Labour Force Survey Longitudinal User Guide (Pdf 95Kb)
Contents
1. Employed at first inactive unemployed at final quarter ENU 18 Unemployed at first employed inactive at final quarter UEN 19 Unemployed at first inactive employed at final quarter UNE 20 Inactive at first employed unemployed at final quarter NEU 21 Inactive at first unemployed employed at final quarter NUE 22 3 or 4 moves between categories Weighting 17 The weighting factors variable name LGWT for these datasets serve two purposes They compensate for non response bias and also produce estimates at the level of the population The calculation of weighting factors for the two quarter datasets involves the following stages i Initial prior weights are calculated such that they reproduce the distribution of the cross sectional sample from the first quarter according to the tenure landlord categories owned rented from local authority housing association privately rented il These prior weights are then multiplied by a single grossing factor except for Northern Ireland where this factor is again multiplied by an adjustment factor to compensate for the different sampling fraction such that the weighted sample cases sum to the overall population control total described below This results in the prior weights used in the calculation of the final weights described below iii A process of calibration weighting also known as generalised raking is then applied to the sample using CALMAR software see Elliot 19972. This process minimises the distance between the prior and final weights while constraining the final weights simultaneously to several marginal distributions or control totals Four sets of control totals are used a the population estimates used for weighting the second quarter s cross sectional LFS dataset for the selected age range classified by sex and age in single years to 24 then five year age groups this produces estimates as close as possible to the population available for sampling in both the linked quarters b the population estimates used for weighting the second quarter s cross sectional LFS dataset for the selected age range classified by region c the weighted cross sectional estimates from the second linked quarter for the selected age range classified by broad economic activity categories in employment unemployed economically inactive d the weighted cross sectional estimates from the first linked quarter for the selected age range classified by broad economic activity categories in employment unemployed economically inactive adjusted to the same total as a to c by reducing the economically inactive category as necessary CALMAR is run using the logit method with the ratio of the final to prior weights constrained to the range 0 5 to 1 7 The elements iii a and b in this process produce population level estimates and also contribute to some extent to compensating for non response bias the
3. other elements complete the compensation for non response bias The extension of this method to create five quarter datasets consists of constraining to the cross sectional economic activity distribution at each of the five quarters This involves repeating the constraint in iii d for the second third and fourth quarters as well as the first adjusting in the same way to achieve a total consistent with the fifth quarter When running CALMAR to create five quarter datasets wider limits have to be set for the ratio of final to prior weights typically 0 6 to 2 3 Sample sizes and threshold levels 18 Because of sampling variability the smaller the group being estimated the poorer the precision of the estimate becomes until eventually the estimate is not reliable enough to be used See Volume 1 of the LFS User Guide for a detailed discussion For the regular quarterly cross sectional LFS datasets a publication threshold is set at 10 000 i e estimates below 10 000 are not published at which level the standard error is about 20 of the estimate and the 95 confidence interval for the estimate is about 4 000 For the two quarter longitudinal datasets the same principle applies but the number of sample cases available for linkage is smaller usually around 60 000 so the threshold level for these datasets is 17 000 19 Because of the lower number of cases available for linking and higher attrition the five quarter datasets contain on
4. d These are transitions between unemployment and inactivity transitions between part time employment and either unemployment or inactivity for women any transitions involving unemployment and for students transitions between employment and unemployment However some of the 6 apparent inconsistencies may be caused by genuine volatility repeated movements back and forth between different economic activity states rather than by response error Contact details All enquiries about the longitudinal datasets should be directed to Mike Young ONS Room B4 03 1 Drummond Gate London SW1V 2QQ telephone 020 7533 6160 e mail mike young ons gov uk Reference Elliot D 1997 Software to weight and gross survey data GSS Methodology Series No 1
5. d Office for ASS National Statistics Labour Force Survey r User Guide LFS TWO QUARTER AND FIVE QUARTER LONGITUDINAL DATASETS 2011 Version 1 0 August 2011 4 LFS LONGITUDINAL USER GUIDE LFS TWO QUARTER AND FIVE QUARTER LONGITUDINAL DATASETS 2011 Introduction 1 The Labour Force Survey LFS is a household survey gathering information on a wide range of labour force characteristics and related topics Since 1992 it has been conducted on a quarterly basis with each sample household retained for five consecutive quarters and a fifth of the sample replaced each quarter The survey was designed to produce cross sectional data but in recent years it has been recognised that linking together data on each individual across quarters would produce a rich source of longitudinal data 2 There are however methodological problems which could distort the data resulting from this linking These fall into two main groups biases arising from non response and the sample attrition arising from it and biases arising from response errors particularly their effects in producing spurious flows between economic activity states ONS has therefore undertaken a joint research project with Southampton University to address these methodological issues This project has now produced a satisfactory methodology for compensating for the biasing effects of non response and a procedure has been developed for applying it in longitudinal datas
