1 Nadeau, Richard, Niemi, Richard and Amato, Timothy, ‘Prospective and Comparative or Retrospective and Individual? Party Leaders and Party Support in Great Britain’, British Journal of Political Science, 26 (1996), 245–258; Clarke, Harold, Mishler, William and Whiteley, Paul, ‘Recapturing the Falklands: Models of Conservative Popularity, 1979–1983’, British Journal of Political Science, 20 (1990), 63–81; and Crespi, Irving, ‘The Case of Presidential Popularity’, in A. Cantril, eds, Polling on the Issues (Washington, D.C.: Seven Locks Press, 1980).
2 Bingham Powell, G. and Whitten, Guy, ‘A Cross-National Analysis of Economic Voting: Taking Account of the Political Context’, American Journal of Political Science, 37 (1993), 391–414; and Persson, Torsten and Tabellini, Guido, Political Economics: Explaining Economic Policy (Cambridge, Mass.: MIT Press, 2000).
3 For example, compare vote choice studies, such as Fiorina, Morris P., ‘Economic Retrospective Voting in American National Elections: A Micro-Analysis’, American Journal of Political Science, 22 (1978), 426–443; Fiorina, Morris P., Retrospective Voting in American National Elections (New Haven, Conn.: Yale University Press, 1981); and Kiewiet, D. R., Macroeconomics and Micropolitics: The Electoral Effects of Economic Issues (Chicago: University of Chicago Press, 1983), to presidential approval studies, such as MacKuen, Michael B., Erikson, Robert S. and Stimson, James A., ‘Peasants or Bankers? The American Electorate and the US Economy’, American Political Science Review, 86 (1992), 597–611.
4 Paldam, Martin, ‘How Robust Is the Vote Function? A Study of 17 Nations over Four Decades’, in Helmut Norpoth, Michael S. Lewis-Beck and Jean-Dominique LaFay, eds, Economics and Politics: The Calculus of Support (Ann Arbor: The University of Michigan Press, 1991).
5 Key, V. O. Jr, The Responsible Electorate: Rationality in Presidential Voting: 1936–1960 (Cambridge, Mass.: The Belknap Press of Harvard University Press, 1966); Key, V. O. Jr, Politics, Parties, and Pressure Groups, 5th edn (New York: Thomas Y. Crowell, 1964); and Downs, Anthony, An Economic Theory of Democracy (New York: Harper and Row, 1957). Important works that are motivated in this way include: Norpoth, Helmut, ‘Presidents and the Prospective Voter’, Journal of Politics, 58 (1996), 776–792; MacKuen, Erikson and Stimson, ‘Peasants or Bankers?’; Chappell, Henry W. and Keech, William R., ‘A New View of Political Accountability for Economic Performance’, American Political Science Review, 79 (1985), 10–27; and Beck, Nathaniel, ‘The Economy and Presidential Approval: An Information Theoretical Perspective’, in Norpoth, Lewis-Beck and LaFay, eds, Economics and Politics. There are also, of course, well-known examples of US economic popularity studies that are explicitly concerned with presidential approval and are motivated as such. For example: Hibbs, Douglas A. Jr, ‘On the Domain for Economic Outcomes: Macroeconomic Performance and Mass Political Support in the United States, Great Britain, and Germany’, Journal of Politics, 44 (1982), 426–462; and Kernell, Samuel, ‘Explaining Presidential Popularity’, American Political Science Review, 72 (1978), 506–522.
6 For example, Key, , The Responsible Electorate, pp. 58–62.
7 For example, Norpoth, Helmut, ‘Presidents and the Prospective Voter’, and Morris Fiorina, Retrospective Voting in American National Elections New Haven, Conn.: Yale University Press, 1981).
8 For example, Frey, Bruno and Schneider, Friedrich, ‘An Empirical Study of Political-Economic Interaction in the United States’, Review of Economics and Statistics, 60 (1978), 174–183; MacKuen, Erikson and Stimson, ‘Peasants or Bankers?’; and Mueller, John E., ‘Presidential Popularity from Truman to Johnson’, American Political Science Review, 64 (1970), 18–34.
