Abstract
Advocates of Medicaid expansion argue that federal Medicaid assistance to states fosters economic activity, generating positive local multiplier effects. Furthermore, during economic downturns, Congress regularly tweaks federal match rates for state Medicaid spending—including during the COVID-19 public health emergency—in order to assist states. Despite heavy reliance on Medicaid funding formulas, identifying the economic effect of these federal transfers has proved challenging. This is because federal Medicaid assistance (to states) is endogenous since funding levels are correlated with unobserved factors driving state economic activity. To address this concern, we construct an instrument based on a nonlinearity in the federal matching rate for state Medicaid spending. Using state-level panel data from 1990 to 2013, we find that federal Medicaid assistance does stimulate economic activity, but the implied cost per job created is quite high, and the multiplier is well below 1. Despite modest economic effects over the entire sample period, we find that federal Medicaid assistance provided powerful fiscal stimulus to states after the Great Recession when the implied multiplier exceeded 1.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
Notes
The pace of growth accelerated further with the Medicaid expansion under the Affordable Care Act (ACA). The CBO estimates that as much as 21 percent of the overall Medicaid funding in 2019 will support adults made eligible because of the ACA Medicaid expansion.
For example, see Kliff (2012) in the Washington Post.
In the other case, they touted prospective gains to state economies from increased federal grants associated with expanding Medicaid. Here, they argued that federal Medicaid spending raises worker productivity partly by improving the health of recipients. This notwithstanding, empirical size of local multipliers is far from clear, as it depends on a number of factors, including how the spending is structured, how it is financed, on macroeconomic conditions, and on possible monetary policy responses.
Among other papers, Carlino and Inman (2016) come closest to estimating the multiplier from intergovernmental federal grants, though not specifically from FMA. Estimating SVAR specifications using time series data from 1960 to 2010, they found large and significant multipliers, in excess of 2 at the peak, from targeted welfare aid combining both AFDC and Medicaid.
Alternative specifications for the full time period sometimes yield a much larger, but still very small, jobs multiplier. For example, our full period estimate is a multiplier of 0.54 at a cost of over $200,000 per job. It should also go without saying that intergovernmental transfers to states serve important purposes beyond creating jobs. And, policymakers will want to consider these other benefits, in addition to multiplier effects.
In another paper, Chodorow-Reich (2019) also uses cross-sectional variation to identify stimulative effects of total ARRA spending. Here, he emphasizes a jobs multiplier of between 1.8 and 2.3 per $100,000 in additional federal grant at a cost per job year of $50,000 with an implied multiplier of 1.5.
In some cases, states may have a different match rate for certain groups, such as those covered by the ACA Medicaid expansion.
Note that, the first (inframarginal) channel could also result in some increased Medicaid spending.
LP approach was originally proposed in Jordà (2005).
While a system of equations is not required, more than one equation may be required if an instrumental variables approach is used to address endogeneity issues.
Note that \({\beta }_{1}^{H}\) in the numerator of \({\beta }_{1}^{H}/H\) is \({\beta }_{1}\) with superscript \(H\) and should not be confused with power \(H\).
Note that using normalized RPCPI in this equation is simply for convenience, as the regression is numerically equivalent to one in which \(\widetilde{\mathrm{RPCPI}}\) is replaced with RPCPI.
See Nakamura and Steinsson (2014) for an alternative empirical approach using panel data.
Note that, while our data extend to 2013, the latest base year used in our analysis is 2010, since some variables include information from the three years following the base year.
Note that confidence intervals for cost per job may not exactly align with the bounds for the coefficients as they are nonlinear functions and their intervals have been estimated using delta method.
References
Bellemare, M. F., Masaki, T., & Pepinsky, T. B. (2017). Lagged explanatory variables and the estimation of causal effect. The Journal of Politics, 79(3), 949–963. https://doi.org/10.1086/690946
Calonico, S., Cattaneo, M. D., & Titiunik, R. (2014a). Robust nonparametric confidence intervals for regression-discontinuity designs. Econometrica, 82(6), 2295–2326. https://doi.org/10.3982/ecta11757
Calonico, S., Cattaneo, M. D., & Titiunik, R. (2014b). Robust data-driven inference in the regression-discontinuity design. Stata Journal, 14(4), 909–946. https://doi.org/10.1177/1536867x1401400413
Carlino, G., & Inman, R. P. (2016). Fiscal stimulus in economic unions: What role for states? Tax Policy and the Economy, 30(1), 1–50. https://doi.org/10.1086/685592
Chodorow-Reich, G. (2019). geographic cross-sectional fiscal spending multipliers: What have we learned? American Economic Journal: Economic Policy, 11(2), 1–34. https://doi.org/10.1257/pol.20160465
Chodorow-Reich, G., Feiveson, L., Liscow, Z., & Woolston, W. G. (2012). Does state fiscal relief during recessions increase employment? Evidence from the American Recovery and Reinvestment Act. American Economic Journal: Economic Policy, 4(3), 118–145. https://doi.org/10.1257/pol.4.3.118
Congressional Budget Office. (2018). Options for Reducing the Deficit: 2019 to 2028, Congressional Budget Office: Washington, D.C.
