Understanding Society User Support: Issueshttps://iserredex.essex.ac.uk/support/https://iserredex.essex.ac.uk/support/support/favicon.ico?15995719382024-03-26T16:09:20ZUnderstanding Society User Support
Redmine Support #2077 (Feedback): Using income variables https://iserredex.essex.ac.uk/support/issues/20772024-03-26T16:09:20ZMhairi Webster
<p>Hello,</p>
<p>I am looking to access the data to use the derived income variables (w_fimnnet_dv). Could you let me know under what access it is under on the UK Data Service as those variables don't appear to be available in the dataset I am using (Understanding Society: Waves 1-8, 2009-2017 and Harmonised <br />BHPS: Waves 1-18, 1991-2009. 11th Edition. UK Data Service. SN: 6614, <a class="external" href="http://doi.org/10.5255/UKDA-SN6614-12">http://doi.org/10.5255/UKDA-SN6614-12</a>).</p>
<p>Many thanks, <br />Mhairi Webster</p> Support #2033 (Resolved): Derived variable on income / earnings of each benefit unithttps://iserredex.essex.ac.uk/support/issues/20332024-01-18T20:03:04ZThomas Stephenst.c.stephens@lse.ac.uk
<p>Hi,</p>
<p>I notice that Understanding Society has a useful derived variable which splits households by their benefit unit (buno_dv); <a class="external" href="https://www.understandingsociety.ac.uk/documentation/mainstage/variables/buno_dv/">https://www.understandingsociety.ac.uk/documentation/mainstage/variables/buno_dv/</a>. This appears to be aligned to how the DWP and Family Resources Survey define a benefit unit.</p>
<p>Is there a derived variable on income strictly for those in each benefit unit? This would ideally include several additional variables, distinguishing between income from all sources, earnings, investments, benefit income, pension, e.t.c. I am aware of household income derived variables and individual income derived variables, and have used them in my other analysis,, but I can't seem to see a set of the same derived variables for the benefit unit. Perhaps this exists and I have missed it.</p>
<p>If it hasn't been created, any advice / code on how it has been constructed in other cases would be very welcome of course.</p>
<p>Thanks in anticipation and let me know if any questions or ambiguities.</p>
<p>Best wishes,</p>
<p>Tom</p> Support #1992 (Resolved): household income https://iserredex.essex.ac.uk/support/issues/19922023-11-08T08:27:14ZAelen Valen
<p>Hello,</p>
<p>I'm using Understanding Society together with Eu SILC and I was wondering whether w_fihhmnnet1_dv+ (*12 months) corresponds to the total disposable income in EUSILC (HY020) which is derived as follows:</p>
<p>Total disposable household income (HY020) can be computed as:<br />- the sum for all household members of gross personal income components<br /> <del>gross employee cash or near cash income (PY010G),<br /> - company car (PY021G),<br /> - gross cash benefits or losses from self-employment (including royalties) (PY050G),<br /> - pensions received from individual private plans (other than those covered under ESSPROS) (PY080G),<br /> - unemployment benefits (PY090G),<br /> - old-age benefits (PY100G),<br /> - survivor' benefits (PY110G),<br /> - sickness benefits (PY120G),<br /> - disability benefits (PY130G),<br /> - education-related allowances (PY140G);<br /></del> plus gross income components at household level<br /> - income from rental of a property or land (HY040G),<br /> - family/children related allowances (HY050G),<br /> - social exclusion not elsewhere classified (HY060G),<br /> - housing allowances (HY070G),<br /> - regular inter-household cash transfers received (HY080G),<br /> - interests, dividends, profit from capital investments in unincorporated business (HY090G),<br /> - income received by people aged under 16 (HY110G));<br />- minus<br /> - regular taxes on wealth (HY120G),<br /> - regular inter-household cash transfer paid (HY130G),<br /> - tax on income and social insurance contributions (HY140G).</p>
<p>Many thanks for the support!!!</p> Support #1979 (Resolved): Using UKHLS for financial year poverty rateshttps://iserredex.essex.ac.uk/support/issues/19792023-10-02T16:40:42ZSam Tims
<p>Dear USOC team,</p>