9 Beck, , ‘The Economy and Presidential Approval’.
10 On the dampening of vote intention volatility produced by partisan identification see: Converse, Philip E. and Dupeux, Georges, ‘Politicization of the Electorate in France and the United States’, Public Opinion Quarterly, 26 (1962), 1–23; and Kayser, Mark and Wlezien, Christopher, ‘Performance Pressure: Patterns of Partisanship and the Economic Vote’ (unpublished manuscript, 2007).
11 On vote choice: Fiorina, ‘Economic Retrospective Voting in American National Elections’; Fiorina, Retrospective Voting in American National Elections; and Kiewiet, Macroeconomics and Micropolitics. On presidential approval: MacKuen, Erikson and Stimson, ‘Peasants or Bankers?’
12 Erikson, Robert S. and Wlezien, Christopher, ‘Presidential Polls as a Timeseries: The Case of 1996’, Public Opinion Quarterly, 63 (1999), 163–177; Jackman, Simon, ‘Pooling the Polls over an Election Campaign’, Australian Journal of Political Science, 40 (2005), 499–517; Pickup, Mark and Johnston, Richard, ‘Campaign Trial Heats as Election Forecasts: Measurement Error and Bias in 2004 Presidential Campaign Polls’, International Journal of Forecasting, 24 (2008), 272–284; and Pickup, Mark and Johnston, Richard, ‘Campaign Trial Heats as Election Forecasts: Evidence from the 2004 and 2006 Canadian Elections’, Electoral Studies, 26 (2007), 460–476.
13 Campbell, James E., ‘Forecasting the Presidential Vote in 2004: Placing Preference Polls in Context’, PS: Political Science & Politics, 37 (2004), 763–767; Campbell, James E., ‘Evaluating the Trial-Heat and Economy Forecast of the 2004 Presidential Vote: All’s Well that Ends Well’, PS: Political Science & Politics, 38 (2006), 763–767; Whiteley, Paul, ‘Electoral Forecasting from Poll Data: The British Case’, British Journal of Political Science, 9 (1979), 219–236; and Kayser and Wlezien, ‘Performance Pressure: Patterns of Partisanship and the Economic Vote’.
14 Erikson, Robert S., Bafumi, Joseph and Wilson, Bret, ‘Could the Close 2000 Elections Have Been Predicted?’, PS: Political Science and Politics, 34 (2001), 815–819.
15 Wlezien, Christopher and Erikson, Robert S., ‘Temporal Horizons and Presidential Election Forecasts’, American Politics Quarterly, 24 (1996), 492–505.
16 Christopher Wlezien graciously provided the necessary data.
17 Samuel, Kernell and Douglas, Hibbs Jr, ‘A Critical Threshold Model of Presidential Popularity’, in D. A. Hibbs, Jr and H. Fassbender, eds, Contemporary Political Economy (Amsterdam: North-Holland, 1981).
18 Campbell, Angus, Converse, Philip, Miller, Warren and Stokes, Donald, The American Voter (New York: Wiley, 1960); Miller, Warren E. and Stokes, Donald E., ‘Constituency Influence in Congress’, American Political Science Review, 57 (1963), 45–56; Butler, David and Stokes, Donald, Political Change in Britain: The Evolution of Electoral Choice (London: Macmillan, 1974); and Budge, Ian, Crewe, Ivor and Farlie, Dennis, Party Identification and beyond: Representations of Voting in the Party Competition (London: John Wiley, 1976).
19 The two inequalities simply require that a government identifier is not going to vote for an opposition party/candidate while still approving of the government and an opposition identifier is not going to vote for the government while they disapprove of it.
20 See Appendix, Note 1, in the Supplementary Materials on the website 〈journals.cambridge.org/jps〉 for a demonstration of why this is always true.
21 Butler, David and Stokes, Donald, Political Change in Britain (New York: St Martin’s, 1969); and Budge, Crewe and Farlie, Party Identification and Beyond.
