RtSWD Reserch Notes Reserch Note No. 11 Previously relesed s RtSWD Working Pper No. 15 Popultion Aging nd Trends in the Provision of Continued Eduction Regin T. Riphhn, Prvti Trübswetter 2007
Reserch Notes of the Council for Socil nd Economic Dt (RtSWD) The RtSWD Reserch Notes series publishes empiricl reserch findings bsed on dt ccessible through the dt infrstructure recommended by the RtSWD. The pre-print series ws lunched t the end of 2007 under the title RtSWD Working Ppers. The series publishes studies from ll disciplines of the socil nd economic sciences. The RtSWD Reserch Notes provide insights into the diverse scientific pplictions of empiricl dt nd sttistics, nd re thus imed t interested empiricl reserchers s well s representtives of officil dt collection gencies nd reserch infrstructure orgniztions. The RtSWD Reserch Notes provide centrl, interntionlly visible pltform for publishing findings bsed on empiricl dt s well s conceptul ides for survey design. The RtSWD Reserch Notes re non-exclusive, which mens tht there is nothing to prevent you from publishing your work in nother venue s well: ll ppers cn nd should lso pper in professionlly, institutionlly, nd loclly specilized journls. The RtSWD Reserch Notes re not vilble in bookstores but cn be ordered online through the RtSWD. In order to mke the series more ccessible to reders not fluent in Germn, the English section of the RtSWD Reserch Notes website presents only those ppers published in English, while the the Germn section lists the complete contents of ll issues in the series in chronologicl order. The views expressed in the RtSWD Reserch Notes re exclusively the opinions of their uthors nd not those of the RtSWD. The RtSWD Reserch Notes re edited by: Chir of the RtSWD (2007/ 2008 Heike Solg; 2009 Gert G. Wgner) Mnging Director of the RtSWD (Denis Huschk) Contct: Council for Socil nd Economic Dt (RtSWD) Mohrenstrße 58 10117 Berlin office@rtswd.de
Popultion Aging nd Trends in the Provision of Continued Eduction Regin T. Riphhn nd Prvti Trübswetter December 2006 This study investigtes whether the incidence of continued voctionl eduction hs chnged s the Germn workforce commenced n ging process which is expected to intensify. As the lifespn in productive employment lengthens humn cpitl investments for older workers become incresingly worthwhile. Using the dt of Germn popultion survey we describe recent trends in the development of humn cpitl investments nd pply decomposition procedures to the probbility of continued eduction. Holding everything else constnt the shift in the popultion ge distribution by itself would hve led to decline in trining prticiption over the considered period, 1996-2004. However, the decomposition nlyses yield tht behviorl chnges cused n increse in trining prticulrly mong older workers. This is confirmed by multivrite regressions on pooled cross-sectionl dt: the increse in trining probbilities is highest mong older workers. JEL Clssifiction: J24, J10, M53 Keywords: specific humn cpitl investment, trining, popultion ging, demogrphic chnge Correspondence to: Regin T. Riphhn Univ. of Erlngen-Nuremberg Lnge Gsse 20 D 90403 Nuremberg Phone: +49-911-5302-268 Fx: +49-911-5302-178 Emil: Regin.Riphhn@wiso.uni-erlngen.de We grtefully cknowledge finncil support of the RtSWD / BMBF Germny. 0
1. Introduction Are humn cpitl investments relly determined by their expected returns? This study offers n nswer to this importnt question. If expected returns ffect humn cpitl investment we should see investments go up fter increses in returns. The returns to investments in humn cpitl rise when workers sty in the lbor force longer development currently occurring in mny demogrphiclly ging Europen societies, where institutionl nd policy chnges cuse workers to sty ctive longer nd retire lter. In West Germny the verge retirement ge rose from 59.2 to 61.1 yers between 1980 nd 2004 (DRV 2005). As the generosity of the unemployment insurnce for older workers declines, the minimum legl retirement ge increses, nd erly lbor force