This field experiment investigates the causal impact of mothers’ perceptions of gender norms on their employment attitudes and labor-supply expectations. We provide mothers of young children in Germany with information about the prevailing gender norm regarding maternal employment in their city. At baseline, over 70% of mothers incorrectly perceive this gender norm as too conservative – the most pronounced misperception among the various gender norms we examine. Our randomized information treatment improves the accuracy of these perceptions, significantly reducing the share of mothers who perceive gender norms as overly conservative. The treatment also shifts mothers’ own labormarket attitudes in a more liberal direction. Leveraging the fact that we assessed attitudes in a prior survey, we show that specifically the shifted attitude is a strong predictor of mothers’ future labor-market participation. Consistently, treated mothers are more likely to plan an increase in their working hours, particularly those with existing support to facilitate their employment.

This paper provides a comprehensive analysis of the forecastability of the real price of natural gas in the United States at the monthly frequency considering a universe of models that differ in their complexity and economic content. Our key finding is that considerable reductions in mean-squared prediction error relative to a random walk benchmark can be achieved in real time for forecast horizons of up to two years. A particularly promising model is a six-variable Bayesian vector autoregressive model that includes the fundamental determinants of the supply and demand for natural gas. To capture real-time data constraints of these and other predictor variables, we assemble a rich database of historical vintages from multiple sources. We also compare our model-based forecasts to readily available model-free forecasts provided by experts and futures markets. Given that no single forecasting method dominates all others, we explore the usefulness of pooling forecasts and find that combining forecasts from individual models selected in real time based on their most recent performance delivers the most accurate forecasts.

The IAB Job Vacancy Survey is a quarterly and representative establishment survey on labor demand and recruitment processes in Germany. The survey identifies the overall stock of vacancies in the German labor market, including those vacancies that are not reported to the Federal Employment Agency (FEA). The first module of the questionnaire collects information about the number and structure of vacancies, future personnel requirements, about the current economic situation and the expected development of participating establishments. The second module enquires about employer attitudes and firm use of current labor market instruments as well as the employer handling of people disadvantaged in the labor market. The third module asks for information about the last new hire and the last case of a failed recruitment effort. The Research Data Centre of the Federal Employment Agency offers the data sets of the survey waves from 2000 onwards.