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1 edition of Forecasting and conditional projection using realistic prior distributions found in the catalog.

Forecasting and conditional projection using realistic prior distributions

Thomas Doan

Forecasting and conditional projection using realistic prior distributions

by Thomas Doan

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  • 36 Currently reading

Published by Federal Reserve BanK of Minneapolis in Minneapolis, Minn .
Written in English


Edition Notes

SeriesWorking paper -- no. 243, Working paper (Federal Reserve Bank of Minneapolis. Research Dept.)
The Physical Object
Pagination71 p.
Number of Pages71
ID Numbers
Open LibraryOL24676011M

Abstract. The vector autoregression (VAR) model is one of the most successful, flexible, and easy to use models for the analysis of multivariate time series. It is a natural extension of the univariate autoregressive model to dynamic multivariate time series. The VAR model has proven to be especially useful for describing the dynamic behavior of economic and financial time series and for Cited by: Doan T, R Litterman and C Sims (), ‘Forecasting and Conditional Projection Using Realistic Prior Distributions’, Econometric Reviews, 3(1), pp 1– Fukač M and A Pagan (forthcoming), ‘Limited Information Estimation and Evaluation of DSGE Models,’ Journal of Applied Econometrics.

Dixon, P.B. and D. McDonald (), “The Australian Economy in –86 and –87”, The Australian Economic Review 2nd Quarter, pp3– Doan, T., R.B. Litterman and C.A. Sims () “Forecasting and Conditional Projection Using Realistic Prior Distributions” Econometric Reviews 3, pp1– Engle, R.F. and G.W.J. Granger (), “Cointegration and Error-Correction.   An unconditional forecast says what output will be at some date. A conditional forecast says what will happen to output if interest rates, and only interest rates, change. An unconditional forecast is clearly much more difficult, because you need to get a whole host of things right. A conditional forecast is easier to get : Mainly Macro.

Forecasting and conditional projection using realistic prior distribution Staff Report, Federal Reserve Bank of Minneapolis View citations () Also in NBER Working Papers, National Bureau of Economic Research, Inc () View citations ().   Forecasting and conditional projection using realistic prior distributions. Thomas Doan et al. Econometric Reviews. Volume 3, - Issue 1. Published online: 21 Mar Article. FRED-MD: A Monthly Database for Macroeconomic Research. Michael W. McCracken et al. Journal of Business & Economic by:


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Forecasting and conditional projection using realistic prior distributions by Thomas Doan Download PDF EPUB FB2

Forecasting and Conditional Projection Using Realistic Prior Distributions Thomas Doan, Robert B. Litterman, Christopher A. Sims. NBER Working Paper No.

Issued in September NBER Program(s):Economic Fluctuations and Growth. This paper develops a forecasting procedure based on a Bayesian method for estimating vector autoregressions. This paper develops a forecasting procedure based on a Bayesian method for estimating vector autoregressions.

The procedure is applied t o 10 macroeconomic variables and is shown to improve out-of-sample forecasts relative Cited by: Forecasting and Conditional Projection Using Realistic Prior Distributions This paper develops a forecasting procedure based on a Bayesian method for estimating vector autoregressions.

The procedure is applied to ten macroeconomic variables and is shown to improve out-of-sample forecasts relative to univariate equations. This paper develops a forecasting procedure based on a Bayesian method for estimating vector autoregressions.

The procedure is applied to ten macroeconomic variables and is shown to improve out-of-sample forecasts relative to univariate by: Forecasting and Conditional Projection Using Realistic Prior Distributions. Tom Doan (), Robert Litterman and Christopher Sims () NoNBER Working Papers from National Bureau of Economic Research, Inc.

Abstract: This paper develops a forecasting procedure based on a Bayesian method for estimating vector autoregressions. The procedure is applied to ten macroeconomic variables and is shown to improve out-of-sample forecasts Cited by: We use conditional forecasting techniques to retrieve bank capital shocks related to regulatory and supervisory initiatives and quantify their impact on credit supply and economic activity.

Forecasting and conditional projection using realistic prior distribution. "Incorporating theoretical restrictions into forecasting by projection methods," CEPR Discussion PapersC.E.P.R. Discussion Zheng & LeSage, James P., "Using spatial contiguity as prior information in vector autoregressive models," Economics.

