Remittances: a lifeline for developing

countries?

Maelan Le Go�∗and Sara Salomone†

October 14, 2013

Abstract

Migrants' remittances to developing countries have become the second largest

source of �nance for developing countries after foreign direct investment. Moreover,

while FDI and foreign aid have been strongly a�ected by the global crisis, remittances

have continued to provide a steady source of foreign currency to developing country

economies. However,the role of remittances for economic development is still an

open issue. This paper provides with some insights an overall portrait of existing

literature using original bilateral remittance data. The �rst section is devoted to the

description of the size and the evolution of remittances, the second one studies the

role of the educational and gender characteristics of migrant diaspora and the third

one explores the e�ects on growth, poverty and inequality in the origin country.

Keywords: International Migration, RemittancesJEL Classi�cation: J16, F22

∗CEPII, maelan.lego�@cepii.fr†IRES, Universite catholique de Louvain, sara.salomone@uclouvain.be

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1 Introduction

According to recent estimates of the World Bank (World Bank, 2013), o�cially recordedremittances to developing countries are estimated at $401 billion in 2012, remaining akey resource �ow far exceeding o�cial development assistance as well as private debt andportfolio equity. Moreover, their �ow to developing countries is expected to grow at 12.3percent reaching $515 billion in 2015, in so sustaining growth and development in emerg-ing markets, and serving as a lifeline to the poor.

However, this optimistic prevision clashes with the theoretical and the empirical �ndingsof the economic literature according to which the role of remittances for economic de-velopment is still an open issue. Indeed, even if remittances keep on growing steadily,their e�ect on poverty and inequality reduction as well as economic growth in recipientcountries is not clearcut, yet. Moreover, since the role of migrants'characteristics seemto be crucial for quantifying the amount of money remitted, two important features needto be considered in order to provide a more reliable portrait: the gender and the educa-tional level of migrants. What's more, in the last few decades, international migrationhas been characterized by a rapidly increasing feminization and brain drain. Secondly,at macroeconomic level, international remittances seem to �ow marginally to the poorestcountries: on the 372 billion received by developing countries in 2011, only 7 percent weresent to LDCs (Least Developed Countries). Among the top ten recipient countries involume in 2011, only one belonged to the LDCs, namely Bangladesh, while all other fellinto the middle income countries category. Considering remittance amounts as a shareof GDP, the picture is slightly more mixed: four of the top ten recipients were LDCs(Liberia, Lesotho, Nepal and Samoa). However, according to a recent UNCTAD's re-port, LDCs' remittance receipts have increased from 3.5 billion US dollars in 1990 to 27billion US dollars in 2011 (of which two-thirds reached Bangladesh, Nepal and Sudan).Furthermore, the report shows that remittances represent a larger share of GDP in LDCsthan in other developing countries (4.4 percent and 1.6 percent respectively). This factis driven by small LDCs, like Lesotho, and traditional recipient countries, like Nepal orHaiti, whose share of remittances in GDP exceeds ten percent. Thirdly, from an empiricalviewpoint, more accurate aggregate and bilateral data have to be preferred to statisticalestimates. A �rst attempt is the Docquier et al. (2012) bilateral remittances databasewhich collects and aggregates �ve available bilateral remittances databases covering from1985 to 2005. Figure 1 shows how when considering the relationship between remittancesand other international capital �ows, as foreign direct investments, portfolio equity ando�cial development assistance, the original portrait provided by the World Bank usingWorld Development Indicators overestimates the amount of aggregate yearly remittances.The aim of this paper is to go through the above three critical points, in providing in the

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light of migrants' characteristics (i.e. skill and gender) an overall portrait of the existingtheoretical and empirical literature on remittances. Section 2 describes the recent datacontribution by Docquier et al. (2012) and provides some �gures where the empirical sec-tion departs from. Section 3 empirically analyses the role of the educational and gendercharacteristics of migrant diaspora on remittances. Given the women and skilled people'spropensity to remit, Section 4 discusses whether remittances are an e�cient instrumentfor the development of recipient countries. Finally Section 5 concludes.

