July 2013
This little piece of code takes an FRS dataset and produces sample weights that makes the dataset (or a subset of it) match 2011 Census data for each local authority in England and Wales. So in principle you can treat the whole FRS sample as if it came from that Local Authority. The weight generator uses a technique described in Survey Reweighting for Tax Microsimulation Modelling by John Creedy.
It currently matches Census totals for:
- Gender;
- Age Group;
- Race
- Tenure Type;
- Number of Rooms;
- Employment Status;
- Occupation
- receipts various benefits
To make sure the routine finds a solution, the categories had to be aggregated somewhat (quite broad age groups and so on). The code can produce weights for the whole FRS, or for samples of it, for instance the LA's enclosing Government Region (reweighting all Londoners to look like Lewisham or Westminster.)
It works quite well still needs a lot of work. I still need to scale income and housing cost variables up - Westminster has higher average wages than Doncaster both because of because it has more bankers, and because Westminster bankers are paid more than Doncaster ones. Likewise for housing costs. But that looks doable. And the code is not at all well organised: I can see a much cleaner way of doing by dumping everything we want into a database and running queries to produce subsets. But this is a start.
The directories contain:
data/ - contains downloaded aggregate census data for Local Authorities, and these dumped as CSV files.
scripts/ - some code in Ruby that parses the CSV files into enumerated types and data declarations for use in the Ada code.
src/ Ada Source files (see below)
tests/ test driver code - at present, the only way to drive it is through the test code.
You need Tax Benefit Model Components, and the dependencies described in that for the Ada code. You'd need to follow the instructions there on creating raw FRS files - no chance, probably...
tests/ contains a AUnit V3 Test Suite, basically just a driver for the generator at the moment.