Identification of Causal Intensive Margin Effects by Difference-in-Difference Methods
dc.contributor.author
Hersche, Markus
dc.contributor.author
Moor, Elias
dc.date.accessioned
2018-11-02T14:46:23Z
dc.date.available
2018-11-02T14:24:03Z
dc.date.available
2018-11-02T14:46:23Z
dc.date.issued
2018-11
dc.identifier.uri
http://hdl.handle.net/20.500.11850/300865
dc.identifier.doi
10.3929/ethz-b-000300865
dc.description.abstract
This paper discusses identification of causal intensive margin effects. The causal intensive margin effect is defined as the treatment effect on the outcome of individuals with a positive outcome irrespective of whether they are treated or not (always-takers or participants). A potential selection problem arises when conditioning on positive outcomes, even if treatment is randomly assigned. We propose to use difference-in-difference methods - conditional on positive outcomes - to esti-
mate causal intensive margin effects. We derive sufficient conditions under which the difference-in-difference methods identify the causal intensive margin effect in a setting with random treatment.
en_US
dc.format
application/pdf
en_US
dc.language.iso
en
en_US
dc.publisher
Center of Economic Research (CER), ETH Zurich
en_US
dc.rights.uri
http://rightsstatements.org/page/InC-NC/1.0/
dc.subject
Intensive margin effect
en_US
dc.subject
Difference-in-diference
en_US
dc.subject
Corner solution models
en_US
dc.subject
Potential outcomes
en_US
dc.subject
Policy evaluation
en_US
dc.title
Identification of Causal Intensive Margin Effects by Difference-in-Difference Methods
en_US
dc.type
Working Paper
dc.rights.license
In Copyright - Non-Commercial Use Permitted
ethz.journal.title
Economics Working Paper Series
ethz.journal.volume
18/302
en_US
ethz.size
25 p.
en_US
ethz.code.jel
JEL - JEL::C - Mathematical and Quantitative Methods::C2 - Single Equation Models; Single Variables::C21 - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions
en_US
ethz.code.jel
JEL - JEL::C - Mathematical and Quantitative Methods::C2 - Single Equation Models; Single Variables::C24 - Truncated and Censored Models; Switching Regression Models; Threshold Regression Models
en_US
ethz.code.jel
JEL - JEL::C - Mathematical and Quantitative Methods::C1 - Econometric and Statistical Methods and Methodology: General::C18 - Methodological Issues: General
en_US
ethz.publication.place
Zurich
en_US
ethz.publication.status
published
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02120 - Dep. Management, Technologie und Ökon. / Dep. of Management, Technology, and Ec.::03877 - Bommier, Antoine / Bommier, Antoine
en_US
ethz.leitzahl.certified
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02120 - Dep. Management, Technologie und Ökon. / Dep. of Management, Technology, and Ec.::03877 - Bommier, Antoine / Bommier, Antoine
en_US
ethz.date.deposited
2018-11-02T14:24:05Z
ethz.source
FORM
ethz.eth
yes
en_US
ethz.availability
Open access
en_US
ethz.rosetta.installDate
2019-01-03T09:11:31Z
ethz.rosetta.lastUpdated
2023-02-06T16:33:54Z
ethz.rosetta.versionExported
true
ethz.COinS
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Working Paper [5849]