<p>I am working on a project exploring the prevalence of mental health for people living in in-work poverty and have some questions on poverty rates and weighting that I hope you can help with. My analysis only uses UKHLS wave 3 onwards. My questions are below.</p>
<p>Thank you in advance,<br />Sam</p>
<p>1. For this analysis I am interested in financial years rather than waves. In constructing my financial years I have followed the process set out in the user guide and in this forum (months 4 to 15 from wave n, months 16 to 24 from wave n-1 and months 1-3 from wave n+1). I am aware that I need to adjust my cross-sectional weights to account for attrition in a similar manner as is set out in box 1 of the weighting FAQ. I note that box 1 includes <code>sum ind [aw=b_indpxub_xw] if b_month>=1 & b_month<=12</code> but this old issue (<a class="external" href="https://iserredex.essex.ac.uk/support/issues/1221">https://iserredex.essex.ac.uk/support/issues/1221</a>) implies the line should end with 24 instead of 12. Could I clarify which is correct?</p>
<p>2. As I am combining three waves in each financial year, I'm currently adjusting to the average weighted total of the three waves which I have seen suggested elsewhere in this forum. Previously I was adjusting by a factor such as <code>wave_1_total / wave_2_total</code> but switched to this method because of slight increases in sample size in some waves. Can I confirm this is an appropriate method for the adjustment? Please note that I have assumed the answer to question 1 is 24, and therefore I am accounting for the entire wave weight, rather than just the specific months I am combining:</p>
<p><code>gen count = 1<br />summarize count [aw = `wave_1'_hh_weight]<br />local `wave_1'_total = r(sum)<br />...<br />local avg = (``wave_1'_total' + ``wave_2'_total' + ``wave_3'_total') / 3<br />gen weight = weight * (`avg' / ``wave_1'_total') if `wave'_month >= 16 & `wave'_month <= 24<br />replace weight = weight * (`avg' / ``wave_2'_total') if `wave'_month >= 4 & `wave'_month <= 15<br />replace weight = weight * (`avg' / ``wave_3'_total') if `wave'_month >= 1 & `wave'_month <= 3</code></p>
<p>3. For part of my analysis I am comparing poverty rates between this data and the FRS, which I expect to be similar but not identical. This is in part because of methodological differences and also because I do not have access to the Council Tax data in Understanding Society so my results will not be perfect. To generate my poverty rates I have followed worksheet 4 in the into to USOC using STATA. However my poverty rates from USOC are quite a bit below the FRS and also below figure 10 here (<a class="external" href="https://www.understandingsociety.ac.uk/sites/default/files/downloads/working-papers/2019-08.pdf">https://www.understandingsociety.ac.uk/sites/default/files/downloads/working-papers/2019-08.pdf</a>). Have other users reported a similar issue? I'd be happy to share my code if useful.</p>
<p>Fin_Year FRS US<br />2012/13 15.4% 12.9%<br />2013/14 15.2% 13.0%<br />2014/15 15.9% 13.1%<br />2015/16 16.3% 12.6%<br />2016/17 16.2% 12.5%<br />2017/18 17.1% 13.0%<br />2018/19 16.7% 13.7%<br />2019/20 17.8% 14.0%</p>
<p>4. Finally is there a single variable to flag if anyone in a household is in receipt of income-related benefits? I haven't spotted such a flag so have constructed my own but it would be good to make sure I haven't missed anything.</p> Support #1860 (Resolved): household income special licence variables https://iserredex.essex.ac.uk/support/issues/18602023-02-20T14:45:27ZSam Khavandi
<p>Hi,</p>
<p>Hoping to get some clarity on one of the UKHLS variables and get an idea what it adds. We will be using UKHLS data to look at fuel poverty and mental health.</p>
<p>Looking to use household income as one of the variables and I have noticed there are household income variables that require special licence (variable names below). These seem to be adjusted for benefits? Wasn't sure how much more these add and whether we should apply for the special licence just for access of these.</p>
