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[Objective:] This study examines whether paternal part-time employment is related to greater involvement by fathers in child care and housework, both while fathers are working part-time and after they return to full-time employment. [Background:] The study draws on four strands of theory—time availability, bargaining, gender ideology, and gender construction. It studies couples' division of labor in Germany, where policies increasingly support a dual-earner, dual-carer model. [Method:] The study uses data from the German Socio-Economic Panel from 1991 to 2015 on employed adult fathers living together with at least one child younger than age 17 and the mother. The analytic sample comprises 51,230 observations on 8,915 fathers. Fixed effects regression techniques are used to estimate the effect of (previous) part-time employment on fathers' child-care hours, housework hours, and share of child care and housework. [Results:] Fathers did more child care and housework while they worked part time. Yet, most fathers reverted to previous levels of involvement after returning to full-time work. The only exception was fathers with partners in full-time employment, who spent more time doing child care and took on a greater share of housework after part-time employment than before. [Conclusion:] The findings are largely consistent with the time availability perspective, although the results for fathers with full-time employed partners indicate that the relative resources and gender ideology perspectives have some explanatory power as well.

This article assesses the effect of climate change on livestock production in Sub‐Saharan Africa, for a sample of 45 countries over the period 2000–2021. Using a two‐factor fixed effects panel data model, our results obtained by the two‐way fixed effects estimator show that (i) climate change negatively influences livestock production through high temperatures, while abundant rainfall is beneficial. (ii) Through transmission channels, we find that maize price volatility exacerbates the negative effect of rising temperatures on livestock production, while it reduces the beneficial effect of abundant rainfall. Furthermore, we find that water availability mitigates the adverse effect of rising temperatures on livestock, while enhancing the beneficial effect of rainfall on livestock. Finally, we concede that conflicts reduce the beneficial effect of rainfall on livestock production. To increase livestock production in Sub‐Saharan Africa, we recommend: the practice of pastoralism, based on the production of plants and fodder adapted to climate change, the improvement of animal nutrition, and the inclusion of breeders in the decision‐making process in the cattle industry.

Objectives We aim to examine the extent to which role ambiguity modifies the association between job stressors and workers’ psychological ill‐being. Methods We used data from 41 962 observations from 13 811 individuals (10 269 males and 3542 females) who participated in three to eight waves of an occupational survey conducted in Japan. We estimated fixed‐effects models to explain psychological distress (defined by Kessler 6 score ≥13) by role ambiguity. Four types of job stressors (i.e., high job demands, low job control, high effort, and low reward), and their interactions were examined along with potential confounders. We repeated a similar analysis for job dissatisfaction. Results The fixed‐effects models showed that role ambiguity as well as the four job stressors were positively associated with psychological distress, albeit somewhat more modestly than the results of the pooled cross‐sectional models. More notably, we found that role ambiguity substantially amplified the association between job stressors and psychological distress; for example, a combination of high job demands and high role ambiguity added to the risk of psychological distress by 3.5% (95% confidence interval [CI]: 2.5%–4.5%), compared with 1.4% (95% CI: 0.4%–2.3%) for a combination of high job demands and low role ambiguity. In contrast, we did not find a modifying effect of role ambiguity on the association between low job control and psychological distress. Similar results were observed for job dissatisfaction. Conclusion The results underscore the importance of reducing role ambiguity to mitigate the adverse impact of job stressors on workers’ psychological ill‐being.

The risk-balancing hypothesis (RBH) suggests that farms will take less business risk as their financial risk increases, but existing literature provides empirical evidence that the RBH might be invalid under certain circumstances. We present a unified model that explains the conditions under which the RBH holds or is invalidated by recognizing the role of latent heterogeneity among farms. We generalize the RBH idea and trace the source of credit risk back to latent heterogeneity among farms. We then apply recent literature to longitudinal data from a panel of Dutch farms and classify segments using a finite mixture regression fixed-effects model and find that the RBH may not apply to all groups in the same way.

