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² See Crewe, Ivor, ‘How to Win a Landslide Without Really Trying: Why the Conservatives Won in 1983’, in Ranney, Austin, ed., Britain at the Polls 1983 (Durham, NC: Duke University Press, 1985), 155–96Google Scholar; Clarke, Harold D., Stewart, Marianne C. and Zuk, Gary, ‘Politics, Economics and Party Popularity in Britain, 1979–83’, Electoral Studies, 6 (1987), 3–16Google Scholar; Norpoth, Helmut, ‘Guns and Butter and Government Popularity in Britain’, American Political Science Review, 81 (1987), 949–59CrossRefGoogle Scholar; Norpoth, Helmut, ‘The Falklands War and Government Popularity in Britain: Rally without Consequences or Surge without Decline’, Electoral Studies, 6 (1987), 3–16CrossRefGoogle Scholar; Mishler, William, Hoskin, Marilyn and Fitzgerald, Roy, ‘Hunting the Shark; or Searching for Evidence of the Widely Touted But Highly Elusive Resurgence of Public Support for Conservative Parties in Britain, Canada, and the United States’, in Cooper, Barry, Kornberg, Allan and Mishler, William, eds, The Resurgence of Conservatism in Anglo-American Democracies (Durham, NC: Duke University Press, 1988).Google Scholar

³ Sanders, et al. , ‘Government Popularity’, p. 312.Google Scholar

⁴ That is, twenty economic variables times thirteen different lags plus four expectation/perception variables and two event variables.

⁵ Cohen, Jacob and Cohen, Patricia, Applied Multiple Regression Correlation Analysis for the Behavioral Sciences (Hillsdale, NY: Lawrence Erlbaum Associates, 1975), p. 103.Google Scholar

⁶ See Whiteley, Paul F., ‘Inflation, Unemployment and Government Popularity – Dynamic Models for the United States, Britain and West Germany’, Electoral Studies, 3 (1984), 3–24CrossRefGoogle Scholar; Clarke, et al. , ‘Politics, Economics and Party Popularity in Britain’Google Scholar; Mishler, William, Hoskin, Marilyn and Fitzgerald, Roy, ‘British Parties in the Balance: A Time-Series Analysis of Long-Term Trends in Labour and Conservative Support’, British Journal of Political Science, 19 (1989), 211–36.CrossRefGoogle Scholar

⁷ According to the traditional ‘Michigan’ conception, party identification constitutes a stable attitudinal predisposition for most voters and therefore does not manifest significant short-term aggregate change. See Campbell, Angus et al. , The American Voter (New York: Wiley, 1960), p. 127Google Scholar. In the Box-Jenkins models estimated below, government popularity and the economic variables are differenced, so the fact that we are measuring short-term changes in these variables makes it legitimate to exclude party identification from these models. See Whiteley, , ‘Inflation and Unemployment’, pp. 10–11Google Scholar. Similarly, alternative ‘rational choice’ conceptions of party identification such as that proposed by Fiorina imply that voters' partisan predispositions may be omitted from models of party support if party performance evaluations are included in such models. See Fiorina, Morris, Retrospective Voting in American National Elections (New Haven, Conn.: Yale University Press, 1981).Google Scholar

⁸ See Mosley, Paul, ‘“Popularity Functions” and the Role of the Media: A Pilot Study of the Popular Press’, British Journal of Political Science, 14 (1984), 117–28CrossRefGoogle Scholar; Särlvik, Bo and Crewe, Ivor, Decade of Dealignment (Cambridge: Cambridge University Press, 1983), pp. 150–9.Google Scholar

⁹ See Jowell, Roger and Airey, Colin, British Social Altitudes: The 1984 Report (Aldershot, Hants: Gower, 1985), p. 174.Google Scholar

¹⁰ Whiteley, , ‘Inflation and Unemployment’, pp. 3–24Google Scholar; Fitzgerald, Roy and Mishler, William, ‘Through A Glass Darkly: The Dynamics of Public Economic Perceptions in Britain, 1978–87’ (paper presented at the Annual Meeting of the Southern Political Science Association, Atlanta, Georgia, 11 1988).Google Scholar

¹¹ Norpoth, , ‘Guns and Butter’, p. 956.Google Scholar

¹² See Hastings, Max and Jenkins, Simon, The Battle for the Falklands (New York: W. W. Norton, 1983), p. 136.Google Scholar

¹³ Sanders, et al. , ‘Government Popularity’, pp. 283–4, notes 9 and 10.Google Scholar

¹⁴ Micro-level analyses show that evaluations of party leader performance in Britain have independent effects on party support. See, e.g., Clarke, et al. , ‘Politics, Economics and Party Popularity’, pp. 133–5Google Scholar. The estimated effects of the Falklands war on evaluations of the Prime Minister's popularity appear in Norpoth, , ‘Guns and Butter’, p. 954Google Scholar; and Norpoth, , ‘The Falklands War’, p. 11.Google Scholar

¹⁵ See Norpoth, Helmut, ‘Guns and Butter’, p. 954; and ‘The Falklands War’, p. 11.Google Scholar

¹⁶ See, for example, Kinder, Donald R. and Kiewiet, D. Roderick, ‘Sociotropic Politics: The American Case’, British Journal of Political Science, 11 (1981), 129–61CrossRefGoogle Scholar; Kiewiet, D. Roderick, Macroeconomics and Micropolitics (Chicago: Chicago University Press, 1983)Google Scholar; Monroe, Kristen, Presidential Popularity and the Economy (New York: Praeger, 1984), Chap. 1.Google Scholar