<p>fihhmnnet3_dv <br />fihhmnnet4_dv</p> Support #1746 (Resolved): reconciling household income between the main survey & covid-19 surveyhttps://iserredex.essex.ac.uk/support/issues/17462022-08-10T13:10:22ZKaren Arulsamy
<p>Hi there,</p>
<p>Can I please get some advice on how to accurately compare household income in the main survey vs. the covid-19 survey?</p>
<p>As I understand, household income is collected differently in the main survey vs. the covid-19 survey. As household income is reported based on different periods in the covid-19 survey, I've first accounted for these periods to obtain a monthly value as follows:</p>
<p>gen covid_hhincome = .<br />replace covid_hhincome = hhincome_amount if hhincome_period 3<br />replace covid_hhincome = hhincome_amount*4 if hhincome_period 1<br />replace covid_hhincome = hhincome_amount*2 if hhincome_period 2<br />replace covid_hhincome = hhincome_amount/12 if hhincome_period 4<br />replace covid_hhincome = hhincome_amount*4 if hhincome_period 5<br />replace covid_hhincome = . if hhincome_amount -9 | hhincome_amount -8 | hhincome_amount -7 | hhincome_amount -2 | hhincome_amount -1</p>
<p>I then use fihhmnnet1_dv from the main survey combined with the above variable to form a total household income variable. Am I using the right income variable from the main survey?</p>
<p>Many thanks<br />Karen</p> Support #1708 (Resolved): Usual and last pay - question on imputation and missing valueshttps://iserredex.essex.ac.uk/support/issues/17082022-05-30T14:33:38ZRebeka Balogh
<p>Hi there,</p>
<p>I'm constructing indicators relating to an individual's current employment in wave 8. My sub-sample consists of employees aged 25 to 60 who reported good self-rated health and no psychological distress in the previous wave. <br />The two indicators in question are<br />1. the relative pay level (using net labour income fimnlabnet_dv), and<br />2. pay volatility (whether there's a discrepancy between usual net pay in current (main) job (paynu_dv) and last net pay in current (main) job (payn_dv).</p>
<p>While the ratio of missing observations for relative pay level are low, that's not the case for pay volatility. The reason for that being that while fimnlabnet_dv (and one of its components, paynu_dv) is imputed, payn_dv isn't. Beyond the number of missing cases, I'm more concerned that pay volatility won't be missing at random as certain respondents might be more likely to refuse to answer questions on their pay (usual net pay and overall net labour income will be imputed for them but lay pay won't be). Could you confirm this? With your experience on the income variables, do you think it's safer to drop the indicator on pay volatility altogether? For the analysis I'm doing, it'd ideal if the assumption of missing at random could hold. I've read the UKHLS income data guidance but couldn't find information on non-response to income questions.<br />Thanks very much</p> Support #1668 (Resolved): Net household income including housing benefit adjustmenthttps://iserredex.essex.ac.uk/support/issues/16682022-03-15T14:55:57ZRebecca Benson
<p>I am trying to get a measure of net household income.</p>
<p>I understand that when housing benefit is implied by differences between net and gross rent, but unreported as a source of income for any household members, it is necessary to use w_hbadjust_dv to include housing benefit income. I further understand that the variable w_fihhmngrs1_dv already adds this for gross income.</p>
<p>To get the equivalent net figure, the obvious solution is to add w_hbadjust_dv and w_figgmnnet1_dv. But this would not take into account any taxes related to the HB amount. Is there another recommended approach?</p> Support #1619 (Resolved): Differentiating between income-based benefits and contribution-based / ...https://iserredex.essex.ac.uk/support/issues/16192021-12-09T10:34:40ZLucas Auer
