On the Implications of Essential Heterogeneity for Estimating Causal Impacts Using Social Experiments:
Randomized control trials are sometimes used to estimate the aggregate benefit from some policy or program. To address the potential bias from selective take-up, the randomization is used as an instrumental variable for treatment status. Does this (popular) method of impact evaluation help reduce th...
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Washington, D.C
The World Bank
2011
|
| Online-Zugang: | Volltext |
| Zusammenfassung: | Randomized control trials are sometimes used to estimate the aggregate benefit from some policy or program. To address the potential bias from selective take-up, the randomization is used as an instrumental variable for treatment status. Does this (popular) method of impact evaluation help reduce the bias when take-up depends on unobserved gains from take up? Such "essential heterogeneity" is known to invalidate the instrumental variable estimator of mean causal impact, though one still obtains another parameter of interest, namely mean impact amongst those treated. However, if essential heterogeneity is the only problem then the naïve (ordinary least squares) estimator also delivers this parameter; there is no gain from using randomization as an instrumental variable. On allowing the heterogeneity to also alter counterfactual outcomes, the instrumental variable estimator may well be more biased for mean impact than the naïve estimator. Examples are given for various stylized programs, including a training program that attenuates the gains from higher latent ability, an insurance program that compensates for losses from unobserved risky behavior and a microcredit scheme that attenuates the gains from access to other sources of credit. Practitioners need to think carefully about the likely behavioral responses to social experiments in each context |
| Beschreibung: | 1 Online-Ressource (13 p) |
| DOI: | 10.1596/1813-9450-5804 |
Internformat
MARC
| LEADER | 00000nmm a2200000zc 4500 | ||
|---|---|---|---|
| 001 | BV048265241 | ||
| 003 | DE-604 | ||
| 007 | cr|uuu---uuuuu | ||
| 008 | 220609s2011 |||| o||u| ||||||eng d | ||
| 024 | 7 | |a 10.1596/1813-9450-5804 |2 doi | |
| 035 | |a (ZDB-1-WBA)NLM010328998 | ||
| 035 | |a (OCoLC)1073825161 | ||
| 035 | |a (DE-599)GBVNLM010328998 | ||
| 040 | |a DE-604 |b ger |e rda | ||
| 041 | 0 | |a eng | |
| 049 | |a DE-12 |a DE-521 |a DE-573 |a DE-523 |a DE-Re13 |a DE-19 |a DE-355 |a DE-703 |a DE-91 |a DE-706 |a DE-29 |a DE-M347 |a DE-473 |a DE-824 |a DE-20 |a DE-739 |a DE-1043 |a DE-863 |a DE-862 | ||
| 100 | 1 | |a Ravallion, Martin |e Verfasser |4 aut | |
| 245 | 1 | 0 | |a On the Implications of Essential Heterogeneity for Estimating Causal Impacts Using Social Experiments |c Ravallion, Martin |
| 264 | 1 | |a Washington, D.C |b The World Bank |c 2011 | |
| 300 | |a 1 Online-Ressource (13 p) | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b c |2 rdamedia | ||
| 338 | |b cr |2 rdacarrier | ||
| 520 | |a Randomized control trials are sometimes used to estimate the aggregate benefit from some policy or program. To address the potential bias from selective take-up, the randomization is used as an instrumental variable for treatment status. Does this (popular) method of impact evaluation help reduce the bias when take-up depends on unobserved gains from take up? Such "essential heterogeneity" is known to invalidate the instrumental variable estimator of mean causal impact, though one still obtains another parameter of interest, namely mean impact amongst those treated. However, if essential heterogeneity is the only problem then the naïve (ordinary least squares) estimator also delivers this parameter; there is no gain from using randomization as an instrumental variable. On allowing the heterogeneity to also alter counterfactual outcomes, the instrumental variable estimator may well be more biased for mean impact than the naïve estimator. Examples are given for various stylized programs, including a training program that attenuates the gains from higher latent ability, an insurance program that compensates for losses from unobserved risky behavior and a microcredit scheme that attenuates the gains from access to other sources of credit. Practitioners need to think carefully about the likely behavioral responses to social experiments in each context | ||
