Showing 1 - 10 of 125
The paper evaluates the usefulness of a nonparametric approach to Bayesian inference by presenting two applications. The approach is due to Ferguson (1973, 1974) and Rubin (1981). Our first application considers an educational choice problem. We focus on obtaining a predictive distribution for...
Persistent link: https://www.econbiz.de/10005832262
In this paper we propose a new estimator for a model with one endogenous regressor and many instrumental variables. Our motivation comes from the recent literature on the poor properties of standard instrumental variables estimators when the instrumental variables are weakly correlated with the...
Persistent link: https://www.econbiz.de/10005130013
In this paper, we explore Bayesian inference in models with many instrumental variables that are potentially weakly correlated with the endogenous regressor. The prior distribution has a hierarchical (nested) structure. We apply the methods to the Angrist-Krueger (AK, 1991) analysis of returns...
Persistent link: https://www.econbiz.de/10005725292
Persistent link: https://www.econbiz.de/10001590475
Persistent link: https://www.econbiz.de/10014247290
Persistent link: https://www.econbiz.de/10013476731
Persistent link: https://www.econbiz.de/10013440502
We examine the implications of arbitrage in a market with many assets. The absence of arbitrage opportunities implies that the linear functionals that give the mean and cost of a portfolio are continuous; hence there exist unique portfolios that represent these functionals. These portfolios span...
Persistent link: https://www.econbiz.de/10005778513
We examine the implications of arbitrage in a market with many assets. The absence of arbitrage opportunities implies that the linear functionals that give the mean and cost of a portfolio are continuous; hence there exist unique portfolios that represent these functionals. The mean variance...
Persistent link: https://www.econbiz.de/10005779022
This paper considers a panel data model for predicting a binary outcome. The conditional probability of a positive response is obtained by evaluating a given distribution function (F) at a linear combination of the predictor variables. One of the predictor variables is unobserved. It is a random...
Persistent link: https://www.econbiz.de/10008456368