Figure 1: Remittances and other resource �ows (from 1985 to 2005)

2 Data analysis

To the best of our knowledge, the most comprehensive bilateral dataset currently avail-able documenting bilateral remittances is the one described in Docquier et al.(2012).1 Itmerges various second-hand sources to capture bilateral remittances from 89 sending to46 receiving countries over the period 1985-2005. The amount of remittances sent by

1The World Bank also provides bilateral remittances estimates for years 2010, 2011 and 2012. Thesedatasets update Ratha and Shaw (2007) by incorporating the latest migration data from 71 destinationcountries created by the University of Sussex Development Research Centre (Parsons et al., 2005) asdescribed in the Migration and Remittances Factbook 2011.

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transferring country j to recipient country i at time t is denoted by Rijt, and the size andstructure of bilateral migration stocks from origin country i to destination country j. ByMk,g

ijt , the stock of migrants with education level k and gender g is denoted.

2.1 Bilateral remittances

The DRS bilateral data set combines �ve existing bilateral databases constructed by otherauthors or organizations: the EU data as documented in a report of Jimenez-Martin, Jor-gensen and Labeaga (2007); the IMF database from Lueth and Ruiz-Arranz (2008); theRomanian one by De Sousa and Duval (2010); IDB one built by the Inter-American De-velopment Bank and the ECB database as in Schioupu and Siegfried (2006). The mergingprocedure, as described at lenght in Docquier et al. (2012), prevents from possible selfselection issues and gives rise to a data set going from 1985 to 2005 in which 8928 obser-vations for 1348 country pairs are available2. The remittances sending countries is: Aus-tralia, Austria, Bahrain, Belarus, Belgium, Canada, Cote d'Ivoire, Croatia, Cyprus, CzechRepublic, Denmark, Estonia, Finland, France, Germany, Greece, Guinea, Hungary, Iraq,Ireland, Israel, Italy, Japan, Kuwait, Kyrgyzstan, Latvia, Lithuania, Luxembourg, Mace-donia, Malaysia, Malta, Morocco, Netherlands, New Zealand, Norway, Oman, Poland,Portugal, Romania, Rwanda, Saudi Arabia, Singapore, Slovak Republic, Slovenia, SouthKorea, Spain, Sweden, Switzerland, Turkey, United Arab Emirates, United Kingdom,United States. While the recipient countries are: Albania, Algeria, Argentina, Armenia,Bangladesh, Belarus, Bolivia, Brazil, Bulgaria, China, Colombia, Costa Rica, Croatia,Dominican Republic, Ecuador, Egypt, El Salvador, Georgia, Ghana, Guatemala, Indone-sia, Israel, Jordan, Kazakhstan, Lebanon, Libya, Macedonia, Moldova, Morocco, Nigeria,Pakistan, Panama, Peru, Philippines, Romania, Russia, Serbia and Montenegro, Slovenia,Suriname, Syria, Tajikistan, Thailand, Tunisia, Ukraine, United States, Venezuela. Theonly developed origin countries are Israel, Slovenia and United States (which correspondsto only the 5% of the sample) so we can reasonably pursue the analysis just referring todeveloping countries e�ects.

2.2 Bilateral migration data

Migration data are taken from Docquier et al. (2012) who construct 195x195 matricesof bilateral migration stocks for 1990 and 2000. The matrices are computed for twoskill groups: migrants with college (tertiary) education, referred to as high-skill, andwith less than college education (primary and secondary), referred to as low-skill. The

2For the complete list of sending and receiving remittances countries see Docquier et al., 2012.

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methodology used in Docquier et al. (2010) consists of three steps. The starting pointis the database described in Docquier, Lowell and Marfouk (2009) documenting bilateralmigration stock to OECD host countries. It is based on a collection of census and registerimmigration data by country of birth and educational level in the 30 OECD countries.The second step consists of a collection of similar immigration data from 46 non-OECDdestinations in 2000 and 31 destinations in 1990. Finally, data collected in steps 1 and 2are used to predict the size and structure of migration to the remaining 119 non-OECDhost countries in 2000 (and 134 in 1990). Gravity regression models were estimated forthe size of bilateral migration from country i to country j in the education group k andgender g. The latter constructed data will not be used in our empirical analysis, whichonly builds on primary census data.