| 700 | 1 | |a Ravallion, Martin |4 oth | |
| 776 | 0 | 8 | |i Ravallion, Martin |a On the Implications of Essential Heterogeneity for Estimating Causal Impacts Using Social Experiments |
| 856 | 4 | 0 | |u https://doi.org/10.1596/1813-9450-5804 |x Verlag |z kostenfrei |3 Volltext |
| 912 | |a ZDB-1-WBA | ||
| 943 | 1 | |a oai:aleph.bib-bvb.de:BVB01-033645435 | |
Datensatz im Suchindex
| _version_ | 1812671726940585984 |
|---|---|
| adam_text | |
| adam_txt | |
| any_adam_object | |
| any_adam_object_boolean | |
| author | Ravallion, Martin |
| author_facet | Ravallion, Martin |
| author_role | aut |
| author_sort | Ravallion, Martin |
| author_variant | m r mr |
| building | Verbundindex |
| bvnumber | BV048265241 |
| collection | ZDB-1-WBA |
| ctrlnum | (ZDB-1-WBA)NLM010328998 (OCoLC)1073825161 (DE-599)GBVNLM010328998 |
| discipline | Wirtschaftswissenschaften |
| discipline_str_mv | Wirtschaftswissenschaften |
| doi_str_mv | 10.1596/1813-9450-5804 |
| format | Electronic eBook |
| fullrecord | <?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>00000nmm a2200000zc 4500</leader><controlfield tag="001">BV048265241</controlfield><controlfield tag="003">DE-604</controlfield><controlfield tag="007">cr|uuu---uuuuu</controlfield><controlfield tag="008">220609s2011 |||| o||u| ||||||eng d</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1596/1813-9450-5804</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(ZDB-1-WBA)NLM010328998</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(OCoLC)1073825161</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)GBVNLM010328998</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-604</subfield><subfield code="b">ger</subfield><subfield code="e">rda</subfield></datafield><datafield tag="041" ind1="0" ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="049" ind1=" " ind2=" "><subfield code="a">DE-12</subfield><subfield code="a">DE-521</subfield><subfield code="a">DE-573</subfield><subfield code="a">DE-523</subfield><subfield code="a">DE-Re13</subfield><subfield code="a">DE-19</subfield><subfield code="a">DE-355</subfield><subfield code="a">DE-703</subfield><subfield code="a">DE-91</subfield><subfield code="a">DE-706</subfield><subfield code="a">DE-29</subfield><subfield code="a">DE-M347</subfield><subfield code="a">DE-473</subfield><subfield code="a">DE-824</subfield><subfield code="a">DE-20</subfield><subfield code="a">DE-739</subfield><subfield code="a">DE-1043</subfield><subfield code="a">DE-863</subfield><subfield code="a">DE-862</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Ravallion, Martin</subfield><subfield code="e">Verfasser</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">On the Implications of Essential Heterogeneity for Estimating Causal Impacts Using Social Experiments</subfield><subfield code="c">Ravallion, Martin</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="a">Washington, D.C</subfield><subfield code="b">The World Bank</subfield><subfield code="c">2011</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">1 Online-Ressource (13 p)</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Randomized control trials are sometimes used to estimate the aggregate benefit from some policy or program. To address the potential bias from selective take-up, the randomization is used as an instrumental variable for treatment status. Does this (popular) method of impact evaluation help reduce the bias when take-up depends on unobserved gains from take up? Such "essential heterogeneity" is known to invalidate the instrumental variable estimator of mean causal