Do Remittances Alter Labor Market Participation? A Study of Albania

Transcription

1 MPRA Munch Personal RePEc Archve Do Remttances Alter Labor Market Partcpaton? A Study of Albana Ermra Hoxha Kalaj Unversty of Trento 2009 Onlne at MPRA Paper No , posted UNSPECIFIED

2 Do Remttances Alter Labor Market Partcpaton? Ermra Hoxha Kalaj Unversty of Trento, Italy Ths draft s prelmnary and ncomplete, not for ctaton Abstract The followng study focuses on the mpact of remttances on the labor market partcpaton usng propensty score matchng. Usng household survey data for Albana, ths paper reles on the matchng approach for the dentfcaton. The nearest neghbor and kernel estmators are used to obtan the matchng results. The vector of covarates ncludes nformaton related to ndvdual and households characterstcs such as; age, gender, schoolng, area of resdence etc. In the model, household ncomes are consdered separately from remttances n order to dentfy whether ncome from remttances have the same effect as other types of household non-labor ncome n the decson of partcpatng n the labor market. Emprcal results show that remttances have a statstcally negatve mpact n the labor market partcpaton for female both n terms of the probablty of workng and the hours of work. No evdence s found n the mpact of these captal flows n the behavor of male n the labor market actvtes Key words: remttances, labor market partcpaton, propensty score matchng JEL classfcaton; F24, J22, C31 1

3 1. Introducton Mgraton out of Albana durng the transton to the market economy has been massve, relatve to the populaton. Accordng to the World Bank (2010) one out of every three households n Albana, 34 percent, has at least one member currently lvng abroad, and 50 percent of these households have more than one. People from urban coastal part of the country are those wth the hghest propensty to mgrate, whle people from the poorer, rural mountan part are the least lkely. Total remttances reported n the balance of payments ncreased from around 889 mlon n 2003 to 1317 mlon n 2009 whch s 10.9 percent of the GDP. These transfers from mgrants can have long-run benefcal mpact on the economy f they are used n productve actvtes (Woodruff and Zenteno, 2001). However, remttances may have undesrable effects on the behavour of those left behnd. In partcular there s a concern about whether remttances could cause Dutch dsease effects (Acosta et. al. 2009). On one hand remttances may ncrease the reservaton wage of members lvng n the recevng-remttance households, but on the other these transfers may be used to relax budget constrants and as a mean of captal mport, facltatng the clmate for self-employment. Remttances may lead to a better partcpaton n the busness nvestments (Klc et. al., 2009) through self employment or asset accumulaton (Adams, 1998). Woodruff and Zenteno (2001) show that 27 percent of mcro-enterprses n the urban areas n Mexco rely on remttances from abroad. 2. Lterature revew Remttances have been examned from both mcro and macro perspectves. Treatng remttances as a household ssue the mcroeconomc lterature examnes the patterns of remttances, the motvatons for makng them and the mpact they have on the labour market and on famly consumpton. Whle the macroeconomc studes on the other hand concentrate on macro effects n recpent countres ncludng economc growth, fnancal development, and poverty reducton. 2

