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4 The reward-punishment and the issue priority models appear to offer diametrically opposed “black and white” views of party support; however, both models are consistent with the rational choice framework. Harold Clarke, Euel Elliott and Barry Seldon show that both models can be subsumed under a single voter utility function (“A Utility Function Analysis of Competing Models of Party Support: Key Assumptions Reconsidered,” Journal of Theoretical Politics 6 [1994], 289–305).CrossRefGoogle Scholar

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6 Alt, James and Chrystal, K. Alec, Political Economics (Berkeley: University of California Press, 1983Google Scholar) is representative of the critical approach to the PBC thesis in the early 1980s. For a review of the empirical evidence against the electoral cycle thesis during this period, see Blais and Nadeau, “The Electoral Budget Cycle.”

7 See notes 1 and 2. Also, for a review, see Blais, André, Blake, Donald and Dion, Stéphane, “Do Parties Make a Difference? Parties and the Size of Government in Liberal Democracies,” American Journal of Political Science 37 (1993), 40–62.CrossRefGoogle Scholar

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10 For recent reviews, see Blais, Blake and Dion, “Do Parties Make a Difference?”; Hibbs, Douglas, “Partisan Theory after Fifteen Years,” European Journal of Political Economy 8 (1992), 361–373CrossRefGoogle Scholar; and Schmidt, Manfred, “When Parties Matter: A Review of the Possibilities and Limits of Partisan Influence on Public Policy,” 30 (1996), 155–183.Google Scholar

11 See the comment by Hibbs that “the main [Frey and Schneider] ideas look better now than ever” (“Partisan Theory after Fifteen Years,” 362). See also Haynes, Stephen and Stone, Joe for evidence of a significant electoral and partisan interaction on macroeconomic outcomes in the United States (“Political Models of the Business Cycle Should Be Revised,” Economic Inquiry 28 [1990], 442–465).CrossRefGoogle Scholar

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13 According to Gallup polls, the proportion of Canadians agreeing with the statement that “big government (as opposed to big labour or big business) is the biggest threat to Canada in the years to come” has risen from 35 per cent in February 1978 to 52 per cent in January 1990.

14 For a review of the political business cycle literature in general, see Paldam, Martin, “Political Business Cycles,” in Mueller, Dennis, ed., Perspectives on Public Choice (Cambridge: Cambridge University Press, 1997), 342–372.Google Scholar

15 See Rogoff, “Equilibrium Political Budget Cycles,” 33; and Blais and Nadeau, “The Electoral Budget Cycle,” 390.

16 See McAllister, James, “Do Parties Make a Difference?” in Gagnon, Alain and Tanguay, Brian, eds., Canadian Parties in Transition (1st ed.; Scarborough: Nelson Canada, 1989), 485–511.Google Scholar

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20 Blais and Nadeau, “The Electoral Budget Cycle”; and Petry, Imbeau and Crête, “Measuring Government Size in the Canadian Provinces.”

21 Chandler, William M., “Canadian Socialism and Policy Impact: Contagion from the Left?” this Journal 10 (1977), 755–780Google Scholar; and McAllister, “Do Parties Make a Difference?” 498. Looking at the few instances of provincial governments being led for extended periods by leaders of the same party, McAllister finds that a change of party leader will affect a province's fiscal effort just as much, if not more, than a change of party. See also, Abizadeh, Sohrab and Gray, John, “Politics and Provincial Government Spending in Canada,” Canadian Public Administration 35 (1992), 519–533CrossRefGoogle Scholar; Cameron, “The Growth of Government Spending”; Petry and Harmatz, “Test empirique d'explications de l' évolution des défenses publiques au Canada”; and Petry, François and Harmatz, Howard, “Politico-Economic Interaction in Canada: An Empirical Assessment,” Public Finance Quarterly 23 (1995), 305–335.CrossRefGoogle Scholar

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23 See Beck, Morris, “The Expanding Public Sector: Some Contrary Evidence,” National Tax Journal 29 (1976), 15–21Google Scholar; and Lowery, James and Berry, William, “The Growth of Government in the United States: An Empirical Assessment of Competing Explanations,” American Journal of Political Science 27 (1983), 665–694.CrossRefGoogle Scholar

24 See Petry, Imbeau and Crête, “Measuring Government Size in the Canadian Provinces.”

25 Chandler, “Canadian Socialism and Policy Impact”; Blais and Nadeau, “The Electoral Budget Cycle”; and Abizadeh and Gray, “Politics and Provincial Government Spending in Canada.”

26 See Graham White, “The Interpersonal Dynamics of Decision Making in Canadian Provincial Cabinets,” in Laver, Michael and Shepsle, Kenneth, eds., Cabinet Ministers and Parliamentary Government (Cambridge: Cambridge University Press, 1994), 251–269.Google Scholar

27 Blais, Blake and Dion, “Do Parties Make a Difference?” 55–56.

28 Petry, Imbeau and Crête, “Measuring Government Size in the Canadian Provinces.”

29 Severe multicollinearity was diagnosed in the time-series equations with interaction terms. Regressing the PARTY and the NON ELECTION variables on the interaction variable often produces R values exceeding .80. Fortunately, the problem can be solved by increasing the number of observations in a pooled design.

30 Beck, Nathaniel and Katz, Jonathan, “What To Do (and Not To Do) with Time-Series Cross-Section Data in Comparative Politics,” American Political Science Review 89 (1995), 634–647.CrossRefGoogle Scholar

31 Parks, R., “Efficient Estimation of a System of Regression Equations when Disturbances Are Both Serially and Contemporaneously Correlated,” Journal of the American Statistical Association 62 (1967), 500–509CrossRefGoogle Scholar. The Parks model eliminates serial correlation of the errors by transforming the data separately for each unit. It is well known in the literature that unit-specific serial correlation estimates are biased downward. As a result, the Parks estimates of standard errors can misestimate variability substantially. The Parks GLS application estimates the matrix of contemporaneous covariance of the errors using, on average, 2T/N observations. In one of our TSCS analyses, the number of time-series units is no larger than the number of cross sections (N = 10 and T = 10). With a T to N ratio of 1, the Parks method estimates the elements of the covariance matrix of the errors with, on average, 2 observations. Under these circumstances, the Parks correction for contemporaneous errors is bound to be grossly overconfident. Beck and Katz demonstrate that the downward bias in standard errors renders the Parks technique misleading unless there are substantially more time points (T) than there are cross-sectional units (N). Based on a series of Monte Carlo experiments, they also show that the OLS technique is more efficient than the Parks application when, as is the case in the TSCS analyses presented here, the T is no more than twice the N.

32 Readers interested in the SAS programme routine that we used for estimating PCSEs may consult Michel Clavet, François Petry et Jean-Sébastien Brien, “Comment analyser les données chronologiques pour devis partitioné en sciences sociales,” Bulletin de méthodologie sociologique no. 61 (1999), 53–69.

33 There are no lagged dependent and trend variables in the TSCS equations because they are not required by the method we use.

34 Blais and Nadeau, “The Electoral Budget Cycle,” 397.

35 Ibid., 399.