Adding in an aggregate country variable (Model 5)(page 5/5)

In the next model (Model 5) we add an aggregate country level variable: centrLTU2002 -centred long term unemployment from the Eurostat New Cronos.

1. We do this by first clicking 'add term' in the equations window and choosing it.

   This model now has age as an explanatory variable from the micro data, long term unemployment from the macro data and the intercepts are allowed to vary from country to country.

   

   We notice that the coefficient of this term is negative: having controlled for age, the higher the level of long term unemployment the lower the voter turnout. We notice that this variable is not statistically significant at the usual 5% significance level, as twice its standard error is more than 0.082 but it has still lead to a 12% reduction in the estimated between country variance (0.260 compared with 0.302). When selected which variables for inclusion we take account of both of these factors, so a variable whose coeficient is not significant may still be included if it reduces the between groups variance. It is evident that many more variables may be needed at the country level to further reduce these variations. At present the relationship between age and chance of voting is assumed to be linear, so we might also want to explore the possibility of a quadratic (curved) relationship with age by adding (cent_age)² to the model.

2. Finally we introduce the interaction term between age and long term unemployment to the model and find that there is a significant coefficient for this term.

   It is negative (-0.002) and just significant - areas with higher long term unemployment (the product of the two variables) tend to have a slightly shallower relationship with age with respect to voter turnout.