exit options re bolished, these developments will gin momentum. When workers re in the lbor force longer, it pys more to trin, lso t older ges. We know from existing studies tht the prticiption of workers in continued eduction progrms is described by concve ge profile, with rpid declines in trining probbilities t older ges (cf. Pischke 2001, OECD 1999). We hypothesize tht the negtive ge grdient of the trining incidence flttens s workers become more likely to work t older ges, just s predicted by humn cpitl theory. To test this hypothesis we investigte whether the incidence of trining hs incresed for older workers in recent yers. This issue hs not been ddressed in the literture on trining nd continued eduction so fr. Most studies in this literture focus on the individul nd firm level determinnts of trining nd on trining's returns for both sides of the lbor mrket. Among mny others, Zwick (2005) nlyses the effect of trining for compnies nd Büchel nd Pnnenberg (2004) or Pischke (2001) looked t the recipients of humn cpitl investments. The only contribution which is close in interest to ours is the study by 1
Shields (1998) on chnges in employer-funded trining in the United Kingdom. He uses three cross-section dtsets of the U.K. Lbour Force Survey to study the chnges in the determinnts of the probbility of receiving trining between 1984 nd 1994. He pplies decomposition nlysis in the spirit of Oxc-Blinder nd confirms the key relevnce of ge, eduction, nd industry for the probbility of receiving trining. Over the time of his dt the relevnce of prior eduction incresed nd the ge profile flttened, which is wht we expect for Germny s well. In our nlysis we pply dt from the Germn Mikrozensus of 1996 nd 2004. After describing our smple nd the mesures of trining incidence we first investigte the overll trend. We decompose the observed chnge in trining intensity in order to distinguish the effects of developments in the popultion ge structure from chnges in ge-specific trining probbilities. In second step we perform regression bsed decomposition nlysis, similr to tht performed by Shields (1998). Finlly, we pply multivrite regression nlyses to study first, whether there re trends in the provision of trining to workers over the time of our dt (1996-2004) nd second, whether we find significnt differences in these time trends cross workers' ge groups. Our key findings re, first, tht most of the increse in the overll trining propensity between 1996 nd 2004 flls disproportiontely on older workers, whose propensity to receive trining increses significntly fster over time thn tht of younger workers. Second, chnges in the chrcteristics of workers nd their employments re not the driving force behind the expnsion in continued eduction. Insted, behviorl chnges in the provision of trining mtter. The rising returns to continued trining might be the determinnts of these chnges in trining behvior. 2
2. Dt nd Descriptive Evidence Our nlysis is bsed on dt from the Germn Mikrozensus, which surveys the residents of one percent of ll Germn dwellings. The key dvntge of this dtset is its size. It covers nnul smples of over 800,000 individul observtions. A disdvntge of the dt for our nlysis of continued trining reltes to the wy informtion on trining prticiption hs been gthered. Since 1996 rndom 45 percent of the full smple hs been sked bout trining ctivities. 1 The wording of the question ws chnged repetedly between surveys. Our nlysis compres the trining propensity for the yers 1996 nd 2004, when individuls were sked bout their prticiption in trining for professionl purposes over the course of the lst yer (see Appendix for detils). In our smple we consider individuls ged 25 through 65 who hve been employed s blue or white collr workers or s civil servnts over the course of the lst clendr yer nd worked t lest 35 hours per week. 2 Thus, we observe 52,445 nd 48,904 workers for 1996 nd 2004, respectively. Figure 1 describes the incidence of trining for both yers by ge group. While the overll shift in the propensity to prticipte in continued eduction my t lest in prt be due to the chnged wording of the question, the grph confirms the importnce of ge for prticiption in continued eduction: for both yers the ge grdient is clerly negtive. To render the ge profiles comprble we provide normlized dt for the yer 2004 where ll ge group-specific probbilities re djusted by the constnt rtio of the overll 1996 probbility of trining (8.7 percent) reltive to the overll 2004 probbility (16.9 percent). The normlized line yields first evidence for fltter ge-profile in 2004 thn in 1996. 