Migrants as second-class workers in urban China? A decomposition analysis

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1 Mgrants as second-class worers n urban Chna? A decomposton analyss Sylve Démurger, Marc Gurgand, L Sh, Yue Xmng * Ths verson: February 29, 2008 Abstract: In urban Chna, urban resdent annual earnngs are 1.3 tmes larger than long term rural mgrant earnngs as observed n a natonally representatve sample n Usng mcrosmulaton, we decompose ths dfference nto four sources, wth partcular attenton to path dependence and statstcal dstrbuton of the estmated effects: (1) dfferent allocaton to sectors that pay dfferent wages (sectoral effect); (2) hourly wage dspartes across the two populatons wthn sectors (wage effect); (3) dfferent worng tmes wthn sectors (hours effect); (4) dfferent populaton structures (populaton effect). Although sector allocaton s extremely contrasted, wth very few mgrants n the publc sector and very few urban resdents worng as self-employed, the sectoral effect s not robust to the path followed for the decomposton. We show that the mgrant populaton has a comparatve advantage n the prvate sector: ncreasng ts partcpaton nto the publc sector does not necessarly mprove ts average earnngs. The opposte holds for the urban resdents. The second man fndng s that populaton effect s sgnfcantly more mportant than wage or hours effects. Ths mples that the man source of dsparty s pre-maret (educaton opportuntes) rather than on-maret. JEL classfcaton: J71, J31, O15, P23 Keywords: Chnese labor maret, earnngs dfferentals, mgraton, dscrmnaton. * Sylve Démurger: Unversty of Lyon, Lyon, F-69003, France; CNRS, UMR 5824, GATE, Ecully, F-69130, France; ENS LSH, Lyon, F-69007, France ; Centre Leon Berard, Lyon, F-69003, France, demurger@gate.cnrs.fr; Marc Gurgand: Pars School of Economcs and Crest, Pars, France, gurgand@pse.ens.fr; L Sh: School of Economcs and Busness, Bejng Normal Unversty, Chna, lsh@bnu.edu.cn; Yue Xmng: Renmn Unversty of Chna, Bejng, Chna, yuexmng@yahoo.com. Ths paper has benefted from fnancal support from the CEPREMAP Trade and Development program. 1

2 1. Introducton The urban labor maret n Chna has gone through tremendous changes over the last three decades of economc reforms. One of the most dramatc over the recent years s related to rural-urban mgraton that has soared wth the loosenng of admnstratve controls over populaton movements between rural and urban areas. Although t s dffcult to evaluate precsely the actual number of rural mgrants n Chnese ctes, estmatons reported by the Natonal Bureau of Statstcs amount to 132 mllon rural worers n ctes n 2006 (Natonal Bureau of Statstcs, 2007) 1. For decades snce the late 1950s, the overall dstrbuton of the Chnese populaton had been shaped by the strct polcy of the household regstraton (huou) system, whch amed at restrctng mgratons both between rural and urban areas and across regons. The man nsttutonal barrer to moblty was then the excluson of rural resdents from the urban welfare system, whch provded food raton, housng, medcal care, educaton, chldcare, and penson to urban resdents. Ths system made t practcally very dffcult, f not mpossble for rural huou holders to survve n ctes. Economc reforms mplemented from the late 1970s onwards have ncreased both the supply of and the demand for rural mgrants n urban areas. As a consequence, populaton movements have rsen sharply although not smoothly especally durng the 1990s. Labor surplus n agrculture combned wth reduced employment opportuntes n townshp and vllage enterprses, ncreasng demand for labor by the boomng urban prvate sector as well as a central government s polcy of lasser-fare towards rural mgraton frst fostered rural populaton movements to urban areas n the early 1990s. As a consequence, the number of rural mgrants jumped from about 30 mllon n 1989 to 62 mllon n 1993 (L, 2007). However, the reform of State-owned enterprses (SOEs) dramatcally changed the stuaton faced by rural mgrants because mllons of urban lad-off worers entered the urban labor maret after The harder competton on the urban labor maret between urban unemployed and rural mgrants was further renforced by admnstratve regulatons aganst rural mgrants. By the end of the 1990s, several cty governments had mplemented local regulatons to restrct rural mgrants employment and even forced enterprses to lay off mgrant worers n favor of urban local worers. Other admnstratve regulatons ncluded a restrcted access to certan job postons to urban resdents only, or the mposton of fees to 1 Gven that 20% of rural mgrant worers are estmated to lve wth ther famly n urban areas, the total number of rural-urban mgrant populaton s estmated at around 160 mllon n

3 mgrant worers and ther employers (Knght et al. 1999, Appleton et al. 2004, Knght and Yueh 2004a, 2004b, Zhao 2005). Ths offcal admnstratve dscrmnaton aganst rural mgrants prevaled untl recently when the central government ssued a seres of documents explctly requrng local governments to enforce equal opportuntes n employment and rghts for rural mgrants (L, 2007). Ths change n polcy towards rural labor moblty made the flow of rural mgrants jumpng agan from about 80 mllon n 2001 to 132 mllon n As t s often the case when two dstnct labor force groups are competng n a labor maret, the growng partcpaton of rural mgrants n the Chnese urban labor maret rases the ssue of potental dscrmnaton behavors aganst mgrants. And ndeed, varous dffcultes faced by rural mgrants n terms of ncome and worng condtons have been hghlghted n the lterature. Besdes low ncome, the delayed payment of wages s a common feature for rural mgrants. Ther job moblty s much hgher than local urban worers (Knght and Yueh 2004a) and they seldom have a contract sgned wth ther employers. Ther worng condtons are tough, and they usually wor much longer than the legal worng tme n lowend jobs that local urban worers do not want to tae 2 (Yao 2001, L 2007). As emphaszed by Zhao (2005), the huou system stll maes t very dffcult for rural mgrants to enter the formal sector. Measures of perceved dscrmnaton by rural mgrants themselves llustrate these ponts by showng that n many aspects rural mgrants consder that they do not enjoy the same treatment as urban worers. As an example, the Chnese Household Income Project (CHIP) 2002 survey data used n ths paper ndcate that 70% of rural mgrants perceve dscrmnaton n terms of wage pad for equal wor, 71% n terms of type of wor and 61% n terms of worng hours. The dsadvantaged poston of rural mgrants s not lmted to earnngs dfferentals and worng condtons. Agan, accordng to CHIP data, 81% of rural mgrants consder beng dscrmnated aganst n ther chance to be promoted, 82% n housng provson, and 85% n socal securty. Ths paper ntends to contrbute to the understandng of the dscrmnatory behavors aganst rural mgrants by specfcally focusng on the explanaton of earnngs dfferentals between rural mgrants and urban resdents. To that purpose, we use a natonally representatve sample of urban resdents and rural mgrants for the year 2002 and we propose an extended form of Oaxaca-Blnder decompostons to explan the observed earnngs dfferentals between the two populatons. One mportant ssue rased n the lterature 2 The constructon sector s a typcal example here. Accordng to the Project Team of Research Councl, State Councl (2006), data from the 2000 Census ndcate that 80% of all the jobs n the constructon sector are taen by rural mgrants. These jobs are typcally low-slled, hard and dangerous, and as such are not valued by urban resdents. 3

