INFORMAL EMPLOYMENT IN DEVELOPING ECONOMIES: MULTIPLE HETEROGENEITY 1

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1 INFORMAL EMPLOYMENT IN DEVELOPING ECONOMIES: MLTIPLE HETEROGENEITY 1 Natala Radchenko 2, Amercan nversty, Washngton, DC 2015 ABSTRACT Ths paper contrbutes to the lterature on the nature of nformal employment n developng economes. Drawng on the model wth essental heterogenety, t offers a lst of scenaros descrbng the behavoural patterns whch nformal workers follow. The lst nests not only classcal patterns of a ratoned formal sector versus an ntegrated labour market, but also dfferent patterns of ratonng. sng non-parametrc technques and data from a few Afrcan economes wth dfferent levels of development, the paper proposes emprcal case studes fttng varous nformalty schemes. Developng economes show dsparate patterns of allocaton of workers and varous patterns of ratonng. JEL Classfcaton: C51, J24, J31, O17 Keywords: Afrcan Economes; labour market segmentaton; nformal employment; wage dfferentals; occupatonal choce; essental heterogenety; margnal treatment effect. 1 Grateful acknowledgment to Franços Gerard for useful dscusson. Computng resources used for ths work are provded by the Amercan nversty Hgh Performance Computng System, whch s funded n part by the Natonal Scence Foundaton (BCS ); see for nformaton on the system and ts uses. 2 E-mal : natalar@amercan.edu. Tel: (001) Fax: (001) Address: Amercan nversty, 4400 Massachusetts Ave NW, Kreeger 104, Washngton DC, , SA. 1

2 1. Introducton A fundamental queston related to labour regulatons n the context of nformal labour s the nature of nformal employment and the mechansms drvng expanson or reducton of nformalty. The queston s partcularly mportant n developng economes, where the phenomenon of nformalty s wdespread and ts mechansms have engendered debate n the lterature for several decades. The most recent lterature suggests heterogenety of nformal employment n developng economes (Felds, 1990; Cunnngham and Maloney, 2002; Dmova et al., 2010; Gunther and Launov, 2012; Bargan and Kwenda, 2014; Radchenko, 2014). Heterogenety mples here that nformal employment conssts of both a ter that s constraned to hold an nformal rather than formal job and a ter that chooses nformal employment. The frst ter fts the dual market model assumng two dstnct segments of the labour market: a formal segment payng hgh wages and provdng job securty as well as socal securty and an nformal sector payng low wages and servng as a last resort to unemployment (Lews, 1954; Harrs and Todaro, 1970; Todaro and Smth, 2003; Felds, 2005a). The second ter s assocated wth an ndvdual s cost-beneft analyss and stems from the voluntary choces of workers (Rosenzweg, 1988; Maloney, 1999, 2004). The majorty of studes emprcally testng the relevance of segmentaton look for groupng effects ndcatng the presence of the two non-ntegrated sectors usng fully parametrc methods (Dckens and Lang, 1985; Heckman and Hotz, 1986; Magnac, 1991; Basu, 1997; Cunnngham and Maloney, 2001; Pratap and Quntn, 2006; Dmova et al., 2010; Gunther and Launov, 2012). Among the man fndngs are heterogenety of workers n terms of human captal, unobserved sklls and dfferent returns to human captal n dfferent segments of the labour market. sng Egyptan household survey data provded by the ELMS household survey, Radchenko (2014) suggests an nnovatve method of analyss by drawng on the model wth essental heterogenety recently proposed by Heckman et al. (2006) and the non-parametrc technques they propose to estmate the model. In addton to dentfyng dfferences n returns to the observable human captal and unobservable sklls of formal and nformal workers, the model allows for one more heterogenety dmenson relatng to ndvdual dfferences n returns to unobservable characterstcs from formal versus nformal employment. Radchenko (2014) shows that the dstrbuton of ndvdual dfferences n unobservable returns from holdng formal rather than nformal job and ts relatonshp to the allocaton process between formal and nformal employment can be assocated wth varous mechansms drvng nformal employment. 2

3 Ths paper bulds on Radchenko s (2014) study whle extendng t n several ways. Frst, t proposes a broader range of scenaros descrbng dfferent behavoural patterns whch nformal workers follow and that are compatble wth dfferent knds of emprcal patterns allowed by the model wth essental heterogenety. Second, unlke Radchenko (2014) whch focuses on a lower-mddle - ncome economy (Egypt s rank accordng to the World Bank classfcaton), the paper offers case studes of an upper-mddlencome economy (South Afrcan) and a low-ncome economy (gandan). Addtonally, t dscusses the dstrbuton of excluson varables requred to dentfy the treatment parameters and offers a senstvty analyss related to the Egyptan case study. The dfferent economes show varyng patterns of allocaton of workers between formal and nformal employment. Moreover, they show varous patterns of ratonng. Thus, the paper contrbutes to the lterature by showng that n terms of workers socal welfare, effcency and neffcency of allocaton between formal and nformal employment s not necessarly assocated wth voluntary and nvoluntary engagement n the nformal segment. Even n the framework of ratoned formal employment, allocaton of workers between the two segments can be effcent. Ths s dfferent from the majorty of work on the heterogenety of nformal employment (Felds, 1990; Cunnngham and Maloney, 2002; Dmova et al.,2010; Gunther and Launov, 2012; Radchenko, 2014) focusng on wthn- economy heterogenety and the neffcency of nformal employment wthout consderng a varety of schemes of ratonng. The paper s organzed as follows. Secton 2 presents the data and dscusses the man features of the Afrcan economes used n the case studes. Secton 3 outlnes the model wth essental heterogenety n the framework of formal and nformal employment and ts relatonshp to varous treatment effects. Secton 4 dscusses the mplcatons of the model n terms of effcency of the allocaton of workers nto dfferent employment groups. Secton 5 dscusses the man emprcal results. Secton 6 concludes. 3

