Forecasting during the COVID-19 pandemic entails a great deal of uncertainty. The same way that we would like electoral forecasters to include their confidence intervals to account for such uncertainty, we assume that COVID-19-related forecasts should follow that norm. Based on literature on...

Does the manner in which results are presented in empirical studies affect perceptions of the predictability of the outcomes? Noting the predominant role of linear regression analysis in empirical economics, we asked 257 academic economists to make probabilistic inferences given different...

Leadership behaviors of wildland firefighting teams engaged in firefighting activities are “shared” despite the existence of a highly bureaucratic and hierarchical organizational structure. This paradoxical type of leadership appears to be based on individual perceptions of the effectiveness...

There are many alternative approaches to selecting mortality models and forecasting mortality. The standard practice is to produce forecasts using a single model such as the Lee-Carter, the Cairns-Blake-Dowd, or the Age- Period-Cohort model, with model selection based on in-sample goodness of...

Outliers are observations that deviate significantly from the norm, and their detection has been a critical topic in various research areas and application domains, such as video surveillance, network intrusion detection, and disease outbreak detection. In recent years, deep learning-based...

This paper investigates which of the core types of innovation can be best predicted based on the website data of firms. In particular, we focus on four distinct key standard types of innovation – product, process, organisational, and marketing innovation in firms. Web-mining of textual data on...

The paper demonstrates the power of alternative data. Relying on the indicators obtained by mining online publicly available news articles, authors analyze their impact on Bitcoin returns. This research shows that in the first quarter of 2022 Bitcoin returns could be explained by the sentiment...

In this paper we adopt a principal components analysis (PCA) to reduce the dimensionality of the term structure and employ autoregressive models (AR) to forecast principal components which, in turn, are used to forecast swap rates. Arguing in favor of structural variation, we propose data...

The authors analyse the macroeconomic impact of the French work-sharing reform of 2000 (a reduction of standard working hours in combination with wage subsidies). Using a vector error correction model (VECM) for several labour market variables as well as inflation and output the authors produce...

This paper deals with the estimation of employment equations for Germany, which are to be used for forecasting and simulation purposes. The authors estimate both single and system error correction equations for German working hours using quarterly raw data covering the period 1980:1-2004:2....