Update Date: September - 2022
The following charts show the baseline total population numbers, with disability or without a disability (in thousands) for: the whole population, the civilian labor force and employed individuals. The chart on the left refers to ages 16 and above, while the chart on the right, to ages 16 to 64. These plots allow us to have a sense of the absolute magnitude of the effects that we are going to analyse in this study.
The following charts show the baseline population numbers with disability (in thousands) for: the whole population, the civilian labor force and employed individuals. The chart on the left refers to ages 16 and above, while the chart on the right, to ages 16 to 64. These plots allow us to have a sense of the absolute magnitude of the effects that we are going to analyse in this study.
A quick inspection of the charts bellow brings out an observation that disabilities shot up from around mid-2021. In this study, we delve into a detailed analysis of the effect and venture some possible explanations. To do so, we measure the changes in disabilities as a percentage of the respective population cohorts.
This section investigates trends in disabilities in the whole population, of which some are in the civilian labor force and others are out.
The civilian labor force corresponds to the population that is actively engaged in the labor market. This population is healthier than the general population, with a lower disability rate.
The employed population correspond to the civilian labor force that is currently employed. This population tends to be slightly healthier than the civilian labor force, with a lower disability rate.
This section analyses the statistical significance of the change in the rate of disability over time. For that purpose we compute the year-on-year (YoY) changes (in percentage) in the disability rate from 2008 to 2022 for the Civilian Labor Force aged 16 to 64 (both sexes). By using yearly changes, we can measure the typical yearly volatility of changes in disability rates, while removing any seasonal patterns that might occur. We then normalise yearly changes in the disability rate by the standard deviation of the changes from 2008, which allows us to estimate how many standard deviations does the yearly change correspond to (lower chart).
When using year-on-year (YoY) changes (in percentage) in the disability rate, we have a tool to estimate significant changes in behaviour of a given time series, but it does not give the full picture as cumulative trends that are longer than a year can be overlooked. Therefore, in this section we analyse changes in disabilities relative its linear trend spanning from 2008 to 2019 (the pre Covid-19 pandemic period). To normalise the changes in disabilities in 2020 onwards relative to the baseline trend, we use as a volatility metric, the standard deviation of the deviation from trend for the period 2008 to 2019.