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On the estimation of a large sparse Bayesian system: the Snaer program

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Dmitry Danilov (Eurandom, Eindhoven University of Technology)
Jan R. Magnus (Department of Econometrics & OR, Tilburg University)

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Abstract

The Snaer program calculates the posterior mean and variance of variables on some of which we have data (with precisions), on some we have prior information (with precisions), and on some prior indicator ratios (with precisions) are available. The variables must satisfy anumber of exact restrictions. The system is both large and sparse. Two aspects of the sta-tistical and computational development are a practical procedure to solve a linear integer system, and a stable linearization routine for ratios. We test our numerical method to solve large sparse linear least-squares estimation problems, and find that it performs well, even when the n ~k design matrix is large(nk equivalent 2^27.5).

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Paper provided by CIRJE, Faculty of Economics, University of Tokyo in its series CIRJE F-Series with number CIRJE-F-478.

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Length: 33 pages
Date of creation: Feb 2007
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Handle: RePEc:tky:fseres:2007cf478

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  1. John M. Abowd & Robert H. Creecy & Francis Kramarz, 2002. "Computing Person and Firm Effects Using Linked Longitudinal Employer-Employee Data," Technical Papers 2002-06, Longitudinal Employer-Household Dynamics, Center for Economic Studies, U.S. Census Bureau. [Downloadable!]
  2. John M. Abowd & Francis Kramarz & David N. Margolis, 1999. "High Wage Workers and High Wage Firms," Econometrica, Econometric Society, vol. 67(2), pages 251-334, March.
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