4 2.1. The study of remttances n relaton to the labour market partcpaton Remttances can ncrease consumpton or stmulate nvestments n economes wth lqudty constrants (Relly and Castaldo, 2007; Woodruff and Zenteno, 2001). One of the frst studes that examned the consequences of remttances on home countres 1 s Funkhouser (1992), who fnds that n Ncaragua that remttances ncrease self-employment for men and reduce the labor supply of women. However, from a development perspectve, a declne n the labor supply n the recpent famles should not necessarly be vewed as a negatve effect. For nstance, women n remttancerecevng households may carry out both parentng and home producton actvtes (Acosta, 2006). Unemployment could ncrease f remttances are seen as provdng a knd of welfare payment. However remttances by reducng the credt constrants n developng economes can encourage frms to ncrease ther nvestment level. The overall effect on the unemployment wll depend on whch of these effects domnates. Snce remttance nflows are smple ncome transfers, recpent households may ratonally substtute unearned remttance ncome for labor ncome. Regardless of ther ntended use, remttance transfers may be subject to moral hazard problems (Cham et al., 2003). These problems may nduce recpents to dvert resources to the consumpton of lesure, thereby reducng ther labor market effort. There are cases n whch members of remttance-recevng famles reduce ther labor market partcpaton n Pakstan (Kozelt and Alderman, 1990) and n Carbbean Basn ctes (Itzgsohn, 1995) The mpact of remttances on the decson to work has been examned by Rodrguez and Tongson (2001) n Manla. Wthout accountng for the endogenety of remttances wth respect to labor supply, they conclude that remttances reduce employment. Usng 2002 data from Mexco, Amuendo-Dorantes and Pozo (2006) show that remttances appear to negatvely affect female work effort only n rural areas and n the nformal sector. Addtonally, ther results ndcate that remttance-recevng men do not reduce ther partcpaton n labor market, but tend to shft nto 1 Home countres are the countres of orgn of the mgrants. 3

5 nformal employment. Ther study acounts for the endogenety of remttance ncome and examnes dfferences n the hours worked n varous types of employment by men and women n urban and rural areas. Usng household survey data from Moldova, Görlch et al. (2007) examne labour market nactvty by consderng three potental explanatons: a dsncentve effect n whch lesure s consdered a normal good and non-labour ncome rases the reservaton wage of a potental worker; a labour subttuton effect, n whch people n remttance-recvng households allocate more tme to household producton than ther counterparts n the non-remttance-recvng households; an educaton effect, n whch mgraton provdes ncentves for addtonal educaton 2 and remttances are used to nvest n the educaton of those remanng at home. There are few emprcal studes of the relatonshp between remttances and labor market ssues n Albana. Konca and Fler (2009), usng Albanan Lvng Standards Measurement Survey (LSMS) for 1996, suggest that remttances have a negatve effect on female labor market partcpaton due to hgher ncome from abroad. Ths fndng s consstent wth studes conducted n other countres. In the Albanan case however, Konca and Fler (2009) fnd that nether the exstence of emgrants n the household nor the amount of remttances receved has an effect on labor force partcpaton of Albanan males. Usng data from the 2005 Albanan LSMS Klc et al. (2007) measure the mpact of past mgraton experence of Albanan households on non-farm busness ownershp through nstrumental varables regresson technques. These results ndcate that households past mgraton experence exerts a postve mpact on the probablty of ownng a non-farm busness. Usng the same dataset, Dermendzheva (2009) nvestgates the effect of mgraton and remttances on labor supply n Albana. A lnear probablty model s estmated for the probablty of a household member to be workng on the subsamples of male and female household members separately. Only after usng the 2 A phenomenon stressed by the bran gan lterature 4

6 nstrumental varable, Dermendzheva (2009) obtans large and negatve coeffcents for recevng remttances for females and older males. The same queston wll be addressed usng an alternatve method, the propensty score matchng. I wll use propensty score matchng to par ndvduals that receve remttances wth other ndvduals that are lke them, expect from remttances. The queston s whether remttances are actng as a dsncentve for the partcpaton n the labor market through a substtuton effect or t may be an ncome effect of consderng that remttances may affect decsons to accept more hours of work. To date the studes on Albana have focused manly on the decson to work and have not consdered that remttances may change the hours worked or the type of work performed n the recevng economy, wthout alterng employment rates. Hence, by focusng on work performance a clearer pcture of the allocaton of labor supply across dfferent types of employment can be establshed Theoretcal framework of labor market partcpaton In the neoclasscal model of labor-lesure choce (Kllngsworth, 1983), ndvduals allocate tme to market actvtes and non-market actvtes maxmzng utlty subject to the budget constrant. The model solates the factors that determne whether an ndvdual works, and f so, how many hours she chooses to work. Ths theory lets us predct how changes n economc condtons or government polces wll affect work ncentves (Borjas, 2005). Indvduals seek to maxmze ther well-beng by consumng goods and lesure. The economc trade-off s clear. If ndvduals don t work, they can consume a lot of lesure, but they have to do wthout the goods and commodtes that make ther lfe more enjoyable, on the other hand f ndvduals work, they wll be able to afford many of these goods, but they must gve up some of ther lesure tme. In ths framework wage rate and other ncome are the key economc varables that determne the allocaton of tme between the labor market and lesure actvtes. 5