4 concerns the respectve contrbuton of dfferent allocatons nto sectors versus dfferent wages earned wthn each sector, what Lu et al. (2004) refer to as between- and wthnoccupaton wage effect. We explore ths queston by focusng on two possble sources of segregaton: (1) a dfferentated access to sectors (we dstngush here the publc sector, the prvate sector and self-employment); and (2) dfferentated earnngs wthn each sector. Although the evoluton of the labor maret n urban Chna has receved a large attenton, evaluatons of the earnngs gap between rural mgrants and urban resdents n Chna reman lmted, manly because of the paucty of relevant data. Even when adequate data s avalable, ther scope tends to be lmted to a few regons or ctes (Knght et al. 1999, Meng 2001, Meng and Zhang 2001). Gven the huge regonal dfferences across Chna, ths lmtaton maes cross-study comparsons dffcult and any generalzaton rrelevant. The most n-depth analyss of earnngs dfferentals between rural mgrants and local urban worers n Chna to date s certanly that of Meng and Zhang (2001). Usng two comparable household survey data sets for Shangha n 1995, they fnd evdence of dscrmnaton aganst rural mgrants n terms of both occupatonal attanment and earnngs. Followng the methodology of Brown et al. (1980), they analyze the extent to whch earnngs dfferentals between rural mgrants and urban resdents are due to nter- or ntra-occupatonal gaps and fnd that 82 percent of the hourly wage dfferental s due to unequal payment wthn occupaton. Ths paper tres to provde a general overvew of earnngs dfferentals between rural mgrants and urban resdents n Chna, usng data from a natonally representatve sample for 2002 made of comparable surveys for urban resdents and rural mgrants. The data set was collected under the Chna Household Income Project (CHIP), and contans about 8,000 observatons for worng ndvduals. It not only provdes a wder scope than prevous analyses, but also enables the comparson of two sub-populatons that may be n strong competton for jobs n urban Chna. Indeed, rural mgrants surveyed n the CHIP data were selected from resdent communtes (Khan and Rsn, 2005). Although not capturng the wde spectrum of rural mgrants (those lvng n constructon stes and factores were excluded from the samplng process), these data are relevant for the purpose of our study snce the surveyed mgrants, already settled n ctes, can be expected to have characterstcs closer to urban resdents aganst whom they are competng n the labor maret. Furthermore, we adopt a decomposton analyss based on mcrosmulaton that substantally departs from the tradtonal approach based on the Brown et al. (1980) extenson of Oaxaca-Blnder decompostons. Our approach, formally based on sector allocaton models 4

5 allows for the evaluaton of drect as well as ndrect effects of changes n sector allocaton on earnngs dfferentals. In partcular, t shows dfferences n comparatve advantages between sectors for rural mgrants and urban resdents n the urban labor maret. The paper s structured as follows. The next secton presents the decomposton methodology and secton 3 descrbes the data used. Occupatonal dstrbuton and wages and hours structures are dscussed respectvely n secton 4 and 5. Secton 6 presents the results of the decomposton analyss and dscusses the varous effects at stae. Concludng remars are gven n secton Decomposton methodology On average, our dataset shows that urban resdents earn 1.3 tmes as much as rural mgrants n We decompose ths gap nto 4 complementary effects: (1) the effect of dfferent allocatons between self-employment, publc jobs and prvate jobs; (2) the effect of dfferent hourly earnngs structures; (3) the effect of dfferent worng tmes; and (4) the effect of the dstrbuton of observed ndvdual characterstcs n the two populatons. The decomposton s mplemented by frst estmatng job allocaton, earnngs and hours equatons, and then smulatng counterfactual job status, earnngs and hours. The tradtonal approach to decomposton n ths context follows the Brown et al. (1980) extenson to Oaxaca-Blnder decompostons, whch explctly treats dfferences n occupatonal dstrbutons between the two groups under nvestgaton. Ths method has been appled n partcular by Lu et al. (2004) for Hong Kong and Meng and Zhang (2001) for Chna. Our approach, however, s substantally dfferent from the Brown et al. model n that t taes nto account the fact that partcpaton changes have ndrect effects on wthn sector average earnngs, as they affect populaton composton n the sectors. As wll be llustrated, tang ths dmenson nto account may greatly affect the results Model To decompose the dfference n average earnngs between urban resdents and rural mgrants, we start wth the followng model. We consder two groups of worers, urban resdents (u) and rural mgrants (m), who can wor nto 3 dfferent sectors ndexed by = 1, 2, 3 (self-employment, publc sector and prvate sector). If Z s a vector of ndvdual 5

