ČAPEK, Jan and Jesús CRESPO CUARESMA. We just estimated twenty million fiscal multipliers. Oxford Bulletin of Economics and Statistics. 2020, vol. 82, No 3, p. 483-502. ISSN 0305-9049. Available from: https://dx.doi.org/10.1111/obes.12351.
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Basic information
Original name We just estimated twenty million fiscal multipliers
Authors ČAPEK, Jan (203 Czech Republic, guarantor, belonging to the institution) and Jesús CRESPO CUARESMA (724 Spain, belonging to the institution).
Edition Oxford Bulletin of Economics and Statistics, 2020, 0305-9049.
Other information
Original language English
Type of outcome Article in a journal
Field of Study 50202 Applied Economics, Econometrics
Country of publisher United Kingdom of Great Britain and Northern Ireland
Confidentiality degree is not subject to a state or trade secret
WWW URL
Impact factor Impact factor: 1.791
RIV identification code RIV/00216224:14560/20:00114005
Organization unit Faculty of Economics and Administration
Doi http://dx.doi.org/10.1111/obes.12351
UT WoS 000503252900001
Keywords in English Fiscal multiplier;structural VAR;meta-analysis
Tags International impact, Reviewed
Changed by Changed by: Mgr. Daniela Marcollová, učo 111148. Changed: 12/4/2021 13:59.
Abstract
Abstract We analyse the role played by data and specification choices as determinants of the size of the fiscal multipliers obtained using structural vector autoregressive models. The results, based on over twenty million fiscal multipliers estimated for European countries, indicate that many seemingly harmless modelling choices have a significant effect on the size and precision of fiscal multiplier estimates. In addition to the structural shock identification strategy, these modelling choices include the definition of spending and taxes, the national accounts system employed, the use of particular interest rates or inflation measures, or whether data are smoothed prior to estimation. The cumulative effects of such arguably innocuous methodological choices can lead to a change in the spending multipliers of as much as 0.4 points.
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GA17-14263S, research and development projectName: Dynamické průměrování předpovědí makroekonomických modelů
Investor: Czech Science Foundation
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