7 Accordng to Becker (1981) there are varous dvson of labor among famly members. The dfferent dvsons of labor are determned partly by bologcal dfferences and partly by dfferent experences and dfferent nvestments n human captal. The theory of comparatve advantages mples that the resources of members of a household should be allocated to dfferent actvtes accordng to ther comparatve or relatve effcences. These dfferences can be dstngushed by the assumpton that an hour of household or market actvty of one member of the household s not a perfect substtute for an hour of tme of another member of the household when they make the same nvestments n human captal. Specalzaton of tasks, such as the dvson of labor between members of the household, mples a dependence on others for certan tasks. An mportant factor determnng the labor market partcpaton decson s the level of the reservaton wage or the lowest wage rate at whch a household member would be wllng to accept a partcular job. Non-labor ncome s a determnant of the reservaton wage. For an ndvdual the non-labor ncome depends on her own assets and the amount of ncome of the other household members. The hgher s the ncome of the other members of the household, the hgher s the reservaton wage of the ndvdual (Cox-Edwards and Rodrguez-Regge, 2007). Ths reservaton wage wll nfluence the probablty of the ndvdual to partcpate n the labor market. In ths context remttances may be consdered as a dsncentve for the market actvtes, because remttances ncrease the level of the non-labor ncome, ncreasng the reservaton wage. Assumng that remttances are not randomly assgned, varous factors may confound ther mpact n the labor market partcpaton by drect comparson of remttance-recevng to non remttance-recevng households. Matchng technques helps avodng these problems. 6

8 3. Methodology 3.1. The estmaton framework The relatonshp between remttances and labor market partcpaton has been examned before for Albana, but the methodology n ths paper dffers from prevous ones. The comparson between remttance-recevng household and those who don t leads to an dentfcaton problem because the presence of remttances may be correlated wth unobserved determnants of partcpaton among these household members. To overcome the potental bas, I wll use the propensty score matchng to fnd a comparson group for ndvduals n remttance-recevng households. The queston arses because I d lke to capture the dfference between the household member s partcpaton n the labor market wth and wthout remttances. It s obvous that we cannot observe both outcomes for the same member at the same tme. Takng the mean outcome of non-partcpants as an approxmaton s not advsable, snce partcpants and non-partcpants usually dffer even n the absence of treatment (Calendo and Kopenng, 2005). Ths problem s known as selecton bas. The matchng approach s one possble soluton to ths problem. Heckmans s (1974, 1978, 1979) sample selecton model was developed usng an econometrc framework for handlng lmted dependent varables. Heckman s orgnal model focused on the ncdental truncaton of a dependent varable. Maddala (1983) extended the sample selecton perspectve to the evaluaton of treatment effectveness. The treatment effect model dffers from the sample selecton model n two aspects: frst, a dummy varable ndcatng the treatment condton w ( w = 1f the partcpant lve n the remttance-recevng household, and w0 = 0 otherwse) s drectly entered nto the regresson equaton and second the outcome varable y of the regresson equaton s observed for both w = 1, and w 0. Specfcally, the treatment 0 = effect model s expressed n two equatons: Regresson equaton: y = xβ + wδ + ε Selecton equaton: w = zγ + u, w = 1f w * > 0, and w = 0 otherwse * 7

