CROSS-COUNTRY INCOME MOBILITY COMPARISONS UNDER PANEL ATTRITION: THE RELEVANCE OF WEIGHTING SCHEMES

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1 CROSS-COUNTRY INCOME MOBILITY COMPRISONS UNDER PNEL TTRITION: THE RELEVNCE OF WEIGHTING SCHEMES uthors: Lus yala Insttuto de Estudos Fscales and Unversdad Rey Juan Carlos Carolna Navarro Unversdad Naconal de Educacón a Dstanca Mercedes Sastre Insttuto de Estudos Fscales and Unversdad Complutense P. T. N. o 19/06 N.B.: Las opnones expresadas en este trabajo son de la exclusva responsabldad de los autores, pudendo no concdr con las del Insttuto de Estudos Fscales. Desde el año 1998, la coleccón de Papeles de Trabajo del Insttuto de Estudos Fscales está dsponble en versón electrónca, en la dreccón: >

2 Edta: Insttuto de Estudos Fscales N.I.P.O.: I.S.S.N.: Depósto Legal: M

3 ÍNDICE 1. INTRODUCTION. TTRITION IN THE EUROPEN COMMUNITY HOUSEHOLD PNEL 3. DJUSTING FOR TTRITION: LONGITUDINL WEIGHTING SCHEMES 4. TTRITION ND INCOME MOBILITY 5. CONCLUSIONS NNEX. CONSTRUCTION OF LONGITUDINL WEIGHTS IN THE ECHP REFERENCES SÍNTESIS. PRINCIPLES IMPLICCIONES DE POLÍTIC ECONÓMIC 3

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5 BSTRCT Ths paper ams to present an assessment of the effects of panel attrton on ncome moblty comparsons for some EU-countres by usng the European Communty Household Panel (ECHP). There are dfferent possbltes of correctng the attrton problem by means of alternatve longtudnal weghtng schemes. The senstvty of moblty estmates to these attrton correcton procedures s tested n the paper. Our results show that ECHP attrton s charactersed by a certan degree of selectvty but only affectng some varables and countres. Dfferent probablty models corroborate the exstence of a certan non-random attrton. The model chosen to construct the longtudnal weghts to correct attrton offers up rather dfferent results than those obtaned when Eurostat s longtudnal weghts are used. lthough attrton does not seem to have a great effect on aggregated moblty ndcators, t does have a decsve effect on decomposton exercses. Fnally, the tests conducted on ncome moblty ndcators reveal a certan senstvty to the weghtng system used. Keywords: Income moblty, attrton, European Communty Household Panel. JEL: D31, D63, J60. 5

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7 Insttuto de Estudos Fscales 1. INTRODUCTION 1 Interest n the study of ncome dstrbuton dynamcs has grown consderably n recent years. Movng from a statc analyss of welfare, nequalty and poverty to a dynamc approach allows us to understand the dstrbuton process better. More accurate assessments can also be made about the effcency of publc polces. Recent mprovements n the study of the dynamcs of nequalty and poverty have been based on the advances made n the development of a sold body of theoretcal work and the avalablty of new databases contanng longtudnal nformaton on households and ndvduals. lthough some countres have a long-standng experence of longtudnal mcrodata such as the Panel Study of Income Dynamcs (PSID) of the Unted States, whch was started up n the 1970s, the 1990s heralded an unprecedented change as varous countres created household surveys for the very frst tme wth the am of montorng ncome level changes and lvng condtons over tme. There s no doubt that the settng up of the European Communty Household Panel (ECHP) supposed a sgnfcant change for most European Unon member states. It was the frst household panel survey contanng homogenous nformaton on dfferent countres and wth a projected tme span of almost a decade. In many of these countres, the only possblty of followng households longtudnally up to then had reled on usng admnstratve records or explotng the rotatng panel nature of some surveys. The detaled nformaton of the ECHP makes possble the analyss of ssues such as labour market transtons, ndvdual decsons on fertlty and marrage, changes n the health status, the evoluton over tme of housng condtons and facltes, lfe cycle fluctuatons n ncome, welfare spells, the varety of exts from the educatonal system or changes n the poston of households wthn the socal scale. However, some ntrnsc characterstcs of longtudnal surveys mpose certan constrants on the analyss of most of the above-mentoned questons. The most relevant of these constrants s the loss of an mportant percentage of the ntal sample as new waves of the survey are conducted. The loss of orgnal observatons over tme (attrton) could ental a bas n the study of ncome dynamcs f t has a selectve character. Prevous studes undertaken usng the ECHP reveal that ths source s not mmune from the attrton problem, although ts ncdence does vary greatly among the countres that have conducted the survey [Hll and Wlls (001), Peracch (00), and Behr et al. (00)]. s varous dynamc processes are affected by the problem of sample attrton, there can be lttle doubt that t s a crucal ssue when measurng ncome moblty. In the analyss of equalty of opportuntes, t s very dfferent a 1 Fnancal support for ths research was provded trough the Mnstry of Scence and Technology (grant SEJ c03-03). 7

