On imputing UNHCR data
Dyadic data from the United Nations High Commissioner for Refugees (UNHCR) on the size of the global refugee population are widely used. However, for a large fraction of the refugee population, these data provide no information about refugees’ country of origin, which contributes to a high nominal r...
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| Format: | Article |
| Language: | English |
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SAGE Publishing
2018-10-01
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| Series: | Research & Politics |
| Online Access: | https://doi.org/10.1177/2053168018803239 |
| _version_ | 1818454516624785408 |
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| author | Moritz Marbach |
| author_facet | Moritz Marbach |
| author_sort | Moritz Marbach |
| collection | DOAJ |
| description | Dyadic data from the United Nations High Commissioner for Refugees (UNHCR) on the size of the global refugee population are widely used. However, for a large fraction of the refugee population, these data provide no information about refugees’ country of origin, which contributes to a high nominal rate of unreported values in the data. In this article, I demonstrate that two imputation approaches outperform the current standard approach, which assumes that all unreported values are zero. The first approach interpolates the unreported values, while the second predicts them based on trends observed in other dyads. Drawing on different types of information, the two approaches’ performance is similar. Replicating a published study on the effect of refugee crises on international war and peace, I demonstrate how both approaches strengthen the author’s findings and help to minimize the risk of a null finding. |
| first_indexed | 2024-12-14T21:56:08Z |
| format | Article |
| id | doaj.art-cbb5cae2a63c478aab37a5ba732c7235 |
| institution | Directory Open Access Journal |
| issn | 2053-1680 |
| language | English |
| last_indexed | 2024-12-14T21:56:08Z |
| publishDate | 2018-10-01 |
| publisher | SAGE Publishing |
| record_format | Article |
| series | Research & Politics |
| spelling | doaj.art-cbb5cae2a63c478aab37a5ba732c72352022-12-21T22:46:07ZengSAGE PublishingResearch & Politics2053-16802018-10-01510.1177/2053168018803239On imputing UNHCR dataMoritz MarbachDyadic data from the United Nations High Commissioner for Refugees (UNHCR) on the size of the global refugee population are widely used. However, for a large fraction of the refugee population, these data provide no information about refugees’ country of origin, which contributes to a high nominal rate of unreported values in the data. In this article, I demonstrate that two imputation approaches outperform the current standard approach, which assumes that all unreported values are zero. The first approach interpolates the unreported values, while the second predicts them based on trends observed in other dyads. Drawing on different types of information, the two approaches’ performance is similar. Replicating a published study on the effect of refugee crises on international war and peace, I demonstrate how both approaches strengthen the author’s findings and help to minimize the risk of a null finding.https://doi.org/10.1177/2053168018803239 |
| spellingShingle | Moritz Marbach On imputing UNHCR data Research & Politics |
| title | On imputing UNHCR data |
| title_full | On imputing UNHCR data |
| title_fullStr | On imputing UNHCR data |
| title_full_unstemmed | On imputing UNHCR data |
| title_short | On imputing UNHCR data |
| title_sort | on imputing unhcr data |
| url | https://doi.org/10.1177/2053168018803239 |
| work_keys_str_mv | AT moritzmarbach onimputingunhcrdata |