impact, though one still obtains another parameter of interest, namely mean impact amongst those treated. However, if essential heterogeneity is the only problem then the naïve (ordinary least squares) estimator also delivers this parameter; there is no gain from using randomization as an instrumental variable. On allowing the heterogeneity to also alter counterfactual outcomes, the instrumental variable estimator may well be more biased for mean impact than the naïve estimator. Examples are given for various stylized programs, including a training program that attenuates the gains from higher latent ability, an insurance program that compensates for losses from unobserved risky behavior and a microcredit scheme that attenuates the gains from access to other sources of credit. Practitioners need to think carefully about the likely behavioral responses to social experiments in each context</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Ravallion, Martin</subfield><subfield code="4">oth</subfield></datafield><datafield tag="776" ind1="0" ind2="8"><subfield code="i">Ravallion, Martin</subfield><subfield code="a">On the Implications of Essential Heterogeneity for Estimating Causal Impacts Using Social Experiments</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.1596/1813-9450-5804</subfield><subfield code="x">Verlag</subfield><subfield code="z">kostenfrei</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">ZDB-1-WBA</subfield></datafield><datafield tag="943" ind1="1" ind2=" "><subfield code="a">oai:aleph.bib-bvb.de:BVB01-033645435</subfield></datafield></record></collection> |
| id | DE-604.BV048265241 |
| illustrated | Not Illustrated |
| index_date | 2024-07-03T19:59:51Z |
| indexdate | 2024-10-12T04:01:09Z |
| institution | BVB |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-033645435 |
| oclc_num | 1073825161 |
| open_access_boolean | 1 |
| owner | DE-12 DE-521 DE-573 DE-523 DE-Re13 DE-BY-UBR DE-19 DE-BY-UBM DE-355 DE-BY-UBR DE-703 DE-91 DE-BY-TUM DE-706 DE-29 DE-M347 DE-473 DE-BY-UBG DE-824 DE-20 DE-739 DE-1043 DE-863 DE-BY-FWS DE-862 DE-BY-FWS |
| owner_facet | DE-12 DE-521 DE-573 DE-523 DE-Re13 DE-BY-UBR DE-19 DE-BY-UBM DE-355 DE-BY-UBR DE-703 DE-91 DE-BY-TUM DE-706 DE-29 DE-M347 DE-473 DE-BY-UBG DE-824 DE-20 DE-739 DE-1043 DE-863 DE-BY-FWS DE-862 DE-BY-FWS |
| physical | 1 Online-Ressource (13 p) |
| psigel | ZDB-1-WBA |
| publishDate | 2011 |
| publishDateSearch | 2011 |
| publishDateSort | 2011 |
| publisher | The World Bank |
| record_format | marc |
| spellingShingle | Ravallion, Martin On the Implications of Essential Heterogeneity for Estimating Causal Impacts Using Social Experiments |
| title | On the Implications of Essential Heterogeneity for Estimating Causal Impacts Using Social Experiments |
| title_auth | On the Implications of Essential Heterogeneity for Estimating Causal Impacts Using Social Experiments |
| title_exact_search | On the Implications of Essential Heterogeneity for Estimating Causal Impacts Using Social Experiments |
| title_exact_search_txtP | On the Implications of Essential Heterogeneity for Estimating Causal Impacts Using Social Experiments |
| title_full | On the Implications of Essential Heterogeneity for Estimating Causal Impacts Using Social Experiments Ravallion, Martin |
| title_fullStr | On the Implications of Essential Heterogeneity for Estimating Causal Impacts Using Social Experiments Ravallion, Martin |
| title_full_unstemmed | On the Implications of Essential Heterogeneity for Estimating Causal Impacts Using Social Experiments Ravallion, Martin |
| title_short | On the Implications of Essential Heterogeneity for Estimating Causal Impacts Using Social Experiments |
| title_sort | on the implications of essential heterogeneity for estimating causal impacts using social experiments |
| url | https://doi.org/10.1596/1813-9450-5804 |
| work_keys_str_mv | AT ravallionmartin ontheimplicationsofessentialheterogeneityforestimatingcausalimpactsusingsocialexperiments |