Arbeitspapier
Nonlinear difference-indifferences in repeated cross sections with continuous treatments
This paper studies the identification of nonseparable models with continuous, endogenous regressors, also called treatments, using repeated cross sections. We show that several treatment effect parameters are identified under two assumptions on the effect of time, namely a weak stationarity condition on the distribution of unobservables, and time variation in the distribution of endogenous regressors. Other treatment effect parameters are set identified under curvature conditions, but without any function form restrictions. This result is related to the difference-in-differences idea, but imposes neither additive time effects nor exogenously defined control groups. Furthermore, we investigate two extrapolation strategies that allow us to point identify the entire model: using monotonicity of the error term, or imposing a linear correlated random coefficient structure. Finally, we illustrate our results by studying the effect of mother's age on infants' birth weight.
- Sprache
-
Englisch
- Erschienen in
-
Series: cemmap working paper ; No. CWP40/13
- Klassifikation
-
Wirtschaft
- Thema
-
identification
repeated cross sections
nonlinear models
continuous treatment
random coefficients
endogeneity
difference-in-differences
- Ereignis
-
Geistige Schöpfung
- (wer)
-
D'Haultfoeuille, Xavier
Hoderlein, Stefan
Sasaki, Yuya
- Ereignis
-
Veröffentlichung
- (wer)
-
Centre for Microdata Methods and Practice (cemmap)
- (wo)
-
London
- (wann)
-
2013
- DOI
-
doi:10.1920/wp.cem.2013.4013
- Handle
- Letzte Aktualisierung
-
10.03.2025, 11:42 MEZ
Datenpartner
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Arbeitspapier
Beteiligte
- D'Haultfoeuille, Xavier
- Hoderlein, Stefan
- Sasaki, Yuya
- Centre for Microdata Methods and Practice (cemmap)
Entstanden
- 2013
Ähnliche Objekte (12)
On repeated difference testing
On repeated difference testing
Entropy Balancing for Continuous Treatments
Subgame Perfect Equilibria in Continuous-Time Repeated Games
Double debiased machine learning nonparametric inference with continuous treatments
Double debiased machine learning nonparametric inference with continuous treatments
Measuring Poverty Dynamics with Synthetic Panels Based on Repeated Cross-Sections
Measuring Poverty Dynamics with Synthetic Panels Based on Repeated Cross-Sections
On repeated games with imperfect public monitoring: from discrete to continuous time
On Repeated Games with Imperfect Public Monitoring: From Discrete to Continuous Time
Do Dropouts Benefit from Training Programs? Korean Evidence Employing Methods for Continuous Treatments
Do dropouts benefit from training programs? Korean evidence employing methods for continuous treatments
On repeated difference testing
On repeated difference testing
Entropy Balancing for Continuous Treatments
Subgame Perfect Equilibria in Continuous-Time Repeated Games
Double debiased machine learning nonparametric inference with continuous treatments
Double debiased machine learning nonparametric inference with continuous treatments
Measuring Poverty Dynamics with Synthetic Panels Based on Repeated Cross-Sections
Measuring Poverty Dynamics with Synthetic Panels Based on Repeated Cross-Sections
On repeated games with imperfect public monitoring: from discrete to continuous time
On Repeated Games with Imperfect Public Monitoring: From Discrete to Continuous Time
Do Dropouts Benefit from Training Programs? Korean Evidence Employing Methods for Continuous Treatments
Do dropouts benefit from training programs? Korean evidence employing methods for continuous treatments
On repeated difference testing
On repeated difference testing
Entropy Balancing for Continuous Treatments
Subgame Perfect Equilibria in Continuous-Time Repeated Games
Double debiased machine learning nonparametric inference with continuous treatments
Double debiased machine learning nonparametric inference with continuous treatments
Measuring Poverty Dynamics with Synthetic Panels Based on Repeated Cross-Sections
Measuring Poverty Dynamics with Synthetic Panels Based on Repeated Cross-Sections
On repeated games with imperfect public monitoring: from discrete to continuous time
On Repeated Games with Imperfect Public Monitoring: From Discrete to Continuous Time
Do Dropouts Benefit from Training Programs? Korean Evidence Employing Methods for Continuous Treatments