<p>Dear Support Team,<br />In my current research project, I am focussing on benefit recipients. More specifically, I would like to compare different claimant types of Jobseeker's Allowance or Employment and Support Allowance, depending on whether they claim the <em>income-based</em> version of these benefits or the <em>contribution-based</em> / "new-style" version. Is there any way to tell the two claimant types apart in the data? I came across a previous ticket (<a class="issue tracker-3 status-3 priority-4 priority-default" title="Support: Is it possible to identify contributory and income-based JSA (Resolved)" href="https://iserredex.essex.ac.uk/support/issues/1187">#1187</a>) that seems related. Unfortunately, I found myself unable to differentiate between income-based and contribution-based claims using the suggested solution. The reason being, that in the income.dta files, I could identify only one value of fi_code relating to each benefit. For my purposes, however, I would expect to require two values each, or, alternatively an additional binary variable depicting whether or not a given claim was contribution-based (income-based). Any more pointers would be greatly appreciated!<br />Many thanks,<br />Lucas</p> Support #1565 (Resolved): Income Variable: Drop negative values?https://iserredex.essex.ac.uk/support/issues/15652021-07-20T13:08:16ZIpsitaa Khullar
<p>Hi,</p>
<p>I am using the fimngrs_dv variable from indresp files. Some of the reported values are negative, for example, I see a minimum value of -17,741.34. Surely I cannot take it as a correct value of monthly income for the individual? Is it common practice to only keep positive values of monthly income data?</p>
<p>Many thanks for your help!</p> Support #1541 (Resolved): Benefit income in indresp and income file: what accounts for the differ...https://iserredex.essex.ac.uk/support/issues/15412021-05-10T07:36:53ZGabriele Mari
<p>Hi,</p>
<p>I am using Understanding Society Waves 1 to 10. I am interested in income from state benefits. Using the income file and this Stata code:</p>
<p>drop if ficode==2|ficode==3|ficode==4|ficode==17|ficode>=24 & ficode<=29|ficode==35|ficode==38</p>
<p>collapse (sum) frmnthimp_dv if frjtkeep_dv==1, by(pidp wave)</p>
<p>I can reproduce the variable fimnsben_dv in indresp. The sum of frmnthimp_dv is equal to fimnsben_dv in indresp, at least for the person-wave observations that are present in both datasets. Yet, many observations in indresp have no match in the income file. For the vast majority of them fimnsben_dv is set to 0, but for 10,412 fimnsben_dv has a positive value but no corresponding record for that person from the income file. I was wondering how these positive values were computed. Specifically, how can I recover the income receipt <em>for each benefit</em> that was then used to compute fimnsben_dv for these person-wave records? I suspect these values are imputed from household members that declare joint receipt, but so far I’ve been unable to reproduce the numbers.</p>
<p>Also, am I correct in assuming that benefit amounts when receipt is joint are always divided by 2, in both the income file and in indresp?</p>
<p>Thanks in advance!<br />Gabriele</p> Support #1476 (Resolved): Calculating Equivalised Income Deciles AHChttps://iserredex.essex.ac.uk/support/issues/14762021-01-06T13:28:57ZHenry Parkesh.parkes@ippr.org
<p>Dear USOC User Team, <br />I've written some code which seeks to work out people's equivalised household income decile after housing costs, and am then looking at the tenure amongst the deciles.</p>
<p>In my analysis - around 60% of the top decile seem to own their property own outright - compared to just 38% in HBAI (using Stat Xplore) - I know they won't perfectly align but this feels like quite a big difference. This has made me doubt my approach to assigning deciles</p>
<p>Please see the code below in STATA, doing the calculations to work out the HH decile (adapting from the code in the USOC moodle tutorial), which I then match on to indresp using the household identifier.</p>
<p>use "E:\ippr\datasets\UKHLS\stata13_se\ukhls_w10/j_hhresp.dta", clear</p>
<p>//Create equivalisation factors for after housing costs: 0.58 for first adult and 0.42 for subsequent adults. 0.4 for children 14+ and 0.2 for children <14<br />gen j_adults = j_npensioner + j_nwage_dv<br />gen j_14pluschildren = j_nkids_dv - j_nchoecd_dv</p>
