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November 2015 Policy Study, Number 15-9

   

Impact of Federal Transfers On State and Local Own-Source Spending

   

Regression analysis of relationship between federal intergovernmental transfers and state and local spending

   

 

Another way to deal with the variation over time uses a statistical approach. One way to separate out the effect of the changes over time from the persistent differences in spending among states is to run a regression that allows for state-specific fixed effects using dummy variable for each state.

 

Figure 9 shows the correlation between the state and local own-source general revenue in a given year and federal intergovernmental transfers in that year after taking out the effect of the state specific dummy and a time trend (red dots). The blue dots show the initial scatter in Figure 6.

 

Figure 9 :      Relationship between federal intergovernmental revenue and state/local own-source general revenue, each state, controlling for state fixed effects, 1972–2012
Graphic 2

 

As expected, the scatter plot of these state-specific effects has a slope that is less steep than the scatter of points in Figure 6. The trendline indicates that for every percentage point increase in federal money to states, state and local spending increases by roughly 0.74 percentage points. The slope is less steep because the regression allocates some of this correlation to the average of state-specific changes over time. Nevertheless, when examined this way, the data still show a correlation of spending from federal and state/local sources.

 

The fixed affects approach is simplistic. It assumes that each state is different from other states, but does not describe the ways in which states differ. It also does not describe how such differences could account for spending from state and local taxes, fees, charges, and other revenue sources apart from own-source spending associated with federal intergovernmental transfers.

 

Previous research identifies several factors that could explain differences in state and local own-source spending. These controls are typical of studies that examine the fiscal behavior of local governments. Each of the following factors vary across states and vary from year-to-year:

 

  • Unemployment, share of labor force;[8]
  • Poverty, share of population;[9]
  • Age 5 and younger, share of population;[10]
  • Age 5-18, share of population;
  • Age 65 and older, share of population;
  • Mining share of gross state product, is included to account for state-by-state differences in the energy and mining sector and also to account for the recent boom in energy and mining markets;[11]
  • Manufacturing share of gross state product;[12] and
  • Population density.[13]

Figure 10 :    Relationship between federal intergovernmental revenue and state/local own-source general revenue, each state, controlling for economic and demographic variation, 1972–2012
Graphic 4

 

Figure 10 shows the correlation between the state and local own source general revenue in a given year and federal intergovernmental transfers in that year after taking out the effect of the state- and year-specific control factors. The scatter plot of these state-specific effects has a slope that is less steep than the scatter of points in Figure 6 and Figure 9. Nevertheless, when examined this way, the data still show a correlation of spending from federal and state/local sources.

 

Table 2 :       Regression results of relationship between state/local own-source general revenue (dependent variable) and federal intergovernmental revenue, by state, controlling for economic and demographic variation, 1980–2012


Variable

Coefficient

Std. Error

Constant

0.109

0.008

***

Federal intergovernmental revenue

0.817

0.044

***

Unemployment, share of labor force

–0.018

0.022

 

Poverty, share of population

–0.086

0.013

***

Age 5 and younger, share of population

0.516

0.094

***

Age 5-18, share of population

–0.123

0.038

***

Age 65 and older, share of population

0.040

0.025

 

Mining share of gross state product

0.121

0.015

***

Manufacturing share of gross state product

–0.024

0.006

***

Population density

2.51E-06

0.000

**

 

 

 

 

R-squared

0.493

 

 

Adj. R-squared

0.490

 

 

Number of observations

1,519

 

 

** denotes significant at the 5 percent level of significance
*** denotes significant at the 1 percent level of significance

 

Table 2 presents the results of a regression that quantifies the relationship between state/local own-source general revenue (as a share of state personal income) and federal intergovernmental revenue (as a share of state personal income) and controlling for the economic and demographic factors that vary across states and over time.

 

The trendline indicates that for every percentage point increase in federal money to states, state and local spending increases by 0.82 percentage points, which is in line with the estimates provided by the scatterplot analysis provided in Figures 4–10. The estimated coefficient is statistically significant at the 1 percent level of significance. This is also consistent with recent academic research finding that each dollar of additional federal grants to states is associated with tax increases in the range 54 cents to 86 cents in new state and local taxes.[14]

 

The regression model has an R-squared statistics of 0.493, which is within the range presented in peer-reviewed articles in this area of research.

 

   

 

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