6 characterstcs, the ndvdual latent propensty to wor n sector for a person belongng to group g = {u, m} s assumed to be of the form: P g = Z δ + η where the parameters δ g are group and sector specfc. A person s observed worng n sector f P max { P j } =. j Wthn each sector, hourly earnngs are gven by: g log w = X β + u where X s a subset of Z that contans human captal varables. Worng tme s gven by: g h = Z γ + v These parameters can have varous nterpretatons. As a general settng, the propenstes to be found worng n a sector, as well as the worng tme n that sector, may depend on: () the expected ncome n sector, () ndvdual preferences for sector, and () a restrcted access to some sectors for some groups. Snce the above specfcatons are reduced forms, the parameters δ g and γ g can capture both preferences and constrants. In partcular, a dfference between δ u and δ m can be explaned by occupatonal segregaton (demand drven) between urban resdents and rural mgrants as well as by dfferent preferences (supply drven) across the two populatons. Dfferences n earnngs parameters β g are more readly nterpretable n terms of segmentaton, although they could also reflect compensatng dfferentals. The sector allocaton model s estmated by maxmum lelhood usng a multnomal logt model. Resduals η are thus assumed to be..d, wth a Gumbell dstrbuton (McFadden, 1973). In ths model, the probablty to wor n sector s: Pr( Z ) = g exp( Zδ ) gj exp( Z δ ) j f belongs to group g. The sectoral choce model can also be used to correct for selectvty n earnngs equatons (Bourgugnon et al., 2007). Yet, achevng dentfcaton for sector choce s problematc snce no avalable varable can be consdered as a fully exogenous nstrument. In an attempt to control for possble selectvty bas, we also estmated selectvty-corrected earnngs functons wth avalable mperfect nstruments and found no quanttatve dfference for the general results (see Appendx 3). We therefore present results based on models estmated wthout selectvty correcton (earnngs and hours equatons are estmated by ordnary least squares) to eep the presentaton and dscusson smple. 6

7 2.2. Decomposton To present the decomposton methodology, the above model s embedded nto a more general notaton. If we note δ g the full vector of sector choce parameters specfc to any group g, and β g and γ g accordngly, the observed dfferental n average ncome between the two populatons can be decomposed nto four parts as follows: 1. The part due to dfferent actvty generatng processes (δ u versus δ m ), through the smulaton of the sector n whch urban resdents would be worng f they had the same actvty allocaton rule as mgrants, and nversely. 2. The part due to dfferent hourly earnngs generatng processes (β u versus β m ), through the smulaton of how much urban resdents would be pad f they were pad accordng to the mgrants earnngs generatng model n a gven actvty, and nversely. 3. The part due to dfferent hours generatng processes (γ u versus γ m ), through the smulaton of how long urban resdents would be worng f ther worng tme model was that of mgrants, and nversely. 4. The part due to a dfferent dstrbuton of observed characterstcs Z n the two populatons. Droppng hours for clarty, a typcal decomposton n the Brown et al. (1980) approach would be: y u y m = = 1 3 = 1 3 = 1 w s [ s u ( u, β )[ s m ( u, δ )[ w m ( u, δ ) w u ( u, δ ) s u ( u, β ) w m ( u, β ) s ( u, δ m ( u, β )] m )] m ( m, δ ) w ( m, β m )] u where s ( u, δ ) s the proporton of urban resdents (u) n sector when the sector allocaton rule s δ u u, and w ( u, β ) s the average hourly earnngs of urban resdents actually observed n actvty when the hourly earnngs generatng process s β u. Ths algebrac decomposton wors well when the actvty dmenson s absent, as n the orgnal Blnder-Oaxaca approach. However, ncludng actvty n the decomposton generates composton effects across sectors: by changng the sector allocaton rule (e.g. from δ u to δ m ) whle eepng the rest constant (notably the earnngs generatng process), the average earnngs n each sector s modfed accordngly because the ndvduals allocated to each sector are not the same any more. Ths s part of the actvty effect. In contrast, the above 7

8 u decomposton uses observed average earnngs ( w ( u, β ) ) to evaluate the effect of actvty changes. Such earnngs level has no counterfactual meanngs. Ths s an mportant ssue f some varables do affect the sectoral allocaton dfferently n the urban and the mgrant models. Ths problem s specfc to the ntroducton of actvty choce and does not appear n the orgnal Oaxaca-Blnder approach. As a result, we propose the followng decomposton: y u y m 1 = U 1 U 1 + U 1 + U 1 M 3 u = 1 3 u = 1 3 u = 1 3 u = 1 3 m = 1 where 1[.] s an ndcator varable, u u w ( Z, β )1[ s( Z, δ ) = ] u m w ( Z, β )1[ s( Z, δ ) = ] m 1[ s( Z, δ ) = ][ w u ( Z, β ) w m m w ( Z, β )1[ s( Z, δ ) = ] m m w ( Z, β )1[ s( Z, δ ) = ] m ( Z, β )] (1) u means all ndvduals belongng to the urban resdent populaton and U s the total sze of ths populaton (resp. m and M for mgrants). Lne 1 mnus lne 2 gves the sector allocaton effect (δ u vs. δ m ), the thrd lne gves the earnngs effect (β u versus β m ) and lne 4 mnus lnes 5 gves the populaton effect 3. Implementng ths decomposton requres smulatng ndvdual counterfactual occupatons. To that am, we ntally draw values of η for each ndvdual, condtonal on Z and hs/her observed actvty. We then use these drawn values to determne the allocaton nto counterfactual sectors. For nstance, f ndvdual s a mgrant and has receved ( ˆ1... η ˆ K η compatble wth her observed sector, her urban resdent sector allocaton counterfactual wll u uj δ f ( Z δ ˆ η ) = max { Z δ + ˆ η j } u be [ s( Z, ) ] = plug n resduals û and vˆ based on observed status Earnngs and hours counterfactuals also j A last ssue, often overlooed n the lterature, s path-dependence. The sector allocaton effect n equaton (1) s computed on the urban resdent populaton and usng the urban resdent earnngs determnaton rule β u. But t could also be based on the rural mgrant populaton, or wth β m, or both. There s no reason to expect that the effect wll be dentcal ) 3 If hours had not been dropped for legblty, there would be an addtonal term showng the worng hours effect. 4 Whenever, the ndvdual s not smulated n her orgnal sector, she s gven a resdual value from the destnaton sector observed dstrbuton, such that her ran n her ntal dstrbuton s preserved. 8

