|Apr 24||Modding Day|
This data load contains 1 file, which is as follows:
|Hours.csv||Data on average weekly hours from ASHE||25,799,453|
These data come from the ASHE (Annual Survey for Hours and Earnings).
Two columns have the information needed to calculate the mean hours:
Aggregating involves summing these two columns appropriately and dividing the result of the first sum for the aggregate concerned (Total hours) by the second sum (Total employment).
The 'Hours.csv' file contains predictions for Average Weekly Hours for the 369 SOC 2010 Unit Groups based on ASHE data.
The first column is the year.
The second to sixth columns, from 'gender' to 'geography', are the characteristics of people covered by the dataset.
The penultimate column is 'Employment', the last column 'TotalHours' represents the total weekly number of hours for the category with the characteristics in columns two to six.
The estimates are based on published ASHE data but the detailed estimates are predictions based on a simple set of assumptions that differentiates across each of the main dimensions/characteristics. The results are constrained to match the published totals using an iterative RAS process.
There is no hours data available for the 'Armed Forces' occupations. There is, therefore, no employment data for 'Armed Forces' in 'Hours.csv'.
The rules of thumb used are:
This is the same as is done for any queries about Employment (including Replacement Demand calculations) and also for Pay.
In the case of Pay and Hours the API needs to use the employment weights included in the relevant 'ashe_pay_main.csv' or 'Hours.csv' file to do the checks, as in 1.and 2. above, but then to report the corresponding pay or hours values as appropriate.
In order to avoid false impressions of precision the API should round up the estimates before delivering the answer to any query. In the case of ASHE weekly hours any number should be rounded to the nearest hour.