1 Up until 1990 everybody ws sked, from 1991 through 1995 the question ws nswered on voluntry bsis, nd since 1996 only 45 percent of the smple is required to nswer the question. 2 Apprentices, militry personnel, fmily helpers, nd the self-employed re not included in our smple. 3
Since we re interested in the reltionship between ge nd trining over time we next sk, to wht degree the increse in the trining propensity ws ffected by overll popultion ging nd wht role shifts in the ge-specific trining propensity plyed. 3. Algebric Decomposition of Chnges in Trining We decompose the chnge in the observed probbility of trining between 1996 nd 2004. The probbility of trining in the popultion t time t, P t (tr), cn be described s the weighted sum of ge-specific trining probbilities: t 65 ( tr) = [ P ( tr Age ) P ( Age )] P (1) = 25 t t In consequence, the chnge in overll trining propensities between 1996 nd 2004 cn be the result of both, chnge in ge-specific trining propensities s well s chnge in the popultion ge distribution. This is clrified by the following decomposition: ΔP ( tr) = P04( tr) P96( tr) 65 65 = [ P ( tr Age ) P ( Age )] P ( tr Age ) P ( Age ) = = = = 25 65 = 25 65 = 25 04 [ ] 65 [ P ( tr Age ) P ( tr Age )] P ( Age ) P ( tr Age )[ P ( Age ) P ( Age )] 04 65 [ Δ P( tr Age ) P ( Age )] + [ Δ P( Age ) P ( tr Age )] shift effect 04 96 04 = 25 = 25 + 04 96 96 96 = 25 96 ge structure effect 96 04 (2) We lbel the first prt of this expression the "shift effect" becuse it reflects the shre in ÎP(tr) tht is independent of chnges in the popultion ge structure nd due only to shifts in ge-specific trining probbilities. In contrst, the second prt lbeled "ge structure effect" mesures the prt of the totl chnge, ÎP(tr), tht is due to chnges in the popultion ge structure nd independent of behviorl chnges. We cn decompose the "shift effect" further, to describe the chnges in trining probbilities for specific ge groups: 4
shift = [ ΔP( tr Age ) P04( Age )] ( Age ) + ΔP( tr Age ) ΔP( tr Age ) ( Age ) + δ = ΔP tr = ΔP tr {[ ] P ( Age )} 04 (3) 1 65 where Δ ( tr Age ) = [ ΔP ( tr )] P Age describes the verge shift of ge-specific 65 25 = 25 trining probbilities over time. It would lso cpture the effects of chnge in the wording of the question for verge trining probbilities. The second term of the eqution sums the weighted "specific ge effects", *, for ll ge yers. If the trining propensities hd chnged in exctly the sme mnner for ll ge yers, then ll specific ge effects, *, were zero. If, however, prticulrly older workers receive more trining thn before, we would expect lrger "specific ge effects" * for these older ge groups thn for others. For the ggregte smple we obtin gross increse in the trining probbility of 8.18 percentge points over the considered period. This increse results mostly from n 8.50 point shift effect. The ge structure effect is negtive t -0.32, indicting tht popultion ging by itself would hve reduced the overll trining probbility. The vst shift effect reflects considerble chnge in ge-specific trining probbilities. Applying the decomposition of eqution (3) yields tht most of this chnge is due to n overll increse in ge-specific trining probbilities: the verge shift reches 8.29 points. The sum of the specific ge effects is smll t only 0.21. However, this hides substntil differences cross ge-groups which re depicted in Figure 2: the weighted chnge for most ge-groups up through ge 44 ws zero or negtive. It is the older workers bove ge 45 who experienced most of the increse in their trining probbility. This result grees with our hypothesis. 5