9 for all combnatons. The same holds for each term of the above decomposton, so that the contrbuton of the varous terms can be senstve to the chosen path. It s thus necessary to compute every varant and chec the robustness of the results. An nterestng stuaton were path-dependence can be mportant occurs when the optmal sector allocaton rules are very dfferent for the two populatons. In that case, no allocaton s generally superor. Consder for example the case where urban resdents are better pad than mgrants n every sector, but mgrants receve hgher wages n the prvate sector, whereas urban resdents receve hgher wages n the publc sector. Snce urban resdents are far more concentrated n the publc sector than mgrants, the result of movng from δ u to δ m (sector allocaton effect) wll be to decrease the share of the publc sector. Dependng on the model chosen for generatng earnngs, ths shft would ether decrease (urban resdents earnngs model) or ncrease (rural mgrants earnngs model) overall ncome. Ths s a stuaton that wll appear n the data. 3. Data The data used n ths paper has been collected durng sprng 2003 under the Chna household ncome project (CHIP), coordnated by the Insttute of Economcs, Chnese Academy of Socal Scences, wth assstance from the Natonal Bureau of Statstcs (NBS). The urban secton of the household ncome survey contans two dstnct sub-samples, one on urban huou households and the other on households lvng n urban areas wthout urban huou. These rural-urban mgrant households are selected from the same twelve provnces 5 as urban households, but not from all of the ctes ncluded n the urban survey. Snce rural-urban mgrants are mostly concentrated n large ctes, the provncal captal ctes plus one or two medum-szed ctes n each provnce have been selected for the mgrant survey. We restrct our analyss to ctes common to the two sub-samples and to ndvduals aged 16 to 60 who declared worng at least part of the year and earnng wages or ncome from self-employment. The sample contans 4,978 observatons for urban huou worng ndvduals and 3,035 observatons for rural mgrants. The sample scheme for the rural mgrant survey was to allocate 200 households to each provnce n the coastal and nteror regons and 150 households to each provnce n the western regon. Wthn each provnce, 100 households were drawn from the captal cty and 5 The twelve provnces are: Anhu, Bejng, Chongqng, Gansu, Guangdong, Henan, Hube, Jangsu, Laonng, Shanx, Schuan and Yunnan. 9

10 50 households from other ctes. Wthn ctes, only rural-urban mgrant households lvng n resdental neghborhoods were sampled. Ths mples that mgrant worers lvng on constructon stes or n factory dormtores are not accounted for (Khan and Rsn, 2005) 6. Wth lttle outsde nowledge about the dstrbuton of the mgrant populaton by age, gender and locaton, t s dffcult to mae a judgment on how representatve the mgrant data s. Ths judgment also depends on how mgrant households are defned. As ndcated n some statstcs from rural-urban ndvdual mgrants, the majorty of mgrants are sngle worers lvng n dormtores or constructon stes. However, these sngle mgrant worers are not our analyss unt snce they experence temporary and short-term mgraton, wth lower expectaton to settle down wth ther famles n ctes. The mgrant households covered n our sample are rather representatve of long-term mgrants lvng wth ther famly and, as such, more drectly comparable to local urban households. The average length of stay n ctes for rural mgrants s 7.34 years at survey year and 50% have been lvng n ctes for more than 6 years; more than 75% had been stayng n ctes for the whole year. Although the nformaton collected n the two sub-surveys s meant to be consstent (wth smlar questons ased n the two surveys), earnngs deserve partcular attenton. For urban huou holders, questons concernng earnngs are rather comprehensve. As dscussed n the lterature, the CHIP data s partcularly careful wth earnngs measures: although t does not fully account for all frnge benefts provded by the publc sector (such as mplct contrbuton to pensons, health nsurance, or preferental housng rents), t ncludes some mportant non-monetary benefts (e.g. housng, medcal care, chld care and regonal subsdes). For urban huou holders, the earnngs varable s thus defned as the ndvdual ncome of actve worers earned from ther own prvate busness or wor unts 7. For wage-earners, t s the sum of cash labor compensatons (basc salary, bonuses, allowances, subsdes and other wages or ncome) and ncome n nd. For rural mgrants, earnngs are computed from the reported average monthly ncome n 2002 from ther current job and the total (net) ncome from other sources. Avalable data do not allow us to tae ncome n nd nto account for rural mgrants, whch may slghtly bas upward the observed ncome gap between mgrants 6 A full descrpton of the samplng method and the data can be found n L et al. (2007). 7 Measurng ncome for self-employed s a hghly debated ssue. A recent paper by de Mel et al. (2008) compares the relatve qualty of drect reports of profts wth detals of revenues and expenses, and concludes that the former are lely to be more accurate n measurng frms profts. In ths ven, our earnngs varable s based on reported net ncome of prvate busnesses. 10

