This paper explores the uniformity of inference for parameters of interest in nonlinear models with endogeneity. The notion of uniformity is fundamental in these models because due to potential endogeneity, the behavior of standard estimators of these parameters is shown to vary with where they...

This paper evaluates the role of various volatility specifications, such as multiple stochastic volatility (SV) factors and jump components, in appropriate modeling of equity return distributions. We use estimation technology that facilitates non-nested model comparisons and use a long data set...

Games with asymmetric information play a prominent role in the theoretical literature of malpractice disputes. The common modeling framework in many papers is a game in extensive form which consists of two stages. In the first stage, one agent makes a settlement demand, and the other agent...

This paper studies the empirical performance of jump-diffusion models that allow for stochastic volatility and correlated jumps affecting both prices and volatility. The results show that the models in question provide reasonable fit to both option prices and returns data in the in-sample...

Due to differences in the effectiveness and side effects of different drugs, uncertainty is an important component of prescription drug choice. This uncertainty can cause patients and doctors to experiment with different drugs until they find a good match. In this paper, we specify and estimate...

This paper provides a general framework that enables many existing inference methods for predictive accuracy to be used in applications that involve forecasts of latent target variables. Such applications include the forecasting of volatility, correlation, beta, quadratic variation, jump...

We evaluate various economic modelsí relative performance in forecasting future US output growth and inflation on a monthly basis. Our approach takes into account the possibility that the modelsí relative performance can be varying over time. We show that the modelsí relative performance has,...

The objective of this paper is to identify which parameters of a model are stable over time. Existing procedures can only be used to test whether a given subset of parameters is stable, and cannot be used to find which subset of parameters is stable. We propose a new procedure that is...

We provide an extensive evaluation of the predictive performance of the U.S. yield curve for U.S. GDP growth by using a new test for forecast breakdown as well as a variety of in-sample and out-of-sample testing procedures. Empirical research over the past decades uncovered a strong predictive...

We propose a new Information Criterion for Impulse Response Function Matching estimators of the structural parameters of macroeconomic models. The main advantage of our procedure is that it allows the researcher to select the impulse responses that are most informative about the deep parameters,...