4. Regression-Bsed Decomposition The bove decomposition yielded tht most of the increse in trining probbilities ws not due to shift in the popultion ge structure but to chnge in ge-specific trining probbilities, which went up substntilly between 1996 nd 2004. In this section we choose different pproch to study the increse in trining propensities. Insted of differentiting only the effects of chnged popultion ge structure from chnges in behvior we look t the chnges of ll potentilly relevnt determinnts of trining nd evlute whether chnges in their vlues or lterntively in their ssocition with the incidence of trining re behind the developments. As first step we provide probit estimtes for the probbility of individul trining, seprtely for the two dt yers. The descriptive sttistics on the individul nd employment chrcteristics s well s the mrginl effects of the independent vribles re presented in Tble 1. A comprison of the men vlues of the covrites for the two yers indictes tht the chrcteristics of the smple hve chnged over time. On verge, workers ged nd eductionl ttinment ws higher in 2004 then in 1996. Also, the shre of blue collr workers declined nd tht of white collr workers incresed. The estimtes of the mrginl effects of these chrcteristics indicte some substntil shifts in the vribles' correltions with the probbility of receiving trining over time. The ge effect is estimted s second order polynomil nd therefore difficult to interpret. Bsed on the coefficient estimtes we clculte tht the highest probbility of receiving trining moved ceteris pribus from ge 32.4 in 1996 to ge 36.9 in 2004, confirming our premonitions. The mrginl effects of sex, ntionlity, nd eduction incresed in bsolute vlue between the two surveys, which is similr to the results Shield (1998) found for the United Kingdom. The sme holds for the blue- nd white-collr worker effects nd for the significnt firm size indictors. This suggests tht the sensitivity of trining to its 6
determinnts my hve incresed over time. It is noteworthy tht the pseudo R 2 vlue of the two regressions ws reltively low t 9.4 nd 10.7 percent for 1996 nd 2004, respectively: only smll frction of the overll chnges in the trining probbility is subject to the systemtic impct of the considered determinnts. As second step we now pply version of the Oxc-Blinder decomposition to quntify the reltive impct of chnges in the vlues of explntory vribles nd of chnges in their effects for the overll development of trining propensities over time. We pply the procedure developed by Firlie (1999, 2005) to trnslte the Oxc-Blinder decomposition to sitution with bivrite dependent vrible. Fundmentlly, the effect of chnges in prmeters (") nd covrites (X) re distinguished using eqution (4): {, } + { P( α, X ) P( α X )} ( tr) = P( α X ) P( α, X ) ΔP 04 96 04 96 04 96 96 = prmeter effect + chrcteristics effect ( ) 04, P α 04, X 04 represents the verge predicted probbility of receiving trining, where every worker's chrcteristics (X) re s observed in 2004 nd the prmeters (") of the probit estimtion for 2004 re pplied. The first term ("prmeter effect") considers the differentil in verge trining probbilities tht results when using the 2004 chrcteristics with both the 2004 nd the 1996 prmeter vector. However, we focus on the second term, the chrcteristics effect, which evlutes the effect on trining probbilities when the prmeter vector " is held constnt, e.g. t the 1996 level, nd individul trining probbilities re clculted using different sets of chrcteristics. This second term indictes the extent to which the chnge in trining probbilities over time cn be ttributed to chnges in worker chrcteristics. Insted of using the prmeter vector s of 1996, s in eqution (4), the chrcteristics effect cn lso be evluted t the 2004 set of prmeters ", or t those from pooled regression, yielding different results. Below, we present the results of ll three pproches. An interesting option within this (4) 7
