Executive Popularity in France: The Promise and Pitfalls of Time Series Data Research and Methods Symposium, October 1 st 2004

The problems  The substantive problem: how do macroeconomic conditions affect support for the dual executive (president and prime minister) in France?  The methodological problem: What techniques are best suited to modeling time- series data? Do any of these models have a reliable predictive component (forecasting)

Some hypothetical data series

Stationary series Y(t) = α, where the estimated constant α is the sample mean

Linear trend Y(t) = α + β(t), where α is the intercept and β the slope of the trend line

“Random walk” Y(t) = Y(t-1) + α, where α is the mean of the first difference (i.e. average change from one period to the next)

France: Executive Popularity

France: the dual executive  In de Gaulle’s formulation, the president has responsibility for ‘high politics’, while the prime minister is responsible for ‘day to day affairs’  The president is directly elected (since 1965), for a five year term (since 2002, seven years previously)  The president appoints the prime minister, who is ‘responsible’ to parliament  The president has no constitutional authority to fire the prime minister, but has acquired the de facto capacity to do this  The president may dismiss the national assembly and call for new elections (no more than once a year)  The possibility exists that the president and prime minister may be drawn from different ideological camps (cohabitation)  Cohabitation has occurred three times: (Mitterrand/Chirac), (Mitterrand/Balladur), and (Chirac/Jospin).

Executive popularity in France Lewis-Beck (1980) finds that Prime Ministers suffer a greater decline in popularity than Presidents due to negative effects of inflation and unemployment Hibbs (1981) finds negative effects of unemployment on presidential approval (but positive effect of inflation!) Appleton (1986) finds negative relationship between unemployment and both presidential and prime ministerial approval, but no inflation effect Anderson (1995) suggests that the relationship is more complex, and depends upon the ideological placement of the prime minister vis a vis the president Lecaillon (1980) finds no impact of macroeconomic variables on executive popularity Anonymous (2004) finds that: presidential approval linked to unemployment, prime ministerial approval suffers from higher inflation, and that presidential popularity rises during cohabitation

Executive Popularity Indicators in France IFOP (Since 1958, aperiodic until 1968, then monthly): “Are you satisfied with [name] as [President, Prime Minister] of France?” June 2004: Chirac 45% Raffarin 32% SOFRES (Since 1978): “How reliable do you think [name] is in dealing with France’s current problems?” ( ): “How effective do you think [name] is in dealing with France’s current problems?” June 2004Chirac 35% Raffarin 28% Also BULL-BVA series ( ’s)

Presidential Popularity in France, Source: SOFRES Mitterrand Chirac Giscard d’Estaing

Prime Ministerial Popularity in France, Source: SOFRES 1.Barre 2.Mauroy 3.Fabius 4.Chirac 5.Rocard 6.Cresson 7.Bérégovoy 8.Balladur 9.Juppé 10.Jospin 11.Raffarin

Executive Popularity in France, Source: SOFRES

Executive Popularity in France – Giscard d’Estaing Source: SOFRES

Executive Popularity in France – Mitterrand Source: SOFRES Chirac Balladur

Executive Popularity in France – Chirac Source: SOFRES Jospin

Relating executive popularity to macroeconomic conditions

Inflation and Unemployment in France, Source: INSEE Giscard Mitterrand Chirac

Bivariate correlations of presidential and prime ministerial popularity, inflation, and unemployment

Simple OLS predicting presidential popularity

Extended OLS predicting presidential popularity

Extended OLS predicting presidential popularity with lagged dependent variable as predictor

Alternative extended OLS predicting presidential popularity with lagged dependent variable as predictor

Extended OLS predicting prime ministerial popularity with lagged dependent variable as predictor

Alternative extended OLS predicting prime ministerial popularity with lagged dependent variable as predictor

Predicted versus actual values from extended OLS model of presidential popularity

Predicted versus actual values from extended OLS model of presidential popularity (Giscard)

Predicted versus actual values from extended OLS model of presidential popularity (Mitterrand)

Predicted versus actual values from extended OLS model of presidential popularity (Chirac)

Moving from OLS to ARIMA

The autoregressive integrated moving average model (ARIMA) The model incorporates:  The autoregressive term p, which is the order of the autoregressive component  The number of differences d, which is used to discount trends over time  The moving average term q, which is the moving average of the prediction error To fit the model, we need to examine the autocorrelation and the partial autocorrelation functions (ACF and PACF)

Differenced series for presidential popularity,

Differenced series for prime ministerial popularity,

ACF and PACF plots for presidential popularity

ACF and PACF plots for presidential popularity (1 difference)

ARIMA (1,0,1) model predicting presidential popularity Number of residuals 279 Standard error Log likelihood AIC SBC Analysis of Variance: DF Adj. Sum of Squares Residual Variance Residuals Variable B SEBT-RATIO APPROX. PROB. AR MA MITTERRA CHIRAC INFLAT UNEMPLOY PM YES Time in Office Cohabitation CONSTANT

Alternative ARIMA (1,0,1) model predicting presidential popularity Number of residuals 273 Standard error Log likelihood AIC SBC Analysis of Variance: DF Adj. Sum of Squares Residual Variance Residuals Variables in the Model: B SEB T-RATIO APPROX. PROB. AR MA MITTERRA CHIRAC TIO COHAB POSTELEC PMYES UNEMPL_ INFLAT_ CONSTANT

Predicted versus actual values of presidential popularity from ARIMA model

ARIMA versus OLS predicted values

Predicted versus actual values of presidential popularity from ARIMA and OLS models (Giscard)

Predicted versus actual values of presidential popularity from ARIMA and OLS models (Mitterrand)

Predicted versus actual values of presidential popularity from ARIMA and OLS models (Chirac)

ARIMA and OLS predicted versus actual values, 1980

ARIMA and OLS predicted versus actual values, 1999

Correlation matrix of predicted values with actual value of presidential popularity

Why choose ARIMA? Linear forecast

Random walk forecast

ARIMA forecast

Pitfalls of ARIMA  Complexities of model specification  Difficulties of interpretation  Sensitivity of data (e.g. missing values)