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Ideology and the size of US state government

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Abstract

This paper theorizes that the impact of ideology on the size of US state governments increases with state income. This idea is tested using state-level ideology data derived from the voting behavior of state congressional representatives. Empirically the interaction of ideology and mean income is a key determinant of state government size. At 1960s levels of income the impact of ideology is negligible. At 1997 levels of income a one standard-deviation move towards the left of the ideology spectrum increases state government size by about half a standard deviation. Estimated income elasticities differentiated by state and time are found to be increasing with ideology and diminishing with income, as predicted by the theory.

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Notes

  1. An extensive literature argues that differences in political culture, expressed in the form of differing political ideologies, play a role in determining the size and scope of government in mixed economies. Acemoglu (2005) makes this point in his critique of Persson and Tabellini (2003, 2004). Using international data Cameron (1978), Cusack (1997) and Tavits (2004) all find a relationship between government size and ideology using fixed ideological data (i.e., defined by parties in power). Pickering and Rockey (2011) found this relationship to be strongly conditional on income levels.

  2. In the context of US states there is an important distinction between tax revenue and public sector expenditure, as the latter is funded in part by transfers from the Federal government. This issue is addressed below.

  3. In common with this paper and Besley and Case (2003), Bjørnskov and Potrafke also emphasize the importance of divided government, as discussed below.

  4. In particular Winters (1976), Dye (1984), Garand (1988) and Gilligan and Matsusaka (1995) all find little evidence that the identity of the party in control (i.e., whether Democrat or Republican) determines the overall level of spending.

  5. The relevant results in Besley and Case (2003:41, 43) are in their Tables 8 and 9. Knight (2000) also finds that Democrat (Republican) control of both houses leads to higher (lower) taxes rates relative to state GDP, Besley and Case (1995) find that Democrats raise taxes and spending when working under term limits and Rogers and Rogers (2000) also find that Democrat control in the house is associated with larger government. Blais et al. (1993) find that party identity plays a small role in driving government spending using international data.

  6. As Berry et al. (2010) note, Soss et al. (2001), Shipan and Volden (2006), Wood and Theobald (2003), Langer and Brace (2005), Songer and Ginn (2002) and Kim and Gerber (2005) all have used these data as determinants of state-level policy.

  7. In this paper we prefer the term ‘policy platform’, but the wider literature often prefers ‘manifesto’. For our purposes, the terms are equivalent.

  8. It is simplest to think of the public good as rival and excludable rather than a public good of the Samuelson variety.

  9. See also Alesina et al. (2001), Alesina and Angeletos (2005), Benabou (2008) and Piketty (1995).

  10. Note that given the properties of F and G the equilibrium is unique and bounded, i.e., 0≤t ∗<1.

  11. As well as entering (2) directly, c m and g also depend on \(\overline{y}\), hence restrictions on the third-order derivatives are required.

  12. Meltzer and Richard (1983) also employ this functional form.

  13. Total taxes are defined as the sum of sales, income and corporate taxes. The data are described in full in Besley and Case (2003).

  14. The liberal-conservative dimension links with the above theory wherein ideology is defined by preferences for the public good relative to private consumption. For example, Saunders (2004) writes that “A liberal… favors activist government and has a progressive vision of the state’s role… through necessarily higher taxes” whilst “the conservative tends to oppose an activist government… (and) usually favors lower… taxes. Simply put a pure conservative believes in the least government possible at all levels.”

  15. Note that because Berry et al. (2010) have since updated their ideology data, estimation is now feasible for the full sample whereas Besley and Case (2003), only had access to ideology data ending in 1993. The ideology data begin in 1960. Following Besley and Case (2003) Nebraska is omitted from the analysis because it has a unicameral non-partisan legislature.

  16. This follows immediately from the state budget constraint.

  17. Besley and Case (2003) also used quadratic terms in income and state population but we have dropped these terms for two reasons. Firstly, they are highly collinear with the other variables. In particular the Variance Inflation Term (VIF) for state income is 180 when column 1 of Table 4 is extended to include the squared terms. Secondly, the theory is concerned with income elasticity and inferences are more straightforward when just the linear term is included.

  18. In Tables 5 and 6 results are reported using the tax share of state GDP as the dependent variable. The results and inference are not substantially altered when total state expenditure as a share of state GDP is used instead as the dependent variable.

  19. When state expenditure is the dependent variable, the impact of ideology becomes significant at $9,000.

  20. Note that the state expenditure data include observations from 1998, thus increasing the sample size by 47.

  21. This specification follows from (7), and is similar to that used by Bjørnskov and Potrafke (2011) with the distinction, following from the theory, that the difference in government size is regressed on the difference in ideology and its interaction with income, as opposed to ideology measured in levels.

  22. In particular, we estimated column 2 of Table 13, column 4 of Table 14 and column 1 of Table 15 in Besley and Case (2003), with the inclusion of the lagged dependent variable, and using clustered robust standard errors. In this more demanding econometric specification, only the super majority rule survived in terms of statistical significance. These results are available on request.

  23. Ideally, we would include all of institutional variables at once. The problem with this approach is that many of these variables are correlated with each other. Besley and Case (2003) also take the approach of examining particular institutions in isolation.

  24. It is not possible to adequately distinguish between the effects of split and vetosplit as they are highly correlated.

  25. The first of these hypotheses restates Eq. (6) and the second Eq. (5).

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Acknowledgements

We thank Tim Besley and Richard Fording for making their data available and seminar participants at the University of York. We also thank the editor and the anonymous referees. The standard disclaimer applies. Part of this work took place whilst Rockey was visiting the Institut d’Economia de Barcelona and he is grateful for their generous support and hospitality.

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Authors and Affiliations

  1. Department of Economics and Related Studies, University of York, Heslington, York, YO10 5DD, UK

    Andrew C. Pickering

  2. Department of Economics, University of Leicester, Leicester, LE1 7RH, UK

    James Rockey

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  1. Andrew C. Pickering
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  2. James Rockey
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Correspondence to James Rockey.

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Pickering, A.C., Rockey, J. Ideology and the size of US state government. Public Choice 156, 443–465 (2013). https://doi.org/10.1007/s11127-012-0026-x

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