4 2. Data and Descrptve Statstcs 2.1 Data Samples The data samples used n the study come from the South Afrca 2011 Quarterly Labor Force Survey (QLFS 2011) and two waves from the ganda Natonal Panel Survey (MPS 2009/2010 and MPS 2010/2011). The QLFS s desgned to be representatve at the provncal level and wthn provnces. The sample sze s 3080 Prmary Samplng nts (PSs). It contans households or about ndvduals. Snce QLFS 2011 does not contan quarter dentfers, the data s averaged over the year. An advantage of averagng procedure s smoothng the data and reducng the nose comng from measurement errors or outlers. The MPS data set s natonally representatve. MPS 2009/2010 and MPS 2010/2011 are the survey rounds run over from approxmately 3000 gandan households. The samples n use are composed of ndvduals who are between 15 and 64 n age and engaged n the labour market. The South Afrca data provdes an ndcator of nformal employment. South Afrca Statstcs uses the largest defnton based on job-based concept and coverng all workers n the nformal sector as well as nformal workers of the formal sector. The nformal sector ncludes employees workng n establshments that do not deduct ncome tax from ther salary/wage and employers or own account workers who are not regstered for ether ncome tax or value-added tax. Informal workers of the formal sector are employees n the formal sector and persons employed n prvate households who are not enttled to basc benefts such as pensons or medcal ad and who do not have a wrtten contract of employment. The gandan data do not provde an ndcator of ndcator but do contan nformaton on taxaton. Based on ths nformaton, nformal employment s dentfed here as consstng of workers whose employers do not deduct or pay ncome tax from the salary and employers and ndependent workers not regstered for ncome tax. The gandan data suffer from hgh rates of non-response: out of 5000 workers reportng ther actvty, about 2000 responded to the queston on tax payment. Among these, less than 20 per cent have reported t twce, when questoned n both the 2009/10 and 2010/11 surveys. Thus, the resultng sample n use does not have a panel dmenson but rather represents pooled cross-sectons. 4

5 2.2 Labour Market Features Table 1 shows the dstrbuton of the workng-age populaton between employed, unemployed and nactve groups n the orgnal QLFS and MPS samples. The table also dsplays the sample dstrbuton of demographc characterstcs and educaton across dfferent groups and mean wages n the formal and nformal sectors. The unemployed and nactve parts of the South Afrcan workng-age populaton are younger than the employed populaton: the average age n ths group s 30 years old whle the average age of employed workers s 38. The average educaton of the non-workng populaton s the same as that of nformal sector (10-12 years). The formal sector conssts of more hghly educated workers. In contrast wth nformal and unemployed workers, whte workers make up a sgnfcant fracton of the formal group (16 per cent versus 2-5 per cent n other groups). Moblty between formal and nformal employment s low: about 5 per cent of workers transted from one group to another wthn a year; the moblty rate between employed and unemployed groups s 7 per cent. One-way transton rates cannot be calculated, but they are below the two-way moblty rates reported above. Accordng to the QLFS, almost half of workers are employed by wholesale and retal trade or communty and socal servces. Trade workers are dstrbuted between nformal and formal groups, whle servce workers are most often formal. Informal male workers are mostly employed by utltes and constructon ndustres (21 per cent and 27 per cent) whle female workers are manly employed n prvate households for pad domestc work (43 per cent). Manufacturng workers are manly men workng formally. The mnng ndustry, whle the man drver of the economy, employs only 3 per cent of workers. The dstrbutons dscussed above result manly from employment of non-whte workers. Whtes follow a dfferent dstrbuton: ther second man sector s fnancal and busness servces rather than trade; fnancal and busness servces workers are dstrbuted between both formal and nformal jobs wth formal jobs more often taken by these workers. Only a few nformal whte female workers are employed n prvate households (3 per cent versus per cent of non-whtes). Whtes are also less lkely to work n utlty and constructon ndustres. 5

6 Table 1. Breakdown of the labour force and ndvdual characterstcs South Afrca, QLFS 2011 Formal Informal nemployed Inactve Breakdown of the workng-age populaton (39%) (13%) (48%) Employment breakdown, % Dscouraged/not avalable for work, % 70 / 30 Age 38 (11) 38 (11) 30 (9) 31 (16) Female, % rban, % Marred, % Afrcan, % Coloured and Asan, % Whte, % Number of years of educaton (Standard error) 14 (5) 10 (5) 12 (4) 10 (4) Ln of hourly wage (Standard error) (0.973) (0.962) ganda, MPS Formal Informal nemployed Inactve Dstrbuton of workng-age populaton, % Employment breakdown,, % Age 39 (11) 34 (15) 26 (10) 29 (13) Female, % rban, % Marred, % Number of years of educaton (Standard error) 11 (3) 8 (4) 11 (4) 7 (4) Ln of hourly wage (Standard error) 9.5 (0.67) 8.43 (1) ganda s case study s nterestng as an example of a low-ncome country. It represents a weakly urbanzed economy wth an unemployment rate of 5 per cent. The bulk of labour s nvolved n low value-added actvtes, partcularly n the nformal and household enterprse sectors. Yearly moblty between formal and nformal employment s weak (less than 1 per cent). There s howtever some rotaton between employed and nactve populatons wth a hgher ext rate from employment than from nactvty (10 per cent versus 4 per cent). 6

