Robot-proofing economic development: econometric, growth diagnostic, and machine learning evidence
Thesis: S.M. in Technology and Policy, Massachusetts Institute of Technology, School of Engineering, Institute for Data, Systems, and Society, 2019
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| Format: | Thesis |
| Language: | eng |
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Massachusetts Institute of Technology
2019
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| Online Access: | https://hdl.handle.net/1721.1/122211 |
| _version_ | 1826191757712293888 |
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| author | Protzer, Eric(Eric Sean McMurtrie) |
| author2 | Elisabeth Reynolds. |
| author_facet | Elisabeth Reynolds. Protzer, Eric(Eric Sean McMurtrie) |
| author_sort | Protzer, Eric(Eric Sean McMurtrie) |
| collection | MIT |
| description | Thesis: S.M. in Technology and Policy, Massachusetts Institute of Technology, School of Engineering, Institute for Data, Systems, and Society, 2019 |
| first_indexed | 2024-09-23T09:00:50Z |
| format | Thesis |
| id | mit-1721.1/122211 |
| institution | Massachusetts Institute of Technology |
| language | eng |
| last_indexed | 2024-09-23T09:00:50Z |
| publishDate | 2019 |
| publisher | Massachusetts Institute of Technology |
| record_format | dspace |
| spelling | mit-1721.1/1222112022-01-31T17:29:43Z Robot-proofing economic development: econometric, growth diagnostic, and machine learning evidence Protzer, Eric(Eric Sean McMurtrie) Elisabeth Reynolds. Massachusetts Institute of Technology. Institute for Data, Systems, and Society. Technology and Policy Program. Massachusetts Institute of Technology. Institute for Data, Systems, and Society Massachusetts Institute of Technology. Engineering Systems Division Technology and Policy Program Institute for Data, Systems, and Society. Technology and Policy Program. Thesis: S.M. in Technology and Policy, Massachusetts Institute of Technology, School of Engineering, Institute for Data, Systems, and Society, 2019 Cataloged from PDF version of thesis. Includes bibliographical references (pages 74-76). Over the course of the 2 0 th century numerous economies have leveraged export-driven industrialization strategies to grow wealthier. The advent of automation technology, however, threatens to disrupt the low-cost manufacturing models which have characterized this process; the future may see factories resituated to high-income, high-skill countries which can successfully deploy automation. This thesis consequently evaluates how developing countries could navigate automation by either innovating abreast of it or specializing away from its impact. It is broadly divided into three sections. First, the stage is set by examining the political economy of industrial policy to highlight how political incentives constrain feasible strategies for economic readjustment of any sort. It is shown that even in a setting with few corruption problems - the European Union - industrial policy is guided by politicians' incentives to maintain power, and thus one ought to be cognizant of such incentives in any context. Second, possible barriers to greater productivity and innovation in developing countries are explored through a case study analysis of Vietnam, which is considered by some to be highly exposed to automation risk. Growth diagnostic tools are applied to identify the binding constraints which prevent it from shifting towards more complex, value-added economic activities. Structural economic reform is found to be critical to greater innovation, as opposed to technocentric solutions that aim to leapfrog to the technological frontier. Third, product space and machine learning methodology are used to simulate how countries' export diversification paths could respond to automation. By conducting sensitivity analysis across a range of automation scenarios it provides insight on how developing countries may be able to respecialize their economies to maintain growth. by Eric Protzer. S.M. in Technology and Policy S.M.inTechnologyandPolicy Massachusetts Institute of Technology, School of Engineering, Institute for Data, Systems, and Society 2019-09-17T16:29:55Z 2019-09-17T16:29:55Z 2019 2019 Thesis https://hdl.handle.net/1721.1/122211 1117710054 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 76 pages application/pdf Massachusetts Institute of Technology |
| spellingShingle | Institute for Data, Systems, and Society. Technology and Policy Program. Protzer, Eric(Eric Sean McMurtrie) Robot-proofing economic development: econometric, growth diagnostic, and machine learning evidence |
| title | Robot-proofing economic development: econometric, growth diagnostic, and machine learning evidence |
| title_full | Robot-proofing economic development: econometric, growth diagnostic, and machine learning evidence |
| title_fullStr | Robot-proofing economic development: econometric, growth diagnostic, and machine learning evidence |
| title_full_unstemmed | Robot-proofing economic development: econometric, growth diagnostic, and machine learning evidence |
| title_short | Robot-proofing economic development: econometric, growth diagnostic, and machine learning evidence |
| title_sort | robot proofing economic development econometric growth diagnostic and machine learning evidence |
| topic | Institute for Data, Systems, and Society. Technology and Policy Program. |
| url | https://hdl.handle.net/1721.1/122211 |
| work_keys_str_mv | AT protzerericericseanmcmurtrie robotproofingeconomicdevelopmenteconometricgrowthdiagnosticandmachinelearningevidence |