9 P( w = 1z ) = Φ( zγ ) and P( w = 0 z ) = 1 Φ( zγ ) where ε j and u j are bvarate normal wth mean zero and covarance matrx σ ε ρ ρ 1 The paper estmates the probablty of recevng remttances as a functon of ndvdual and household characterstcs, rank remttance-recevng and non-recevng ndvduals by ther propensty score, par those ndvduals wth smlar propensty scores, and calculate the average dfference n labor force partcpaton across them. The focus wll be n the comparson of the labor market partcpaton of ndvduals exposed to no treatment (non-remttance recevng households) and labor market partcpaton of ndvduals exposed to treatment (remttance recevng households). Snce only one of these two outcomes s observed for each ndvdual, I wll estmate the dfference n labor market partcpaton between those treated and those wth the same probablty of beng treated (Ichno and Meall, 2005). Propensty score enables usng one-dmensonal nonparametrc regresson technques to estmate average treatment effect. Rosenbaum and Rubn (1983) showed that, f treatment assgnment and potental outcomes are ndependent condtonal to covarates X, then they are ndependent condtonal on a one-dmensonal propensty score, whch s the probablty of treatment gven X. Hence nstead of regressng on all covarates X t s suffcent to regress on ths propensty score to avod selecton bas. The propensty score s; p(x) P(D=1 X=x) = E(D X=x) where; ( X) F( h( )) p = X F (). can be the normal or the logstc cumulatve dstrbuton, D= 1f the subject s treated (receve remttances) and 0 otherwse, X s the vector of pre-treatment characterstcs. 8

10 3.2. The matchng methods The estmate of the propensty score s not enough to estmate ATT of nterest. The reason s that the probablty of observng two ndvduals wth exactly the same value of propensty score s n prncple zero snce p ( X) s a contnuous varable (Becker and Ichno, 2002). To overcome the problem the most wdely used are nearest neghbor matchng, radus matchng, kernel matchng and stratfcaton matchng. The nearest neghbor method conssts of matchng each treated (remttance-recevng) ndvdual wth the control (non remttance-recevng) ndvdual that has the closest propensty score. The method s usually appled wth replacement n the control unts. The nearest neghbor matchng estmator sorts all records by the estmated propensty score, and then searches forward and backward for the closest control unts. Treated s matched to that non-treated j such that: p p j = mn. { p } pk { D= } k 0 If for a treated unt forward and backward matches happen to equally well, then t wll be drawn ether the forward or forward matches. The nearest neghbor matchng wth replacement wll be used, where an ndvdual can be used more than once as a match. Matchng wth replacement nvolves a trade-off between bas and varance (Calendo and Kopeng, 2005). Wth replacement the average qualty of matchng wll ncrease and the bas wll decrease. On the other hand t ncreases the varance of the estmator (Smth and Todd, 2005). Wth the nearest neghbor method each treated unt has a match, but ths s not necessary the best match snce we are lookng for the closest. A soluton to the problem s to defne a neghborhood wthn whch a match can be consdered. Ths method s called radus matchng. The selecton of the radus should be approprate snce a very small radus can reject treated observaton. Kernel estmator compares the outcome of each treated unt to the average outcome of a group of non-treated ndvduals where the weght of each ndvdual n the comparson group s proportonal to the ndvdual s closeness to that n the comparson group. Kernel and Local Lnear 9

11 Matchng are non-nonparametrc matchng estmators that use weghted average of all ndvduals to construct a counterfactual outcome. Kernel matchng assocate to the outcome y of treated a matched outcome gven by a kernel-weghted average of the outcome of all non-treated, where the weght gven to non-treated j s n proporton to the closeness between and j: Y j = j D= 0 j D= 0 p p j K Y h p p j K h j Control j s outcome Y s weghted by; p p j K h w j = Where h s the closeness of matches p p j K j D= 0 h Weghts depend on the dstance between each ndvdual from the control group for whch the counterfactual s estmated. The applcaton of Kernel matchng needs to choose the kernel functon and the bandwdth parameter. The second appears to be more mportant, hgh bandwdth values lead to a better ft and a decreasng varance between the estmated and true densty functon. The dfference between kernel and local lnear matchng s that the second ncludes n addton to the ntercept a lnear term n the propensty score of a treated ndvdual. Ths seems an advantage when the comparson group s dstrbuted asymmetrcally around the treated ndvduals, e.g. when there are gaps n the propensty score dstrbuton (Calnedo and Kopeng, 2005). Another method consstng n the dvson n ntervals of the range of varaton of the propensty score s the stratfcaton matchng. Wthn each nterval treated and control ndvduals have on average the same propensty score. 10