6. d quarters There are 243 possible sequences over five quarters many of which will have very small frequencies particularly the ones involving 3 or 4 moves For this reason a simplified categorisation is presented which combines together those sequences where only the timing differs for example all cases which start in employment and end in unemployment with no other transitions are in category 4 below regardless of the wave in which they became unemployed The codes and categories are as follows 1 In employment in all quarters E 2 Unemployed in all quarters U 3 Inactive in all quarters N 4 In employment at first quarter unemployed at final quarter EU 5 In employment at first quarter inactive at final quarter N 6 Unemployed at first quarter inactive at final quarter UN 7 Unemployed at first quarter in employment at final quarter UE 8 Inactive at first quarter in employment at final quarter NE 9 Inactive at first quarter unemployed at final quarter NU 10 Employed at first unemployed in employment at final quarter EUE 11 Employed at first inactive in employment at final quarter ENE 12 Unemployed at first inactive unemployed at final quarter UNU 13 Unemployed at first employed unemployed at final quarter UEU 14 Inactive at first employed inactive at final quarter NEN 15 Inactive at first unemployed inactive at last quarter NUN 16 Employed at first unemployed inactive at final quarter EUN 17
7. ets linking two or five adjacent quarters 3 This guide describes the two quarter and five quarter longitudinal LFS datasets and how to use them It describes briefly how they are produced but does not give details of the methodological development this is covered in detail in paper 17 of the GSS Methods and Quality series entitled Methodological Issues in the Production and Analysis of Longitudinal Data from the Labour Force Survey by Paul Clarke and Pam Tate 4 It is also important to note that the second methodological problem that of response error bias is still under investigation Progress so far on this is also described in the Methods and Quality paper This guide includes some discussion of the possible effects of response error bias on analyses of the longitudinal datasets including which kinds of analyses are more or less likely to be affected in the light of our present state of knowledge from the investigation For further information please see for example http www iser essex ac uk files survey ulsc methodological research mols 2006 scientific social programme papers Eideh pdf Datasets 5 The quarterly LFS started in spring 1992 but the rotational pattern of the sample was not established until winter 92 93 therefore this is the first quarter available for longitudinal linking Two quarter longitudinal datasets have been produced for all pairs of adjacent quarters from winter 1992 93 onwards for example the w
8. first quarter 2 to 11 at the second quarter and 3 to 11 at both quarters 23 Most analyses of interest are likely to be cross tabulations of a characteristic at the first quarter with a characteristic at the second or fifth quarter often restricted to a subgroup Some examples are lone parents of working age at both quarters by sex and age of youngest child and by economic activity at both quarters young people aged 18 to 24 unemployed at the first quarter by educational qualification and economic activity at the last quarter people reaching retirement age by the last quarter by economic activity at both quarters and by reason for inactivity if inactive Doing analyses of this kind the numbers of cases in some cells can very quickly fall below the threshold level 24 Research so far on response error has been based on empirical analysis of differences in levels of transitions between different economic activity categories and of apparent internal inconsistencies The findings so far are therefore provisional and will be updated with the results of further research However the initial investigations have provided evidence supporting the suggestion that response error is likely to affect the longitudinal datasets probably in the direction of an upward bias in estimates of gross flows between different broad economic activity categories It has also provided some tentative indications of transitions and subgroups particularly likely to be affecte
9. h a suffix of 1 added to the original variable name and all the variables relating to the second of the linked quarters have a suffix of 2 added to the original variable name and so on For example if we link together the summer 97 and summer 98 quarters then the variable TEN96 from the first quarter summer 97 becomes TEN961 in the linked dataset and TEN96 from the second quarter autumn 97 becomes TEN962 and so on until the summer 98 variable becomes TEN965 This is true for all the variables in all the datasets except for the unique identification variable and the variables for sex and date of birth which are used for checking that the match between the two quarters is correct These must be identical for each of the quarters being linked and therefore have no suffix 13 Some of the variables are not available for all quarterly interviews and are therefore not available in one or both of the quarters of some of the linked datasets For example the variable HITQUA is only available for Spring MM and Autumn SN quarters from 1996 Therefore it will be available for the first quarter of the spring summer 2000 linked dataset as HITQUA1 but not the second quarter Similarly it will be available for the second quarter of the winter 99 spring 2000 dataset as HITQUA2 but not available for the first quarter 14 As SPSS only allows variable names to be eight characters long a few variable names which are already eight characters long have