8 stuaton where households havng the greatest probablty of leavng the sample are those wth hghest or lowest ncome from when most of the exts correspond to households wth mean ncome levels. Smlarly, f the objectve s to analyse whether changes n ncome dstrbuton over tme are ndependent of the orgnal stuaton, a relatonshp, for nstance, between attrton and ncome or other socoeconomc characterstcs could bas the results. Regardng the specfc case of the ECHP a key pont n assessng the effects of attrton on ncome moblty or poverty dynamcs s the growng attenton pad by European polcymakers to ths source. The launchng of Natonal cton Plans to combat Poverty and Socal Excluson n the EU member states reled on the research of the ECHP. Ths s the only avalable source for comparatve analyss of achevements n some of the Plans goals lke reducng persstent poverty. Poltcal evaluaton could be constraned by data varablty due to sample attrton. The am of ths paper s two-fold. On the one hand, t makes an attempt to assess the effects of attrton on ncome moblty and, on the other, t examnes the dfferent possbltes there are of correctng the attrton problem. Dfferent longtudnal weghtng systems to correct attrton exst, and these could produce very dfferent results. In ths paper we analyse the effects generated by usng dfferent weghtng systems for both synthetc ncome moblty ndcators as well as for the structure of ncome moblty. In as far as the ECHP s attrton problem dffers substantally among the countres that have partcpated n ths survey, we take dfferent natonal samples nto consderaton. The use of a comparatve framework enables us to verfy not only how the problem of attrton can affect moblty n each country dfferently, but also to ascertan by up to what degree the problem can condton comparatve analyses. The study s structured as follows. The followng secton looks nto the problem of ECHP sample attrton. Dfferent procedures to correct ts effects n dynamc analyses are estmated n the thrd secton. The fourth secton examnes the consequences of attrton on the measurement of ncome moblty n a selected group of countres. The senstvty of moblty estmates to attrton correcton procedures s also assessed n ths secton. The study ends wth a bref lst of conclusons.. TTRITION IN THE EUROPEN COMMUNITY. HOUSEHOLD PNEL The European Communty Household Panel (ECHP) was conducted by Eurostat n collaboraton wth natonal statstcs agences between 1994 and 001. Ths database contans longtudnal nformaton on ncome, as well as on a set of soco-economc and demographc characterstcs on households and 8

9 Insttuto de Estudos Fscales ndvduals. It therefore consttutes an oblgatory pont of reference for comparatve studes on ncome structures and ther dynamcs over tme n dfferent countres. Of all the countres makng up the ECHP, ths paper focuses ts attenton on fve dfferent experences: the Unted Kngdom, Germany, France, Italy and Span. These are countres for whch we have avalable emprcal evdence suppled by varous natonal studes. In addton, these countres represent dfferent models regardng both the levels of nequalty as well as the possble determnng factors for moblty. The ECHP was developed dfferently n each country. In Span, France and Italy, among others, the survey was completely new, gven the absence of comparable sources that could be adapted to the harmonsaton requrements lad down by EUROSTT. In Belgum, the Netherlands and Sweden whch joned n 1997, other already exstng surveys were used to create the natonal samples. n unusual stuaton arose n Germany, the Unted Kngdom and Luxembourg, as there were two dfferent panels durng the frst three waves. The ECHP stopped beng conducted n these countres n 1997, and snce then the data was gathered from already exstng panels. The problem of attrton s present n all the cases under consderaton. By defnton, ths problem arses n longtudnal databases when there s nonresponse n ntervews subsequent to the ntal one. The result s a loss of observatons over tme that can hamper the followng of an mportant segment of the sample. Ths knd of phenomena can have an nfluence on the results f the sample s no longer representatve of the populaton under study. The problem of attrton has been the object of study n natonal longtudnal surveys lke the mercan PSID [(Beckett et al., 1988), (Ftzgerald et al., 1998 a, b)] and the German Soco Economc Panel (GSOEP) [(Pannenberg, 001), (Rendtel and Büchel, 1994)], as well as n the ECHP tself [(Watson and Healy, 1999), (Buck and McCulloch, 001), (Neukrch, 00), (Behr et al. (00), (Peracch, 00), (Ncolett and Peracch, 00), (Rendtel, 00)]. Focusng our attenton on the countres chosen for analyss and takng ndvduals as the unt of reference, the avalable data show that both the evoluton and scope of attrton are very dfferent n each country under consderaton (Fgure 1). The presence of very dfferent sample loss patterns stands out despte the fact that a certan degree of stablty over tme can be seen wth year-on-year losses of almost 9%, except for 1996 when most of the countres regstered very mportant sample reductons. The dfferences n the scope of the problem are also strkng. t the end of the last wave, only 45 percent of the ntal observatons for the ECHP as a whole remaned. Ths percentage was greater n the case of the fve countres under consderaton, The Swedsh data come from a cross-secton survey whch does not montor ndvduals over tme, thereby mpedng longtudnal analyses from beng conducted. 9

10 although notable dfferences among them can be observed. Generally speakng, countres havng ther own panel, lke Germany and the Unted Kngdom, had much lower attrton rates (almost a thrd of the sample) than the rest. The case of Span s outstandng, as t s at the opposte extreme wth a loss of the ntal sample amountng to 55 percent. In only eght years, the ECHP n Span reached an attrton rate smlar to the rate the SOEP n Germany (Rendtel, 00) took sxteen years to get to or whch the mercan PSID reached after more than two decades (Ftzgerald et al., 1998). Fgure 1 TTRITION IN THE ECHP, Span Germany France Unted Kngdom Italy UE-5 UE-15 The progressve loss of ntal sample observatons can cause bases n the estmates. The magntude of these effects depends on ther nfluence on the sample s structure and, more specfcally, on whether or not the bas s shared out randomly. s dfferent studes have shown, attrton even f t s hgh only consttutes a problem f t s selectve (Jménez-Martín and Peracch, 00). If some soco-demographc categores do ndeed exst n whch the ncdence of the loss of ntal observatons s above the average, possble estmates of the dstrbuton process could be based. Hence, f ndvduals wth hgher ncomes have, for nstance, a greater probablty of leavng the sample, the trmmng of the dstrbuton could artfcally reduce nequalty dependng logcally on the senstvty of the ndcator chosen. n ntal method to address the problem s ncdence by soco-economc categores, s to analyse the extent of attrton wthn each specfc group. In order to do so, the percentage of those stayng n the panel can be analysed by populaton categores, takng nto account both household as well as strctly ndvdual characterstcs. In general terms, there s a certan smlarty n most 10

11 Insttuto de Estudos Fscales countres attrton patterns, though some dfferences do exst dependng on the soco-economc categores under consderaton (Table 1). Table 1 PERCENTGE OF INDIVIDULS REMINING IN THE ECHP S EIGHT WVES (by households characterstcs) Characterstcs Span France UK Germ. Italy djusted Dsposable Household Income (a). Decles Decle Decle Decle Decle Decle Decle Decle Decle Decle Decle Total Household head s man source of ncome Wages and salares Income from self-employment Pensons Unemployment/Redundancy benefts ny other socal benefts or grants Prvate ncome Total Household type 1-person household: aged 65 or more person household: aged person household: less than Sngle parents adults wthout chldren adults wth one chld adults wth two chldren adults wth three chldren or more adults wthout chldren, no members aged < adults wthout chldren, one or more < adults wth one chld adults wth two chldren adults wth three or more chldren Total (Keep.)

