Synthesizing Cash for Clunkers: Stabilizing the Car Market, Hurting the Environment?

Stefan Klößner and Gregor Pfeifer

MPRA Paper from University Library of Munich, Germany

Abstract: We examine the impact of the EUR 5 billion German Cash-for-Clunkers program on vehicle registrations and respective CO2 emissions. To construct proper counterfactuals, we develop the multivariate synthetic control method using time series of economic predictors (MSCMT) and show (asymptotic) unbiasedness of the corresponding effect estimator under quite general conditions. Using cross-validation for determining an optimal specification of predictors, we do not find significant effects for CO2 emissions, while the stimulus’ impact on vehicle sales is strongly positive. Modeling different buyer subgroups, we disentangle this effect: 530,000 purchases were simply windfall gains; 550,000 were pulled forward; and 850,000 vehicles would not have been purchased in absence of the subsidy, worth EUR 17 billion.

Keywords: Generalized Synthetic Controls; Cross-Validation; Cash-for-Clunkers; CO2 Emissions (search for similar items in EconPapers)
JEL-codes: C31 C32 C52 D04 D12 H23 H24 L62 Q51 (search for similar items in EconPapers)
Date: 2018-07-23
New Economics Papers: this item is included in nep-ene, nep-env, nep-reg and nep-tre
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

Downloads: (external link)
https://mpra.ub.uni-muenchen.de/88175/1/MPRA_paper_88175.pdf original version (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:pra:mprapa:88175

Access Statistics for this paper

More papers in MPRA Paper from University Library of Munich, Germany Ludwigstraße 33, D-80539 Munich, Germany. Contact information at EDIRC.
Bibliographic data for series maintained by Joachim Winter ().