22 Brynin, Malcolm and Sanders, David, ‘Party Identification, Political Preferences and Material Conditions’, Party Politics, 3 (1997), 53–77.
23 Lanoue, D. J. and Bowler, S., ‘The Sources of Tactical Voting in British Parliamentary Elections, 1983–1987’, Political Behaviour, 14 (1992), 141–157.
24 Cain, Bruce E., ‘Strategic Voting in Britain’, American Journal of Political Science, 22 (1978), 639–655; Evans, Geoffrey, ‘Tactical Voting and Labour's Prospects’, in Anthony Heath, Roger Jowell and John Curtis, eds, Labour's Last Chance? The 1992 Election and Beyond (Aldershot, Hants.: Dartmouth, 1994); and Fisher, Stephen and Curtis, John, ‘Tactical Unwind? Changes in Party Preference Structure and Tactical Voting in Britain between 2001 in 2005’, Journal of Elections, Public Opinion and Parties, 16 (2006), 55–76.
25 Plots of the data and the rationale for the time period studied for each case is provided in the Appendix, Note 2, in the Supplementary Materials on the website 〈journals.cambridge.org/jps〉.
26 Note 8, in the Supplementary Materials on the website 〈journals.cambridge.org/jps〉.
27 The mean squared perturbation is similar to the variance but squares the difference between a month’s value and the previous month’s rather than the series’ mean. This is more appropriate in this context, as it is the month-to-month stability that is of greatest interest and the variance will overstate the month-to-month instability in a series that trends.
28 Further details are provided in the Appendix, Note 3, in the Supplementary Materials on the website 〈journals.cambridge.org/jps〉.
29 FPE = final prediction error, AIC = Akaike’s information criterion, SBIC = Schwarz’s Bayesian information criterion and HQIC = Hannan and Quinn information criterion.
30 This produces a structural VAR that has a recursive structure and so a causal interpretation can be applied.
31 For a description of the economic data used in these models, see Appendix, Note 4, in the Supplementary Materials on the website 〈journals.cambridge.org/jps〉.
32 The post-election trending is modelled using three count variables that begin the month after each election.
33 Clarke, Harold and Lebo, Matthew, ‘Fractional (Co)integration and Governing Party Support in Britain’, British Journal of Political Science, 33 (2003), 283–301.
34 The impact of 9/11 is estimated using a dummy that equals one for the month of the event and the four months following. The impact of the second Iraq war is estimated by a variable that equals the cumulative number of British casualties in Iraq.
35 The Appendix, Note 5, in the Supplementary Materials on the website 〈journals.cambridge.org/jps〉, describes the transformation for this particular ECM. For further details, see Banerjee, Anindya, Dolado, Juan, Galbraith, John W. and Hendry, David F., Co-integration, Error-Correction, and the Econometric Analysis of Non-Stationary Data (Oxford: Oxford University Press, 1993); and Hendry, David F., Dynamic Econometrics (Oxford: Oxford University Press, 1995). For an example of the use of the dead-start autoregressive distributive-lag model in the British context, see David Sanders, ‘The Real Economy and the Perceived Economy in Popularity Functions: How Much Do Voters Need to Know? A Study of British Data, 1974–97’, Electoral Studies, 19 (2000), 275–294.
36 The ECMs were estimated in WinBUGS. See the Appendix, Note 6, in the Supplementary Materials on the website 〈journals.cambridge.org/jps〉 for further estimation details.
37 The direction of the effect is as we would expect for unemployment but a little peculiar for inflation.
38 Note that the largest one-month increase during this period is 0.2 percentage points.
39 Norpoth, Helmut, ‘Party Identification in West Germany: Tracing an Elusive Concept’, Comparative Political Studies, 11 (1978), 36–61.
