The model specification problem is perhaps the Achilles heel of applied econometrics. Rather than test down to a single model as is usually done, we estimate 72 different demand systems and use Bayesian averaging procedures over all 72 systems to generate meta estimates of the parameters (e.g., elasticities) of interest
Table of Contents: Background of Papers, by George C. Davis Econometric Methodologies for the Mo...
This paper develops the theoretical background for the Limited Information Bayesian Model Averaging ...
Standard statistical practice ignores model uncertainty. Data analysts typically select a model from...
The model specification problem is perhaps the Achilles heel of applied econometrics. Rather than te...
A model averaged estimator is composed of estimators, each obtained from a different model, that are...
The standard practice of selecting a single model from some class of models and then making inferenc...
Share equations for the translog and almost ideal demand systems are estimated using Markov Chain Mo...
This article describes the process of Bayesian specification analysis using state of the art simulat...
Standard statistical practice ignores model uncertainty. Data analysts typically select a model from...
2 Share equations for the translog and almost ideal demand systems are estimated using Markov Chain ...
Abstract. Standard statistical practice ignores model uncertainty. Data analysts typically select a ...
The standard methodology when building statistical models has been to use one of several algorithms ...
The method of model averaging has become an important tool to deal with model uncertainty, for exam...
Many statistical scenarios initially involve several candidate models that describe the data-generat...
The method of model averaging has become an important tool to deal with model uncertainty, for examp...
Table of Contents: Background of Papers, by George C. Davis Econometric Methodologies for the Mo...
This paper develops the theoretical background for the Limited Information Bayesian Model Averaging ...
Standard statistical practice ignores model uncertainty. Data analysts typically select a model from...
The model specification problem is perhaps the Achilles heel of applied econometrics. Rather than te...
A model averaged estimator is composed of estimators, each obtained from a different model, that are...
The standard practice of selecting a single model from some class of models and then making inferenc...
Share equations for the translog and almost ideal demand systems are estimated using Markov Chain Mo...
This article describes the process of Bayesian specification analysis using state of the art simulat...
Standard statistical practice ignores model uncertainty. Data analysts typically select a model from...
2 Share equations for the translog and almost ideal demand systems are estimated using Markov Chain ...
Abstract. Standard statistical practice ignores model uncertainty. Data analysts typically select a ...
The standard methodology when building statistical models has been to use one of several algorithms ...
The method of model averaging has become an important tool to deal with model uncertainty, for exam...
Many statistical scenarios initially involve several candidate models that describe the data-generat...
The method of model averaging has become an important tool to deal with model uncertainty, for examp...
Table of Contents: Background of Papers, by George C. Davis Econometric Methodologies for the Mo...
This paper develops the theoretical background for the Limited Information Bayesian Model Averaging ...
Standard statistical practice ignores model uncertainty. Data analysts typically select a model from...
DOI
Add to ORKG