Why Do Small States Receive More Federal Money? U.S. Senate Representation and the Allocation of Federal Budget

Abstract

In this paper we provide new evidence on the importance of the so-called small state advantage for the allocation of the US federal budget. We also provide a new interpretation of the available empirical evidence. Analyzing outlays for the period 1978-2002, we show that not only does the population size of a state matter, but so too does its dynamics. Once population scale and change effects are separated, the impact of population size is substantially reduced, and population change turns out to be an important explanatory variable of current spending patterns. The impact of scale and change effects varies substantially across spending programs. Small states enjoy an advantage in defense spending, whereas fast growing ones are penalized in grants allocations. Our results imply that the interests of the states are not easily aligned around their population size alone. The distortion associated with population dynamics is concentrated on federal grants where formulas play a substantial role in limiting budgetary adjustments. Hence, a large part of the inverse relationship between spending and population appears to be driven by mechanisms of budgetary inertia which are compatible with incrementalist theories of budget allocation. JEL Codes: D72, H61, H77

Fiscal Transfers and Fiscal Sustainability

“…The regression model including the lagged dependent variable in column (2) is our preferred specification because federal grants regarding several policy fields may be relatively persistent over time (see Lee and Oppenheimer , p. 172). The effects of the control variables are in line with Larcinese, Rizzo, and Testa (). The coefficient of the population size has a negative sign and is statistically significant at the 10% level.…”

“…For the U.S. states, we control for the main indicators of the U.S. transfer system following Larcinese, Rizzo, and Testa (): population, the share of young inhabitants (age 5–17), the share of old inhabitants (age above 65 years), real per capita personal income, the unemployment rate, and senators per capita. We include the explanatory variables in period t − 1 because many transfer projects for period t are determined in period t − 1.…”

“…Standardized data on real GDP in the U.S. states are available since 1977 and we use the GDP deflator to compute real values. In a some of our regressions, we include lagged real income and consequently our first year in the sample is 1978 (see Sørensen, Wu, and Yosha , and Larcinese, Rizzo, and Testa who also use data starting in 1978).…”

Rural prosperity and federal expenditures, 2000–2010

“…Medicare and Social Security benefits for example, are expected to be higher in counties with a higher proportion of residents over the age of 65 years. Finally, county population and percent change in population are included to control for scale effects and change effects (Larcinese ).…”

Spatial Interaction in Local Expenditures Among Italian Municipalities: Evidence from Italy 2001-2011

“…The lagged dependent variable, ! ("#)*) , which is an important determinant of the municipal expenditure (Veiga and Veiga, 2007;Larcinese et al, 2013), is correlated with the municipality fixed effects in the error term, leading to biased and inconsistent fixed effects estimations (Nickell, 1981). Thus, we use the system GMM (SYS-GMM) dynamic panel estimator (Arellano and Bover,1995;Blundell and Bond, 1998).…”