11 and urban resdents. However, gven that rural mgrants have restrcted access to subsdzed servces, ths should not be a serous ssue. An mportant component of earnngs dfferentals n Chna may arse from dfferences n lvng standards between dfferent ctes. To account for ths ssue, earnngs are adjusted for provncal purchasng power dfferences, usng Brandt and Holz (2006) urban provncal-level spatal prce deflators. Ths adjustment maes cross-provnces data much more comparable than the non-deflated data usually used n the lterature. Table 1 shows statstcs on sector allocaton, average earnngs and worng tme by sector (self-employment, publc sector and prvate sector). Urban resdents annual earnngs are 1.3 tmes larger than rural mgrant earnngs: 11,881 yuan vs. 9,335 yuan. Ths results from a large dfference n hourly wage between the two populatons that s compensated by longer mgrant worng hours. The hourly wage of urban resdents s on average twce that of rural mgrants, the rato beng much hgher n the publc sector (2.3) than n both self-employment (1.3) and the prvate sector (1.5). However, rural mgrants wor on average 69 hours per wee, whereas urban resdents wor on average 44 hours a wee. The fact that rural mgrants, who receve lower hourly earnngs, also tend to wor longer may mply a strong ncome effect n labor supply behavor, but may also result from worng constrants mposed by employers to worers wth lmted negotatng power. Table 1 also shows that occupatonal dstrbutons are extremely contrasted across the two groups and, as such, ths s a potentally mportant source of ncome dfferences, as sectors have dfferent wage-settng structures (Chen et al., 2005). Indeed, there s a very strong concentraton of rural mgrants n self-employment and, to a lower extent, n the prvate wage-earnng sector (respectvely 57% and 36%), whereas urban resdents are overwhelmngly employed n the publc sector (71%) and only slghtly n self-employment (4%). The comparson between the publc and the prvate sector hourly wage structure also reveals an nterestng dfference between urban resdents and rural mgrants. Indeed, whle urban resdents worng n the publc sector get a much hgher hourly wage than those worng n the prvate sector (1.4 tmes hgher), rural mgrants earn slghtly less n the publc sector than n the prvate sector. Table 2 provdes a descrpton of ndvdual characterstcs, whch hghlghts very mportant endowment dfferences between the two groups. Hence, urban resdents are on average older and much more educated (almost 4 years dfference) than rural mgrants. As compared to the Shangha sample used by Meng and Zhang (2001), mgrants n our sample 11

12 are slghtly older (34.31 versus 27.07) and most are marred (90% versus 55%), whch s consstent wth the fact that we are focusng on less temporary mgrants. Urban resdents are also far more often members of the Communst Party and have much more experence than rural mgrants, experence beng measured by the actual number of years of wor n urban areas. Last, n terms of job status, the lower average qualfcaton of rural mgrants s llustrated by ther very low share n whte collar jobs: only 4.5% of rural mgrants hold professonal or techncan postons (to be compared wth 32.7% of urban resdents) and 2.2% are offce worers (aganst 19.6% for urban resdents). 4. Occupatonal dstrbuton As descrbed n secton 2, we can evaluate the extent to whch the occupatonal dstrbuton s based aganst rural mgrants by smulatng the occupatonal dstrbuton of each group usng the other group s sector allocaton model. We frst run a multnomal logt model over the choce of actvty (self-employment, publc sector, prvate sector), whose results are reported n Table 3. Explanatory varables nclude ndvdual characterstcs (educaton, age, gender, communst membershp, geographcal resdence) as well as household characterstcs (household sze, number of chldren less than 6 years old). Educaton nfluences the choce of both urban resdents and rural mgrants towards the publc sector, the estmated effect beng sgnfcantly stronger for urban resdents 8. Ths mples that the urban resdent model selects educated worers nto the publc sector much more strongly than the rural mgrant model does. Moreover, although educaton ncreases the probablty for rural mgrants to wor n the prvate sector as compared to self-employment, t does not sgnfcantly ncrease ther chances to wor n the publc sector as compared to the prvate sector (whch s not the case for urban resdents). The mpact of age on actvty choce only appears sgnfcant for rural mgrants. Estmatons show an nverted U-shape relatonshp between age and the probablty of enterng self-employment: rural mgrants n ther early 40s have the hghest probablty to wor as self-employed. A potental explanaton s that young mgrants enterng the urban 8 Although coeffcents absolute values are not drectly comparable n Table 3, the sgnfcance of the dfference between urban resdents and rural mgrants equatons has been checed by poolng the data and addng nteracton terms for all varables wth a mgrant dummy. 12

13 labor maret mostly start worng n the wage-earnng sector and only swtch to a more rsy poston when they have acqured enough economc, human and socal captal 9. From the multnomal logt model, we can smulate the sector allocaton of each ndvdual n the sample, under the rules that preval n the other populaton. In other words, the smulaton answers the queston: n whch sector would urban resdents (rural mgrants) wor f they were allocated to actvtes accordng to the rural mgrants (urban resdents) model?. Table 4 compares the observed and the smulated margnal dstrbutons. Shftng from the mgrant model to the urban model decreases the share of selfemployment from 57% to 11% f appled to the mgrant populaton and from 50% to 4% f appled to the urban populaton. Inversely, the same model change ncreases publc sector share from 7% to 52% n the mgrant populaton and from 14% to 72% n the urban populaton. The fact that the ampltude of these effects s senstve to the populaton ndcates that contrasted occupatonal dstrbutons are only partly explaned by a segregaton (or model) effect and that populaton characterstcs do play a role. However, t s nterestng to note that the dstrbuton of occupatons based on the rural mgrant model s much less senstve to populaton changes than the dstrbuton based on the urban model. Ths suggests that observed ndvdual characterstcs play a stronger role n the urban resdent model than n the rural mgrant model, as was already apparent from Table Earnngs and hours structures Sx earnngs and hours equatons have been estmated, for self-employment, the publc and the prvate sectors, and for the two populatons (see Appendx A1 and A2). Table 5 provdes a synthetc vew of the correspondng structures 11. In order to neutralze wthnpopulaton composton effects, smulated hourly earnngs (and worng hours) are computed separately for the whole urban and mgrant populatons, and for each of the sx selfemployment/publc/prvate urban/mgrant model combnatons. For nstance n panel A, the frst row shows n the frst column, the average hourly earnngs for the whole urban resdent populaton under the urban/self-employment earnngs model (.e. based on β u,self ), and n the second column, the average hourly earnngs for the whole urban resdent populaton under the mgrant/self-employment earnngs model (.e. based on β m,self ). It ndcates that, f pad 9 Ths result s consstent wth Meng (2001) who fnds that, n 1995, rural mgrants n Jnan cty are more lely to be self-employed n the nformal sector as ther cty wor experence ncreases. 10 In ths respect, the populaton effect n the decomposton should be stronger whenever based on the urban occupaton model (see secton 6). 13