2.2.1 Some descriptive statistics

Table 1 reports some descriptive statistics concerning bilateral remittances and their re-lationship with the skill level and gender of the migrants. The �rst set of results concernsthe total amount of remittances. The mean level equals 5660890 up to 7718173 dol-lars if just high income destinations are considered. The best preferred North-Southcorridors are Bangladesh-United States, Bangladesh-United Kingdom, Philippines-UnitesStates, Philippines-Italy. If we aggregate remittances by remittances recipient countrythe Philippines occupy the �rst place with more than 6.26e+09 dollars per year. Thesecond set of results depicts the amount of remittances per migrant. The third one theamount of remittances by skilled migrant as well as share of skilled people among themigrants. The fourth one refers to the amount of remittances by female migrants plus abrief description of the share of women. For each set of results, we consider low and high-income destinations. The average level of remittances per migrant is 1022.92 dollars withSuriname-Cyprus being the �rst South-North corridor, 4508.71 per skilled individual withThailand-Israel occupying the �rst place as North-South corridor and 2549.25 per woman.The most feminized corridor is Guatemala-Greece while the one to which the more skilledwomen belong to is Tajikistan-Portugal. Additionally, the dispersion of remittances permigrant is very high, depending on the income nature of the paying country. The sameholds if the skill level or the gender of the migrant is accounted for. Finally, consideringthe skill and the gender composition of the migrant diaspora3. The mean level of the skillshare is 0.23 with slightly higher level if high-income countries are chosen meaning thatsome kind of positive self selection is in place. Inversely, if low income destinations areconsidered the level of skilled people drops drammatically. Concerning women instead,

3The skill and the female share of migrants have been calculated respectively as the ratio of tertiaryeducated migrants and females over total migrants

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the mean level of female share equals 0.37 up to 0.48 in high income destinations and 0.16in poor countries, showing a clear feminization of migration to developed countries.Figure 2 integrates the above analysis showing how between 1990 and 20004 both femalemigration and the brain drain have increased. On a global scale, the number of womenwho migrate is equal to that of men, and in certain regions is even higher. In 2000,women amounted to approximately 49 per cent of the total number of migrants in theworld. More precisely, migrating women and girls were slightly more numerous than menin developed countries. In developing countries, however, they totalled slightly less than45 per cent of all migrants. On a regional level, migrant women numerically outnumberedmen in Europe, Latin America and the Caribbean,North America and Oceania, while inAfrica and in Asia they were generally underrepresented when compared to men. Be-tween 1990 and 2000, the stock of skilled immigrants in OECD countries increased by 64percent. The rise was stronger for immigrants from developing countries (up 93 percent),especially from Africa (up 113 percent) and Latin America and the Caribbean (up 97percent). The same trend is performed by international remittances as Figure 3 shows.The main recipient countries are the Philippines, Bangladesh, Croatia and Thailand.

Figure 2: Skilled and female migration (from 1990 to 2000)

4We restricted the analysis to the decade between 1990 and 2000 because the Docquier et al. (2012)database at our disposal cover just these two years. However, as it will explained at lenght in Section ??

these two phenomena have lasted untill nowadays.

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Table 1: Summary StatisticsVariable Obs Mean Std. Dev. Min Max

Total bilateral remittancesFull dataset 8838 5660890 2.41e+07 0 2.81e+08Low income destinations 556 6089,414 44365,19 0 500000High Income destinations 5594 7718173 2.79e+07 0 2.81e+08

Remittances per migrantFull dataset 6822 1022,92 4108,12 0 56854,26Low income destinations 190 25,66 206,28 0 1907,18High Income destinations 6632 1051,49 4162,89 0 56854,26