frmework of nlysis is to decompose the chrcteristics effect further nd to mesure the extent to which certin groups of covrites explin the totl chrcteristics effect. To mesure the effect of the group of covrites X k we evlute k k k k k k k k ( X α X ) P( α X + X ) P α. (5) 04 04 + 04 04 04 96 α04 04 Agin, this expression cn be evluted either using the estimtes for 2004 (s in eqution (5)) or for 1996, or for the pooled smple. Ech group of covrites k cn be evluted seprtely nd their individul contributions dd up to the totl "chrcteristics effect" s in eqution (4). The distinguishing feture of the Firlie pproch is tht the verge of individul predictions is clculted insted of prediction t verge covrite vlues, which is usully done (see e.g. Shields 1999). 3 The problem of mtching observtions on X k from different yers is solved using procedure kin to propensity score mtching (c.f. Firlie 2005). The stndrd errors re clculted using the delt method. We pply the Stt9 lgorithm "firlie" provided by Jnn (2006). The results of our nlysis re summrized in Tble 2. Agin, we strt with rw difference in trining probbilities of 8.18 percentge points between 1996 nd 2004. Depending on which set of bse prmeters we use, between 6.3 nd 12 percent of this percentge increse is due to chnges in the chrcteristics of the observed smple (see row 3 of Tble 2). This implies tht most of the chnge cnnot be explined by chnges in the covrite vlues over time. When we investigte the min fctors behind the effect of covrite chnges we obtin the results presented in the bottom prt of Tble 2: the smple ge chnged lot over time, however, it would hve cused mssive decline in probbilities rther thn the observed increse. Insted, just bout ll the other significnt chrcteristic effects help explin the increse in trining probbilities. The lrgest effect 3 In logit model estimted with constnt the verge of the predicted vlues exctly mtches the smple verge, i.e. eqution (4) holds exctly. This is neither the cse for the probit estimtor nor in the stndrd cse where the predicted vlues re clculted bsed on verge covrite vlues. 8
derives from the increse in the workforce's eduction which by itself ccounts for t lest 70 percent of the totl chrcteristics effect (which however ccounts for only 6-12 percent of the totl increse in trining). Importnt other contributors re the distribution of the workforce between blue nd white collr workers, nd civil servnts, where the ltter hve the highest probbility of receiving trining, nd the distribution of workers cross regions. Overll, however, we cn explin only smll portion of the chnges in trining probbilities by looking t worker chrcteristics. This leves bout 90 percent of the difference to be explined by either chnge in employee nd employer behviors, by chnges in the survey design, or by other "unexplined" fctors. 5. Multivrite Anlysis of the Chnge in Trining Probbilities over Time In this section we tke closer look t the dynmics of the chnge in trining probbilities. We explin the probbility of individul trining pplying pooled probit model on nnul dt for the yers between 1996 nd 2004, in order to cpture the developments in the overll trining probbilities s well s ge-group specific developments over time. The dynmics of the chnge in trining probbilities for the different ge groups re modeled by intercting liner time trend with ge-group indictors. As the design of the questionnire slightly chnged over the yers, we use individul yer dummies insted of liner time trend to control for the min time effect. This provides the gretest flexibility to ccount for chnges in nswering behvior nd to cpture the generl trend in trining probbilities. As our dt is designed s repeted cross section, we cnnot pply pnel estimtors. However, following Verbeek (2005), probit model with repeted cross sections cn be estimted using pooled probit estimtion combined with the ssumption 9