7 In contrast wth the South Afrcan labour market whch shows a rather equal gender dstrbuton among the two employment groups, gandan employment n both groups s prmary male; female partcpaton n the labour market s low and more often formal. Age and educaton dstrbutons by sector follow smlar patterns n both labour markets: the age dstrbuton s relatvely equal between formal and nformal groups; the majorty of hghlyeducated workers are employed formally whle the majorty of workers wth no or low levels of educaton are employed nformally; the hgher the level of educaton, the greater the porton of workers n formal employment and the smaller ther part n nformal employment. Fgures 1-2 show wage dstrbutons (n logarthm forms) n the formal and nformal employment groups. In both labour markets, the wage dstrbuton among formal workers s statstcally superor to that of nformal workers Kernel Densty Estmate Logarthm of Hourly Wage Informal employment Formal employment Logarthm of Hourly Wage Informal employment Formal employment Fgure 1. Earnng s dstrbuton n South Afrca Fgure 2. Earnng s dstrbuton n ganda 3. Essental Heterogenety: Model Outlne n the Context of Formal and Informal Labour Markets Radchenko (2014) shows how the model wth essental heterogenety (Heckman et al., 2006) apples to the framework of workers allocaton between formal and nformal segments of the labour market. Ths secton traces out the man setup detaled n Radchenko (2014). The populaton of workers holdng formal (nformal) jobs s desgnated as the treated (untreated) populaton. Dependng on the worker s employment segment, ether the outcome from beng treated, formal earnng, or the outcome from beng untreated, nformal earnng, s observed for 7

8 each worker. One s dfference between formal and nformal earnngs s unobserved and defnes one s treatment effect. In addton to the classcal selecton nto treatment related to the same unobservable determnants of both groups, workers engagement n formal versus nformal employment and workers earnngs, the model allows for a correlaton between ndvdual gans (or losses) from holdng a formal rather than an nformal job and allocaton between dfferent types of employment. The dstrbuton of the ndvdual treatment effect, gans or losses from holdng a formal rather than an nformal job and ts relatonshp wth the assgnment process may reveal behavoural varaton drvng the assgnment nto dfferent groups. 3.1 Base Framework The model wth essental heterogenety s represented by two related parts, the selecton equaton and the wage equaton. As n Radchenko (2014), workng ndvduals are employed ether n the formal ( D = 1 ) or nformal ( D = 0 ) employment groups based on the followng selecton process: D 1, 0, f f F( Z ) F( Z ) D, D, (1) where F Z ) s the propensty score representng the probablty of workng formally gven worker s ( observed characterstcs Z. F denotes the normal cumulatve densty functon. D, s the unobservable counterpart of F Z ), the propensty score of workng nformally based on workers unobserved ( characterstcs. By constructon, s unformly dstrbuted over [0;1]. D W 1, and W 0, denote two potental outcomes correspondng to formal and nformal wages. The observed and unobserved heterogenety s modelled by allowng W 1, and W 0, to vary wth observed ndvdual wage determnants X and unobserved ndvdual wage determnants the two segments: 0,,, 1 dfferng n lnw lnw 1, 0, X 1 X ,, f, f 0, D D 1 0 (2) where 0, 1, 0, 1 are unknown parameters of the wage equatons. E ) 0, E ( 1 X ) 0. ( 0, X The emprcal model referred to below s based on the followng representaton of system (2): 8

9 lnw 0 0X D 0, here s the overall ndvdual treatment effect: (3) ) ( ) X ( ) (4) ( , 0, The total treatment effect ncludes wage dfferentals related to observable ndvdual characterstcs ATE( x ) ( ) X ) and unobserved treatment heterogenety ). ( 1, 0, ( 1 0 ( 1, 0, ) descrbes essental heterogenety, the heterogeneous dfference of one returns from unobservable wage determnants earned f holdng formal rather than nformal job. Moreover, essental heterogenety mples that D, s correlated wth, 1, 0,. 3.2 Model Outcomes The outcomes of the model represented by the selecton equaton (1) along wth wage equaton (3-4) are detaled n Radchenko (2014) and summarzed n ths subsecton. They nclude a set of treatment parameters descrbng the dstrbuton of the treatment effects and ts relatonshp wth the selecton process. The most general parameters are the ATE, TT and TNT, descrbng average gaps n earnngs from holdng formal versus nformal jobs n all employment, ts formal and nformal segments respectvely: E(lnW lnw0 ), E (lnw1 lnw0 D 1) and E (lnw1 lnw0 D 0). 1 Addtvty of the model n terms of observable and unobservable wage determnants allows for decomposton of the treatment effects, that s earnng gaps, nto the effects specfc to workers observable and unobservable characterstcs: ATE = ATE X + ATE, TT = TT X +TT and TNT = TNT X +TNT. Radchenko (2014) ponts out dual sources of earnng gaps n terms of observable characterstcs: ther dfferent returns n dfferent employment segments and ther unequal dstrbuton across the two segments. The correspondng ATE X, TT X and TNT X are ( 0) E( X ), ( ) 0 E( X D 1) and ( ) 0 E( X D 0). TT The effects related to unobservable determnants are defned as ATE ), ) E( D 1) and TNT ) E( D 0). ( ( ( 1 0 The dfferences between TT (TNT) and ATE defne sortng on the gan from workng formally (nformally). The sortng on the gan comng from unobservable determnants ( SG 1 TT ATE and SG 0 TNT ATE ) s the key tool of analyss provded by the model wth essental 9