Background The fixed effects model is a useful alternative to the mixed effects model for analyzing stepped-wedge cluster randomized trials (SW-CRTs). It controls for all time-invariant cluster-level confounders and has proper control of type I error when the number of clusters is small. While all clusters in a SW-CRT are typically designed to crossover from the control to receive the intervention, some trials can end with unexposed clusters (clusters that never receive the intervention), such as when a trial is terminated early due to safety concerns. It was previously unclear whether unexposed clusters would contribute to the estimation of the intervention effect in a fixed effects analysis. However, recent work has demonstrated that including an unexposed cluster can improve the precision of the intervention effect estimator in a fixed effects analysis of SW-CRTs with continuous outcomes. Still, SW-CRTs are commonly designed with binary outcomes and it is unknown if those previous results extend to SW-CRTs with non-continuous outcomes. Methods In this article, we mathematically prove that the inclusion of unexposed clusters improves the precision of the fixed effects intervention effect estimator for SW-CRTs with binary and count outcomes. We then explore the benefits of including an unexposed cluster in simulated datasets with binary or count outcomes and a real palliative care data example with binary outcomes. Results The simulations show that including unexposed clusters leads to tangible improvements in the precision, power, and root mean square error of the intervention effect estimator. The inclusion of the unexposed cluster in the SW-CRT of a novel palliative care intervention with binary outcomes yielded smaller standard errors and narrower 95% Wald Confidence Intervals. Conclusions In this article, we demonstrate that the inclusion of unexposed clusters in the fixed effects analysis can lead to the improvements in precision, power, and RMSE of the fixed effects intervention effect estimator for SW-CRTs with binary or count outcomes.

We revisit the Helmert transformation, and provide a useful and simple derivation of the joint distribution of the sample mean and the sample variance in samples from independently and identically distributed normal random variables. Our derivation is distinguished by concreteness, very little abstractness, and should be appealing to beginning students of statistics, and to both beginning and advanced students of econometrics. We also highlight one fruitful application of the Helmert transformation in panel data econometrics. The Helmert transformation can be used to eliminate the fixed effects in the estimation of fixed effects models, and we briefly review this application of the transformation in the panel data context.

Summary This paper studies the random effects model and the fixed effects model for spatial panel data. The model includes a Cliff and Ord type spatial lag of the dependent variable as well as a spatially lagged one-way error component structure, accounting for both heterogeneity and spatial correlation across units. We discuss instrumental variable estimation under both the fixed and the random effects specifications and propose a spatial Hausman test which compares these two models accounting for spatial autocorrelation in the disturbances. We derive the large sample properties of our estimation procedures and show that the test statistic is asymptotically chi-square distributed. A small Monte Carlo study demonstrates that this test works well even in small panels.

Previous research suggests that household tasks prohibit women from unfolding their full earning potential by depleting their work effort and limiting their time flexibility. The present study investigated whether this relationship can explain the wage gap between mothers and nonmothers in West Germany. The empirical analysis applied fixed-effects models and used self-reported information on time use and earnings as well as monthly family and work histories from the German Socio-Economie Panel (1985-2007, N = 1,810; Wagner, Frick, & Schupp, 2007). The findings revealed that variation in reported time spent on child care and housework on a typical weekday explains part of the motherhood wage penalty, in particular for mothers of very young children. Furthermore, housework time incurred a significant wage penalty, but only for mothers. The authors concluded that policies designed to lighten women's domestic workload may aid mothers in following rewarding careers.

We examined 7 life-course pathways from adolescence through the early adult years and their links with general health and psychosocial adjustment among 2,290 women from the National Longitudinal Study of Adolescent Health. Young women who followed a pathway involving college attendance to full-time employment with no family-formation transitions were functioning comparatively well with respect to general health, depression, and self-esteem. In contrast, young women who followed pathways involving early motherhood were functioning less well. Fixed-effects models suggested that the differences were due to selection factors. Young women who followed the pathway of college to full-time employment exhibited an increase in heavy drinking, whereas women who became married mothers exhibited a decrease in the same. Involvement in illegal behavior declined for all groups but least so for women who attended college.

We consider estimation and inference in panel data models with additive unobserved individual specific heterogeneity in a high-dimensional setting. The setting allows the number of time-varying regressors to be larger than the sample size. To make informative estimation and inference feasible, we require that the overall contribution of the time-varying variables after eliminating the individual specific heterogeneity can be captured by a relatively small number of the available variables whose identities are unknown. This restriction allows the problem of estimation to proceed as a variable selection problem. Importantly, we treat the individual specific heterogeneity as fixed effects which allows this heterogeneity to be related to the observed time-varying variables in an unspecified way and allows that this heterogeneity may differ for all individuals. Within this framework, we provide procedures that give uniformly valid inference over a fixed subset of parameters in the canonical linear fixed effects model and over coefficients on a fixed vector of endogenous variables in panel data instrumental variable models with fixed effects and many instruments. We present simulation results in support of the theoretical developments and illustrate the use of the methods in an application aimed at estimating the effect of gun prevalence on crime rates.