and overeducation decisions, the unexplained portion of the GPG disappears among overeducated workers, while it remains significant among properly educated individuals. Originality/value The authors draw the conclusion that overeducation is, first, a first-best matching for individuals (both men and women) compensating with more education for their lower productive characteristics. Second, it may be a signaling device for women spending their useless-for-the-job diploma to inform employers on their valuable though unobservable productive characteristics and fight gender wage discrimination. The results favor education as a tool of counteracting gender discrimination. Hence, as females are less overeducated than males despite their larger representation in higher education, there should not be concern that expanding higher education will disadvantage females.

A prototype of a hydrogen generator with double selection of atoms by quantum state is developed. Results of measurements of the instability of the frequency of a hydrogen frequency standard based on this generator are presented.

This paper examines how spouses in dual-earner couples weigh each partner's expected wage growth in the decision to migrate. Previous research suggests that husbands' job prospects dominate the migration choice irrespective of their relative earnings potential. Based on British panel data, this paper employs an endogenous switching model and estimates wage differentials of migrating vs. staying for husbands and wives corrected for double selectivity of migration and employment. Dual-earner couples attach a positive weight to each partner's expected wage gains when deciding to migrate. Moreover, migrant wives' employment decreases temporarily, and there are significant selection effects in migration and employment amongst non-migrants.

By a theorem due to Sklar, a multivariate distribution can be represented in terms of its underlying margins by binding them together using a copula function. By exploiting this representation, the 'copula approach' to modelling proceeds by specifying distributions for each margin and a copula function. In this paper, a number of families of copula functions are given, with attention focusing on those that fall within the Archimedean class. Members of this class of copulas are shown to be rich in various distributional attributes that are desired when modelling. The paper then proceeds by applying the copula approach to construct models for data that may suffer from selectivity bias. The models examined are the self-selection model, the switching regime model and the double-selection model. It is shown that when models are constructed using copulas from the Archimedean class, the resulting expressions for the log-likelihood and score facilitate maximum likelihood estimation. The literature on selectivity modelling is almost exclusively based on multivariate normal specifications. The copula approach permits selection modelling based on multivariate non-normality. Examples of self-selection models for labour supply and for duration of hospitalization illustrate the application of the copula approach to modelling.

Cette étude porte sur les déterminants informationnels du processus d’accès à la formation professionnelle à la demande du salarié, à partir de l’enquête Defis (2015). Un modèle multivarié permet de traiter les biais de sélection au cours de la séquence des choix des salariés en matière de demande et de participation à une formation, et de rendre compte de formes de non-recours pour certaines catégories : seniors, salariés peu qualifiés, ouvriers et employés, salariés en contrats courts. Les informations diffusées lors d’entretiens professionnels ou par la hiérarchie, favoriseraient le sentiment de penser possible de se former et la demande effective de formation. La participation à une formation demandée serait conditionnée par le fait que l’information soit donnée par un interlocuteur impliqué dans la formation (hiérarchie, RH ou représentant du personnel).Classification JEL : C34, J08, J24, M53. Information and employee’s initiative on training process and outcomesThis study examines the informational determinants of training access, when training relies upon employee’s demand. We use an original French dataset (Defis, 2015) to construct measures of the training informational environment, and specify a multivariate sequential Probit model which allows to control different selection biases along the training access and outcome processes. Our results point to the existence of training “non take-up” for some employees categories : senior, low-qualified, blue and white collars, short-term employees. Information has to be dispatched by hierarchy or during employee interviews in order to promote employees initiative on training application. Access to training is then conditional to having information provided by interlocutors familiar with training policy (hierachy, human resources, staff representative).

This study investigates the public-private sector wage gap in Latvia using microdata from the labour force survey. The severity of public sector wage cuts employed as a response to the economic crisis and subsequent recovery provides a test bed to analyse whether and how the public-private sector wage gap has adjusted after consolidation-driven wage cuts. Findings reveal that the observed wage gap is slightly in favour of the public sector; however, once differences in individual characteristics and selection effects are considered, results point to a private sector wage premium. Findings also suggest that the private sector wage premium has increased since the pre-crisis period. A significant private sector wage premium raises doubts on whether a system that is reliant on discretionary fiscal measures is efficient enough in eliminating unwarranted differences in wage. In particular, whether a re-adjustment process of public sector wages works after consolidation-driven wage cuts.