14 accordng to the urban rules, the urban populaton would earn 3.90 yuan per hour on average n self-employment, whereas, accordng to the mgrant rules, the same populaton would earn only 3.11 yuan per hour n the same sector. Unsurprsngly, whatever the earnngs model, the smulated wage for the urban populaton (left table) s always hgher than the correspondng smulated wage for the mgrant populaton (rght table). Hence, for any wage structure, rural mgrants earn less than urban resdents, whch s clearly a composton effect. Table 5 also shows that the urban resdent s earnngs structure s always more favorable than the mgrant s earnngs structure when appled to the urban populaton, but not when appled to the mgrant populaton. Indeed, accordng to the urban resdent earnngs model, the average hourly earnngs for the urban populaton would be 3.90 yuan n selfemployment, 5.92 yuan n the publc sector and 4.93 yuan n the prvate sector, whereas accordng to the rural mgrant earnngs model, the correspondng average hourly wage for the same populaton would respectvely be only 3.11 yuan, 5 yuan and 3.52 yuan. Results for the mgrant populaton hghlght a dfferent pattern snce, n the prvate sector, the mgrant model s actually more favorable to mgrants than s the urban resdent model: the smulated hourly wage under the mgrant earnngs model (2.83 yuan) s hgher than the smulated wage under the urban resdent earnngs model (2.61 yuan). Another nterestng result s that the publc sector always pays better than selfemployment and the prvate sector, except for mgrants under the mgrant model. Indeed, n the mgrant model, both self-employment and the prvate sector are more favorable to mgrants (wth a smulated hourly wage of respectvely 2.90 yuan and 2.83 yuan) than s the publc sector (2.59 yuan per hour). These results suggest that mgrants may have a comparatve advantage wth respect to self-employment and the prvate sector. Snce ths feature does not apply to the urban resdent populaton, t s certanly related to some specfc combnatons of productve characterstcs. One explanaton les n the nature of publc jobs offered to mgrants and n returns to human captal. Indeed, rural mgrants generally hold low-end non-tenured jobs n the publc sector, whch are very poorly pad on average, but wth some returns to educaton. On the other hand, self-employment and the prvate sector provde better pad jobs to mgrants, but wth smaller 11 The smple structure of weely hours gven n panel B does not deserve much explanaton and wll not be dscussed here. The man result s that worng hours are longer n self-employment and the prvate sector, as well as n the mgrant model, wth no excepton. As urban resdents are more concentrated n the publc sector, ths provdes two reasons for the lower average worng hours observed n ths populaton. 14

15 returns to educaton 12. As a result, n a populaton wth a low educaton level, hgher returns to educaton n the publc sector do not mae up for low baselne wages: publc wages are lower on average. Hence, rural mgrants are relatvely better off n self-employment and the prvate sector where the returns to human captal are lower for them. In the more educated urban populaton, a hgher return to schoolng ensures that publc wages are hgher on average. As mentoned n secton 2, ths feature s lely to generate strong path-dependence n the sectoral decomposton because shftng mgrants away from self-employment wll not always mae them better off. 6. Decomposton analyss Puttng all these elements together, we can decompose the earnngs dfferental between urban resdents and rural mgrants nto actvty, earnngs, hours and populaton effects. As mentoned n secton 2, there are several paths to the decomposton. For nstance, the effect of changng the sector choce model can be computed ether on the urban or on the mgrant populaton, and n each case, usng ether urban or mgrant earnngs and hours models. Ths results n 8 dfferent possbltes. To start wth an overvew, Table 6 presents the average effects over all paths, both n absolute value and as a percentage of the observed gap. The average observed dfference n annual earnngs s 2,546 yuan. If the two populatons dffered only by ther allocaton nto sectors, ths dfference would be only -32 yuan on average, or 2% of the total dfference. Unsurprsngly, movng from the mgrants hourly earnngs model to the urban resdents hourly earnngs model would ncrease the earnngs gap to 1,162 yuan (46% of the total). Inversely, everythng else equal, mgrants would earn 2,068 yuan more than urban resdents as a result of ther much longer worng tme (82% of the total). Fnally, the strongest effect s related to dfferences n observed characterstcs between the two populatons: by tself, t generates a 3,487 yuan earnngs dfference. In a nutshell, ths means that gven the sgnfcant worng tme effect, urban resdents would not earn much more on average f they dd not have much better endowments, such as educaton and cty wor experence. Ths s renforced by the fact that part of the hourly earnngs effect may also capture unobserved productve characterstcs that are not evenly dstrbuted n the two populatons (and should belong to the populaton effect) Table A1 llustrates these dfferences n returns to schoolng across sectors for mgrants. 13 A common lmtaton of the earnngs dfferentals lterature s that the constants ncorporate dfferences n means of unobserved characterstcs across populatons. In ths respect, we arbtrarly ncorporate nto 15

