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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Bayesian Full Information Analysis of Simultaneous Equation Models Using Integration by Monte Carlo

Bayesian Full Information Analysis of Simultaneous Equation Models Using Integration by Monte Carlo

Bauwens, L.

Paperback

Series: Lecture Notes in Economic and Mathematical Systems, Book 232

Business GeneralEconomics

ISBN10: 3540133844
ISBN13: 9783540133841
Publisher: Springer Nature
Published: Sep 1 1984
Pages: 114
Weight: 0.48
Height: 0.27 Width: 6.69 Depth: 9.61
Language: English
In their review of the Bayesian analysis of simultaneous equation systems, Dr ze and Richard (1983) - hereafter DR - express the following viewpoint about the present state of development of the Bayesian full information analysis of such sys- tems i) the method allows a flexible specification of the prior density, including well defined noninformative prior measures; ii) it yields exact finite sample posterior and predictive densities. However, they call for further developments so that these densities can be eval- uated through 'numerical methods, using an integrated software packa e. To that end, they recommend the use of a Monte Carlo technique, since van Dijk and Kloek (1980) have demonstrated that the integrations can be done and how they are done. In this monograph, we explain how we contribute to achieve the developments suggested by Dr ze and Richard. A basic idea is to use known properties of the porterior density of the param- eters of the structural form to design the importance functions, i. e. approximations of the posterior density, that are needed for organizing the integrations.

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