Evidence aggregation in development economics via Bayesian hierarchical models
Thesis: Ph. D., Massachusetts Institute of Technology, Department of Economics, 2017.
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Format: | Thesis |
Language: | eng |
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Massachusetts Institute of Technology
2017
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Online Access: | http://hdl.handle.net/1721.1/111358 |
_version_ | 1811069190290800640 |
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author | Meager, Rachael |
author2 | Esther Duflo. |
author_facet | Esther Duflo. Meager, Rachael |
author_sort | Meager, Rachael |
collection | MIT |
description | Thesis: Ph. D., Massachusetts Institute of Technology, Department of Economics, 2017. |
first_indexed | 2024-09-23T08:07:08Z |
format | Thesis |
id | mit-1721.1/111358 |
institution | Massachusetts Institute of Technology |
language | eng |
last_indexed | 2024-09-23T08:07:08Z |
publishDate | 2017 |
publisher | Massachusetts Institute of Technology |
record_format | dspace |
spelling | mit-1721.1/1113582019-04-09T16:46:37Z Evidence aggregation in development economics via Bayesian hierarchical models Meager, Rachael Esther Duflo. Massachusetts Institute of Technology. Department of Economics. Massachusetts Institute of Technology. Department of Economics. Economics. Thesis: Ph. D., Massachusetts Institute of Technology, Department of Economics, 2017. Cataloged from PDF version of thesis. Includes bibliographical references (pages 185-193). It is increasingly recognized that translating research into policy requires aggregating evidence from multiple studies of the same economic phenomenon. This translation requires not only an estimate of the impact of an intervention across different contexts, but also an assessment of the generalizability of the evidence and hence its applicability to policy decisions in other settings. This thesis performs evidence aggregation using Bayesian hierarchical models, which both aggregate evidence and assess the true underlying heterogeneity across settings, for applications in development economics. Where necessary, the thesis develops new methods to aggregate evidence on certain measures of evidence currently neglected in the aggregation literature such as distributional treatment effects or risk ratios. The applications considered are randomized controlled trials of expanding access to microcredit and randomized access to vitamin A supplementation in developing nations. by Rachael Meager. Ph. D. 2017-09-15T15:30:39Z 2017-09-15T15:30:39Z 2017 2017 Thesis http://hdl.handle.net/1721.1/111358 1003291099 eng MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission. http://dspace.mit.edu/handle/1721.1/7582 193 pages application/pdf Massachusetts Institute of Technology |
spellingShingle | Economics. Meager, Rachael Evidence aggregation in development economics via Bayesian hierarchical models |
title | Evidence aggregation in development economics via Bayesian hierarchical models |
title_full | Evidence aggregation in development economics via Bayesian hierarchical models |
title_fullStr | Evidence aggregation in development economics via Bayesian hierarchical models |
title_full_unstemmed | Evidence aggregation in development economics via Bayesian hierarchical models |
title_short | Evidence aggregation in development economics via Bayesian hierarchical models |
title_sort | evidence aggregation in development economics via bayesian hierarchical models |
topic | Economics. |
url | http://hdl.handle.net/1721.1/111358 |
work_keys_str_mv | AT meagerrachael evidenceaggregationindevelopmenteconomicsviabayesianhierarchicalmodels |