¹⁷ Jenkins, Gwilym, Practical Experiences with Modelling and Forecasting Time Series (St. Helier, Jersey: G.J.P. Publications, 1979), p. 191.Google Scholar

¹⁸ See Klein, Lawrence R., An Introduction to Econometrics (Englewood Cliffs, NJ: Prentice-Hall, 1962), p. 101.Google Scholar

¹⁹ See Maddala, G. S., Econometrics (New York: McGraw-Hill, 1979), pp. 183–90.Google Scholar

²⁰ Clarke, Stewart and Zuk, for example, report that the Falklands war (modelled as an abruptpermanent effect) increased Conservative popularity by approximately 7 points net of controls for inflation, unemployment and several other predictor variables; see Clarke, et al. , ‘Politics, Economics and Party Popularity’, pp. 131–3Google Scholar. Dunleavy and Husbands estimate an abrupt-permanent effect of nearly 17 points; see Dunleavy, Patrick and Husbands, Christopher, British Democracy at the Crossroads (London: Allen and Unwin, 1985), p. 153.Google Scholar

²¹ Ostrom, Charles W. Jr, Time Series Analysis: Regression Techniques, Sage University Paper Series on Quantitative Applications in the Social Sciences (Beverly Hills, Calif.: Sage Publications, 1978), pp. 25–31.Google Scholar

²² See Box, George E. and Jenkins, Gwilym M., Time Series Analysis: Forecasting and Control, revd. edn. (San Francisco: Holden-Day, 1976)Google Scholar; Box, George E. and Tiao, Gregory C., ‘Intervention Analysis with Applications to Economic and Environmental Problems’, Journal of the American Statistical Association, 70 (1975), 70–9CrossRefGoogle Scholar. For an introduction to these methods see McCleary, Richard and Hay, Richard A., Applied Time Series Analysis (Beverly Hills, Calif.: Sage, 1980).Google Scholar

²³ The main diagnostic test is the Ljung-Box Q statistic, which measures whether or not there is any significant information in the model's residual autocorrelation function over a specified period of lags. See Ljung, Greta and Box, George E. P., ‘On a Measure of Lack of Fit in Time Series Models’, Biometrika, 64 (1978), 297–304.CrossRefGoogle Scholar

²⁴ The economic variables are the seasonally adjusted percentage unemployed, corrected for government changes in the series to ensure validity over time, and the retail price index, seasonally adjusted. Personal and general economic expectations are measured the same way as in SWM, i.e. the percentage thinking economic conditions will improve minus the percentage thinking they will deteriorate. However, the data are not exactly the same as those employed by SWM. SWM's economic expectations series was constructed by splicing together responses from two different Gallup series; for the sake of consistency we use one series for the entire period. The two series are very highly correlated (r = 0.93), and show the same trends of increasing voter optimism in the spring of 1982.

²⁵ Preliminary diagnostics indicated that the three economic variables needed to be logged and differenced to ensure variance and mean stationarity. Cross-correlation functions for the economic series showed that they did not suffer from multicollinearity. At the lags at which the variables were employed in the models the correlation (r) between inflation and unemployment was −0.14, whereas those for inflation and personal expectations, and unemployment and personal expectations were 0.05 and −0.01 respectively. Relatedly, the correlations of the estimates for the effects of the economic variables are quite modest (maximum values = 0.33).

²⁶ The calculation is:

See McCleary, and Hay, , Applied Time Series Analysis, p. 174.Google Scholar

²⁷ The assumption that macroeconomic variables influence political support according to a reward-punishment process is virtually ubiquitous in the popularity function literature. See e.g., Monroe, Presidential Popularity, Chaps 1 and 2. The possibility of alternative issue-priority effects in the British case is discussed in Clarke, et al. , ‘Politics, Economics and Party Popularity’, pp. 127–30Google Scholar and in Mishler, and Fitzgerald, , ‘British Parties in the Balance’.Google Scholar

²⁸ The calculation of the month-to-month effects of the gradual-permanent intervention model is as follows: first month = ω₀ second month = ω₀(1 + δ); third month = ω₀(1 + δ + δ.δ), and so on. The long-term or asymptotic change is: ω₀/(1 − δ). Again, because the dependent variable is measured in the log metric, the percentage change in the expected value of the series in a given month is computed by taking the anti-logs of the values produced by these calculations. The predicted percentage increase in the level of the series for a given month is the pre-intervention expected value (i.e., the mean Conservative popularity for the period July 1979 to April 1982 = 29.3 per cent) times the computed percentage change minus 29.3 per cent. See McCleary, and Hay, , Applied Time Series Analysis, p. 184.Google Scholar

²⁹ The calculation of the month-to-month effects of the gradual-temporary intervention model is: δ(n − 1)ω₀ + δ(n − 1)ω₁, where n is the number of months since the interventions occurred. Conversions of the computed statistics into percentage changes in the expected value of the series and the predicted increase in the level of the series for a given month follows the procedure outlined in fn. 26 and fn. 28.

³⁰ Norpoth, , ‘Guns and Butter’, p. 954Google Scholar. Similarly, analyses of satisfaction with the Prime Minister, Mrs Thatcher, which includes inflation, unemployment, personal expectations and the three Falklands models discussed above, all show that the war had strong effects. As in Norpoth's analyses, the adjustment parameter (δ) for the gradual-temporary model is very large (0.94), indicating that a substantial proportion of the war's impact on public evaluations of Mrs Thatcher's performance remained at the time of the 1983 election.

³¹ The war had a positive impact on personal (and general) economic perceptions with controls for inflation, unemployment, interest rates, real income, economic shocks of various kinds, election campaigns, and budget debates. See Fitzgerald, and Mishler, , ‘Through a Glass Darkly’.Google Scholar