10 heterogenety offered by Heckman et al.(2006). Radchenko (2014) ponts out that the sortng on the gan comng from observables also takes place n the framework of formal/nformal allocaton of workers snce observable productvty characterstcs among formal and nformal workers are also unequally dstrbuted. 0 The sortng on the gan comng from workers unobservable characterstcs s not zero unless or 1 ( 1 0 ) D, that s n the event that the return to these characterstcs s not the same n the formal and nformal employment groups and that allocaton between the groups s selectve based on the correspondng dfferences. The resultng correlaton between ) and D ( 1 0 consttutes essental heterogenety and represents an addtonal flexblty of the model as compared to the class of models based on wage dfferentals. In partcular, t captures workers consderatons of the earnng gans (related to ther unobservable characterstcs and occupatonal choce) when engagng nto formal or nformal employment. Varous scenaros related to the postve, negatve and zero correlaton are the focus of ths paper and are dscussed n the next secton. The second selecton term s the classcal selecton bas defned as SB E D 1) E( D 0) (or smlarly SB E D 0) E( D 1) 1 0 ( 0, 0, 0 1 ( 1, 1, captures the gap related to the unobservable heterogenety of workers employed n dfferent groups and provdes addtonal parameters of analyss comng from dfferences n unobservable sklls and the backgrounds of the formal and nformal workers. Heckman et al.(2006) show that the correct dentfcaton of the set of treatment parameters n the framework of the model wth essental heterogenety and dscussed above s provded based on a seres of local treatment effects. More specfcally, the treatment parameters descrbng average wage dfferentals n the whole populaton or populatons correspondng to the two dfferent groups are dentfed by ntegratng the margnal treatment effect, MTE, over the dstrbuton of the probablty of selectng nto one group rather than another (workng formally rather than nformally n our context). In practce, ths mples calculaton of the MTE weghted averages (see Radchenko (2014) for the detaled presentaton). The margnal treatment effect s defned as the mean margnal gross return to formal versus nformal work followng an nfntesmal ncrease n the partcpaton rate. In theory, there s a contnuum of MTE defned over the whole support of P (Z). A pont MTE s a local parameter assocated to a specfc pont of P (Z) denoted by D, :. It 10

11 E(ln W X x, P( Z ) p) MTE( x, ud, ) E(lnW1, lnw0, X x, D, ud, ) p p ud, In the framework of model (1), (3)-(4), MTE s addtve n ts components related to observables (X ) and unobservables ( D, ) (Radchenko (2014) provdes more detals): MTE( x, u ) ( ) x MTE D, 1 0, where MTE, s the margnal gap between worker s formal and nformal earnngs resultng from nfntesmal changes of D,. D, s unobserved. However, t can be calculated at the pont where worker s ndfferent about workng n segment 1 or segment 0. From (1) t follows that at ths pont F( Z ) and D, therefore, equals the propensty score P (Z) to work formally that can be predcted from (1). D MTE, s thus the margnal gap between one s formal and nformal earnngs resultng from nfntesmal changes n the partcpaton rate. 3.3 Model Estmaton The estmaton procedure s based on Heckman et al.(2006) and s descrbed n detal n Radchenko (2014). Ths subsecton brefly outlnes ts man stages. Snce MTE s defned n terms of the propensty score P, ts estmaton s based on the followng semparametrc representaton of wage equaton (3): ( ) x p K( p lnw 0x 1 0 ) (5) where the last term s defned by: 0 K( p ) ( ) p E( D 1, P( Z ) p ) p (6) 1 0 1, 0, The structural parameters 0 and 1 0 are estmated wthout explctly modellng K(p). Frst, the propensty scores p are predcted from selecton equaton (1). Next, equaton (5) s estmated usng the double resdual sem-parametrc regresson. Ths regresson allows for the estmaton of nformal returns ( 0 ) to one s observable characterstcs ( x ) and the dfferences n returns n the two sectors 11

12 ( ) 1 0 whle leavng the remanng varaton of the earnng to be non-parametrc functon of the propensty scores assocated to workng formally or nformally. The predcted resduals W x ( ) x p ) (ln 1 0 are then regressed on p by runnng 0 local quadratc regresson. The lnear term coeffcents of the local quadratc regresson correspond to the formal defnton of margnal treatment effects MTE. The resduals are predcted followng ths second stage. The aggregated treatment effects are dentfed over the common support, that s, over the sample of formal and nformal workers whose postve propensty scores (probablty of workng formally) overlap. Ths provdes comparablty of the two populatons (formal and nformal) as requred for dentfcaton of any treatment evaluaton estmator. The correspondng weghts are calculated n a way suggested by Radchenko (2014). Statstcal nference about estmators s obtaned by bootstrappng. 3.4 Identfcaton of the Average Treatment Parameters Two techncal requrements underlyng the dentfcaton of the average treatment effects dscussed above are the full common support and vald excluson varables (Heckman et al., 2006). The frst requrement mples that the common support correspondng to the overlap of the propensty scores of the formal and nformal workers be the unt nterval [0;1]. The second requrement mples that the whole set of regressors Z n the selecton equaton (1) contans some excluson varables Z \ X that mght nfluence the wage equaton only through the P (Z) but are not ts drect determnants. The drect determnants X of the wage equaton make up a subset of Z. Excluson varables nducng local margnal changes of P ( Z X ). Z \ X allow for dentfcaton of the margnal treatment effects by The body of lterature focusng on the model wth essental heterogenety and the method of local nstrumental varables s not explct on the nature of the dstrbuton of the excluson varables and the related dstrbuton of the condtonal propensty score P( Z X ) F( Z X ),.e. varaton of the propensty score due to varaton of the nstruments. Fortunately, the revew offered by Heckman (2010) dsspates confuson occurrng at the ntersecton of the structural modellng and use of the treatment effects. It dscusses the margnal treatment approach n relatonshp wth the nature of the nstruments and P (Z) dstrbuton. It shows n partcular the mportance of the contnuty of the propensty score, P(Z), over the unt nterval. Such contnuty of the support D assocated wth the propensty score P(Z) s warranted 12

