While traditional empirical models using determinants like size and trade costs are able to predict RTA formation reasonably well, we demonstrate that allowing for machine detected non-linear patterns helps to improve the predictive power of RTA formation substantially. We employ machine...

Using a unique dataset of 22.5 million news articles from the Dow Jones Newswires Archive, we perform an in depth real-time out-of-sample forecasting comparison study with one of the most widely used data sets in the newer forecasting literature, namely the FRED-MD dataset. Focusing on U.S. GDP,...

We forecast New York state tax revenues with a mixed-frequency model using a number of machine learning techniques. We found boosting with two dynamic factors extracted from a select list of New York and U.S. leading indicators did best in terms of correctly updating revenues for the fiscal year...

This paper investigates the impact of news media information on improving short-term GDP growth forecasts by analyzing a large and unique corpus of 12.4 million news articles spanning from 1991 to 2018. We extract business cycle-related sentiment from each article using an annotated dataset from...

We examine the profitability of personalized pricing policies that are derived using different specifications of demand in a typical retail setting with consumer-level panel data. We generate pricing policies from a variety of models, including Bayesian hierarchical choice models, regularized...

We postulate a nonlinear DSGE model with a financial sector and heterogeneous households. In our model, the interaction between the supply of bonds by the financial sector and the precautionary demand for bonds by households produces significant endogenous aggregate risk. This risk induces an...

We study a competitive model in which market incompleteness implies that debt-financed firms may default in some states of nature and default may lead to the sale of the firms' assets at fire sale prices when markets are illiquid. This incompleteness is the only friction in the model and the...

The frequency with which firms adjust output prices helps explain persistent differences in capital structure across firms. Unconditionally, the most exible-price firms have a 19% higher long-term leverage ratio than the most sticky-price firms, controlling for known determinants of capital...

This short article studies the tax effects on a start-up investment decision under uncertainty. Since the representative firm can decide both when to invest and how much to borrow, the distortive effects are twofold. We thus show that the deadweight loss (namely, the ratio between the welfare...

In this article we use a stochastic model with one representative firm to study business tax policy under default risk. We will show that, for a given tax rate, the government has an incentive to reduce (increase) financial instability and default costs if its objective function is welfare (tax...