40 Arzheimer, Kai, ‘ “Dead Men Walking?” Party Identification in Germany, 1977–2002’, Electoral Studies, 25 (2006), 791–807; and Zelle, Carsten, ‘A Third Face of Dealignment? An Update on Party Identification in Germany, 1971–94’, in Christopher Anderson and Carsten Zelle, eds, Stability and a Change in German Elections: How Electorates Merge, Converge, or Collide (London: Praeger, 1998), pp. 55–70.
41 The Appendix, Note 3, in the Supplementary Materials on the website 〈journals.cambridge.org/jps〉, provides a translation of these questions.
42 These complications include the fact that the New Federal States (former East Germany) are substantively different, both economically and politically, than the Old Federal States (Feld, Lars P. and Kirchgässner, Gebhard, ‘Official and Hidden Unemployment in the Popularity of the Government: An Econometric Analysis for the Kohl Government’, Electoral Studies, 19 (2000), 333–347.
43 See the Appendix, Note 2, in the Supplementary Materials on the website 〈journals.cambridge.org/jps〉, for the relevant figure.
44 The cycling is captured by including two terms in the regression: [Θ1(sin (λθ)] and [Θ2(cos (λθ)], where Θ1 and Θ2 are the parameters to be estimated and λ is the frequency (1/wavelength) of the popularity cycle, which is defined by the length of the inter-election period. Estimated parameters Θ1 and Θ2 can be used to calculate the phase for the inter-election cycle.
45 The correlation is also relatively large at the individual level, ranging in any given month from 0.6 to 0.7.
46 As before, the assumption of covariance stationarity requires that non-stationary dynamics be accounted for in the models. As it turns out though, once economic variables are included in the following models, the inter-election cycle is statistically insignificant. Therefore, for the sake of efficiency, the ECMs only include the trending term.
47 For a description of the economic data used in these models, see the Appendix, Note 4, in the Supplementary Materials on the website 〈journals.cambridge.org/jps〉.
48 Campbell, Converse, Miller and Stokes, The American Voter.
49 Miller, and Stokes, , ‘Constituency Influence in Congress’.
50 Page, Benjamin I. and Jones, Calvin C., ‘Reciprocal Effects of Policy Preferences, Party Loyalties, and the Vote’, American Political Science Review, 73 (1979), 1071–1089; Markus, Gregory B. and Converse, Philip E., ‘A Dynamic Simultaneous Equation Model of Electoral Choice’, American Political Science Review, 73 (1979), 1055–1070; Fiorina, Retrospective Voting in American National Elections.
51 Miller, Warren E., ‘Party Identification, Realignment, and Party Voting: Back to the Basics’, American Political Science Review, 85 (1991), 557–568; Bartels, Larry M., ‘Partisanship and Voting Behaviour, 1952–96’, American Journal of Political Science, 44 (2000), 35–50; and Bartels, Larry M., ‘The Impact of Electioneering in the United States’, in David Butler and Austin Ranney, eds, Electioneering: A Comparative Study of Continuity and Change (Oxford: Clarendon Press, 1992), pp. 244–277.
52 For arguments against the decline, see: Green, Donald and Palmquist, Bradley, ‘How Stable is Party Identification’, Political Behaviour, 43 (1994), 437–466; and Green, Donald and Palmquist, Bradley, ‘Of Artefacts and Partisan Instability’, American Journal of Political Science, 34 (1990), 872–902. For the arguments against the resurgence, see: Fiorina, Morris, ‘Parties and Partisanship: A 40-Year Retrospective’, Political Behaviour, 24 (2002), 93–115.
53 See Johnston, Richard, ‘Party Identification: Unmoved Mover or Sum of Preferences?’, Annual Review of Political Science, 9 (2006), 329–351. There is evidence that the strength of partisan attachment can be relatively volatile (Allsop, Dee and Weisberg, Herbert, ‘Measuring Change in Party Identification in an Election Campaign’, American Journal of Political Science, 32 (1988), 996–1017; and Brody, Richard A. and Rothenberg, Lawrence S., ‘The Instability of Partisanship: An Analysis of the 1980 Presidential Election’, British Journal of Political Science, 18 (1988), 445–465), but it is the stability of the individual level direction that is of relevance here.