12 The set of covarates wll nclude the followng ndvdual and household characterstcs: age, age squared, gender, schoolng, martal status, and number of chldren less than sx n the household, area of resdence, regon and ncome net from remttances. 4. Results In the study are ncluded 9,177 ndvduals between the ages of 19 and 65 from the four areas; Coastal, Central, Mountan and the captal Trana. In Fgure 1 we can notce the dstrbuton of the remttances and ther use. The majorty, about 82 percent of the remttances goes to the buldng or remodellng of the houses, whle only about 5 percent serves as nvestment to the households own busness. Fgure 1: Remttances n relaton to ther use Percent Investment n own busness Buldng/remodelng house Other 4 It s mportant to know who receves remttances how much dfferent s the household from the one not recevng anythng f sgnfcant dfferences exst. Table 1 presents statstcal tests of the dfferences n the two groups of households those recevng remttances and those not recevng. 11

13 Table1. Comparatve descrptve statstcs condtonal on recevng remttances Non Remttance Remttance Dfferences recevng HH Mean Standard devaton recevng HH Mean Standard devaton Dfferences Standard errors HH sze ***.054 Urban ***.015 Age *.393 Female ***.015 Educaton ***.125 Not workng ***.014 Central **.013 (Area) Mountan ***.013 (Area) Hours work ***.400 (per week) Head ***.013 Number of observatons 7,909 1,268 Note: ***, **, and * ndcate the statstc sgnfcance respectvely at 1, 5 and 10 percent level or better. Table 1 s desgned to compare the means of the two groups and test the statstc sgnfcance of the dfference of the means. As we can notce from the results the dfferences are all statstcally sgnfcant at dfferent sgnfcance level. Remttance-recevng households have a smaller household sze (4.27) n respect to the non remttance-recevng households (4.90). Ths dfference may be related to the fact that members or part of the household has mgrated. Remttance recevng are more lkely to be older and lvng n rural areas far from the central part of the country. The members of the household recevng remttances are less lkely to be the head of the famly and less lkely to be female. Remttance-recevng ndvduals have completed less years of schoolng (8.72) n comparson to ndvduals (9.05) that don t receve remttances. Not all the dfferences are statstcally sgnfcant at 1 percent level. However t s mport to put emphass n the hgher probablty of not workng for those ndvduals that lve n remttance-recevng households. There s a statstcally sgnfcant dfference n the hours of work durng a week around 2.26 more for those lvng n non remttance-recevng households. 12

14 A rgorous propensty score modelng begns wth estmaton of the condtonal probablty of recevng treatment, n our case of recevng remttances. In ths study I used the logstc regresson for estmatng the condtonal probablty of recevng remttances usng a vector of observed covarates shown n Table 2. Table 2: Estmaton of the probablty of recevng remttances Logstc regresson Receve Remttances (1) HH sze (.023)*** Urban (.087)*** Educaton.499 (.140)*** Educaton Squared (.025)*** Age (.021)** Age Squared.008 (.003)** Female (.095)*** Marred.083 (.031)* Coastal.302 (.121) Central.128 (.123) Mountan (.129) Head of HH (.117)*** Cons (.524) From the logstc estmaton the probablty of recevng remttances s the household lves n the urban area and the sze of the household s smaller. Beng marred and not the head of the famly ncreases the probablty of recevng remttances; maybe ths s related to the fact that male head members of the famly mostly mgrate lvng behnd the rest of the household. It s nterestng and n contrast wth Table 1 the postve relaton between the years of educaton and the probablty of recevng remttances. However, as expected the square of the years of educaton s negatvely 13

