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https://hdl.handle.net/10419/20277
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DC Field | Value | Language |
---|---|---|
dc.contributor.author | Lechner, Michael | en |
dc.date.accessioned | 2009-01-28T16:12:56Z | - |
dc.date.available | 2009-01-28T16:12:56Z | - |
dc.date.issued | 2004 | - |
dc.identifier.uri | http://hdl.handle.net/10419/20277 | - |
dc.description.abstract | This paper proposes sequential matching and inverse selection probability weighting toestimate dynamic causal effects. The sequential matching estimators extend simple,matching estimators based on propensity scores for static causal analysis that have beenfrequently applied in the evaluation literature. A Monte Carlo study shows that the suggestedestimators perform well in small and medium size samples. Based on the application of thesequential matching estimators to an empirical problem - an evaluation study of the Swissactive labour market policies - some implementational issues are discussed and results areprovided. | en |
dc.language.iso | eng | en |
dc.publisher | |aInstitute for the Study of Labor (IZA) |cBonn | en |
dc.relation.ispartofseries | |aIZA Discussion Papers |x1042 | en |
dc.subject.jel | C40 | en |
dc.subject.ddc | 330 | en |
dc.subject.keyword | dynamic treatment effects | en |
dc.subject.keyword | nonparametric identification | en |
dc.subject.keyword | causal effects | en |
dc.subject.keyword | sequential randomisation | en |
dc.subject.keyword | programme evaluation | en |
dc.subject.keyword | panel data | en |
dc.subject.stw | Kausalanalyse | en |
dc.subject.stw | Schätztheorie | en |
dc.subject.stw | Matching | en |
dc.subject.stw | Nichtparametrisches Verfahren | en |
dc.subject.stw | Arbeitsmarktpolitik | en |
dc.subject.stw | Wirtschaftspolitische Wirkungsanalyse | en |
dc.subject.stw | Theorie | en |
dc.subject.stw | Schweiz | en |
dc.title | Sequential Matching Estimation of Dynamic Causal Models | - |
dc.type | Working Paper | en |
dc.identifier.ppn | 380765799 | en |
dc.rights | http://www.econstor.eu/dspace/Nutzungsbedingungen | en |
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