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On forecasting the Hong Kong economy...

Chow, Wai Yip William.

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On forecasting the Hong Kong economy with Bayesian Vector Autoregression model.

Record Type:	Electronic resources : Monograph/item
Title/Author:	On forecasting the Hong Kong economy with Bayesian Vector Autoregression model./
Author:	Chow, Wai Yip William.
Description:	167 p.
Notes:	Source: Dissertation Abstracts International, Volume: 59-12, Section: A, page: 4478.
Contained By:	Dissertation Abstracts International59-12A.
Subject:	Economics. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=9914332
ISBN:	9780599129610

On forecasting the Hong Kong economy with Bayesian Vector Autoregression model.
Chow, Wai Yip William.

On forecasting the Hong Kong economy with Bayesian Vector Autoregression model. - 167 p.

Source: Dissertation Abstracts International, Volume: 59-12, Section: A, page: 4478.

Thesis (Ph.D.)--Hong Kong University of Science and Technology (Hong Kong), 1998.

This thesis evaluates various specifications of Bayesian Vector Autoregression (BVAR) and their implication on forecast accuracy with respect to Hong Kong data. In particular, I construct a Hierarchical Bayes model within the conventional BVAR framework using the Minnesota Prior. The design aims at bypassing the restriction of cross-equation independence of the coefficients and arbitrary fine-tuning of the hyperparameters in traditional BVARs. Estimation is facilitated by Markov Chain Monte Carlo methods because of the lack of analytical expressions for the solutions. The reduced form model so estimated is then "identified" into a structural counterpart that can offer meaningful economic interpretations. Empirical results from these exercises are consistent with the currency board system in general with monetary variables responding endogenously to shocks that hit the Hong Kong economy.

ISBN: 9780599129610Subjects--Topical Terms:

517137
Economics.

On forecasting the Hong Kong economy with Bayesian Vector Autoregression model.
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245 1 0 $a On forecasting the Hong Kong economy with Bayesian Vector Autoregression model.
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500 $a Source: Dissertation Abstracts International, Volume: 59-12, Section: A, page: 4478.
502 $a Thesis (Ph.D.)--Hong Kong University of Science and Technology (Hong Kong), 1998.
520 $a This thesis evaluates various specifications of Bayesian Vector Autoregression (BVAR) and their implication on forecast accuracy with respect to Hong Kong data. In particular, I construct a Hierarchical Bayes model within the conventional BVAR framework using the Minnesota Prior. The design aims at bypassing the restriction of cross-equation independence of the coefficients and arbitrary fine-tuning of the hyperparameters in traditional BVARs. Estimation is facilitated by Markov Chain Monte Carlo methods because of the lack of analytical expressions for the solutions. The reduced form model so estimated is then "identified" into a structural counterpart that can offer meaningful economic interpretations. Empirical results from these exercises are consistent with the currency board system in general with monetary variables responding endogenously to shocks that hit the Hong Kong economy.
590 $a School code: 1223.
650 4 $a Economics. $3 517137
650 4 $a Economic theory. $3 1556984
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710 2 $a Hong Kong University of Science and Technology (Hong Kong). $3 1022235
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792 $a 1998
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