13 by hgh varaton of Z and a contnuous excluson varable Z \ X operatng through the margnal changes of P ( Z X ). Dscrete nstruments wth hgh varaton combned wth contnuous X also allow for the tracng out of MTE over more of the support of D and reachng out the full unt nterval. However, a bnary excluson varable combned wth contnuous X as used by Radchenko (2014), rsks the producton of dscontnuty ponts where the MTE s not dentfed (see Appendx A for more dscusson). Consequently, the average treatment parameters resultng from ntegratng MTE over the support of D can be based. 4. Effcency of Allocaton The relatonshp between MTE and D s the leadng pont of the analyss. The aggregate treatment parameters dscussed above follow ths relatonshp. MTE are not ndvdual-specfc. However, they are spread over the populaton of workers correspondng to the common support. Therefore, t shows the general behavoural pattern of the whole populaton n the event of full common support or that of a fracton of workers correspondng to the common support otherwse. The common support defned n terms of propensty scores s nterrelated drectly wth Snce D. D represents the propensty to work nformally due to workers unobservable factors, MTE correspondng to ts hgh (low) values show mnmum gan or loss due to unobservable characterstcs motvatng nformal (formal) employment rather than formal (nformal) employment. More specfcally, the postve (negatve) MTE s a worker s margnal gan (wllngness to pay) f workng formally ( D = 1 ) or margnal wllngness to pay (margnal gan) f workng nformally ( D = 0 ). relatonshp to Radchenko (2014) suggests several model mplcatons related to the behavour of MTE n D and dependng on whether the correlaton between MTE and D s negatve, zero or postve. The dscusson below offers extended vews on possble scenaros assocated wth dfferent knds of relatonshps between MTE and D. 4.1 Postve Sortng on the Gan The frst scheme correspondng to the decreasng shape of MTE n relatonshp to D mples effcent allocaton of both formal and nformal workers. Indeed, n ths case, the average treatment effects correspondng to unobservable gaps wthn the formal employment populaton (TT ), the nformal employment populaton (TNT ) and the total employment populaton (ATE ) are ordered as 13

14 TT > ATE > TNT. Ths mples a postve sortng on the gan: the average gan of the formal workers from holdng formal rather than nformal jobs, TT, s hgher than the average gan across the whole populaton, ATE ; the average gan of the nformal workers from holdng formal rather than nformal jobs, TNT, s the lowest n the populaton; n partcular, a negatve value of TNT, mples postve gan of the nformal workers from ther actual allocaton nto nformal employment (t follows from equvalence of E D 0) 0 and E D 0) 0 ). ( 1 0 ( 0 1 Radchenko (2014) assocates ths scheme wth an ntegrated market where access s open to both formal and nformal segments: workers antcpate ther gans from workng n one segment rather than n the other and choose the segment that provdes them wth hgher earnngs. Informal employment n such a labour market s voluntary and chosen based on comparatve advantage consderatons. However, ths scheme requres further nvestgaton snce t may be the net result of several alternatve patterns. Indeed, whle earnngs dstrbutons n the formal and nformal groups have substantal overlap, TT representng the average gan from workng formally n the populaton of the formal workers s lkely to be postve and s certanly postve under postve sortng on the gan. The sgn of the TNT representng the average gan from workng formally n the populaton of nformal workers s ambguous and under a postve sortng on the gan may depend on prevalence of dsparate ters of nformal employment. More specfcally, TT > ATE > 0 > TNT mples prevalence of upper-ter nformal employment. Accordng to Felds (1990) who ntroduces the term, the upper-ter conssts of nformal workers endowed wth some fnancal and/or human captal. Eventually, the captal could be acqured from havng held formal jobs. The related endowment may allow for developng small unregulated busnesses. The upper-ter s most hghly assocated wth voluntary engagement n nformal employment. Negatve TNT mples postve average gan from workng nformally n the populaton of nformal employment and therefore fts the scenaro n whch the labour market s to a large extent ntegrated. In terms of ther poston relatve to formal employment, the lower- ter, or easy entry ter as advanced by Felds (1990), s opposed to the upper ter by ts nvoluntary survvalst nature: the lower ter conssts of the poorest workers preferrng any low-payng actvty to open unemployment. The presence of the lower ter havng negatve gan from workng nformally as compared to workng formally mght balance postve gans of the upper ter. The average TNT n the nformal populaton 14

15 depends on the relatve mportance of the upper versus lower ter and the average gans and losses n the two subpopulatons. Therefore, TT > ATE > TNT > 0 sgnals the presence of a lower ter. Weakly postve TNT mght sgnfy a balance between the gans and losses of the upper and lower ters. However, a postve sortng on the gan mples effcent allocaton n terms of socal welfare of employment drven by an mportant place taken by the upper ter. In the event of ratoned formal employment and a weakly developed upper ter, effcent ratonng correspondng to a postve sortng on the gan s consstent wth heterogeneous costs of entry nto formal employment and selecton of workers based on these costs: only workers wth monetary gans that cover the entry cost choose to compete for formal jobs. The entry cost n the framework of the developng economy can be related to the movng cost from rural to urban areas wth hgher demand n the formal sector; t may also nclude the rsk of becomng or stayng unemployed when nvestng tme n the search for formal employment. In ths framework, workers choose to compete or not for formal jobs based on ther expected gans from success. Workers the most lkely to work nformally are those whose counterfactual formal earnngs are not sgnfcantly hgher. Such a pattern mples low gaps between formal and nformal wages for a porton of employment and mght ft therefore a labour market wth no or very weak mnmum wages n the formal sector. The pattern s effcent from the pont of vew of workers socal welfare and could be consdered as nterposed between an ntegrated market and neffcent ratonng correspondng to the flat dscussed next. MTE whch s 4.2 Zero Sortng on the Gan Zero correlaton between MTE and D mples no relatonshp between antcpated gans from occupatonal choce and workers preferences. The lkely scenaro n the framework of a developng labour market s constant postve MTE yeldng the same average formal-nformal wage gap (due to unobservables) across the whole populaton of workers (TT = ATE = TNT ). Such a scheme s assocated wth a segmented labour market: workers do not sort themselves based on antcpated ndvdual gans. Segmentaton here mples neffcent ratonng: contrary to the prevous case, ratonng s neffcent from the perspectve of workers socal welfare maxmzaton. We refer to ths as weakly neffcent ratonng to dfferentate t from the strongly neffcent ratonng dscussed below. 15