12 (Contnuaton.) Characterstcs Span France UK Germ. Italy Household head's age ged less than 30 ged ged 65 or more Total Household head's sex Varon Mujer Total Household head's martal status Marred Separated Dvorced Wdowed Never marred Total Household head's educatonal attanment Recognsed thrd level Second stage of secon. Less than second stage Stll at school Total Tenure status Owner Rent ccommodaton s provded rent-free Total Number of chldren (<18) n the household and more Total Number of full tme workers n the household and more Total (Keep.)

13 Insttuto de Estudos Fscales (Contnuaton.) Characterstcs Span France UK Germ. Italy Household sze Total Unlke other natonal panels lke the mercan PSID, there s no complete evdence that rchest ndvduals reman n the panel for longer perods. Whle n countres lke France, the Unted Kngdom and Germany there s a defnte relatonshp wth lower attrton among the rchest decles, Span and Italy seem to concde as both have a greater range of attrton varaton by decles and a poorly defned pattern. Ths sngularty of the Latn model also appears when other varables are taken nto account, such as the man source of ncome. The attrton rates of households whose man source of ncome s socal transfers are above the average n Span and Italy, whle just the opposte happens n the other three countres. There are more smlartes n the results for households dependent on earnngs. The greater economc stablty of ths group, compared wth those who manly receve property ncome, ncreases the possblty of followng these households. The greater volatlty and uncertanty of the latter knd of ncome gves rse to a lower proporton of stayers, except n the case of Germany. The hypothess of households dependent on pensons havng a hgher probablty of leavng the sample s smlarly logcal. Ther attrton rates are above average n all the countres. It s therefore not surprsng to fnd that the attrton profle by age groups n almost all countres shows consderably hgher than average ext rates for those aged over 65 and, except for Span, for households wth younger heads. The ageng of the populaton s n fact one the characterstcs havng the greatest explanatory capacty for leavng the sample n other countres wth household panels coverng a longer perod of tme (Ftzgerald et al., 1998). The hgher attrton rate of younger people s also a natural fact, gven ther greater economc and resdental moblty. Smlarly, the dstrbuton of attrton by household sze and type does not appear to be random n any country. France, the Unted Kngdom and Germany have a pattern n whch the hghest attrton rates are for sngle-parent and smaller households. In Italy and, to a lesser extent, Span, larger households have a hgher probablty of remanng n the sample. Ths fact s related to the greater 13

14 stablty of households wth many chldren. ll the countres are over-represented n the sample by couples wth chldren. The results concernng martal status seem to corroborate ths mpresson, wth much lower percentages of households wth dvorced or separated heads remanng n the sample. Regardng labour status, the stayer rates for two adults employed on a fulltme bass are hgher n all countres than for the other categores. ttrton s hghest among households wth no ndvduals workng full-tme. The dvergence between the Latn model and the rest s also reflected n the dstrbuton of attrton by the head educatonal attanment. Whle n France, the Unted Kngdom and Germany the hghest levels of educatonal attanment seem to be assocated wth longer perods n the sample, n Span and Italy educaton does not seem to be a factor for leavng t nor does there appear to be ether a quadratc or lneal relatonshp wth ncome. In the case of Span, ths result contrasts wth those obtaned usng other sources lke the Encuesta Contnua de Presupuestos Famlares (Contnuous Famly Budget Survey) [Gradín et al., 004]. Fnally, gven the natural assocaton between household resdental moblty and the probablty of remanng n the sample, t seems approprate to analyse the dstrbuton of attrton by type of housng tenure. The frequency dstrbuton appears to back the hypothess that households ownng ther own dwellng have a lower attrton rate assocated to a lower level of resdental moblty than those lvng n rented housng. 3. DJUSTING FOR TTRITION: LONGITUDINL 3. WEIGHTING SCHEMES Descrptve analyss shows that there are dfferent populaton categores wth hgher attrton rates. It appears to be a certan selectvty n attrton, although for only some varables and countres. For the survey to be longtudnally representatve, t s necessary to construct a longtudnal weghtng system for each observaton that reflects the probablty of leavng the sample. Followng along the same lnes as prevous papers (Ftzgerald et al., 1998, Pape, 004, Gradín et al., 004), we construct longtudnal factors based on the propensty score or probablty of remanng n the survey, condtoned to a set of socoeconomc characterstcs (Ps ). These longtudnal weghts are therefore the result of estmatng the probablty of how a specfc observaton represents observatons that have left the sample. Indvduals havng a greater lkelhood of leavng the sample wll be assgned a greater weght. The startng pont s therefore some sort of lnear probablty estmaton of remanng n the sample based on the characterstcs of 14

