Pooling Time Series Based on Slightly Different Questions About the Same Topic Forty Years of Survey Research on Happiness and Life Satisfaction in The Netherlands

Survey research on subjective wellbeing in The Netherlands started in the early 1970s. The time series happiness and life satisfaction that have emerged since then are unfortunately based on slightly different survey items of which one part uses verbal response scales and another part uses numerical response scales. The diversity of the survey items and a number of other measurement issues, such as the effects of changes in survey mode, hamper comparison over time and make it difficult to establish whether life became any better over the last forty years. These problems can be tackled using the recently developed Reference Distribution Method with which responses to equivalent but not identical survey questions can be pooled to obtain long, consistent time series. We applied the Reference Distribution method to pool time series of happiness and life satisfaction. We conclude that in the past 40 years the Dutch have become slightly happier and satisfied with their lives

Conversion of Verbal Response Scales: Robustness Across Demographic Categories

Happiness and life satisfaction have traditionally been measured using verbal response scales, however, these verbal scales have not kept up with the present trend to use numerical response scales. A switch from a verbal scale to a numerical scale, however, causes a severe problem for trend analyses, due to the incomparability of the old and new measurements. The Reference Distribution Method is a method that has been developed recently to deal with this comparison problem. In this method use is made of a reference distribution based on responses to a numerical scale which is used to decide at which point verbally labelled response options transit from one state to another, for example from ‘happy’ to ‘very happy’. Next, for each wave of the time series in which the verbal scale is used, a population mean is estimated for the beta distribution that fits best to these transition points and the responses in this wave. These estimates are on a level that is comparable to that of the mean of the reference distribution and are appropriate for use in an extended time series based on the responses measured using a verbal and a numerical scale. In this paper we address the question of whether the transition points derived for the general population can be used for demographic categories to produce reliable, extended time series to monitor differences in trends among these categories. We conclude that this is possible and that it is not necessary to derive transition points for each demographic category separately