Remittances per skilled migrantFull dataset 6610 4508,712 14866,7 0 155000Low income destinations 176 98,87484 762,4331 0 6787,33High Income destinations 6434 4629,341 15050,02 0 155000

Share of skilledFull dataset 8826 0,2339 0,215 0 0,883Low income destinations 556 0,064 0,132 0 0,539High Income destinations 5614 0,304 0,212 0 0,883

Remittances per female migrantFull dataset 6619 2549,247 9979,202 0 123405,7Low income destinations 190 59,65525 480,0127 0 4437,869High Income destinations 5148 2526,163 9706,142 0 109411,8

Share of femalesFull dataset 8827 0,371 0,282 0 0,988Low income destinations 556 0,164 0,235 0 0,888High Income destinations 5630 0,481 0,243 0 0,988

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Figure 3: Total Remittances (from 1990 to 2000)

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3 Empirical results

As Figure 2 and 3 have anticipated in Section 2.2.1, in the last few decades, internationalmigration has been characterized by a rapidly increasing feminization and brain drain.On one hand, women started to migrate more independently rather than for family re-uni�cation reasons or as dependants of male migrants and this led the number of womenwho migrate to become equal to that of men (and in certain regions is even higher). Onthe other hand, the quality-selective immigration biased policies implemented in manytraditional destinations boosted the immigration �ows of highly-skilled people. Thesenew migration patterns had, of course, direct consequences in terms of the economic andsocial development of the origin countries through the loss in terms of human capital, butalso an indirect impact through remittances. Many papers have addressed the �nancialcontribution of female migrant workers in their country of origin underlying how menand women di�er as far as their intentions to remit are concerned. On one hand, femaleswould remit more both overall and as a percentage of income because they tend to man-tain stronger networks with their restricted and extended family (Tacoli, 1999; Richterand Havanon, 1995; Phongpaichit, 1982; Chant and Radcli�e, 1992) and because theirremitting behaviour is driven more by altruism (Orozco, Lowell and Schneider, 2006). In-versely, women would remit less because of disadvantaged labor market conditions (Cortes,2011) and family reuni�cations (Holst, Schafer and Schrooten, 2012). The same holds forskilled migrants. At a macro level, Faini (2007) and Niimi, Ozden and Schi� (2010) foundthat migrants' remittances decrease with the proportion of skilled individuals among em-igrants. Dustmann and Mestres (2010) and Duval and Wol� (2011) evidenced the samenegative e�ect of education on remittances but at micro level. Schioupu and Siegfried(2006) showed instead a negative correlation between the share of low-skill workers andremittance receipts, suggesting that in contrast to the results obtained with aggregatedata, migrants' skills seem to raise remittances. Optimistic conclusions were also reachedby Docquier et al. (2012) who underlined the role of immigration policies in determiningthe sign and magnitude of the relationship between remittances and migrants' education.At a micro level, Bollard et al. (2011) found, instead, a mixed pattern between higher ed-ucation and the likelihood of remitting, and a strong positive relationship between highereducation and the amount remitted conditional on remitting5.

Since there is no consensus in the literature on the role of the educational and gender

5While a growing litterature has investigated the gender and skills of migrants as potential determi-nants of remittances, only little research has examined the role of gender and skills in remittance practicesand their e�ect on the development of home countries. While one should expect motivations behind re-mittances and the way in which they are spent, to vary with the gender and skills of migrants, theempirical literature analyzing the development outcomes of remittances has neglected these parameters

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characteristics of migrant diaspora on remittances, the aim of this paragraph is to shedsome light on it using bilateral remittances and a simple gravity model as in Docquier etal. (2012).6 The empirical model writes as follows:

lnRijdt = ηi + ηj + ηd + ηt + α0 + α1 lnMs+uijt + α2Fijt + α3Sijt

+α4 lnDij + α5Lij + α6Cij + α7Yit + α8Yjt + εijt (1)

where lnRijdt measures total remittances in US dollars in logs from transferring (i.e.immigration) country j to recipient (i.e. emigration) country i at time t in data set d,lnM s+u

ijt is the log of the bilateral migration stock from i to j, Fijt is the share of femalesover total bilateral migration and Sijt is the share of skilled people over total bilateralmigration. lnDij, Lij and Cij are three bilateral variables accounting for geographical,linguistic and cultural distances. Origin, destination, time and database �xed e�ects areincluded. We also control for nominal GDP at origin and destination (Yit and Yjt).

