We identify the individual resources that predicted psychological resilience during the COVID-19 lockdown. Using UK data, we compare psychological distress observed before COVID-19 with distress measured in April, May, and June 2020. After matching respondents on key characteristics, we find...

We provide empirical evidence on the impact of oil supply shocks on global aggregates. To do this, we first extract structural oil supply shocks from a standard oil-price determination model found in the literature. Impulse response functions are then estimated using local projections. This...

This note uses industry data and a unique dataset of small and medium-sized merchants to provide insights into the acquirer-merchant market in Canada. Three main findings are presented. First, smaller merchants pay their acquirer more for every dollar of card payment than larger merchants....

We study how the large and unexpected increase in the minimum wage in Poland impacted the gender wage gap. For this purpose, we employ a distribution regression model coupled with a difference-in-differences estimator that recovers changes in the gender wage gap with minimum assumptions on the...

We apply a relatively novel leading-lagging (LL) method to four leading and one lagging indexes for industrial production (IP) in Germany. We obtain three sets of results. First, we show that the sentiment-based ifo index performs best in predicting the general changes in IP (−0.596, range...

The National University of Colombia boasts a clear and egalitarian salary regime for its academic staff. Apart from rules concerning maternity and paternity leaves, which follow national Colombian legislation, the Academic Personal Statute is completely free of gender-based norms. Salaries are...

This paper uses information theoretic methods to introduce a new class of probability distributions and estimators for competing explanations of the data in the binary choice model. No explicit parameterization of the function connecting the data to the Bernoulli probabilities is stated in the...

Dummy variables can be used to detect, validate and measure the impact of outliers in data. This paper uses a model to evaluate the effectiveness of dummy variables in detecting outliers. While generally confirming some findings in the literature, the model refutes the presumption that the...

We study the global impact of the Chinese economy based on a novel indirect approach where the spillover effect is quantified from a forecast error model under relatively favorable identifying con-ditions. Findings from the real-time World Economic Outlook data over the period 2004-2015 indicate...

Datasets that are terabytes in size are increasingly common, but computer bottlenecks often frustrate a complete analysis of the data. While more data are better than less, diminishing returns suggest that we may not need terabytes of data to estimate a parameter or test a hypothesis. But which...