Forecasting and Conditional Projection Using Realistic Prior Distributions ABSTRACT This paper develops a forecasting procedure based on a Bayesian method for estimating vector autoregressions.

The procedure is applied to ten macroeconomic variables and is shown to improve out-of-sample fore-casts relative to univariate equations. Doan, T., Litterman, R.B.

and Sims, C.A. () Forecasting and Conditional Projection Using Realistic Prior Distribution. Econometric Review, 3, as fiA Bayesian Procedure for Forecasting with Vector Autoregression,flMassachusetts Institute of Technology, Department of Economics Working Paper, Another important early paper: Doan, Litterman and Sims, fiForecasting and Conditional Projection Using Realistic Prior Distributions.flEconometric Reviews ŒFile Size: KB.

Forecasting and Conditional Projection Using Realistic Prior Distributions. By Thomas Doan, Although cross-variables responses are damped by the prior, considerable interaction among the variables is shown to be captured by the provide unconditional forecasts as of and We also describe how a model such as this.

Forecasting and Conditional Projection Using Realistic Prior Distributions Authors. Christopher A. Sims. Robert B. Litterman. Thomas Doan. Forecasting and Conditional Projection Using Realistic Prior Distributions Share.

We also describe how a model such as this can be used to make conditional projections and analyze policy. This paper develops a forecasting procedure based on a Bayesian method for estimating vector autoregressions.

The procedure is applied to ten macroeconomic variables and is shown to improve out-of-sample forecasts relative to univariate equations. Bayesian inference requires an analyst to set priors. Setting the right prior is crucial for precise forecasts. This paper analyzes how optimal prior changes when an economy is hit by a recession.

For this task, an autoregressive distributed lag (ADL) model is chosen. The results show that a sharp economic slowdown changes the optimal prior in two directions.

Forecasting and Conditional Projection Using Realistic Prior Distributions,Econometric Review. By Thomas Doan, Robert Litterman, Christopher A. Sims, Thomas Doan, Robert Litterman and Christopher Sims.

Abstract. in Economic Fluctuations. Any opinions expressed are those of th. Forecasting and conditional projection using realistic prior distributions.

Econometric Reviews ; Google Scholar {15} Todd RM. Improving economic forecasting with Bayesian vector autoregression. Quarterly Review, Federal Reserve Bank of Minneapolis ; Google Scholar {16} Litterman RB. A statistical approach to economic Author: ChenAn-Sing, T LeungMark. Forecasting and Conditional Projection Using Realistic Prior Distributions by Thomas Doan, Robert Litterman, Christopher Sims, Abstract - Cited by (6 self) - Add to MetaCart.

“Forecasting and Conditional Projection Using Realistic Prior Distributions,” Econometric Reviews, 3, 1– zbMATH CrossRef Google Scholar Granger, C.W.J. “Investigating Causal Relations by Econometric Models and Cross Spectral Methods,” Econometrica, 37, – In this paper we focus on the development of multiple time series models for forecasting Irish Inflation.

The Bayesian approach to the estimation of vector autoregressive (VAR) models is employed. This allows the estimated models combine the evidence in the data with any prior information which may also be available.

A large selection of inflation indicators are assessed as potential. Forecasting and Conditional Projection Using Realistic Prior Distributions Thomas Doan, Robert B. Litterman, Christopher A. Sims Economics, Computer Science. "Forecasting and conditional projection using realistic prior distribution," Staff Rep Federal Reserve Bank of Minneapolis.

Sims, Christopher A & Zha, Tao, " Bayesian Methods for Dynamic Multivariate Models," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of.Get this from a library!

Forecasting and Conditional Projection Using Realistic Prior Distributions. [Christopher A Sims; Thomas Doan; Robert B Litterman; National Bureau of Economic Research.;] -- This paper develops a forecasting procedure based on a Bayesian method for estimating vector autoregressions.

The procedure is applied to ten macroeconomic variables and is shown to improve.“Forecasting and Conditional Projection Using Realistic Prior Distributions" (with T.

Doan and R. Litterman), Econometric Reviews,No. 1. Review of Specification, Estimation and Analysis of Econometric Models, by Ray C. Fair, Journal of Money, Credit, File Size: 75KB.