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Estimating fiscal multipliers by combining statistical identification with potentially endogenous proxies

Sascha Alexander Keweloh et al.

Econometrics Journal2025https://doi.org/10.1093/ectj/utaf027article
AJG 3ABDC A*
Weight
0.50

Abstract

Summary Different proxy variables used in fiscal policy structural vector autoregressions (SVARs) lead to contradicting conclusions regarding the size of fiscal multipliers. Our analysis suggests that the conflicting results may stem from violations of the proxy exogeneity assumptions. We propose a novel approach to include proxy variables in a Bayesian non-Gaussian SVAR, tailored to accommodate potentially endogenous proxies. Using our model, we find that increasing government spending is more effective in stimulating the economy than reducing taxes.

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https://doi.org/https://doi.org/10.1093/ectj/utaf027

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@article{sascha2025,
  title        = {{Estimating fiscal multipliers by combining statistical identification with potentially endogenous proxies}},
  author       = {Sascha Alexander Keweloh et al.},
  journal      = {Econometrics Journal},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.1093/ectj/utaf027},
}

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Estimating fiscal multipliers by combining statistical identification with potentially endogenous proxies

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

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