Government Decision-Making and the Incidence of Federal Mandates

60 Pages Posted: 2 Nov 2001

See all articles by Katherine Baicker

Katherine Baicker

Harvard University - Department of Health Policy & Management; National Bureau of Economic Research (NBER)

Multiple version iconThere are 2 versions of this paper

Date Written: September 2000


This paper analyzes the effects of federally-mandated program changes on state spending and revenues, incorporating and evaluating the predictive value of several common theories of the state decision-making process. Using several sources of exogenous increases in public medical spending, I estimate that the entire state portion of the burden of mandated spending is borne by decreases in other public welfare spending. While federal mandates may influence the composition of benefits at the state level, it is much more difficult for them to change the total level of state transfers. Comparison of state reactions to different shocks suggests that these reductions are due in part to the substitutability of programs in the voter utility function but also in part to the "stickiness" of spending within budget categories. States with greater racial differences between recipients and voters and states with less generous neighbors reduce other public welfare spending by even more, alleviating the burden the medical expansions imposed on their taxpayers. Mandates may thus serve only in to increase inequality across states.

Keywords: fiscal federalism, Medicaid, social insurance, spillovers

JEL Classification: H7, I0, H0

Suggested Citation

Baicker, Katherine, Government Decision-Making and the Incidence of Federal Mandates (September 2000). Available at SSRN: or

Katherine Baicker (Contact Author)

Harvard University - Department of Health Policy & Management ( email )

677 Huntington Avenue
Boston, MA 02115
United States

National Bureau of Economic Research (NBER)

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

Here is the Coronavirus
related research on SSRN

Paper statistics

Abstract Views
PlumX Metrics