The estimation of the equation (1) entails various econometric issues7 that may lead theOLS estimation to generate inconsistent estimates. Moreover, there is a large proportionof zeros for the dependent variable (bilateral remittances) due to the fact that we con-structed our comprehensive database on remittances to make it as balanced as possible,as extensively discussed in Docquier et al. (2012).

To the best of our knowledge, the most appropriate way to estimate the above modelis the Poisson regression by pseudomaximum likelihood. The new command PPML inStata di�ers from the old one called poisson because it uses the method of Santos Silvaand Tenreyro (2010) to identify and drop regressors that may cause the nonexistence ofthe (pseudo-) maximum likelihood estimates. All the PPML models are estimated bydefault with robust standard errors.

Table 2 reports estimation results for the base speci�cation. The share of females atdestination is always positive and signi�cant as well as the share skilled migrants8, evenwhen both are controlled for simoultaneously. Moreover, the stock of migrants at desti-nation is positive and signi�cant, too. On the validity of the gravity factors (Lueth andRuiz-Arranz, 2008), geographical distance is negative but not signi�cant, linguistic and

6The empirical speci�cation adopted in this paper consists in a gravity model which has been �rstused by Lueth and Ruiz-Arranz (2008). The educational level of the migrants was instead present inSchioupu and Siegfried (2006).

7between remittances and female migration. In the micro literature the presence of an implicit familyloan arrangement can hide circular family migration due to remittances (see Poirine, B. (1997): A Theoryof Remittances as an Implicit Family Loan Arrangement, World Development, Vol. 25, N.4, 589-611)and this can imply that the intention to remit is endogenous.

8In Docquier et al. (2012) the skill ratio was used in order to be consistent witht the theoretical part.

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cultural proximity are positive and highly signi�cant. As far as nominal GDP variablesare concerned, the positive sign for both the level of GDP at origin and that at destinationcon�rms that larger countries receive (and send) larger volumes of remittances in dollarterms. For the interpretation of the results, Poisson coe�cients have to interpreted assemi-elasticities. Given the exponential function form of the conditional mean, it meansfor example that a one unit increase in the share of females in the migration diasporaleads to a 11% increase in annual remittances. Then, a one unit increase in the shareof skilled in the migration diaspora leads to a 8% increase in annual remittances. Thepercentage increases remain stable even when the two covariates are jointly controlled for.Finally, as an addittional empirical exercise, the share of skilled and unskilled females inthe diaspora is introduced (column 4 and 5). It is shown that the remitting propensity byfemales is clearly driven by skilled women relatively to the unskilled ones. More precisely,the increase corresponds to (100 ∗ eβ − 1) and just the multiplicative e�ect to (eβ). Themultiplicative e�ect on remittances for the female share in the migration diaspora is equalto 1.11, for the skill share to 1.08, and �nally if just skilled women are taken into account1.23.

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Table 2: Poisson estimations accounting for gender and educationPoisson Poisson Poisson Poisson PoissonRijdt Rijdt Rijdt Rijdt Rijdt(1) (2) (3) (4) (5)

Stock of Migrants at dest. (log) 0.739*** 0.665*** 0.760*** 0.761*** 0.743***(0.029) (0.06) (0.032) (0.030) (0.029)

Share of females at dest. 0.112*** 0.109***(0.035) (0.035)

Share of skilled people at dest. 0.085** 0.075*(0.045) (0.045)

Share of skilled females at dest. 0.214***(0.058)

Share of unskilled females at dest. 0.062*(0.0357)

GDP at origin (log) 1.36* 1.557** 1.111* 1.158* 0.939*(0.75) (0.779) (0.739) (0.751) (0.749)