15 Insttuto de Estudos Fscales the ndvduals ntervewed n the frst wave. These probabltes can be estmated through a probt model. Usng the nverse of such probabltes 3, the longtudnal weght of each observaton can be calculated as follows: (1/Ps ) 1 Nt=1 φ,t = = (1) (1/Ps ) Ps (1/Ps ) N t=1 where N t=1 represents the ntal sample s sze, and from whch we can deduce that φ,t = 1. The frst term of Equaton (1) s the propensty score weght, whch s the nverse of the probablty of remanng n the sample throughout the perod under consderaton. The second term seeks to ensure that the sum of the estmated weghts s equvalent to the whole ntal populaton. By generatng a constant common factor for all observatons of a wave, each observaton s relatve weght would not be modfed. ny varables dentfed as sgnfcant n the avlable emprcal evdence on attrton have been ncluded n the estmates made to obtan longtudnal weghts. Ths, however, does not avod a hgh degree of senstvty n the results to both the choce of varables as well as ther specfcaton. Moreover, there s an addtonal problem concernng mssng values. The probt models estmated exclude from the analyss those observatons havng mssng values for some of the explanatory varables. It s mpossble, therefore, to estmate a weght for such observatons. n alternatve les n assgnng to such observatons the average value of the dstrbuton of the varables for whch nformaton s unavalable. However, these mputatons can generate mportant problems by fttng the nformaton more to statstcal crtera than to actual data. It seems to be more advsable to exclude from the regressons the varables havng a hgher proporton of non-response. nother choce also has to be made when estmatng the models n order to obtan the weghts, as t s possble to use both the nformaton offered by data referrng to household and heads characterstcs, as well as strctly ndvdual data. Ths range of optons requres the estmaton of dfferent models and choosng those whch produce the most robust results among them. In ths study we estmate two types of models. The frst type takes nto account household and heads characterstcs. The presence of mssng values n some varables, usually dentfed as assocated to the probablty of remanng n the sample, oblges us to examne the results produced dependng on whether or not they are ncluded n the model. Ths s why three dfferent models are estmated usng ths frst type of 3 s Kalton and Brck (1994) pont out, ths procedure can turn out to be lmted f the jont probablty of a household leavng the sample and the ndvdual probablty of each of ts members are not known correctly. 15

16 nformaton. The frst of these models ncludes household ncome by equvalent adult, the households man source of ncome, the type of household, housng tenure and varous of the head characterstcs, ncludng age, sex, martal status and educatonal attanment. s the latter varable regsters the greatest number of mssng values n all countres, a second model ncludes all of the same varables except educatonal attanment. The thrd model once agan takes educatonal attanment nto account and adds other household varables, such as household sze, the number of chldren and the number of workng adults. The second type of model employs strctly ndvdual characterstcs, usng the ECHP s personal fle to do so 4. The frst sub-model uses net ndvdual ncome, labour status, sex, martal status and the ndvdual s educatonal attanment as explanatory varables for attrton. The second model adds age to these, and the thrd model addtonally ncludes health status. The results obtaned from estmatng the dfferent models are shown n Tables and 3. They corroborate the general concluson that attrton s not random, as some varables regster statstcally sgnfcant effects. Estmates usng nformaton on the head and the household confrm some of the prelmnary statstcal analyss features. However, a more obvous postve relatonshp can generally be observed of the probablty of remanng n the ECHP wth ncome, but negatve when the latter s expressed n quadratc form except n the case of Italy. Ths probablty s also generally lower n households that depend on property ncome, whle dependence on pensons does not turn out to be sgnfcant n most of the countres. Ths does not seem to go aganst the dea that as the age of the household head ncreases, the lower the chances are of followng the household over tme. The results also allow to dentfy couples wth chldren as the type of household wth the hghest probablty of remanng n the sample once other characterstcs are controlled, though some of these categores are not sgnfcant n several of the countres under study. The stuatons of beng separated or dvorced are especally sgnfcant almost wthout excepton, as they lower the probablty of remanng n the sample. The same can be sad for type of tenure, wth a much lower probablty of remanng n the sample f the house s rented. The dfferent educatonal varables coeffcents turn out to be sgnfcant n France, Germany and Span. It s worth hghlghtng that there are no great changes n the remanng varables when the former s not consdered n the estmates, as s the case n the second model proposed. ddtonally, ths second model offers better results than the thrd model estmated, whch ncludes other relevant varables, such as the number of chldren, household sze and the number of workng adults. The calculaton of weghts for chldren and adults wth ncomplete questonnares were therefore excluded from the estmates. 4 16

17 Table PROBBILITY OF REMINING IN THE ECHP LL WVES (household characterstcs) (1) Span France Unted Kngdom () (3) (1) () (3) (1) () (3) djusted Dsposable Household Income (a) djusted Dsposable Household Income (a) squared Numer of chldren (aged less than 18) Household sze squared Number of full tme workers Man source of ncome Income from self-employment Pensons Unemployment/Redundancy benefts ny other socal benefts or grants Prvate ncome Household type 1-person household: aged person household: less than 30 Sngle parents adults wthout chldren adults wth one chld adults wth two chldren adults wth three chldren or more 3+adults wthout chldren, no members aged less than 5 3+adults wthout chldren,wth members aged less than 5 3+adults wth one chld 3+adults wth two chldren -1.3e e (*) -0.0 (*) 0.0 (*) -0.5 (*) 0.54 (*) (*) (*) e e * * * * * * * * * * (**) * * (**) * * (**) * * (**) (**) (**) * * * (**) (**) (**) 0.04 (**) (**) (**) (**) (**) * (**) (**) (**) 0.07 (**) (**) (**) * * * (**) (**) (**) (*) * * * * * (**) * * (**) -0.0 (*) * * * (**) (**) * * * 0.0 (*) * * * (**) (**) * * * * (*) * * * (**) (**) (**) (**) (**) (**) 0.53 (*) * * * * * (**) (**) (**) 0.16 (**) 0.09 (*)* (**) (**) (**) (**) (**) (**) (**) (**) * * * (**) * 0.14 (**) 0.15 (**) (**) 0.16 (**) 0.3 (*) 0.14 (*) 0.10 (*)* (**) (**) * * (**) (**) (**) 0.19 (*) * * * * * (**) (**) (**) * 0.05 (*)* (**) (**) (**) (**) * * * -0.0 (*)* (**) (**) (**) (**) * * * (**) 0.05 (*)* (**) (**) (**) (**) (**) (**) (**) (**) e e (*) -0.1 (*) 0.0 (*) (*) 0.58 (*) (*) (*) e-07 (*) -4.99e-13 (*) (*) -0.3 (*) (*) (*) (*) 0.3 (*) e-07 (*) -6.9e-13 (*) (*) (*) -0.1 (*) (**) (*)* (**) (**) (**) (**) (**) (**) (**) (*) (*) 0.3 (*) e e-13 (*) 0.9 (*) -0.0 (*) 0.14 (*) (*) 0.17 (*) (*) (*) (*) 0.17 (*) e-05 (*) -5.81e-10 (*) (*) (*) 0.5 (*) (*) (*) e-05 (*) -5.94e-10 (*) (*) (*) 0.4 (*) (*) (*) e e-10 (*) 0.1 (*) -0.0 (*) 0.16 (*) (*) 0.31 (*) (**) 0.43 (*) -0.0 (**) (**) (Keep.)

