Emirati women do not shy away from competition: evidence from a patriarchal society in transition

We explore gender attitudes towards competition in the United Arab Emirates—a traditionally patriarchal society which in recent times has adopted numerous policies to empower women and promote their role in the labor force. The experimental treatments vary whether individuals compete in single-sex or mixed-sex groups. In contrast to previous studies, women in our sample are not less willing to compete than men. In fact, once we control for individual performance, Emirati women are more likely to select into competition. Our analysis shows that neither women nor men shy away from competition, and both compete more than what would be optimal in monetary terms as the fraction of men in their group increases. We offer a detailed survey of the literature and discuss possible reasons for the lack of gender differences in our experiment

Can urban coffee consumption help predict US inflation?

Motivated by the importance of coffee to Americans and the significance of the coffee subsector to the US economy, we pursue three notable innovations. First, we augment the traditional Phillips curve model with the coffee price as a predictor, and show that the resulting model outperforms the traditional variant in both in-sample and out-of-sample predictability of US inflation. Second, we demonstrate the need to account for the inherent statistical features of predictors such as persistence, endogeneity, and conditional heteroskedasticity effects when dealing with US inflation. Consequently, we offer robust illustrations to show that the choice of estimator matters for improved US inflation forecasts. Third, the proposed augmented Phillips curve also outperforms time series models such as autoregressive integrated moving average and the fractionally integrated version for both in-sample and out-of-sample forecasts. Our results show that augmenting the traditional Phillips curve with the urban coffee price will produce better forecast results for US inflation only when the statistical effects are captured in the estimation process. Our results are robust to alternative measures of inflation, different data frequencies, higher order moments, multiple data samples and multiple forecast horizons