16 There are, however, several sources of uncertanty over the meanng of these averages. One s path dependence. Another comes from the fact that all counterfactual earnngs are based on estmated parameters: f these parameters are not precsely estmated, we may well shft on one sde or the other by mere chance. Therefore, t s mportant to tae nto account the varances of the estmators. Fnally, some resduals follow from random draws, whch brngs addtonal randomness. In order to assess the robustness of our results, we have bootstrapped (200 tmes) the data so as to generate a dstrbuton of occupaton, earnngs and hours equaton parameters. For each of the 200 teratons, we have drawn new resduals and computed the effects along all possble paths. Fgures 1 to 4 draw the dstrbuton of each of the four decompostons presented n Table 6, expressed as a percentage of the observed earnngs gap. Each fgure shows the full dstrbuton for the dfferent paths. For example, Fgure 1 shows the dstrbuton of the actvty effect for the four possble paths: the urban populaton under the urban earnngs/hour model (urbpop/urbwage), the urban populaton under the mgrant earnngs/hour model (urbpop/mgwage), the mgrant populaton under the urban earnngs/hour model (mgpop/urbwage), the mgrant populaton under the mgrant earnngs/hour model (mgpop/mgwage). The sgn of the hours and populaton decompostons (Fgures 3 and 4) s robust, although the populaton effect s rather senstve to the model of reference, as antcpated n secton Both the actvty effect and the hourly earnngs effect deserve specfc attenton. Fgure 1 and Table 7 ndcate that the small average actvty effect actually hdes strong path dependence. They both show the effect on total earnngs of movng from the mgrant to the urban occupaton model, when appled alternatvely to the urban and the mgrant populaton and usng the urban or the mgrant earnngs and hours structures. The effect s clearly postve when appled to the urban populaton usng the urban earnngs structure. In contrast, t s clearly negatve when appled to the mgrant populaton usng the mgrant earnngs structure. Indeed, the effect of shftng from mgrant actvty (e.g. self-employment) to urban resdent actvty (e.g. publc sector) ncreases total earnngs, whereas the effect of beng more nto the publc sector decreases ncome under the mgrant wage model. The man reason for ths negatve effect has been antcpated n secton 5: mgrants have a comparatve advantage n dfferences n wage and partcpaton structure (δ, γ, and β) across the two populatons, what may n fact belong to an unobserved composton effect. As there s usually no natural experment able to create exogenous varatons n group dentty, ths s a general dentfcaton problem n the segmentaton/dscrmnaton lterature. 14 There are only two paths for the populaton decomposton because we have only computed exact decompostons for the sae of nternal consstency: populaton change s computed once changes n all other parameters have been ntroduced, so that they rely ether on all urban parameters or on all mgrant parameters. 16

17 the prvate sector or self-employment gven ther earnngs generatng structure. Snce the urban occupaton rules mply fewer people n self-employment and the prvate sector and more n the publc sector, these rules are suboptmal for mgrants under the mgrant wage structure, and would mply lower ncomes on average. Our results corroborate Meng and Zhang (2001) fndngs of a small mpact of occupatonal segregaton on the earnngs gap between mgrants and urban worers n Shangha, but they also hghlght the possblty of a strong path dependence that reveals nterestng patterns. From Table 7, t seems that usng the urban populaton and the mgrant wage model generates a strong postve effect. However, Fgure 1 clearly shows that ths s an average over a very mprecse smulaton, drven by a large rght tal. As a result, the actvty decomposton lacs robustness manly because t s extremely path dependent and, to some extent, because of statstcal mprecson. Regardng the hourly earnngs effect, Fgure 2 shows generally postve effects, although small and qute mprecse when appled to the mgrant populaton usng the mgrant actvty structure. Indeed, the urban resdent earnngs structure s most of the tme more favorable, but the prvate sector pays better under the mgrant model for the mgrant populaton (Table 5). The mpact of dfferent hourly earnngs structures s small when the prvate sector has a lmted weght (.e. under the urban actvty model) but t s strong under the mgrant actvty model. Fgures A1 to A4 n Appendx 3 show the robustness of these results to the ncluson of selectvty correcton n the earnngs equatons, wth the actvty decomposton beng agan very path dependent. The man dfference les n the fact that the dstrbutons have much larger varances wthn each path, whch comes from the fact that the selectvty model s less precsely estmated. Fnally, t should be noted that employment n the publc sector encompasses a varety of statuses. For urban resdents, 95% are tenured jobs, most of the tme as cvl servants. However, rural mgrants employed n the publc sector are mostly under short-term contracts. As such, some of the dfferences n the publc wage structures between urban and mgrant employees may result from contrasted employment status and could arguably be nterpreted as sectoral effects rather than wage segmentaton. Therefore, we have reproduced the whole estmaton and smulaton procedure wth all non-tenured publc jobs allocated to the prvate sector category 15. As shown n Table A4, the decomposton s not affected by ths defnton 15 We are left wth only 2% of the mgrant populaton n tenured publc jobs (nstead of 7%). 17

18 change: average effects are smlar n magntude and the small actvty effect s agan the result of contrasted paths. 7. Concluson Ths paper assesses the sources of the strong ncome dfferences between urban resdents and long term rural mgrants n contemporary urban Chna, usng natonally representatve data. In partcular, we dsentangle the effect of dfferent earnngs structures wthn self-employment, the prvate and the publc sectors from the effect of a dfferent allocaton nto sectors wth dfferent payments. Ths s mportant because mgrants access to the publc sector s very restrcted, so that ths could be expected to be an mportant source of ncome dfferences. A decomposton analyss based on mcrosmulatons ndcates that despte a much contrasted sectoral allocaton, the mpact of sector allocaton on earnngs dfferences s nether strong nor robust. We fnd a stronger, but only partly robust wthn sector earnngs dscrmnaton effect between urban resdents and rural mgrants. Explanatons of these results can be found n the fact that the sector allocaton and, to a lesser extent, the earnngs effects, are path dependent n the decomposton because rural mgrants have a comparatve advantage nto self-employment and the prvate sector: shftng nto the publc sector s not always advantageous to them, whereas t s for urban resdents or usng the urban resdent earnngs structure. Ths result may cast doubt on the lterature that concludes to lmted sectoral effects on wage contrasts wthout checng path dependence. Our fndngs on a segmented labor maret between urban resdents and rural mgrants that reflects dfferent comparatve advantages are consstent wth prevous studes based on smaller datasets. Usng data on 2,900 mgrants surveyed n 1995 n 118 enterprses located n four ctes, Knght et al. (1999) fnd that urban resdents and rural mgrants are hghly mperfect substtutes n urban frms producton functon. Rural mgrants are both able to bear hardshps and easly manageable, two assets that mae them accept jobs that non-mgrants would not. Usng data on 1,500 mgrants n Jnan cty n 1995, Meng (2001) fnds that among rural mgrants, those who possess hgher human captal are more lely to be self-employed n the nformal sector and are better off than those who wor n the formal sector, whch s consstent wth our fndngs. Are rural mgrants second-class worers n urban Chna? Our analyss suggests that segregaton n terms of both access to jobs and on-the-job earnngs s not the major 18

