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Synthetic decomposition for counterfactual predictions
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Canen, Nathan and Song, Kyungchul (2023) Synthetic decomposition for counterfactual predictions. Working Paper. Coventry, UK: University of Warwick. Department of Economics. Warwick economics research papers series (WERPS) (1466). (Unpublished)
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Official URL: https://warwick.ac.uk/fac/soc/economics/research/w...
Abstract
Counterfactual predictions are challenging when the policy variable goes beyond its pre-policy support. However, in many cases, information about the policy of interest is available from different (“source”) regions where a similar policy has already been implemented. In this paper, we propose a novel method of using such data from source regions to predict a new policy in a target region. Instead of relying on extrapolation of a structural relationship using a parametric specification, we formulate a transferability condition and construct a synthetic outcome-policy relationship such that it is as close as possible to meeting the condition. The synthetic relationship weighs both the similarity in distributions of observables and in structural relationships. We develop a general procedure to construct asymptotic confidence intervals for counterfactual predictions and prove its asymptotic validity. We then apply our proposal to predict average teenage employment in Texas following a counterfactual increase in the minimum wage.
Item Type: | Working or Discussion Paper (Working Paper) | ||||||
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Subjects: | H Social Sciences > HB Economic Theory | ||||||
Divisions: | Faculty of Social Sciences > Economics | ||||||
Library of Congress Subject Headings (LCSH): | Policy sciences -- Computer simulation, Counterfactuals (Logic), Decomposition (Mathematics) | ||||||
Series Name: | Warwick economics research papers series (WERPS) | ||||||
Publisher: | University of Warwick. Department of Economics | ||||||
Place of Publication: | Coventry, UK | ||||||
ISSN: | 0083-7350 | ||||||
Official Date: | July 2023 | ||||||
Dates: |
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Number: | 1466 | ||||||
Institution: | University of Warwick | ||||||
Publication Status: | Unpublished | ||||||
Access rights to Published version: | Free Access (unspecified licence, 'bronze OA') | ||||||
RIOXX Funder/Project Grant: |
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