tht ny unobserved individul effects plus the rndom error term follow stndrd norml distribution. The results of the probit estimtion nd mrginl effects re presented in Tble 3. The time dummies re generlly highly sttisticlly significnt. They cpture ny differences in the wording of the question over time s well s the overll trend which seems to be upwrd sloping. The ge-group indictors confirm the negtive reltionship between trining probbility nd ge tht we found erlier. The older workers re, the less likely they prticipte in trining mesures. All ge-groups seem to be chrcterized by significnt smller trining probbilities thn the 25-29 yer olds. Our min interest focuses on the interction effects between ge-group indictors nd time trend. The coefficients of the interction effects re sttisticlly significntly different from zero nd yield cler pttern of incresing trining prticiption over time for ll ge-groups. To visulize these developments Tble 4 presents the predicted trining probbilities for mle reference person, who works in Berlin, in firm with more thn 50 employees in the mnufcturing industry, nd hs no schooling degree. The tble describes the predicted trining probbilities cross different ge-groups for both the first nd lst yer of our dt. We observe lrge increse in trining probbilities cross ll ge-groups over time. The increse rnges from 64 percent for the youngest ge groups (25 to 30 nd 30 to 35) to over 200 percent for the oldest ge groups (over 55) (see the lst column). The bottom row indictes tht the chnges in levels over time were ccompnied by chnges in the ge distribution of trining recipients: while in 1996 the chnce of receiving trining ws bout 5 times higher mong those ged 25-30 compred to those bove ge 60, this rtio fell to less thn 3 by 2004. Reltive to younger co-workers the chnce of receiving trining rose strongly for older employees. 10
This exct development is depicted in Figure 3, which shows the trining probbility of the oldest ge group, 60-65, reltive to tht of the youngest ge group, 25-30. The level of trining is much lower for older workers. Their probbility of receiving trining mounts to only 19 percent of tht of young workers in 1996. However, older workers ctch up to 40 percent by 2004. Therefore, even if the level of trining for older workers remins much lower thn tht for younger workers throughout the observtion period, we see very cler development over time. This rising trining propensity for older workers over time my reflect tht firms incresingly employ older workers for longer work-life, most likely becuse they re needed in the production process. 6. Conclusions The objective of the nlyses ws to test whether the probbility of receiving trining incresed for older Germn workers in recent yers. We find both, generl increse in trining probbilities which in prt my be due to chnges in the survey instrument s well s shifts in the ge-specific trining incidence, which is unlikely to be ffected by the wording of the survey question. The overll increse in the incidence of trining is not due to chnge in the popultion ge structure. It ws mostly generl increse in trining probbilities which benefited older workers most, s hypothesized. A regression bsed decomposition nlysis confirms tht most of the chnge over time cnnot be explined by chnges in worker or employment chrcteristics. The overll trining incidence would hve declined in the ging workforce, hd it not been for djustments in conditionl trining probbilities. The nlysis corrobortes tht older workers benefited from disproportionte increse in their trining incidence in recent yers, which is likely to be influenced by incresing returns to humn cpitl investments. From the point of view of humn cpitl theory, postponement of retirement to older ges should increse the 11
trining probbilities prticulrly of older workers. This is confirmed by our estimtion results. Apprently firms djust the provision of trining opportunities in view of the expected employment needs in the production process. 12