19 explanaton for a large share of earnngs dfferences between urban resdents and rural mgrants n 2002 as compared to dfferences n endowments. The strongest source of earnngs dfferences s ndeed found to be related to dfferences n populaton structures. The two populatons are substantally dfferent: rural mgrants are younger, much less experenced and much less educated than urban resdents. Pre-maret dscrmnaton, resultng manly from lower educaton opportunty n rural areas, s thus more mportant n explanng earnngs dfferences than any form of on-maret dscrmnaton resultng from sector allocaton or earnngs generatng processes. The ey polcy mplcaton of ths result s to emphasze the mportance of publc polces towards rural educaton n order to reduce the endowment gap between rural mgrants and urban resdents n the urban labor maret. References Appleton, Smon, John Knght, Lna Song and Qngje Xa (2004) Contrastng Paradgms: Segmentaton and Compettveness n the Formaton of the Chnese Labor Maret, Journal of Chnese Economc and Busness Studes 2(3): Bourgugnon, Franços, Martn Fourner and Marc Gurgand (2007) Selecton bas correctons based on the multnomnal logt model: Monte-Carlo comparsons, Journal of Economc Surveys 21(1): Brandt, Loren and Carsten A. Holz (2006) Spatal Prce Dfferences n Chna: Estmates and Implcatons, Economc Development and Cultural Change 55(1): Brown, Randall S., Marlyn Moon and Barbara S. Zoloth (1980) Incorporatng occupatonal attanment n studes of male-female dfferentals, Journal of Human Resources 15(1): Chen, Y, Sylve Démurger and Martn Fourner (2005), Earnngs dfferentals and ownershp structure n Chnese enterprses, Economc Development and Cultural Change 53(4): de Mel Suresh, Davd J. McKenze and Chrstopher Woodruff (2008) Measurng Mcroenterprse Profts: Must we as how the sausage s made?, Journal of Development Economcs do: /j.jdeveco Khan, Azzur R. and Carl Rsn (2005) Chna s household ncome and ts dstrbuton, 1995 and 2002, The Chna Quarterly 182: Knght, John and Lna Song (2005) Towards a Labour Maret n Chna, Oxford: Oxford Unversty Press. 19

20 Knght, John, Lna Song and Huabn Ja (1999) Chnese Rural Mgrants n Urban Enterprses: Three Perspectves, Journal of Development Studes, 35(3): Knght, John, and Lnda Yueh (2004a) Job moblty of resdents and mgrants n urban Chna, Journal of Comparatve Economcs 32: Knght, John, and Lnda Yueh (2004b) Urban nsders versus rural outsders: Complementarty or competton n Chna s urban labor maret?, Department of Economcs, Dscusson Paper Seres 217, Unversty of Oxford. L, Sh (2007) Rural Mgrant Worers n Chna: Scenaro, Challenges and Publc Polcy, School of Economcs and Busness, Bejng Normal Unversty. L, Sh, Chulang Luo, Zhong We and Xmng Yue (2007) 1995 and 2002 Household Surveys: Samplng and Data descrpton, n B. Gustafsson, L Sh and Terry Scular (eds.), Inequalty and Publc Polcy n Chna. Cambrdge Unversty Press, forthcomng. Lu, Pa-Wa, Junsen Zhang and Shu-Chuen Chong (2004) Occupatonal segregaton and wage dfferentals between natves and mmgrants: evdence from Hong Kong, Journal of Development Economcs 73: McFadden, Danel (1973) Condtonal logt analyss of qualtatve choce behavor, pp n P. Zaremba (ed.), Fronters n Econometrcs, Academc Press, New Yor. Meng, Xn (2001) The Informal Sector and Rual-Urban Mgraton A Chnese Case Study, Asan Economc Journal 15(1): Meng, Xn and Junsen Zhang (2001) The Two-Ter Labor Maret n Urban Chna Occupatonal Segregaton and Wage Dfferentals between Urban Resdents and Rural Mgrants n Shangha, Journal of Comparatve Economcs 29: Natonal Bureau of Statstcs (2007) Stuaton of rural mgraton n Chna n Internal Research Report No. 18. Project Team of Research Offce, State Councl (2006) Research Report of Rural Mgrant Worers n Chna, Chna Yansh Press. Yao, Yang (2001) Socal Excluson and Economc Dscrmnaton: The Status of Mgrants n Chna s Coastal Rural Areas, Worng Paper No. E Bejng: Chna Center for Economc Research, Peng Unversty. Zhao, Zhong (2005) Mgraton, Labor Maret Flexblty, and Wage Determnaton n Chna: A Revew, The Developng Economes, 43(2):

21 Table 1 Earnngs, worng tme and actvty of urban resdents and rural mgrants n 2002 Urban resdents Rural mgrants Mean or % Std. Dev. Mean or % Std. Dev. Annual earnngs 11,881 7,713 9,335 13,387 Self-employed 10,223 12,015 10,077 11,536 Publc sector 12,742 7,435 6,967 5,139 Prvate sector 9,639 7,061 8,625 11,929 Hourly wage Self-employed Publc sector Prvate sector Weely worng tme Self-employed Publc sector Prvate sector Actvty Self-employed 4.16% 56.97% Publc sector 71.47% 7.08% Prvate sector 24.37% 35.95% # of obs. 4,978 3,035 Source: CHIP data, authors calculaton. 21