18 (Contnuaton.) 3+adults wth three or more chldren ge of household s head ged ged 65 or more Sex of household s head Woman Martal status of household head Separated Dvorced Wdowed Never marred Hghest level of educaton completed Second stage of secondary level of educaton Less than second stage of secondary level of educaton Stll at school Tenure status Rent ccommodaton s provded rent-free Constant Sample sze Log lkelhood LR ch Prob > ch Pseudo R (1) Span France Unted Kngdom () (3) (1) () (3) (1) () (3) 0.1 (*)* (**) (**) (**) (**) * * (**) (**) (*) (*) (*) -0.4 (*) -0.1 (*) * * * (**) (**) (**) -0.4 (*) -0.1 (*) -0.4 (*) (*) (*) * * * * * * * * (**) (*) 0.08 (**) 0.07 (**) 0.07 (**) (*) (*) (**) (**) (*) (*) (**) (**) (**) (**) * * (**) (*) (*) (*) * * * (**) (**) * * * (*) (*) (*) (*) (**) (*) * * * * * * * * * (*) -0.4 (*) (*) -0.1 (*) -0.9 (*) -0.1 (*) (*) (*) (**) (**) (**) (**) * * * (*) (*) (**) (**) (**) (**) * * * (**) * * * (*) -0.8 (*) (*) -0.7 (*) (*) -0.6 (*) 0.08 (*) 0.05 (*) 0.08 (*) * * * * (**) (**) 0.05 (*) (*) (*) * * * * (**) (**) (*) (*) (*) (*) * * (**) (**) -0.0 (*) -0.0 (*) -0.0 (*) (*) (*) (*) -0.3 (*) -0.4 (*) -0.0 (*) * * * * * * * * * 0.07 (*) 0.08 (*) 0.07 (*) (**) (**) (*) -0.4 (*) -0.8 (*) -0.5 (*) * * * * * * * (**) (**) (**) (**) (**) (**) * * * (8)= (33)= (8)= (34)= (*) (*) (8)= (*) (34)= (Keep.)

19 (Contnuaton.) djusted Dsposable Household Income (a) djusted Dsposable Household Income (a) squared Numer of chldren (aged less than 18) Household sze squared Number of full tme workers Man source of ncome Income from self-employment Pensons Unemployment/Redundancy benefts ny other socal benefts or grants Prvate ncome Household type 1-person household: aged person household: less than 30 Sngle parents adults wthout chldren adults wth one chld adults wth two chldren adults wth three chldren or more 3+adults wthout chldren, no members aged less than 5 3+adults wthout chldren,wth members aged less than 5 3+adults wth one chld 3+adults wth two chldren 3+adults wth three or more chldren (1) Germany Italy () (3) (1) () (3) 1,15e-05 (*) 1.9e-05 (*) 8.87e-06 (*) -7.96e-06 (*) -8.08e-06 (*) -8.85e-06 (*) * * * * * * -7.69e-11 (*) -8.34e-11 (*) -6.35e-11 (*) 7.65e-11 (*) 7.59e-11 (*) 8.48e-11 (*) * * * * * * 0.16 (*) * 0.1 (**) (*) 0.10 (*) * (*)* * 0.03 (**) (*) (*) (*) (*) (*) (*) * * * * * * 0.3 (*) (*) (**) 0. (*) * * * (*)* (*)* (*)* (*) * * (*)* * * * (*)* (*)* (*)* (*)* (*)* (*)* (*) (*) (*) (*) (*) -0.4 (*) (*) -0. (*) (*)* * * * * (*) -0.6 (*) -0.3 (*) (*)* (*)* (*)* * * * -0.1 (*)* (*)* (*)* (*)* (*)* (*)* (*)* (*)* * (*)* (*)* (*)* (*)* (*)* (*)* * * 0.0 (*)* (*)* (*)* * * (*)* 0.06 (*)* (*)* (*)* * * (*)* (*)* (*)* * * (*)* -0.7 (*) * * * (*)* (*)* (*)* -0.4 (*) * * * * * (*)* -0.3 (*) * * * * * (*)* (**) (*)* * * (*)* (*) (**) -0.3 (*) -0.0 (*) (*) -0.3 (**) (*) (*) 0.1 (*) 0.39 (*) 0.40 (*) (*) 0.4 (*) 0.7 (*) 0.58 (*) 0.3 (*) (*) 0.1 (*) 0.39 (*) 0.39 (*) (*) 0.4 (*) 0.7 (*) 0.59 (*) 0.4 (*) (**) (*)* (*)* (*)* * * (*)* (Keep.)

