Normalization in Econometrics

  title={Normalization in Econometrics},
  author={James D. Hamilton and Daniel F. Waggoner and Tao Zha},
The issue of normalization arises whenever two different values for a vector of unknown parameters imply the identical economic model. A normalization implies not just a rule for selecting which among equivalent points to call the maximum likelihood estimate (MLE), but also governs the topography of the set of points that go into a small-sample confidence interval associated with that MLE. A poor normalization can lead to multimodal distributions, disjoint confidence intervals, and very… CONTINUE READING

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2003a): “A Gibbs Sampler for Structural Vector Autoregressions,

D. F. Waggoner, T. Zha
Journal of Economic Dynamics and Control, • 2003
View 4 Excerpts
Highly Influenced

Bayesian Reduced Rank Regression in Econometrics,

J. Geweke
Journal of Econometrics, • 1996
View 5 Excerpts
Highly Influenced

Dummy Observation Priors Revisited,

C. A. Sims
View 3 Excerpts
Highly Influenced

Markov Chain Monte Carlo Estimation of Classical and Dynamic Switching and Mixture Models,

S. Frühwirth-Schnatter
Journal of the American Statistical Association, • 2001
View 4 Excerpts
Highly Influenced

Estimation and Hypothesis Testing in Finite Mixture Models,

M. Aitkin, D. B. Rubin
Journal of the Royal Statistical Society Series B, • 1985
View 3 Excerpts
Highly Influenced

Model Uncertainty and Bayesian Model Averaging in Vector Autoregressive Processes,

R. Strachan, H. K. van Dijk

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