References Büchel, Felix nd Mrkus Pnnenberg, 2004, Berufliche Weiterbildung in West- und Ostdeutschlnd, Zeitschrift für Arbeitsmrktforschung 37(2), 71-126. DRV (Deutsche Rentenversicherung), 2005, Durchschnittliche Zugngslter nch Zweigen, downloded Sept.6, 2005 t http://forschung.deutscherentenversicherung.de/forschportlweb/contentaction.do?sttzrid=04fe630a4515a7b9 C1256A390043F804&chsttzr_Rente=WebPgesIIOP905&open&viewNme=sttzr_Rent e#webpgesiiop905 Firlie, Robert W., 1999, The Absence of the Africn-Americn Owned Business: An Anlysis of the Dynmics of Self-Employment, Journl of Lbor Economics 17(1), 80-108. Firlie, Robert W., 2005, An Extension of the Blinder-Oxc Decomposition Technique to Logit nd Probit Models, Journl of Economic nd Socil Mesurement 30(4), 305-316. Jnn, Ben, 2006, firlie Nonliner decomposition of binry outcome differentils, softwre module vilble with Stt 9 (downloded August 3, 2006). OECD, 1999, Employment Outlook, Pris. Pischke, Jörn-Steffen, 2001, Continuous Trining in Germny, Journl of Popultion Economics 14, 523-548. Shields, Michel, 1998, Chnges in the Determinnts of Employer-Funded Trining for Full-Time Employees in Britin, 1984-1994, Oxford Bulletin of Economics nd Sttistics 60(2), 189-214. Verbeek, Mrno, 2005, Pseudo pnels nd repeted cross-sections, mimeo. Zwick, Thoms, 2005, Continuing Voctionl Trining Forms nd Estblishment Productivity in Germny, Germn Economic Review 6(2), 155-184. 13
Figure 1 Trining Incidence by Age Group nd Yer.2.15 P(Tr).1.05 0 25-29 30-34 35-39 40-44 45-49 50-54 55-59 60-65 Age group yer 1996 yer 2004 yer 2004, normlized Note: The normlized line for 2004 divides the entries for 2004 by the fixed rtio of the verge probbility for 1996 over tht of 2004. Source: Own clcultions bsed on Germn Mikrozensus 1996 nd 2004. 14
Figure 2 Age-specific Chnge in the Conditionl Trining Probbility (*).0015.001 delt.0005 0 -.0005 -.001 25-29 30-34 35-39 40-44 45-49 50-54 55-59 60-65 Age group Source: Own clcultions bsed on Germn Mikrozensus 1996 nd 2004. 15
Figure 3 Reltive Predicted Trining Probbility of Older Workers (60-65) Compred to Younger Workers (25-30) (in percent) 40.00 35.00 30.00 25.00 20.00 15.00 10.00 5.00 0.00 1996 1997 1998 1999 2000 2001 2002 2003 2004 yer Source: Own clcultions bsed on Germn Mikrozensus 1996 to 2004. 16
Tble 1 Dt description nd mrginl effects in probit estimtion of the probbility of reporting trining for the smples of 1996 nd 2004 Men Men M.E. M.E. (Std. dev.) (Std. dev.) Probit Probit 1996 2004 1996 2004 Age 41.389 42.767 0.002 0.008** (10.097) (42.767) (1.76) (5.14) Age squred / 100 18.150 19.226-0.005** -0.012** (8.594) (8.420) (4.00) (6.88) Sex (mle=1) 0.673 0.665 0.019** 0.027** (7.94) (7.56) Mritl sttus (mrried=1) 0.684 0.636-0.017** -0.014** (6.84) (4.01) Ntionlity (Germn=1) 0.948 0.947 0.028** 0.058** (5.09) (7.45) Huptschule 0.416 0.323 ref. ref. Mittlere Reife 0.176 0.212 0.037** 0.057** (10.00) (10.73) FH-Reife 0.021 0.038 0.077** 0.085** (8.84) (8.83) Abitur 0.046 0.074 0.065** 0.075** (10.34) (9.83) Polytechn. Oberschule (DDR) 0.132 0.123 0.022** 0.027** (4.43) (3.37) University degree 0.160 0.172 0.060** 0.127** (13.96) (20.09) Schooling missing 0.050 0.057 0.002-0.011 (0.40) (1.33) Civil servnt 0.090 0.085 ref. ref. White collr worker 0.516 0.567-0.013** -0.044** (3.29) (7.37) Blue collr worker 0.394 0.348-0.059** -0.147** (13.10) (22.21) Firmsize 1-10 workers 0.124 0.127 ref. ref. Firmsize 11-19 workers 0.096 0.099-0.003-0.003 (0.66) (0.43) Firmsize 20-49 workers 0.138 0.138 0.012** 0.020** (2.67) (3.00) Firmsize more thn 50 workers 0.634 0.622 0.020** 0.026** (5.48) (5.04) Firmsize unknown 0.008 0.013-0.002-0.028 (0.17) (1.86) Pseudo R-squred 0.0944 0.1066 Notes: The columns entitled M.E. represent mrginl effects, bsolute vlues of z-sttistic re presented in prentheses. ** nd * indicte sttisticl significnce t the 1 nd 5 percent level. Not presented re the mrginl effects for 15 federl sttes nd 10 industries. The estimtion for 1996 ws estimted on smple of 52,445 observtions, the one for 2004 used 48,904 observtions. 17
