Dynamic discrete choice models (DDC) are not identified nonparametrically. However, the non-identification of DDC models does not necessarily imply non-identification of counterfactuals of interest. Using a novel approach that can accommodate both nonparametric and restricted payoff functions,...

This paper develops a vector autoregression (VAR) for time series which are observed at mixed frequencies - quarterly and monthly. The model is cast in state-space form and estimated with Bayesian methods under a Minnesota-style prior. We show how to evaluate the marginal data density to...

In recent years, there has been renewed interest in the moments of the yield curve (or alternatively, the term spread) as a predictor of future economic activity, defined as either recessions, or industrial production growth. In this paper, we re-examine the evidence for this predictor for the...

We propose two new jump-robust estimators of integrated variance based on high-frequency return observations. These MinRV and MedRV estimators provide an attractive alternative to the prevailing bipower and multipower variation measures. Specifically, the MedRV estimator has better theoretical...

This article examines the performance of various financial variables as predictors of subsequent U.S. recessions. Series such as interest rates and spreads, stock prices, currencies, and monetary aggregates are evaluated singly and in comparison with other financial and non-financial indicators....

This paper proposes a new way of displaying and analyzing macroeconomic time series to form recession forecasts. The proposed data displays contain the last three years of each expansion. These allow observers to see for themselves what is different about the last year before recession. Based on...

This paper is concerned with the estimation of the parameters in a dynamic simultaneous equation model with stationary disturbances under the assumption that the variables are subject to random measurement errors. The conditions under which the parameters are identified are stated. An...

We consider identification of nonparametric random utility models of multinomial choice using "micro data," i.e., observation of the characteristics and choices of individual consumers. Our model of preferences nests random coefficients discrete choice models widely used in practice with...

I prove that the joint distribution of random coefficients and additive errors is identified in a mulltinomial choice model. No restrictions are imposed on the support of the random coefficients and additive errors. The proof uses large support variation in choice-specific explanatory variables...

We study habitual brand loyalty, one of the earliest empirically-studied forms of switching costs and a classic source of structural state-dependence in consumer demand. Auxiliary instruments and economically-motivated restrictions can tighten nonparametric bounds on the extent of brand loyalty...