5 papers
Testing for Endogeneity: A Moment-Based Bayesian Approach
Siddhartha Chib, Minchul Shin, Anna Simoni
A standard assumption in the Bayesian estimation of linear regression models is that the regressors are exogenous in the sense that they are uncorrelated with the model error term.…
ForeComp: An R Package for Comparing Predictive Accuracy Using Fixed-Smoothing Asymptotics
Minchul Shin, Nathan Schor
We introduce ForeComp, an R package for comparing predictive accuracy using Diebold-Mariano type tests of equal predictive ability with standard and fixed smoothing inference. The…
Bayesian Estimation and Comparison of Conditional Moment Models
Siddhartha Chib, Minchul Shin, Anna Simoni
We consider the Bayesian analysis of models in which the unknown distribution of the outcomes is specified up to a set of conditional moment restrictions. The nonparametric exponen…
On the Aggregation of Probability Assessments: Regularized Mixtures of Predictive Densities for Eurozone Inflation and Real Interest Rates
Francis X. Diebold, Minchul Shin, Boyuan Zhang
We propose methods for constructing regularized mixtures of density forecasts. We explore a variety of objectives and regularization penalties, and we use them in a substantive exp…
Bayesian Estimation and Comparison of Moment Condition Models
Siddhartha Chib, Minchul Shin, Anna Simoni
In this paper we consider the problem of inference in statistical models characterized by moment restrictions by casting the problem within the Exponentially Tilted Empirical Likel…