15 related wth the condtonal probablty. Younger members of the household are more lkely to receve remttances. The area of resdence of the household s not statstcally sgnfcant. By defnton a propensty score s a condtonal probablty of a study partcpant recevng treatment gven observed covarates; hence not only treated partcpants but also control partcpants have non zero propensty scores. Havng obtaned propenstes I used nearest neghbor matchng wthn a calper of.25σ p. For each treated observaton I fnd the non-treated observatons that are closest to the treated observaton to serve as the correspondng control observaton. Fgure 2: Propensty score hstogram by treatment status Propensty Score Wthout Remttances Wth Remttances Fgure 2 represents the dfferences n terms of partcpaton n the labor market of the two groups of remttance-recevng and non remttance-recevng condtonal to the covarates. In order to answer the queston posed n the begnnng of the paper I have to examne the dfference n the probablty of not workng and the hours of work per week. I group data n three categores; treated ndvduals, non-treated ndvduals, and matched control ndvduals. There are a total of 1,268 treated or remttance-recevng household members. However the common support s made of 953 household members. 14

16 In Table 3 are gven the dfferences between treated and matched controls and tested ther sgnfcance. We can notce the expected dfference between treated and non-treated ether n the probablty of not workng or n quantty of hours worked per week. However the most mportant dfference for us s the one between treated and the matched control. The comparson between a remttance-recevng ndvdual and a non remttance-recevng ndvdual does not gve us the nsght to understand completely the labor market partcpaton. Ths s why we need an ndvdual that s n every dmenson exactly alke the ndvdual who receves remttances except for the recept of remttances. Ths s the matched control. As we can notce, the dfference between the matched and the treated males s not statstcally sgnfcant. In the case of female the probablty of not partcpatng n the labor market s greater for those recevng remttances; ths dfference s not large enough n relaton to ts standard error to conclude that there s a sgnfcant dfference n ths probablty. However recevng remttances affect the hours worked for females, who are found to work around 3 hours fewer per week f they receve remttances. Ths dfference s statstcally sgnfcant. Propensty score matchng method accounts for endogenety because t captures unobservable characterstcs dstngushng remttance-recevng households from non remttancerecevng households. Table 3: Descrptve statstcs for the treated, non-treated and matched groups Treated Not Treated Test of the dfferences Matched Male Test of the dfferences Not n the labor force (.019)** Hours per week (.616)*** Female (.044) (2.023) Not n the labor force (.025)** (.011) Hours per week (.666)** (1.192)** Note: ***, **, and * ndcate the statstc sgnfcance respectvely at 1, 5 and 10 percent level or better. 15

17 Emprcal results show that recevng remttances for males does not have any mpact n the probablty of workng or hours worked per week. Recept of remttances seems to mpact the labor market behavor of females, because they reduce ther hours worked n presence of remttances. 4. Conclusons and comments The paper analyss whether the recept of remttances have any effect n the labor market partcpaton. I used propensty score matchng procedure to assess the relatonshp between remttances and the probablty of beng n the labor market. Results show that remttances do not alter the behavor of men on ther labor force partcpaton or hours worked. However there s a statstcally sgnfcant change n the labor market partcpaton of women. Women who work appear to reduce ther hours worked by 2.8 per week. A possble explanaton s that remttances ncrease the reservaton wage for women. Another explanaton maybe related wth the fact that the departure of a famly member may ncrease the need for more presence n the house envronment. It s mportant to hghlght the fact that remttances are receved by households wth sgnfcant dfferences n characterstcs. Accordng to the statstcal test n mean dfferences remttances are more lkely to be receved from older persons lvng n the rural area of the country. Remttancerecevng household members result to have less years of schoolng. Beng older and less educated puts persons n a bad poston n the labor market even wthout the presence of remttances. Mcro aspects of the dstorton n the labor market partcpaton due to the presence of remttances maybe an explanaton for the macro dynamcs of the labor market. Durng the last two decades of open economy era for Albana there has been a paradox n the relatonshp between growth rate and unemployment rate. Increasng trends of economc growth were not accompaned wth the decrease n the labor market. Ths can be consdered a consequence of remttances. These captal flows dscourage the partcpaton n the labor market wthout decreasng the unemployment rate bur n the other sde encourages consumpton of goods and servces. 16