20 (Contnuaton.) ge of household s head ged ged 65 or more Sex of household s head Woman Martal status of household head Separated Dvorced Wdowed Never marred Hghest level of educaton completed Second stage of secondary level of educaton Less than second stage of secondary level of educaton Stll at school Tenure status Rent ccommodaton s provded rent-free Constant Sample sze Log lkelhood LR ch Prob > ch Pseudo R Note: ll chldren aged less than 18. (*) Sgnfcant at 95%, (**) Sgnfcant at 90%. (a) Modfed OECD equvalent scale. (1) Germany Italy () (3) (1) () (3) 0.09 (*) 0.1 (*) 0.08 (*) 0.10 (*) 0.09 (*) 0.10 (*) * * * * * * (*) (*) (*) * * * (*)* (*)* (*)* (*) (*) (*) (*) (*) (*) * * * * * * (*) (*) -0.1 (*)* (*)* * * * (*) * * * (*)* -0.0 (*) (**) (*) (*) (*) (**) -0.1 (*) (*) (**) (*) (*) (*) * * * * * * (*)* (*)* (*)* (*)* (*)* (*)* (*) -0.5 (*) (*)* (*)* (*)* (*)* -0.4 (*) * * (*)* (*)* (*) (*) (*) * * * * (*) -0.1 (*) (*) -0.1 (*) -0.1 (*) -0.1 (*) * * * * * * (*) (*) (*) -0.1 (*) -0.1 (*) -0.1 (*) * * * * * * 0.35 (*) (*) 0.30 (*) * * * (*)* (*)* (*)* (34)= (34)=

21 Table 3 PROBBILITY OF REMINING IN THE ECHP LL WVES (ndvdual characterstcs) Total net personal ncome Total net personal ncome squared Man actvty status of adult and aged more or less than 65 Unemployed (aged less than 65) Early retrement (aged less than 65) Other economcally nactve (aged less than 65) Inactve (aged 65 or more) ge of ndvdual squared Sex of ndvdual Woman Women Martal status of adult Separated Dvorced Wdowed Never marred Hghest level of educaton completed of adult Second stage of secondary level of educaton Less than second stage of secondary level of educaton Stll at school Health status of adult Good Far Bad Very bad Constant Sample sze Log lkelhood LR ch Prob > ch Pseudo R (1).70e e (*) 0.06 (*) (*) 0.06 (*) (*) (*) (*) (*) 0.06 (**) 0.08 (*) (*) (13)= Span France Unted Kngdom () (3) (1) () (3) (1) () (3) 3.75e-08 (**) -1.e (*) 0.08 (*) 0.04 (*) * * * * * * * * * * * * (**) (**) (**) * * * * * * * * (**) (**) (**) (**) * * * * * * * * * * * * (**) (**) * * * * * * 0.07 (*) * * * * * * * * * * * * * * * (*) (*) -0.1 (*) -0.3 (*) * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * (*) 3.49e-08 (**) -1.13e (*) 0.09 (*) 0.03 (*) 0.07 (*) (*) (*) -0.1 (*) -0.3 (*) (*) 3.86e-07 (*) -.05e-13 (*) -0.6 (*) (*) (*) 0.1 (*) -0.7 (*) -0.0 (*) -0.4 (*) -0.0 (*) (*) -0.1 (*) -0.1 (*) 4.59e-07 (*) -.37e-13 (*) -0.6 (*) (*) (*) (*) 0.1 (*) -0.7 (*) -0.0 (*) -0.0 (*) -0.6 (*) (*) (*) -0.5 (*) 4.7e-07 (*) -.4e-13 (*) -0.5 (*) (*) (*) (*) 0.1 (*) -0.6 (*) (*) (*) -0.6 (*) (*) (*) -0.6 (*) (**) (**) * * * (**) (**) (**) * * * * * * (**) (**) (**) (**) (*) -0.4 (*) (**) (18)= * * * (**) (**) (**) (**) (**) (**) (**) (**).84e-05 (*) -5.65e-10 (*) (*) (*) (*) 0.15 (*) -0.4 (*) (*) (*) (*) * * * * * * 0.5 (*) (14)= (*) (*) (*) 0.37 (*) (19)= * * * * * * * (*) (14)= e-5 (*) -5.86e-10 (*) (*) 0.8 (*) -0.1 (*) (*) (*) 0.14 (*) (*) (*) (*) (*) (*) e-56 (*) -6.00e-10 (*) (**) 0.8 (*) (*) (*) (*) 0.14 (*) (*) (*) (*) (*) (**) (*) (*) 0.7 (*) (19)= (Keep.)

22 (Contnuaton.) Total net personal ncome Total net personal ncome squared Man actvty status of adult and aged more or less than 65 Unemployed (aged less than 65) Early retrement (aged less than 65) Other economcally nactve (aged less than 65) Inactve (aged 65 or more) ge of ndvdual squared Sex of ndvdual Woman Women Martal status of adult Separated Dvorced Wdowed Never marred Hghest level of educaton completed of adult Second stage of secondary level of educaton Less than second stage of secondary level of educaton Stll at school Health status of adult Good Far Bad Very bad Constant Sample sze Log lkelhood LR ch Prob > ch Pseudo R (*) Sgnfcant at 95%, (**) Sgnfcant at 90%. (1) 5.4e-06 (*) -.55e-11 (*) Germany Italy () (3) (1) () (3) 5.43e-06 (*) -.61e-11 (*) 5.3e-06 (*) -.61e-11 (*) * * * * * * -.0e e e e e e (*) 0.10 (**) (*) (*) 0.15 (*) * * * (*)* (*)* (*)* * * (*)* * * (*)* (*)* (*)* (*)* (*)* -0.9 (*) (*) (*) 0.17 (*) -0.9 (*) (**) (*) (*) (*) (*) (*) * * * * (*)* (*)* * * * 0.13 (*) 0.13 (*) 0.13 (*) * * (*)* (*)* 0.01 * (*)* (*) (*) -0. (*) -0.6 (*) -0.3 (*) (*) -0.0 (*) -0.9 (*) (*) (*) -0.0 (*) -0.9 (*) * * * * * * * * * (*) -0.4 (**) (*) (*) (*) -0.4 (**) (*) -0.4 (**) (*) -0.4 (**) (*) -0.4 (*) * * * * * * * * * * * (**) -0.4 (*) (**) -0.4 (*) (**) -0.3 (*) (*)* (*)* (*)* * * * (*)* (*)* (*)* (*)* (*)* (*)* (*)* (*)* (**) 0.43 (*) (*)* * (*)* * (*)* * * * * * * * 0.37 (**) 0.49 (*) (**) (*) 0.45 (*) 0.3 (*) (*) (*) (*) 0.40 (*) (14)= (19)= (14)= (19)=

