We propose a method to correct estimates from historical linked data for bias arising from type-I error--"false matches." We estimate the rate of false matching from the disagreement rate in characteristics that should agree across the two linked datasets. Combined with an understanding of the...

Broad, long-term financial and economic datasets are a scarce resource, in particular in the European context. In this paper, we present an approach for an extensible, i.e. adaptable to future changes in technologies and sources, data model that may constitute a basis for digitized and...

We provide data and code that successfully reproduces nearly all crosssectional stock return predictors. Our 319 characteristics draw from previous meta-studies, but we differ by comparing our t-stats to the original papers' results. For the 161 characteristics that were clearly significant in...

Managing big data and data analytics poses unique challenges to many organisations. The effective use of such data is essential to planning business strategies and ensuring future corporate success. Organizations need to know how best to capitalise on the information that they have access to....

This review article, which was solicited by the Geneva Risk and Insurance Review, surveys work that has been done using an empirical framework for analyzing selection in insurance markets developed by Einav, Finkelstein, and Cullen (2010). We briefly review that framework, and then describe a...