Two percent of CEOs are fired per year on average. To evaluate this magnitude, I solve and estimate a dynamic model of forced CEO turnover. The model features costly turnover and learning about CEO ability. To rationalize the two percent firing rate, boards must behave as if replacing the CEO...

A key distinction between some models of IPO pricing (e.g., auctions and bookbuilding) and others (e.g., fixed-priced models) is whether price discovery occurs in the primary market or the secondary market. We show that higher investment bank reputation is associated with 1) more active filing...

Asymmetric information models suggest that a borrower's choice of debt maturity depends on its private information about its default probabilities, i.e., borrowers with favorable information prefer short-term debt while those with unfavorable information prefer long-term debt. We test this...

We develop a model in which time-varying real investment opportunities lead to time-varying adverse selection in the market for initial public offerings. The model is consistent with several stylized facts known about the IPO market: economic expansions are associated with a dramatic increase in...

We develop a model in which time-varying real investment opportunities lead to time-varying adverse selection in the market for initial public offerings. The model is consistent with several stylized facts known about the IPO market: economic expansions are associated with a dramatic increase in...

Some existing nonparametric two-sample tests for equality of multivariate distributions perform unsatisfactorily when the two sample sizes are unbalanced. In particular, the power of these tests tends to diminish with increasingly unbalanced sample sizes. In this article, we propose a new...

The first essay uses a model of profit-maximizing hospitals to examine hospital responses to global budgeting in the forms of dumping and cost shifting. The main findings include: (1) Hospitals dump insured patients when the covered services are priced under costs. Whetherthe budget target is...

We put forward a quick clustering method for large numbers of data, with high dimensions, which is based on sensitive subspace consisting of the data set's sensitive dimensions. We first estimate the probability density of each dimension by the parzen window algorithm, enhance its optional...