By A. Rice, Jones
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Extra resources for Applied Health Economics: Jones (Routledge Advanced Texts in Economics and Finance)
The modal category is good health, and a clear majority of respondents report either excellent or good health. The distribution is skewed, rather than symmetric, with a long right-hand tail of individuals who report fair, poor or very poor health. Comparing the distribution over time there is a decrease in the proportion reporting excellent health and an increase in those reporting fair or worse health. The next step is to present the distribution of SAH by age group. To do this a new variable (healthtab) is created that divides individuals into ten-year age groups.
Log”, replace As this is a panel dataset it is useful to specify new variables that contain the individual (i) and time (t) indices. These can be used to sort the data prior to analysis: • iis pid • tis wavenum • sort pid wavenum Describing the dynamics of health 13 The BHPS includes missing data owing to both unit and item non-response, so not all individuals in our dataset are observed at every wave. As described above, this gives two options for the analysis: using the unbalanced panel, that includes all available observations, or the balanced panel, that restricts the sample to those individuals who have a complete set of data for all of the waves.
A formal test for normality (sktest) is applied to HUI, using the survey weights provided. 000 Variants of the glcurve command can be used to produce generalized Lorenz, Lorenz, generalized concentration curves, and concentration curves for HUI. The latter use log(income) as the ranking variable, rather than ranking by HUI itself (sortvar (lincome)): • glcurve hui [aweight=nmweight] • glcurve hui [aweight=nmweight], lorenz • glcurve hui [aweight=nmweight], sortvar (lincome) • glcurve hui [aweight=nmweight], sortvar (lincome) lorenz The command can also be used to assess Lorenz dominance, illustrated here by splitting the sample according to gender and income quintiles.