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Support #1743

Averaging regional data to obtain control variables for individuals

Added by Carolin Schmidt over 1 year ago. Updated 4 months ago.

Status:
Resolved
Priority:
Normal
Category:
Weights
Start date:
08/05/2022
% Done:

100%


Description

Hi there,

I am using wave 6 to study household heads' homeownership probabilities. I am looking at native Brits and immigrants (I came up with an immigrant dummy for every household head).

I would now like to generate a control variable for each of my household heads: the variable should reflect the proportion of immigrants in the UK region where the person resides (that is, every household head in e.g London will have the same immigrant share attached, etc.). I am wondering how I should calculate that average: does it have to be weighted (i.e. egen immishare = wtmean(immigrant), weight(indscui_xw) by(region) using the gwtmean package which calculates weighted statistics)? I would think so, because without weighting it, I would have an average immigrant share based on the (not-per-se representative) raw data. However, if I calculate a weighted mean, then I would effectively double-weight the data because the regression itself would be weighted too, no?

I am unsure how to proceed and would appreciate any help.

Best wishes,
Carolin

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