Conley, T. G., & Dupor, B. (2013). The American recovery and reinvestment act: Solely a government jobs program? Journal of Monetary Economics, 60(5), 535–549. https://doi.org/10.1016/j.jmoneco.2013.04.011
Council of Economic Advisers. (2014a). Economic report of the president.
Council of Economic Advisers. (2014b). Missed opportunities the consequences of state decisions not to expand medicaid.
Jordà, Ò. (2005). Estimation and inference of impulse responses by local projections. American Economic Review, 95(1), 161–182. https://doi.org/10.1257/0002828053828518
Jordà, Ò., & Taylor, A. M. (2016). The time for austerity: Estimating the average treatment effect of fiscal policy. The Economic Journal, 126(590), 219–255. https://doi.org/10.1111/ecoj.12332
Kliff, T. (2012). Medicaid’s stimulative effect [Blog post]. Retrieved from https://www.washingtonpost.com/news/wonk/wp/2012/07/10/medicaids-stimulative-effect/
Lundqvist, H., Dahlberg, M., & Mörk, E. (2014). Stimulating local public employment: Do general grants work? American Economic Journal: Economic Policy, 6(1), 167–192. https://doi.org/10.1257/pol.6.1.167
Leung, P., (2016). Four Essays on the Economics of Social Programs (Doctoral dissertation). Retrieved from http://arks.princeton.edu/ark:/88435/dsp018s45qc191.
McCrary, J. (2008). Manipulation of the running variable in the regression discontinuity design: A density test. Journal of Econometrics, 142(2), 698–714. https://doi.org/10.1016/j.jeconom.2007.05.005
Mitchell, A. (2020). Medicaid's Federal Medical Assistance Percentage (FMAP). Retrieved from https://sgp.fas.org/crs/misc/R43847.pdf
Nakamura, E., & Steinsson, J. (2014). Fiscal stimulus in a monetary union: Evidence from US regions. American Economic Review, 104(3), 753–792. https://doi.org/10.1257/aer.104.3.753
Ramey, V. A., & Zubairy, S. (2018). Government spending multipliers in good times and in bad: Evidence from US historical data. Journal of Political Economy, 126(2), 850–901. https://doi.org/10.1086/696277
Serrato, J. C. S., & Wingender, P. (2016). Estimating local fiscal multipliers (No. w22425). National Bureau of Economic Research. https://doi.org/10.3386/w22425
Wilson, D. J. (2012). Fiscal spending jobs multipliers: evidence from the 2009 American recovery and reinvestment act. American Economic Journal: Economic Policy, 4(3), 251–282. https://doi.org/10.1257/pol.4.3.251
Zidar, O. (2019). Tax cuts for whom? Heterogeneous effects of income tax changes on growth and mployment. Journal of Political Economy, 127(3), 1437–1472. https://doi.org/10.1086/701424
Acknowledgements
We thank the editor David Agrawal, two anonymous referees, Jason Seligman, Bo Zhao, conference participants at the National Tax Association’s 112th Annual Conference on Taxation, Federal Reserve System Regional Conference, and the WEAI’s 96th Annual Conference for helpful comments. Views expressed here are those of the authors and do not necessarily reflect those of the Federal Reserve Bank of Dallas or the Federal Reserve System or the University of Texas at Dallas
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Appendix
Appendix
Relationship of FMA with lags and leads of job growth. Notes: The figure plots IV estimates with their 95 percent confidence intervals from specifications with lags and leads of job growth as dependent variables. Estimates are based on the specification in column (5) of Table 5. See notes to Table 5 for other covariates included
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Giertz, S.H., Kumar, A. The local fiscal multiplier of intergovernmental grants: evidence from federal medicaid assistance to states. Int Tax Public Finance (2023). https://doi.org/10.1007/s10797-023-09792-y
Accepted:
Published:
DOI: https://doi.org/10.1007/s10797-023-09792-y