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Government spending and multi-category treatment effects:The modified conditional independence assumption

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  • Koiti Yano

Abstract

I devise a novel approach to evaluate the effectiveness of fiscal policy in the short run with multi-category treatment effects and inverse probability weighting based on the potential outcome framework. This study's main contribution to the literature is the proposed modified conditional independence assumption to improve the evaluation of fiscal policy. Using this approach, I analyze the effects of government spending on the US economy from 1992 to 2019. The empirical study indicates that large fiscal contraction generates a negative effect on the economic growth rate, and small and large fiscal expansions realize a positive effect. However, these effects are not significant in the traditional multiple regression approach. I conclude that this new approach significantly improves the evaluation of fiscal policy.

Suggested Citation

  • Koiti Yano, 2020. "Government spending and multi-category treatment effects:The modified conditional independence assumption," Papers 2007.08396, arXiv.org, revised Aug 2020.
    • Handle: RePEc:arx:papers:2007.08396
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    1. Òscar Jordà & Alan M. Taylor, 2016. "The Time for Austerity: Estimating the Average Treatment Effect of Fiscal Policy," Economic Journal, Royal Economic Society, vol. 126(590), pages 219-255, February.
    2. Peren Arin, K. & Koray, Faik & Spagnolo, Nicola, 2015. "Fiscal multipliers in good times and bad times," Journal of Macroeconomics, Elsevier, vol. 44(C), pages 303-311.
    3. Joshua D. Angrist & Guido M. Kuersteiner, 2011. "Causal Effects of Monetary Shocks: Semiparametric Conditional Independence Tests with a Multinomial Propensity Score," The Review of Economics and Statistics, MIT Press, vol. 93(3), pages 725-747, August.
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