23 Insttuto de Estudos Fscales The models constructed wth the sample of adult ndvduals offers up smlar results, except n the case of the sex varable (Table 3). The relatonshps wth ncome, labour status or martal status are smlar to the ones obtaned n the above-mentoned models. In addton, the educatonal attanment varables seem to make lttle contrbuton to mprovng the estmates. The general stuaton does not change when age and health atatus are taken nto account. In order to calculate the longtudnal weghts, we wll use the second submodel, whch excludes educatonal attanment, so as to avod reducng the number of observatons. Nonetheless, t s convenent to test trough senstvty analyss the range of possble varaton wth dfferent weghts. It also seems mportant to compare the longtudnal weghts obtaned through the probt models wth those offered by the Eurostat mcrodata fle. lthough the procedures are apparently smlar, there s no reason for the results to concde. Eurostat recommends usng the so-called base weghts of the last wave ncluded n the analyss (varable rg003 of the mcrodata fles) for longtudnal studes that nclude nformaton on varous waves 5. Eurostat also pont out that n prncple t s possble to modfy these base weghts to take nto account possble attrton, partcularly f t s selectve by age, sex, labour status or any other relevant characterstcs. Eurostat consders that the base weghts for 1996 would be suffcent for a longtudnal analyss that ncludes ndvduals present n the panel s frst three waves. Some authors, however, have questoned the weghts estmated by Eurostat (Peracch, 00). The constructon by Eurostat 6 of the base weghts needed for longtudnal analyses was developed n varous stages, whch are descrbed n nnex 1. The procedure conssts of assgnng sample people some ntal weghts for Wave 1 that are nversely proportonal to the lkelhood of beng selected for the sample on the bass of the sample s ntal desgn. Takng these ntal weghts as a reference and consderng the non-response patterns among successve waves (calculated through a logstc regresson), together wth calbraton procedures that take external controls nto account, the base weghts of the survey s successve waves are obtaned. These weghts take nto account both the sample s desgn as well as the non-response patterns among successve waves. Table 4 shows the correlaton matrx of the dfferent weghts. The seven types of longtudnal weghts respectvely correspond to the weghts offered by Eurostat ( φ E ), the ones estmated usng household and head characterstcs ( φ ), and the weghts estmated usng ndvdual characterstcs 1, φ, φ3 ( B B φ ). The comparson s logcally made by solely takng nto account the 1, φ, φ B 3 5 ECHP UDB Manual: European Communty Household Panel Waves 1 to 8. Survey years 1994 to 001. Eurostat, DOC. PN 168/ Constructon of weghts n the ECHP. Eurostat DOC.PN 165/

24 ndvduals havng complete questonnares. The scant relatonshp of the results wth Eurostat weghts and the ones estmated usng the two types of models s strkng. Ths ntroduces the possblty of obtanng very dfferent results f the estmates are very dependent on the weghtng scheme. Table 4 CORRELTION MTRIX OF LONGITUDINL WEIGHTS Span φ E φ 1 φ E φ φ φ φ B φ 1 B φ φ B 3 Germany φ E φ 1 φ E 10 φ B 1 B B 3 φ φ φ φ φ φ France φ E φ 1 φ E 10 φ B 1 B B 3 φ φ φ φ φ φ Italy φ E φ 1 φ E 10 φ φ φ φ φ φ φ B 1 B B 3 4 φ 3 φ 3 φ 3 φ 3 B φ 1 B φ 1 B φ 1 B φ 1 B φ B φ B φ B φ B φ 3 B φ 3 B φ 3 B φ 3 (Keep.)

25 Insttuto de Estudos Fscales (Contnuaton.) U. Kngdom φ E φ 1 φ E 10 φ B 1 B B 3 φ φ φ 3 φ φ φ φ φ E : Eurostat longtudnal weghts. φ 1 φ B 1, φ, φ φ B,, 3 φ B 3 : Longtudnal weghts from probt models (head and household characterstcs). : Longtudnal weghts from probt models (ndvdual characterstcs). B φ 1 B φ B φ 3 The correlaton among the weghts correspondng to the frst type of models s very hgh for all the countres. The ncluson or not of educatonal attanment does not seem to be relevant. Ths turns out to be a crucal ssue n so far as choosng Model enables us to avod elmnatng a consderable number of observatons n some countres. However, choosng ndvdual nstead of household characterstcs does seem to have great mportance. The correlaton between both types of weghts s postve but moderate, whch could lead to a certan senstvty n the results. s was stated prevously, the possblty of usng all of the sample s observatons suggests employng the second varety of the frst type of models estmated. Ths sub-model s not very senstve to the ncluson or not of other household varables. Its weghts, however, are somewhat dfferent from those resultng from takng nto consderaton strctly ndvdual nformaton. They don t show at all a relatonshp wth Eurostat weghts. smple way of verfyng the relablty of the estmated weghts s to compare the ntal frequency dstrbuton wth the dstrbuton that would result from applyng to the ntal wave the weghtng system estmated for the ndvduals that stayed n the sample durng the whole perod. If the specfcaton of the model used as reference s correct, there should a pror be many concdences between the ntal frequency dstrbuton and the balanced panel s dstrbuton weghted by the factors constructed wth the propensty score. Table 5 shows the frequency dstrbutons of the varous varables for the ECHP s frst wave usng dfferent weghtng systems. The frst column for each country reflects the data of the frst wave of the panel wthout any weghtng at all ( φ = 1). The second column shows the frst wave s frequency dstrbuton weghted wth the cross-sectonal weghts suppled by Eurostat (φ = φ E ). The 5