<p>//j_adults: number of adults. j_14pluschildren: number of children 14+. j_nchoecd_dv: number of children 0-13</p>
<p>gen j_ahc_equivalisation = 0.58 + ((j_adults - 1)*0.42) + (0.4 * j_14pluschildren) + (0.2 * j_nchoecd_dv) <br />replace j_ahc_equivalisation = . if j_adults == 0 //Get rid of cases where household contains no adults...</p>
<p>//Generate equivalised household income variables<br />gen j_ehhnetinc1_ahc = (j_fihhmnnet1_dv - j_houscost1_dv)/j_ahc_equivalisation <br />lab var j_ehhnetinc1_ahc "equivalised net HH income after housing costs"</p>
<p>rename j_nchoecd_dv j_under14<br />rename j_14pluschildren j_over14</p>
<p>//Create equivalised income decile variables: <br />_pctile j_ehhnetinc1_ahc [aw = j_hhdenub_xw], nquantiles(100)<br />return list</p>
<p>global j_p10 = r(r10)<br />global j_p20 = r(r20)<br />global j_p30 = r(r30)<br />global j_p40 = r(r40)<br />global j_p50 = r(r50)<br />global j_p60 = r(r60)<br />global j_p70 = r(r70)<br />global j_p80 = r(r80)<br />global j_p90 = r(r90)</p>
<p>gen j_decile = .<br />replace j_decile = 1 if j_ehhnetinc1_ahc < j_p10 & j_ehhnetinc1_ahc<. <br />replace j_decile = 2 if j_ehhnetinc1_ahc >= j_p10 & j_ehhnetinc1_ahc < j_p20 & j_ehhnetinc1_ahc<. <br />replace j_decile = 3 if j_ehhnetinc1_ahc >= j_p20 & j_ehhnetinc1_ahc < j_p30 & j_ehhnetinc1_ahc<. <br />replace j_decile = 4 if j_ehhnetinc1_ahc >= j_p30 & j_ehhnetinc1_ahc < j_p40 & j_ehhnetinc1_ahc<. <br />replace j_decile = 5 if j_ehhnetinc1_ahc >= j_p40 & j_ehhnetinc1_ahc < j_p50 & j_ehhnetinc1_ahc<. <br />replace j_decile = 6 if j_ehhnetinc1_ahc >= j_p50 & j_ehhnetinc1_ahc < j_p60 & j_ehhnetinc1_ahc<. <br />replace j_decile = 7 if j_ehhnetinc1_ahc >= j_p60 & j_ehhnetinc1_ahc < j_p70 & j_ehhnetinc1_ahc<. <br />replace j_decile = 8 if j_ehhnetinc1_ahc >= j_p70 & j_ehhnetinc1_ahc < j_p80 & j_ehhnetinc1_ahc<. <br />replace j_decile = 9 if j_ehhnetinc1_ahc >= j_p80 & j_ehhnetinc1_ahc < j_p90 & j_ehhnetinc1_ahc<. <br />replace j_decile = 10 if j_ehhnetinc1_ahc >= j_p90 & j_ehhnetinc1_ahc<.</p>
<p>lab var j_decile "equivalised income decile (AHC)"</p>
<p>keep j_pov_ahc j_hhdenub_xw j_hidp j_fihhmnnet1_dv j_houscost1_dv j_decile j_tenure_dv<br />save j_pov_ahc, replace<br />}</p>
<p>Thanks for any help/advice you can offer!<br />Henry</p> Support #1352 (Resolved): Differences between fihhmngrs_dv over different data downloadshttps://iserredex.essex.ac.uk/support/issues/13522020-05-20T11:46:31ZCameron Harries
<p>Hi,</p>
<p>I was previously working with an older download of US that contained waves 1-7. I recently re-downloaded the data including waves 1-9 and comparing the fihhmngrs_dv variable across the two datasets there are appears to be differences. I tried to find some guidance on the website regarding this, but it mentions that no changes have been applied to the raw data.</p>
<p>Is there any reason why this variable might have changed (i.e. comparing the same household in the same wave across the different downloads of the data).</p>
<p>Apologies if this has been mentioned or asked previously, I have spent some time trying to understand this.</p>
<p>Thank you in advance!</p> Support #1291 (Resolved): Measurement error in savings datahttps://iserredex.essex.ac.uk/support/issues/12912019-12-10T00:53:19ZMihai Codreanu
<p>Hi,</p>
<p>I am currently working with the savings data in USoc (save, saved, svamt etc.) and the savdocs variable shows that very few (less than 10%) actually have shown to the interviewer any documents on their savings. I was wondering if there is any systematic information on how the distributions given by the variables is compared to real data on savings or more focused wealth-assets surveys (such as WAS). And, secondly if anything has been done to deal with it.</p>
<p>Thanks!</p> Support #1290 (Resolved): Zero/negative values of monthly labour incomehttps://iserredex.essex.ac.uk/support/issues/12902019-12-09T16:35:51ZC Jostenjostenc@hotmail.de
<p>Hi!</p>
<p>I'd like to better understand what a value of zero means for the variable fimnlabgrs_dv. Similarly, what does it mean if this value is negative?</p>
<p>Thanks and best,<br />C</p>