10. inter 1992 93 dataset was linked with the spring 1993 dataset Five quarter longitudinal datasets have also been produced for the same period for example linking spring 1993 with spring 1994 and containing data from all five waves of the survey New datasets will continue to be created as further LFS quarterly data becomes available All the datasets are available as portable SPSS files those with por extension which are straightforward to access in either SPSS or SAS Coverage 6 Since the focus of analyses of these datasets was expected to be the population of working age it was decided in consultation with major customers to restrict the datasets to women aged 15 to 59 at the first quarter and men aged 15 to 64 at the first quarter ya For the period from winter 1995 6 the datasets cover the UK The Northern Ireland survey did not change from an annual to a quarterly survey until winter 1994 95 and the rotation pattern of the sample was not fully established until winter 1995 96 therefore the longitudinal datasets which include quarters before winter 1995 96 cover just Great Britain 8 The small proportion of people in the sample whose data at any of the linked quarters had been imputed by rolling forward from the previous interview were excluded from the longitudinal datasets 9 From spring 1996 onwards with the introduction of the household matrix approach to gathering data on the people present in the household a small prop
11. ly around 11 000 cases each compared to 60 000 on the two quarter datasets Therefore the results are subject to greater variability and the threshold levels for producing reliable estimates are much higher than the 17 000 recommended for the two quarter datasets However it is possible to combine results from several datasets to reduce the threshold level The table below shows the thresholds that should be used for different categories of ANFLOW 20 For estimates below these figures the standard error is likely to be greater than 20 of the estimate and therefore the estimate should not be used The figures are higher for the unemployed category because of the design effect and higher attrition within this group For some of the other categories particularly those involving more than one transition there may be very few cases present in each dataset Therefore it may be necessary to combine categories or use several datasets to get a reliable result Some points on longitudinal analysis including the implications of response error bias 21 All analyses should be run weighted by LGWT otherwise the results will be distorted by non response bias and possibly misleading 22 Careful thought is needed about the precise coverage of any analysis is it the population of working age at the first quarter the second quarter or both quarters The variable FLOW can be used to select any of these groups codes 3 to 12 give working age at the
12. ortion of people in the sample have no data available on economic activity People with no data on economic activity at one or more of the linked quarters have been excluded from the longitudinal datasets Linking procedure 10 The regular quarterly individual level LFS dataset for the first of the quarters to be linked is used to produce a reduced cross sectional dataset confined to the age range and variables to be used for the longitudinal dataset A unique identification variable is created A similar procedure is followed for the other quarters The reduced cross sectional datasets for the two or five quarters to be linked are matched by the unique identification variable and checked to ensure that the cases linked match also on sex and date of birth All unmatched cases are dropped as are all cases where the data were rolled forward or where there are no data on economic activity at any of the quarters Variables 11 Because of the resources involved in production and the size of the resultant datasets the longitudinal datasets include only a subset of the full LFS variable set This subset has been agreed in consultation with users and represents the most important and commonly used variables covering the main areas of the survey A full variable list has been created which shows the content of each of the datasets 12 When the linked datasets are created all the variables relating to the first of the linked quarters are renamed wit
13. to be amended when the suffix is added These are as follows 1st Qtr 2nd Qtr 3 4 5 NMANAGE2 NMNAGE21 NMNAGE22 3 4 5 IOUTCOME IOUTCOM1 IOUTCOM2 3 4 5 SHFTWK99 SHFTWK91 SHFTWK92 3 4 5 15 A variable FLOW has been added to the datasets It gives in a convenient form the categories relating to labour force gross flows distinguishing between states in and outside working age The codes and categories are as follows 1 Aged 15 at both quarters 2 Entrant to working age between first and final quarter 3 In employment at first quarter in employment at final quarter EE 4 In employment at first quarter unemployed at final quarter EU 5 In employment at first quarter inactive at final quarter N 6 Unemployed at first quarter in employment at final quarter UE 7 Unemployed at first quarter unemployed at final quarter UU 8 Unemployed at first quarter inactive at final quarter UN 9 Inactive at first quarter in employment at final quarter NE 10 Inactive at first quarter unemployed at final quarter NU 11 Inactive at first quarter inactive at final quarter NN 12 Reached retirement age by final quarter For the two quarter datasets this variable shows the flow over a 3 month period while for the five quarter datasets it shows the flow over a 12 month period 16 In addition a variable ANFLOW has been added to the five quarter datasets It gives categories relating to labour force gross flows across all five of the linke
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