16 4.3 Negatve Sortng on the Gan The thrd scheme n terms of dfferent shapes of the relatonshp between MTE and D s ncreasng assocaton, mplyng a negatve correlaton between relatve gans based on unobservables and the selecton equaton. It means that the hgher the relatve gans from workng formally due to unobservables, the weaker the selecton nto ths type of employment based on the same unobservables. The treatments effects are ordered as TT < ATE < TNT. Radchenko (2014) cautously assocates ths pattern wth the non-pecunary comparatve advantage consderaton, pontng out that ths pattern would ft the model only under the assumpton of a negatve correlaton between monetary and non-monetary relatve gans based on the same unobserved factors. Such a strong assumpton entals weak plausblty of the prevalence of the nonpecunary comparatve advantages n a mechansm drvng workers allocatons between formal and nformal employment groups. A settng whch rather fts the negatve sortng on the gan n the framework of a developng economy s a labour market wth hgh unemployment and strong prevalence of the lower ter of nformal employment over ts upper ter. In such a settng, the lower ter nformal segment may host the poorest part of the job seeker populaton, whch uses the nformal sector as a last resort and accepts any wage level. A negatve sortng on the gan mples here that those who are the most lkely to work nformally are those whose reservaton wage s partcularly low, makng the gap between ther formal counterfactual earnngs and actual nformal earnngs partcularly hgh. In terms of the socal welfare of workers, ths pattern suggests neffcent ratonng of formal employment and mples that workers use nformal jobs as a subsstence strategy. 5. Results The presentaton of the results follows estmaton steps summed up n 3.3: selecton equaton frst and wage equaton and dfferentals next. The estmates are reported n Tables 2 and Selecton nto Formal or Informal Employment Both Afrcan labour markets under consderaton show a progressve postve mpact of educaton on the selecton process nto formal employment. Formal employment conssts of more hghly-educated workers. Ths s n lne wth emprcal fndngs based on data from developng and, n partcular, Afrcan economes: for example, the same progressve mpact s reported by Radchenko(2014) usng Egyptan data and Dmova et al.(2010) explorng the data from the largest economc centres of Côte d Ivore, Mal, Benn, Senegal, Togo, Nger, Burkna Faso. 16

17 Gender dfferences n the ntensty of engagement nto formal employment vary across countres. In South Afrca, women are more lkely to work nformally (6% margnal effect): they are manly engaged n the agrcultural and household related work, whch s more frequently nformal and less remuneratve (Valoda, 2001; Casale and Posel, 2002; Devey et al., 2005; Banerjee et al., 2008; Rodrk, 2008). In ganda there s no gender dfference n allocaton between dfferent groups of employment. In lne wth descrptve statstcs and lterature fndngs, younger/unexperenced workers are more lkely to be employed nformally whle older and marred workers are more lkely to work formally. However, the dfference by age s very weak n South Afrca. Another factor unque to South Afrca s that a sgnfcant porton of the populaton s whte, and whtes partcpate n formal employment at hgher rates than non-whtes. Ths s partly due to the spatal separaton between busness centres and areas of resdence of Afrcans (Banerjee et al., 2008) nherted from aparthed. Fnally, several excluson varables are used to provde exogenous varatons of the propensty scores necessary to dentfy the MTE. They are data-specfc and dscussed n detal n Appendx B. Table 2.South Afrca Estmates Selecton equaton: Probt estmates. Postve outcome: formal employment Wage equaton: Double resdual sem-parametrc regresson estmates Selecton equaton Wage equaton Informal employment Worker s Characterstc Coeffcent (SE) Educaton Prmary Incomplete (0.076) Prmary 0.088** (0.041) Secondary 0.603*** (0.039) Preparatory 1.421*** (0.045) Tertary 1.740*** (0.059) Female *** (0.014) Age *** (0.001) Marred 0.127*** (0.015) Coeffcent, ˆ 0 (SE) (0.107) (0.061) ** (0.097) 0.177*** (0.263) (0.524) *** (0.039) (0.002) (0.032) Wage equaton Gap n formal-nformal return Coeffcent, ˆ ˆ ) (SE) (0.282) (0.147) 0.618*** (0.188) (0.389) ** (0.640) 0.248*** (0.057) 0.009*** (0.003) (0.048) (

18 Job Tenure 0.035*** (0.001) Race Afrcan/Black *** (0.030) Coloured *** (0.035) Indan/Asan * (0.056) Whte - Provnce Western Cape 0.217*** (0.037) Eastern Cape 0.119*** (0.034) Northern Cape (0.042) Free State (0.034) KwaZulu-Natal 0.146*** (0.036) North West 0.294*** (0.036) Gauteng 0.133*** (0.031) Mpumalanga 0.099*** (0.033) Lmpopo ** (0.005) *** (0.128) *** (0.101) (0.209) 0.426*** (0.082) (0.054) 0.029*** (0.072) 0.116** (0.056) (0.048) 0.189** (0.074) 0.588*** (0.060) 0.144*** (0.054) *** (0.008) 0.729*** (0.169) 0.755*** (0.123) (0.247) *** (0.116) (0.088) *** (0.112) *** (0.093) *** (0.082) *** (0.116) *** (0.092) *** (0.091) rban 0.188*** (0.019) 0.120** (0.049) (0.079) Fetch water *** (0.020) PS unemployment rate *** (0.044) Constant *** (0.045) Number of observatons * sgnfcant at the 10% level; ** sgnfcant at the 5% level; *** sgnfcant at the 1% level 18

