Understanding Society User Support: Issueshttps://iserredex.essex.ac.uk/support/https://iserredex.essex.ac.uk/support/support/favicon.ico?15995719382022-08-05T10:14:30ZUnderstanding Society User Support
Redmine Understanding Society User Support - Support #1743 (Resolved): Averaging regional data to obtain ...https://iserredex.essex.ac.uk/support/issues/17432022-08-05T10:14:30ZCarolin Schmidtcs2100@cam.ac.uk
<p>Hi there,</p>
<p>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).</p>
<p>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?</p>
<p>I am unsure how to proceed and would appreciate any help.</p>
<p>Best wishes,<br />Carolin</p> Understanding Society User Support - Support #1558 (Resolved): Cross-sectional vs longitudinal we...https://iserredex.essex.ac.uk/support/issues/15582021-06-28T12:15:24ZCarolin Schmidtcs2100@cam.ac.uk
<p>Hello,</p>
<p>I am working with Understanding Society for the first time and have a few questions.</p>
<p>My coauthors and I are analysing immigrants’ age at immigration and their housing outcomes (own or rent). We’ll merge household data with individual (i.e. respondent) data so that we can use the person’s age at migration and other variables together with household data. My questions mainly refer to the weights that we should use.</p>
<p>Since we’re interested in an invariant variable (age at migration) we cannot use household fixed effects and would therefore run regressions in the pooled sample in our main regressions. We classify a household as an immigrant household if the respondent is an immigrant. If I’m not mistaken, that means that we should use cross-sectional (i.e. a_, b_, c_, …) household (i.e. hhden_) weights, is that correct? That is, I’ll have „a_hhden_“ for all cases in wave 1, „b_hhden_" in wave 2, etc. If we run robustness checks within age-at-migration subgroups, we can make use of the panel structure again. I suppose we should use the longitudinal weights then?</p>
<p>We are not only interested in immigrants from the five subgroups mentioned in Q4 of the FAQ help file, but also in immigrants from other countries. If, in the pooled sample, we first use data from wave 1 onwards and run additional checks using only data from wave 6 onwards, am I right that we’d have to use us_ weights (wave 1 onwards) and ui_ weights (wave 6 onwards), and that it would be wrong to use data from wave 1 onwards with us_weights and an „if wave >= 6" qualifier?</p>
<p>Thanks a lot in advance.</p>
<p>Best wishes,<br />Carolin</p>