26 thrd column reflects the same wave s frequency dstrbuton for the balanced panel sub-sample adjusted wth Eurostat s longtudnal weghts. The frst wave s balanced panel frequences adjusted wth the weghts estmated wth the submodel ( φ = φ ) appear n the last column for each country. Frstly, t seems reasonable to compare the frequency dstrbuton of the balanced panel sample s frst wave usng the estmated longtudnal factors (column 4) wth the frst wave s unweghted dstrbuton (column 1). The data for the dfferent countres reveal a hgh degree of symmetry among the frequency dstrbutons for a wde-rangng set of characterstcs. The devatons are very small despte the fact that the ft for each country s dfferent. We can also compare the frequences of the frst wave s balanced panel sample weghted by the longtudnal factors of Eurostat (column 3) wth the frst wave s frequency dstrbuton weghted wth the cross-sectonal weghts also suppled by Eurostat (column ) 7. The overall result s that there s a notable dstance between the orgnal frequences and those resultng from applyng Eurostat s longtudnal weghts to the balanced panel s sample. Ther use entals assgnng a greater relatve weght to specfc populaton categores. In the case of Germany, the Unted Kngdom and France, the rchest decles are gven a greater weght. In the case of Italy and Span, there does not appear to be a clear pattern. There are also remarkable changes regardng the households man source of ncome. In general terms, a greater weghtng can be seen for households havng earnngs as well as a reducton n the proporton of pensoners. There s not a clear common pattern of change for property ncome. Eurostat s weghts also modfy the dstrbuton by household type, wth sngle-ndvdual and sngle-parent households losng weght. The opposte happens wth households havng a greater number of chldren. Dvergences n the dstrbuton by age can also be dscerned when these weghts are appled. The relatve mportance of ndvduals under 65 years of age ncreases, whle that of older people s reduced. Generally speakng, applyng the longtudnal weghts of Eurostat produces a more lmted ft n the categores for whch greater problems of sample attrton were observed. To sum up, dfferent ways of correctng the problem of selectve attrton exst, whch can affect the sample s structure. Ths fact has sgnfcant mplcatons for statc ncome dstrbuton analyses and could a pror have even greater consequences for dynamc analyses. 7 lthough n theory the longtudnal weghts suppled by Eurostat have the same logc as the models we estmate n ths paper, other condtonng factors could n practce ntervene whch are related to the method of estmaton, gvng rse to some dfferences. Lkewse, Eurostat s longtudnal weghts not only make an effort to correct the problem of attrton but also am to correct the ntal wave s non-response bas (see nnex). 6

27 djusted Dsposable Household Income (a). Decles Decle 1 Decle Decle 3 Decle 4 Decle 5 Decle 6 Decle 7 Decle 8 Decle 9 Decle 10 Household head man source of ncome Wages and salares Income from self-employment Pensons Unemployment/Redundancy benefts ny other socal benefts or grants Prvate ncome Household type 1-person household: aged 65 or more 1-person household: aged person household: less than 30 Sngle parents adults wthout chldren Table 5 FREQUENCY DISTRIBUTION OF THE FIRST WVE Span Germany France f = 1 E f = f f = f f = 1 E f = f f = f f = 1 E f = f f = f Wave 1 Wave 1 Balanced panel W1 Balanced panel W1 Balanced Wave 1 Wave 1 panel W1 Balanced panel W1 Balanced Wave 1 Wave 1 panel W1 Balanced panel W1 10,01 10,00 10,00 9,99 10,01 10,00 9,99 10,01 10,00 9,99 9,36 9,67 9,9 9,50 10,15 10,35 9,68 10,10 10,91 10,98 9,9 11,0 10,11 10,1 9,31 11,38 10,73 8,45 9,1 10,19 9,57 10,19 10,35 9,94 9,68 10,10 10,76 9,66 9,69 10,05 10,00 10,01 9,99 10,0 9,98 9,99 10,00 10,00 10,01 9,99 11,47 8,68 9,6 8,64 9,56 9,3 9,8 10,78 10,68 1,4 8, 8,17 9,76 9,07 8,8 10,10 10,68 11, 10,60 13,36 9,54 9,63 10,3 9,93 9,98 10,47 10,11 9,79 9,94 10,8 10,0 9,99 10,01 10,00 9,99 10,00 10,0 10,00 9,98 10,00 9,77 9,57 9,64 9,68 10,0 9,83 10,00 10,34 10,5 10,64 7,57 8,87 9,36 9,64 10,48 10,04 11,07 11,30 11,7 10,40 9,11 9,6 9,83 9,97 10,13 10,50 10,48 10,3 10,38 9,66 57,49 1,44 17,74 4,59 5,84 1,90 57,70 1,6 17,87 4,79 5,38 1,99 61,4 14,15 11,88 4,80 4,74 3,19 57,40 1,49 17,7 4,57 5,85 1,97 7,51 5,46 11,70 3,96,31 4,06 64,1 5,1 18,07 4,03 3,06 5,4 69,64 5,77 13,86 3,37 1,86 5,51 7,45 5,50 11,64 3,90,3 4,18 6,76 7,47 18,93 1,79 6,87,18 61,94 7,40 0,41 1,83 6,17,5 68,55 7,43 16,34 1,15 4,86 1,67 6,81 7,55 18,93 1,76 6,79,16,65 1,48 0,1 0,93 14,14,43 1,41 0,0 0,78 14,63 1,37 1,05 0,03 0,46 10,89,65 1,49 0,0 0,94 14,16 3,3 3,41 1,58,54,61 6,37 6,43,43,77 6,3 4,57 6,30,17 1,03 18,61 3,5 3,68 1,57,5,57 4,30 4,15 1,95 3,45,51 5,10 4,66,19 3,7 4,15,67,77 1,0,5 0,31 4,31 4,0 1,95 3,47,43 (Keep.)