Constructing generalizable geographic natural experiments
A natural experiment is a real-world situation that generates as-if random or haphazard assignment to treatment. Geographic or administrative boundaries can be exploited as natural experiments to construct treated and control groups. Previous research has demonstrated that matching can help enhance...
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| Format: | Article |
| Language: | English |
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SAGE Publishing
2022-07-01
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| Series: | Research & Politics |
| Online Access: | https://doi.org/10.1177/20531680221113763 |
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| _version_ | 1849419451513962496 |
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| author | Owura Kuffuor Giancarlo Visconti Kayla M Young |
| author_facet | Owura Kuffuor Giancarlo Visconti Kayla M Young |
| author_sort | Owura Kuffuor |
| collection | DOAJ |
| description | A natural experiment is a real-world situation that generates as-if random or haphazard assignment to treatment. Geographic or administrative boundaries can be exploited as natural experiments to construct treated and control groups. Previous research has demonstrated that matching can help enhance these designs by reducing imbalances on observed covariates. An important limitation of this empirical approach, however, is that the results are inherently local. While the treated and control groups may be quite similar to each other, they could be substantially different from the target population of interest (e.g., a country). We propose a simple design inspired by the idea of template matching to construct generalizable geographic natural experiments. By matching our treated and control groups to a template (i.e., the target population), we obtain groups that are similar to the target population of interest and to each other, which can increase both the internal and external validity of the study. |
| format | Article |
| id | doaj-art-65774032e5f842c5a6dde1dbb0e1add7 |
| institution | Kabale University |
| issn | 2053-1680 |
| language | English |
| publishDate | 2022-07-01 |
| publisher | SAGE Publishing |
| record_format | Article |
| series | Research & Politics |
| spelling | doaj-art-65774032e5f842c5a6dde1dbb0e1add72025-08-20T03:32:04ZengSAGE PublishingResearch & Politics2053-16802022-07-01910.1177/20531680221113763Constructing generalizable geographic natural experimentsOwura KuffuorGiancarlo ViscontiKayla M YoungA natural experiment is a real-world situation that generates as-if random or haphazard assignment to treatment. Geographic or administrative boundaries can be exploited as natural experiments to construct treated and control groups. Previous research has demonstrated that matching can help enhance these designs by reducing imbalances on observed covariates. An important limitation of this empirical approach, however, is that the results are inherently local. While the treated and control groups may be quite similar to each other, they could be substantially different from the target population of interest (e.g., a country). We propose a simple design inspired by the idea of template matching to construct generalizable geographic natural experiments. By matching our treated and control groups to a template (i.e., the target population), we obtain groups that are similar to the target population of interest and to each other, which can increase both the internal and external validity of the study.https://doi.org/10.1177/20531680221113763 |
| spellingShingle | Owura Kuffuor Giancarlo Visconti Kayla M Young Constructing generalizable geographic natural experiments Research & Politics |
| title | Constructing generalizable geographic natural experiments |
| title_full | Constructing generalizable geographic natural experiments |
| title_fullStr | Constructing generalizable geographic natural experiments |
| title_full_unstemmed | Constructing generalizable geographic natural experiments |
| title_short | Constructing generalizable geographic natural experiments |
| title_sort | constructing generalizable geographic natural experiments |
| url | https://doi.org/10.1177/20531680221113763 |
| work_keys_str_mv | AT owurakuffuor constructinggeneralizablegeographicnaturalexperiments AT giancarlovisconti constructinggeneralizablegeographicnaturalexperiments AT kaylamyoung constructinggeneralizablegeographicnaturalexperiments |