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Testing Models of Distributive Politics using Exit Polls to Measure Voters’ Preferences and Partisanship
Published online by Cambridge University Press: 14 November 2012
Abstract
This article tests several hypotheses about distributive politics by studying the distribution of federal spending across US states over the period 1978–2002. It improves on previous work by using survey data to measure the share of voters in each state that are Democrats, Republicans and Independents, or liberals, conservatives and moderates. No evidence is found that the allocation of federal spending to the states is distorted by strategic manipulation to win electoral support. States with many swing voters are not advantaged compared to states with more loyal voters, and ‘battleground states’ are not advantaged compared to other states. Spending appears to have little or no effect on voters’ choices, while partisanship and ideology have large effects.
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Footnotes
Department of Government and STICERD, London School of Economics and Political Science (email: [email protected]); Department of Government, Harvard University, and NBER; and Department of Economics, Royal Holloway University of London, Erasmus University (Rotterdam) and Tinbergen Institute, respectively. We thank participants of seminars at LSE, Harvard, MIT, Columbia, Cambridge, Oxford, Bocconi, Warwick, Ferrara and Pavia. We are grateful to James Alt, Ciro Biderman, John Patty, Albert Sole’ Olle and Vera Troeger for useful comments and suggestions and to Indraneel Sircar for dedicated research assistance. The usual caveat applies. James Snyder gratefully acknowledges the financial support of National Science Foundation Grant SES-0079035. Data and replication material is available at the Dataverse Archive: http://dvn.iq.harvard.edu/dvn/. An online appendix containing additional information is available at: http://dx.doi.org/10.1017/S0007123412000245.
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57 Rather than reporting all possible specifications, we focus on ${{{\mathop{\hat\alpha }\limits^{}} }_I} $ and ${{{\mathop{\hat\alpha }\limits^{}} }_C} $ in Cases 1 and 2, and on ${{{\mathop{\hat\alpha }\limits^{}} }_P} $ in Cases 3 and 4. However, we always report the results for the case in which all variables are included. We also ran simulations that incorporate measurement error into the ‘direct’ measure of voters’ partisanship – that is, in the share of independent variable Ij. In these simulations the estimated coefficient on the term measured with error $ ({{\hat{a}}_I}) $ is biased toward zero. This is the usual attenuation bias associated with regressors that are measured with error. The other coefficients are almost unaffected, however. Results of these simulations are in Appendix Table A.1, which can be found in the Supplementary Material of this paper, at http://dx.doi.org/10.1017/S0007123412000245
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68 Each respondent could vote in six or seven races – two presidential races and three House races, and either one or two Senate races.
69 Results are available from the authors upon request.
70 We constructed analogous variables using the party affiliation of the majority in the house (House majority copartisans) and senate (Senate majority copartisans) as well as the political affiliation of state senators (Senator Copartisans). The results are substantively the same as those obtained in the case of presidential affiliation. We do not report them here, but they are available from the authors upon request.
71 When we use presidential term as the time unit, instead of a dummy for natural disasters, we include the share of the term that contained years in which a natural disaster occurred: possible values are therefore 0, 0.25, 0.5, 0.75 and 1. The total population size captures the effects of malapportionment of the US Senate, as small states are extremely over-represented. It may, however, also capture budgetary lags. Because of ‘incremental budgeting’, population growth is likely to negatively affect per-capita expenditure levels. If there are lags in adjusting the allocation of transfers to population shifts, then as a state's population grows its per-capita transfers will automatically fall. Economies of scale might also lead to a negative effect of population on per-capita transfers.
72 We do not include variables to measure committee positions or seniority. Previous studies have found little or no evidence that these variables are important determinants of aggregate spending in states or districts. See Owens and Wade, ‘Federal Spending in Congressional Districts’; Ritt, ‘Committee Position, Seniority, and the Distribution of Government Expenditures’; Levitt and Snyder, ‘Political Parties and the Distribution of Federal Outlays’.
73 Results are available from the authors upon request.
74 Detailed results are available in the online appendix.
75 Another concern is that federal expenditure could be spatially autocorrelated. To deal with this possibility, we have included census division dummies and division-specific trends in the specifications that do not include state fixed effects. When state fixed effects are included we only add division-specific trends. Since these modifications only marginally change our results, in the interest of space we do not include the tables in the article. Results are available in the online appendix.
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86 Some other studies in the literature also find insignificant effects of state expenditure on voting, for example Besley, Principled Agents? The Political Economy of Good Government.
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93 Our results do not exclude the possibility that strategic distribution of funds might occur in particular years (such as pre-election years) when electoral concerns might be stronger. The hypothesis of a ‘political cycle’ in distributive politics is not considered by the large existing literature that we have revisited in our work, but it represents a very interesting avenue for future theoretical and empirical research on pork barrel spending.
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