Frequency and duration of enumeration
The frequency with which data is collected typically involves a trade-off between survey goals and available resources. All other things being equal, more frequent collection of data will improve the timeliness of estimates available to analysts and policy-makers, and will make it easier to discern trends in the data over time. More frequent enumeration, however, is more costly both in terms of the resources involved in conducting the data collection and in terms of the burden placed upon respondents. It is therefore important that decisions around the frequency of data collection are made with a clear view to the relationship between the timeliness and frequency of the data produced and the goals of the data collection exercise.
It is not possible to provide specific guidelines for how frequently measures of subjective well-being should be collected covering every contingency, since the range of possible data uses is large and the frequency at which data are needed will vary depending on the intended use and on the type of measure in question. However, some general advice can be provided. Aggregate measures of subjective well-being generally tend to change only slowly over time. This reflects the relatively slow movements in most of the social outcomes that affect subjective well-being and the fact that many changes only impact on a small proportion of the population. For example, unemployment - which is associated with a change of between 0.7 and 1 on a 0 to 10 scale (Winkelmann and Winkelmann, 1998; Lucas et al., 2004) - typically affects between three and 10% of the adult population. Thus, even a large shift in the unemployment rate - say, an increase of 5 percentage points - will translate only into a small change in measures of subjective well-being (Deaton, 2011).
The relatively slow rate of change in measures of subjective well-being might appear to suggest that such measures do not need to be collected frequently. However, the small absolute size of changes in subjective well-being also means that standard errors tend to be large relative to observed changes. A number of observations are therefore needed to distinguish between a trend over time and noise in the data. Box 3.1 illustrates this point. For this reason, despite (or indeed, because of) the relatively slow rate of change in subjective well-being data, it is desirable that measures are collected on a regular and timely basis. For the most important measure used in monitoring well-being, an annual time series should be regarded as the essential minimum in terms of frequency of enumeration. More frequent monthly or weekly data is, however, likely to be of lower value (Deaton, 2011). (It should be pointed out that frequent, or rolling sample, surveys increase the possibilities for identifying the causal impacts of other factors whose dates can be identified. It was only the daily frequency of observations that made it so easy to discover and eliminate the question-order effects in Deaton (2011).