19 Table 3. ganda Estmates Selecton equaton: Probt estmates. Postve outcome: formal employment Wage equaton: Double resdual sem-parametrc regresson estmates Selecton Equaton Worker s Characterstc Coeffcent (Standard Error) Educaton Years of educaton 0.091*** (0.012) Female 0.208*** (0.079) Age 0.020*** (0.003) Marred 0.359*** (0.090) # of elderly persons 0.056* (0.031) Regon Kampala (0.131) Central *** (0.109) Eastern (0.115) Northern (0.118) Wage Equaton Coeffcent (Standard Error) 0.039** (0.017) *** (0.090) 0.020*** (0.006) 0.211* (0.114) 0.885*** (0.225) 0.613*** (0.190) (0.228) (0.199) Western - - rban 0.231*** (0.081) (0.155) Communty characterstcs Agrcultural extenson servces 0.177** (0.095) Market sellng agrcultural nputs 0.407*** (0.156) 2010/2011 vs 2009/ *** (0.073) (0.067) Constant *** (0.213) Number of observatons * sgnfcant at the 10% level; ** sgnfcant at the 5% level; *** sgnfcant at the 1% level 5.2 Common support The resultng dstrbutons of the propensty scores of the formal and nformal workers are shown on Fgures 3 (South Afrca) and 4-5 (ganda). The large sze of the South Afrca survey provdes strong and full common support. gandan common support s rather full but weak (Fgure 4). Weakness of the common support s related to too low nvolvement n formal employment, nsuffcent sample sze provdng nformalty status, and selecton based on educaton: workers wth uncompleted prmary educaton hold nformal 19

20 jobs. Thus, we focus on those who have completed at least prmary educaton (Fgure 5). The selected sample provdes stronger support, but t s ncomplete and does not allow workng wth the full support. Whle aggregated treatment effects rsk beng based n that case, margnal treatment effects are more relable when usng a stronger support (Heckman et al., 2006) Propensty Score Informal Sector Formal Sector Fgure 3. South Afrca Kernel Densty Estmate Propensty Score Informal Sector Formal Sector Propensty Score Informal Sector Formal Sector Fgure 4. ganda. All workers educaton Fgure 5. ganda. Workers wth at least prmary completed 5.2 Earnngs from Formal versus Informal Employment The results detaled below show that the two countres under the focus of ths analyss follow very dfferent patterns of workers allocaton between formal and nformal employment groups. Along wth the Egyptan case study offered by Radchenko (2014), the results ft the three major scenaros dscussed n secton 4. 20

21 The central aggregate estmates of the treatment parameters for South Afrca and ganda are dsplayed n Table 4. The results replcatng the Egyptan case usng the mproved set of excluson varables are reported n Appendx C. Fgures 6-9 show the dstrbutons of the MTE estmates. Country Table 4. Estmated Effects ATE, TT, TNT and ther decompostons Treatment Effect Total TT X ATE X TNT X TT ATE SB 1 0 SB 0 1 TNT South Afrca TT 1.061*** (0.039) ATE 1.663*** (0.036) TNT 2.191*** (0.058) ganda TT 1.055* *** (0.738) ATE 0.748* *** (0.472) TNT (0.453) *** South Afrca estmates show negatve sortng on the gan, (0 < TT < ATE < TNT) fttng the thrd pattern dscussed n secton 4. All the effects are postve, mplyng hgher returns from workng formally for any worker. On average, the formal earnng of a worker randomly drawn from the sample s more than twce as hgh as ther nformal counterfactual earnngs. 50 per cent of the dfferental s related to dfferent returns to observables (educaton, gender, race and so forth). More than 100 per cent of the dfferental s related to unobservable characterstcs. The results suggest a negatve sortng on the gan n terms of both observable and unobservable characterstcs. Race and gender are among the factors of negatve sortng related to observables (the estmates can be seen n Table 2): Afrcans are less lkely to work formally whle they have lower returns from nformal employment. The same holds for women. Ths may be explaned by socal stgma n regards to women s work nducng women to engage n nformal agrcultural and household related work, whch s more frequently nformal and less remuneratve. Ths s related to the hstorcal legacy of aparthed, where Afrcans and n partcular women were not allowed to work formally and had to hold subsstent jobs (Valoda, 2001). In terms of unobservable characterstcs, the least educated porton of the Afrcan populaton (wth some prmary educaton at most) would not gan from workng formally. Ths s shown by the flat shape of the MTE curve at ts left tal (Fgure 6). nsklled Afrcan workers do not sort themselves based on the antcpated ndvdual gans. The unobserved factors pushng workers nto 21

22 nformal employment mght be rather specfc to the local labour markets and lmted occupatonal opportuntes for unsklled workers. Therefore, formal employment of unsklled workers s ratoned and ther allocaton between the two employment groups s weakly neffcent. Educated workers (workers havng at least some secondary educaton) gan more f workng formally. Ths s due to the hgher returns to educaton n formal employment. Moreover, relatve gans from formal employment are channelled through unobservable characterstcs as mpled by postve MTE. However, the upward shape of the MTE curve mples negatve sortng on the gan: the larger the ndvdual earnng gaps, the smaller the propensty for workng formally based on unobservable characterstcs. The frst of the scenaros fttng the negatve sortng on the gan and offered n 4.3 s the prevalence of non-monetary comparatve advantages of the nformal jobs over ther monetary advantages where monetary and non-monetary components are negatvely correlated. The specfc context of South Afrca, wth remarkably hgh unemployment (25 per cent) as compared to other upper-mddle economes, does not allow for the applcaton of such a scenaro. Strong unemployment along wth an underdeveloped nformal sector s a controversal ssue n the lterature on South Afrcan labour market. On the one hand, the unemployed labour force mght have relatvely hgh reservaton wages and prefer open unemployment over lower ter of nformal employment (nemployment Lower ter). In support of ths, the OECD ponts to the wdespread welfare system n South Afrca. Accordng to the QLFS data, only 15 per cent of the nactve populaton reles on old age pensons and 13 per cent receve chld support grants; 77 per cent of both unemployed and nactve workers are supported nstead by other members of ther households. Household transfers mght also ncrease the reservaton wages of unemployed ndvduals. These data mply that at least a fracton of unemployed labour force conssts of workers unwllng to engage to the lower ter of nformal employment. On the other hand, the phenomenon s explaned by ncreasng unsklled labour supply and an nflux of female labour supply on the South Afrcan labour market over the transton perod snce the dsmantlng of aparthed (Banerjee et al., 2008). It s also explaned by de ndustralzaton of the South Afrcan economy: Accordng to Rodrk (2008), the weakenng of manufacturng and a shft to the tertary sector yelded a drop n demand for low-sklled workers. A large nflux of unsklled workers combned wth shrnkng demand for them mples an unlmted labour supply to the lower ter of the nformal sector. For the poorest of these workers, unemployment s the worst opton (Lower ter nemployment). Ths body of lterature mples a hgh fracton of labour force wllng to engage n the lower ter of nformal employment and havng low reservaton wages (Kngdon and Knght, 2004). 22

