5.4  Working fewer hours (labour force participants)

5.4.1  Methods

For those people participating in the labour force, ill health may result in them being contracted to work fewer hours. This is likely to be the case for those who have been in poor health for longer. For those participating in the labour force at any point in the reference period a basic linear regression model was used to estimate the relationship between self-rated health and the total number of hours a respondent worked in the annual reference period while controlling for a set of other variables.

A linear regression model quantifies the relationship between the number of hours worked and self-rated health, while holding all other variables constant. A list of these control variables together with the results is given in Appendix F. Figure 5 shows the form of the equation. In this case, the coefficients indicate the additional number of hours that are worked as a result of having certain characteristics relative to the base category. The coefficients can be positive or negative. For example, the negative coefficient for poor health indicates how many fewer hours are worked owing to being in poor health relative to being in excellent health. Those regression coefficients for the self-rated health indicators (β) which were significant were then used to estimate the additional number of hours that may be worked by each person in the absence of ill health (that is, if they had excellent health). These hours were evaluated at the average hourly full-time rate. The formula can be found in Appendix D.[48][49]

One drawback of using a single equation linear regression model to estimate the relationship between health and the amount of hours worked is endogeneity. While giving an initial indication of the possible relationship between the total number of hours worked and health, the standard linear regression model does not account for endogeneity. Endogeneity occurs when the explanatory variables are not exogenous; true exogenous variables are not affected by the outcome variable or by other unobserved characteristics. This is likely to be a problem when trying to estimate the impact of health on hours worked. A fuller discussion of the reasons for this can be found in Holt (2010).

SoFIE is a longitudinal survey and therefore potentially allows more complex modelling techniques to be undertaken to try to account for endogeneity. This entails comparing changes in self-rated health to hours worked. However, the majority of people in SoFIE will not experience an acute health shock in the first three waves of the survey. When health shocks do occur and do not cause the respondent to leave the labour force, it may take time for this to feed through to total usual hours worked, possibly as respondents wait to see if their health improves or while changes in usual hours worked are negotiated with their employers. As a result the number of hours a person usually works in a given period is likely to be impacted, in the main, by their longer-term health.

Despite the availability of a limited number of waves of longitudinal data, the importance of the longer-term health level makes estimating the relationship between health and hours worked using panel models more difficult. Fixed effects panel models consider how changes in health are related to hours worked and there is no way of estimating the impact of the level of health. These models therefore do not provide a full picture. Random effects models do allow for an estimate of both health shocks and health level to be made; however, this requires assumptions to be made about the relationship between the unobserved variables that are correlated with self-rated health. If this assumption is not correct, or if correlation between the unobserved variables and health remains after this assumption has been made, the resulting model will be biased. As such the panel models do not completely meet the needs of this research. For these reasons a basic linear regression model, for which it is possible to obtain an estimate of the level of health, is used to estimate the relationships between health and the number of hours worked. When interpreting the results from the models it should be remembered that the impact estimates are likely to be upper bounds of the true impact as some of the relationship between hours and health status may be the result of other factors that it is not possible to control for in the analysis. Future analysis could attempt to incorporate panel models into the analysis to try to better understand the impact of health on participation.

As discussed in Holt (2010) there are issues with using self-rated health to measure health. One issue is that self-rated health is measured at the interview date and is compared with participation over the reference period. For some people the self-rated health state at the interview date will not be the same as the health state at different points in the reference period. Another limitation is that while self-rated health may be a more current and inclusive measure of health than variables such as the number of chronic diseases a person has been diagnosed with, it is more subjective and, as such, is open to potential bias. Further, self-rated health may not be entirely comparable between respondents. Some respondents may be consistently more optimistic in their health rating and others consistently more pessimistic. In addition the health base respondents use as a comparator when answering this question may change over time. For example, the SoFIE question on self-rated health does not ask respondents to rate their health relative to the health of other people of the same age. Some respondents may compare their health to that of others, but others may compare their current health to their past health. Given that this report focuses on those of working age, this ageing effect appears to be small. A further limitation of using self-rated health as a measure of health is that it is likely to include ill health as a result of injury. Despite these limitations this measure of health is used in this report in the absence of a viable alternative.