18 References: Acosta, P. (2006). Labor Supply, School Attendance, And Remttances From Internatonal Mgraton: The case of El Salvador. World Bank Polcy Research Workng Paper 3903, Washngton DC: World Bank. Acosta, P., P. Fajnzylber and Lopez J. H. (2009). The Impact of Remttances on Poverty and Human Captal: Evdence from Latn Amercan Household Surveys. World Bank Polcy Research Workng Paper 4247, Washngton DC: World Bank. Adams, R. and J. Page. (2005). Do Internatonal Mgraton and Remttances Reduce Poverty n Developng Countres?. World Development 32: Amuedo-Dorantes, C. and S. Pozo. (2006). Mgraton, Remttances, and Male and Female Employment Patterns. The Amercan Economc Revew, 96: Azzarr, C. and C. Calogero. (2009). Modelng mgraton Dynamcs n Albana. A Hazard Functon Approach. World Bank Polcy Research Paper 4945, Washngton DC: World Bank. Becker, G. (1991). A Treatse on the Famly Enlarged Edton Cambrdge, Harvard Unversty Press. Becker, S., A. Ichno. (2002). Estmaton of Average Treatment Effects Based on Propensty Score. Stata Journal, 4 Cham, R., Fullenkamp C. and Jahjah S. (2003). Are Immgrant Remttance Flows a Source of captal for Development. IMF Workng Papers 03/189, Washngton, Internatonal Monetary Fund. Dermendzheva, Z. (2009). Mgraton, Remttances, and Labor Supply n Albana. Center for Economc Research and Graduate Educaton, Charles Unversty, Prague Funkhouser, E. (1995). Remttances from Internatonal Mgraton: A comparson of El Salvador and Ncaragua. Revew of Economcs and Statstcs, 77(1): Görlch, D., M., Toman O., and Ch. Trebesch. (2007). Explanng Labor Market Inactvty n Mgrant-Sendng Famles: Housework, Hammock, or Hgher Educaton?. Kel Insttute for World Development, Workng Paper Itzgsohn, J. (1995). Mgrant Remttances, Labor Markets, and Household Strateges: A comparatve Analyss of Low Income Household Strateges n the Carbbean Basn. Socal Forces, 74: Klc, T., Carletto, C., D., Benjamn, and A. Zezza. (2007). Investng Back Home: Return Mgraton and Busness Ownershp n Albana. World Bank Research Workng Paper seres 4366, Washngton DC: World Bank. Kozel, V. and H.Alderman. (1990). Factors Determnng Work Partcpaton and Labor Supply Decson n Pakstan s Urban Areas. Pakstan Development Revew, 29: Rapoport, H. and Docquer F. (2005). The Economcs of Mgrants Remttances, IZA Dscusson Paper, 153 Rodrguez, E. R. and E. Tongson. (2001). Temporary Mgraton Overseas and Household Labor Supply: Evdence from Urban Phlppnes. Internatonal Mgraton Revew, 35: Rosenbaum, P., D. Rubn. (1983). The Central Role of the Propensty Score n Observatonal Studes for Causal Effects. Bometrka. Woodruff, Ch. and R. Zenteno. (2007). Mgraton Network and Mcroenterprses n Mexco, Journal of Development Economcs, 82: Wooldrdge, Jeffrey M. (2002). Econometrc Analyss of Cross Secton and Panel Data, the MIT Press, Cambrdge Massachusetts. World Bank, (2010). Mgraton and Remttances Factbook