We leverage insights from machine learning to optimize the tradeoff between bias and variance when estimating economic models using pooled datasets. Specifically, we develop a simple algorithm that estimates the similarity of economic structures across countries and selects the optimal pool of...

We develop a framework to nowcast (and forecast) economic variables with machine learning techniques. We explain how machine learning methods can address common shortcomings of traditional OLS-based models and use several machine learning models to predict real output growth with lower forecast...

This essay critically revisits the roles and influences of tax havens in the world economy. It combines various massages of available studies in one scheme, documents a number of observations, and proposes several issues for future research. -- tax havens ; tax avoidance ; tax evasion ;...

How did the rise of multinational enterprises (MNEs) put pressure on the prevailing international corporate tax framework? MNEs, and firms with market power, are not new phenomena, nor is the corporate income tax, which dates to the early 20th century. This prompts the question, what is...

Excess profit taxes (EPTs) emerge as an option to contribute to the extra needed revenues, avoiding a general increase in corporate tax rates, while having the prospect to serve as a gateway to converge toward a permanent efficient rent tax instaed of the corporate income tax. General unilateral...

In this study, we estimate the impacts of differences in international tax rates on the probability of choosing a location for an affiliate of a multinational firm. In particular, we distinguish between the tax sensitivity of Greenfield and M&A investments. Based on a novel firm-level dataset on...