Tble 2 Results of Regression Decomposition Totl percentge point difference to be explined: 0.0818 Decomposition bse: 1996 2004 Pooled Shre of totl difference explined: 11.8 % 6.3 % 12.0 % Explined effect due to: Age -45.9 % ** -150.2 % ** -42.9 % ** Sex 4.8 % ** 11.6 % ** 5.1 % ** Mritl Sttus 8.9 % ** 29.8 % ** 17.2 % ** Ntionlity 1.3 %** 2.0 %** 1.0 %** Eduction 71.2 % ** 92.6 % ** 70.9 % ** Region of Residence 27.9 % ** 44.1 % ** 23.4 % ** Blue / White Collr / Civil Servnt 37.6 % ** 46.4 % ** 24.3 % ** Firmsize -0.1 % 2.3 % 0.3 % Industry -5.8 % * 21.5 % ** 0.6 % Note: ** nd * indicte sttisticl significnce t the 1 nd 5 percent level. The stndrd errors were obtined using the delt method. 18
Tble 3 Probit Coefficient Estimtes nd Mrginl Effects of the Probbility of Trining (Pooled Dt 1996 to 2004) Probit M.E. time dummies, omitted: 1996 97 0.021 0,0028 (1.73) 98-0.009-0,0012 (0.70) 99-0.291** -0,0323 (19.53) 00-0.297** -0,0329 (18.31) 01-0.302** -0,0333 (16.93) 02-0.339** -0,0366 (17.21) 03 0.313** 0,0493 (15.11) 04 0.282** 0,0436 (12.42) Age group dummies, omitted: 25-29 30-34 -0.079** -0,01 (3.95) 35-39 -0.206** -0,0245 (10.00) 40-44 -0.278** -0,0318 (13.16) 45-49 -0.361** -0,0393 (16.29) 50-54 -0.434** -0,0448 (18.12) 55-59 -0.601** -0,0554 (22.83) 60-65 -0.784** -0,0592 (15.55) Interction effects between ge nd liner trend trend * gegroup 30-34 -0.001-0,0002 (0.41) trend * gegroup 35-39 0.015** 0,002 (4.12) trend * gegroup 40-44 0.016** 0,0021 (4.38) trend * gegroup 45-49 0.023** 0,003 (6.06) trend * gegroup 50-54 0.028** 0,0037 (6.99) trend * gegroup 55-59 0.034** 0,0044 (7.45) trend * gegroup 60-65 0.031** 0,0041 (4.05) Constnt -1.842** (48.52) Notes: The column entitled M.E. represents mrginl effects, bsolute vlues of z-sttistic re presented in prentheses. ** nd * indicte sttisticl significnce t the 1 nd 5 percent level. Not presented re the effects for 15 federl sttes, 10 industries, nd the bove shown personl nd job chrcteristics. The estimtion is bsed on 455,285 observtions over 9 yers (1996 to 2004). 19
Tble 4 Predicted Probbilities bsed on the Probit Estimtion (Tble 3) Age group 1996 2004 Chnge 04/96 (in%) 25-30 0,0750 0,1235 64,68 30-35 0,0643 0,1057 64,44 35-40 0,0515 0,1094 112,60 40-45 0,0444 0,0983 121,40 45-50 0,0378 0,0951 151,68 50-55 0,0325 0,0906 178,76 55-60 0,0224 0,0726 224,74 60-65 0,0142 0,0483 240,56 60-65 s percentge of 25-30 18,89 39,06 106,81 Notes: The reference person is mle. He works in Berlin in firm with more thn 50 workers in the mnufcturing industry. He hs no schooling degree. 20
Appendix Wording of questions nd coding of the indictor for the first nd lst wve (1996 nd 2004) We coded the trining prticiption indictor bsed on these questions of the surveys: 1996 Question EF 293: Do you currently prticipte in voctionl trining, continued eduction or re-trining, or did you do so within the lst four weeks? If nswer is No, question EF 294 is sked: Hve you since the end of April 1995 prticipted in voctionl trining, continued eduction, or re-trining? The indictor ws coded Yes if either question EF 293 or question EF 294 were nswered positively. 2004 Question EF 275: Hve you prticipted in one or severl generl or voctionl trinings, be it course, seminr, conference, or privte instruction, since the end of Mrch of 2003 or re you currently prticipting? If nswer is Yes, question EF 276 is sked: Wht ws the purpose of this trining? (Answer options: professionl / privte.) The indictor ws coded Yes if, both, question EF 275 ws nswered positive nd the nswer to question EF276 ws "professionl". Originl Germn lnguge wording of the questions: 1996 EF 293: Nehmen Sie gegenwärtig n einer beruflichen Ausbildung, Fortbildung oder Umschulung teil, oder hben Sie n einer solchen in den letzten vier Wochen teilgenommen? EF 294: Hben Sie seit Ende April 1995 n einer beruflichen Ausbildung, Fortbildung oder Umschulung teilgenommen? 2004 EF 275: Hben Sie seit Ende März 2003 n einer oder mehreren Lehrvernstltung(en) der llgemeinen oder beruflichen Weiterbildung in Form von Kursen, Seminren, Tgungen oder Privtunterricht teilgenommen oder nehmen Sie gegenwärtig teil? EF 276: Ws ist (oder wr) der Zweck dieser Lehrvernstltung)? (Beruflich / Privt) 21