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  • paper-2019.12.16-MLL-

    Rights statement: This is an Accepted Manuscript of an article published by Taylor & Francis in Economic Systems Research on 09/01/2020, available online: https://www.tandfonline.com/doi/abs/10.1080/09535314.2019.1707170

    Accepted author manuscript, 345 KB, PDF document

    Available under license: CC BY-NC: Creative Commons Attribution-NonCommercial 4.0 International License

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Bayesian input–output table update using a benchmark LASSO prior

Research output: Contribution to journalJournal articlepeer-review

Published
<mark>Journal publication date</mark>2/07/2020
<mark>Journal</mark>Economic Systems Research
Issue number3
Volume32
Number of pages15
Pages (from-to)413-427
Publication StatusPublished
Early online date9/01/20
<mark>Original language</mark>English

Abstract

We propose updating a multiplier matrix subject to final demand and total output constraints, where the prior multiplier matrix is weighted against a LASSO prior. We update elements of the Leontief inverse, from which we can derive posterior densities of the entries in input-output tables. As the parameter estimates required by far exceed the available observations, many zero entries deliver a sparse tabulation. We address that problem with a new statistical model wherein we adopt a LASSO prior. We develop novel numerical techniques and perform a detailed Monte Carlo study to examine the performance of the new approach under different configurations of the input-output table. The new techniques are applied to a 196 ×196 U.S. input-output table for 2012.

Bibliographic note

This is an Accepted Manuscript of an article published by Taylor & Francis in Economic Systems Research on 09/01/2020, available online: https://www.tandfonline.com/doi/abs/10.1080/09535314.2019.1707170