This paper designs and implements a Bayesian dynamic latent factor model for a vector of data describing the Iowa economy.
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Paper provided by University of Iowa, Department of Economics in its series Working Papers with number
96-14.
Length: 26 pages Date of creation: 1996 Date of revision: Handle: RePEc:uia:iowaec:96-14
Contact details of provider: Postal: University of Iowa, Department of Economics, Henry B. Tippie College of Business, Iowa City, Iowa 52242 Phone: (319) 335-0829 Fax: (319) 335-1956 Web page: http://www.biz.uiowa.edu/econ/ More information through EDIRC
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Find related papers by JEL classification: E17 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Forecasting and Simulation C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - General C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Statistical Simulation Methods
Cited by: (explanations, Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.)
James D. Hamilton & Daniel F. Waggoner & Tao Zha, 2004.
"Normalization in econometrics,"
Working Paper
2004-13, Federal Reserve Bank of Atlanta.
[Downloadable!]
Other versions:
James D. Hamilton & Daniel F. Waggoner & Tao Zha, 2007.
"Normalization in Econometrics,"
Econometric Reviews,
Taylor and Francis Journals, vol. 26(2-4), pages 221-252.
[Downloadable!] (restricted)