54 Duverger, Maurice, Political Parties (New York: Wiley, 1964).
55 Johnston, Richard, Hagen, Michael G. and Hall Jamieson, Kathleen, The 2000 Presidential Election and the Foundations of Party Politics (Cambridge: Cambridge University Press, 2004).
56 Brody, Richard A., Assessing the President: The Media, Elite Opinion, and Public Opinion (Stanford, Calif.: Stanford University Press, 1991).
57 Data obtained from Polling Report Web Site: www.pollingreport.com/BushJob.htm.
58 Pickup and Johnston, ‘Campaign Trial Heats as Election Forecasts’; Erikson and Wlezien, ‘Presidential Polls As a Timeseries’; Converse, Philip E. and Traugott, Michael W., ‘Assessing the accuracy of polls and surveys’, Science, No. 234, 28 November 1986, pp. 1094–1098; and Lau, Richard R., ‘An Analysis of the Accuracy of “Trial Heat” Polls during the 1992 Presidential Election’, Public Opinion Quarterly, (58 (1994), 2–20.
59 Erikson, and Wlezien, , ‘Presidential Polls as a Timeseries’.
60 No constant is included in the model, so no month needs to be excluded as a reference.
61 As this is a fairly standard technique discussed at length elsewhere, the details of the estimation are relegated to the Appendix, Note 7, in the Supplementary Materials on the website 〈journals.cambridge.org/jps〉. For a more lengthy discussion on this technique, see Pickup and Johnston, ‘Campaign Trial Heats as Election Forecasts’.
62 For a description of the economic data, see the Appendix, Note 4, in the Supplementary Materials on the website 〈journals.cambridge.org/jps〉.
63 France: Lafay, J.-D., ‘Political Change and Stability of the Popularity Function: The French General Election of 1981’, in H. Eulau and M.S. Lewis-Beck, eds, Economic Conditions and Electoral Outcomes: The United States and Western Europe (New York: Agathon, 1985), pp.78–97; and Lafay, J.-D., ‘Political Dyarchy and Popularity Functions: Lessons from the 1986 French Experience’, in Norpoth, Lewis-Beck, and Lafay, eds, Economics and Politics, pp. 123–139. Latin America: Weyland, Kurt, ‘Peasants or Bankers in Venezuela? Presidential Popularity and Economic Reform Approval, 1989–1993’, Political Research Quarterly, 51 (1998), 341–362; and Davis, Charles L. and Langley, Ronald E., ‘Presidential Popularity in a Context of Economic Crisis and Political Change: The Case of Mexico’, Studies in Comparative International Development, 30 (1995), 24–48.
64 Edwards, George C. III, ‘Riding High in the Polls: George W. Bush and Public Opinion’, in Colin Campbell and Bert Rockman, eds, The George W. Bush Presidency: Appraisals and Prospects (Washington, D.C.: Congressional Quarterly Press, 2004), pp. 16–45; Edwards, George C. III, Presidential Influence in Congress (San Francisco: W. H. Freeman, 1980); and Brace, Paul and Hinckley, Barbara, Follow the Leader: Opinion Polls and the Modern Presidents (New York: Basic Books, 1992).
65 Nannestad, Peter and Paldam, Martin, ‘The VP-function: A Survey of the Literature on Vote and Popularity Functions after 25 Years’, Public Choice, 79 (1994), 213–245.
66 Such models use actual electoral outcomes as the dependent variable.
* Department of Politics, University of Oxford (email: email@example.com). The author is grateful to the University of Oxford, the Killam Trust and the University of Calgary for research support. An earlier version of this Research Note was presented to the 2006 Annual Meeting of the American Political Science Association, 2006. Thanks are due for astute comments and advice from Harold Clarke at the APSA session and on other occasions since, and to Christina Schneider and the anonymous reviewers for extremely helpful comments. An appendix is published as Supplementary Materials on the website 〈journals.cambridge.org/jps〉.
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