23 Overall, the lterature suggests a heterogeneous pool of job seekers. The results of the present analyss mply that nformal employment of the South Afrcan labour market hosts the poorest of them, those who have the lowest reservaton wages. Indeed, gven the negatve sortng on the gan, workers who are the most lkely to be pushed toward nformal employment are those whose losses from workng nformally are partcularly hgh. The hgh losses yeld partcularly low earnngs from nformal employment. Such a behavoural pattern s n lne wth the second scenaro offered n 4.3. It suggests a strong prevalence of the lower ter of nformal employment over ts upper ter: South Afrcan workers use the nformal sector as a last resort and accept any wage level. Ths result concurs further wth hgher lkelhood of nformal employment n localtes wth stronger unemployment rates reported by the prevous subsecton. Fnally, t s consstent wth a composton of nformal employment whch more frequently hosts Afrcan workers employed by the utltes and constructon ndustres and female workers employed n prvate households. The gandan estmates do not show dfferent returns to the observable ndvdual characterstcs of formal and nformal workers. The neffcency of the dfferental estmates (not reported) may be due to an nsuffcent sample sze. Yet, the wage equaton followng the classcal Mncer s format shows postve return to educaton and experence proxed by age (Table 3). MTE s postve and constant over all support, mplyng hgher earnngs n the formal sector for any worker. Ths s llustrated by the flat graph (Fgure 7) yeldng no correlaton between the gans and the selecton process. These results provde strong evdence of a segmented labour market n ganda whch pays hgher wages n formal employment. The aggregated effects are consstent wth postve and homogenous MTE : they are postve and close n magntude. More detaled nterpretaton of the aggregate effects would not be relable as these effects are based on the weak or ncomplete support and rsk beng subjected to bas (Heckman and Vytlacl, 2006). Overall, the gandan results mply an neffcent allocaton of workers between formal and nformal employment due to the strongly ratoned formal employment; the embryonc state of the formal economy does not leave room for developng compettve mechansms or shapng varous ters wthn nformal employment. The Egyptan results of the selecton and wage equatons (Table C.1, Appendx C) are very close to those of Radchenko (2014). Ths nduces the same estmates of the average treatment effects and sortng on the gan related to the observables characterstcs of workers (Table C.2, Appendx C) as those reported n Radchenko (2014) usng 1998 and 2006 ELMS surveys. The components of the 23

24 treatment effects whch are related to unobservables dffer. However, they concur wth the conclusons obtaned by Radchenko (2014). Indeed, Fgure 8 shows the same pattern of the decreasng MTE, mplyng a postve sortng on the gan n the Egyptan labour market n The average effects also order n the same way, TT > ATE > 0 > TNT. In terms of the analyss n secton 4, the pattern fts the labour market whch s to a large extent ntegrated: nformal employment conssts here of the upper-ter workers who are endowed wth some captal to develop an unregulated busness. Radchenko (2014) argues that, gven the dstrbuton of human captal and estmates of the selecton bas terms, nformal workers were mostly dsadvantaged workers. They would not do better f workng formally. Ths effcency of worker s socal welfare n 1998 s corroborated by the results wth an extended set of nstruments. Radchenko (2014) reports that, followng the structural changes on the Egyptan labour market experenced over , the mechansm drvng nformal employment has changed. The results obtaned usng the extended set of nstruments corroborate wth Radchenko (2014): they also show neffcent reallocaton of workers nduced by deformalzaton of employment through reducton of the publc sector and an nflow of cvl and young workers nto nformal employment. Moreover, the extended set of nstruments strengthens the effect of the negatve sortng on the gan (TT < ATE < TNT ) whch s seen at the rght tal of the MTE dstrbuton (Fgure 9). In terms of secton 4 defntons, the allocaton of workers between formal and nformal employment s strongly rather than weekly neffcent: nformal employment became a last resort for a sgnfcant porton of workers n Appendx C provdes further dscusson of the senstvty analyss of the results. 24

25 South Afrca ganda Margnal treatment effect wth 95% Confdence Interval Margnal treatment effect wth 95% Confdence Interval -1 MTE d Lower Bound pper Bound MTE Fgure 6 Egypt, 1998 Fgure 7 Egypt, 2006 MTE MTE d Lower Bound pper Bound MTE -2-1 MTE Fgure d Lower Bound pper Bound MTE Fgure 9 The propensty score s ordered by the horzontal axs. Low abscssa values correspond to the workers who are less lkely to be employed n the formal sector than n the nformal based on ther observable characterstcs. As dscussed n secton 3.1, MTE are evaluated at the ndfference ponts where propensty scores equal D. Low abscssa values are assocated therefore wth low V values and consequently hgh probablty to be employed n the formal versus nformal sector based on unobservable characterstcs holdng the observables fxed d Lower Bound pper Bound MTE 6. Conclusons Ths paper contrbutes to the recently growng lterature on the heterogenety of nformal employment n developng economes. Drawng on the model wth essental heterogenety, t enrches the analyss offered by Radchenko (2014) by extendng a lst of scenaros descrbng behavoural patterns followed by nformal workers. The paper shows that the model wth essental heterogenety yelds not only classcal patterns of a ratoned formal sector versus an ntegrated labour market, but also dfferent 25