GDP at dest. (log) 0.152*** 0.147*** 0.151*** 0.147*** 0.154***(0.317) (0.317) (0.319) (0.319) (0.314)

Distance (log) -0.008 -0.015 -0.008 -0.018 -0.011(0.016) (0.016) (0.016) (0.016) (0.016)

Common language (dummy) 0.417*** 0.375** 0.337* 0.268 0.521***(0.159) (0.168) (0.173) (0.171) (0.156)

Colony (dummy) 0.808*** 0.658** 0.812*** 0.767*** 0.740***(0.168) (0.167) (0.168) (0.170) (0.163)

Constant -39.43** -44.76** -40.81** -41.04** -36.33**(16.47) (17.21) (16.43) (16.71) (16.64)

Origin FE yes yes yes yes yesDestination FE yes yes yes yes yesYear FE yes yes yes yes yesDatabase FE yes yes yes yes yesPseudo log-likelihood -4.58E+13 -4.574e+10 -4.52E+13 -4.53E+13 -4.57E+13Observations 8,888 8,888 8,888 8,888 8,888

* Signi�cant at the 10% level ** 5% level *** 1% levelRobust standard errors in parentheses below the estimates.

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4 Remittances and development of migrants' origin coun-

tries

According to our empirical part, the recent feminization and the increasing quali�cation ofmigrants should have a signi�cant and positive e�ect on amounts of remittances receivedby developing countries. However, uncertainty still remains about the e�ect of remittanceson the development of migrant origin countries. While the poverty-reducing impact ofremittances has been extensively highlighted in the literature, their ability to reduceincome inequality whithin recipient countries and to foster economic growth are still indebate. The impact of migrant remittances on recipient economies, especially with respectto poverty reduction and economic growth, depends on who bene�ts from remittances, onthe amounts remitted and how these �nancing �ows are spent. While a growing litteraturehas investigated the gender and skills of migrants as potential determinants of remittances,only little research has examined the role of gender and skills in remittance practices andtheir e�ect on the development of home countries. While one should expect remittancerecipients, motivations behind remittances and the way in which they are spent, to varywith the gender and skills of migrants, the empirical literature analyzing the developmentoutcomes of remittances has neglected these parameters.

4.1 Poverty and inequality

Representing an additional source of income for recipient households, migrant remittancesmay potentially contribute to poverty and income inequality reduction in developing coun-tries.9 Several cross-country studies found evidence of an average poverty-decreasing ef-fect of international remittances. For example, using a sample of 71 developing countries,Adams and Page (2005) showed that international remittances signi�cantly mitigate theincidence, depth and severity of poverty in recipient countries. On average, a 10 percentincrease in international remittances per capita received may reduce poverty incidenceby 3.5 percent. Similar �ndings were obtained in samples of Latin American countries(Acosta et al., 2008), Asian and Paci�c countries (Jongwanich, 2007) or African economies(Gupta et al., 2007; Anyanwu and Erhijakpor, 2010). Moises and Donghun (2011) in-vestigated the impact of international remittances across poverty quantiles in developingcountries. Their results evidenced that the poverty-alleviating e�ect of remittances is moreimportant in countries belonging to the poorest quantiles. Similarly, most of country-casestudies show a signi�cant e�ect of international remittances on the share of population

9This "curative" e�ect of remittances on the prevalence of poverty may be reinforced by a "preventinge�ect". Indeed, by playing as an informal insurance mechansim, remittances may prevent householdslocated in the bottom of the income scale from falling in poverty in case of an income shock.

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living below the poverty line, but the size of the impact varies with countries and withthe methodology used. Early studies examined the impact of remittances on poverty bytreating remittances as an exogenous source of income. Using this approach in the caseof household level data on Lesotho, Gustafsson and MacKonnen (1993) found that remit-tances have a signi�cant poverty-alleviation e�ect, especially for the depth and severityof poverty. Because this methodology denies the possible income loss consecutive to theleave of the migrant, some scholars adopted a counterfactual approach. This consists inregarding remittances as a substitute to virtual earnings that could have been generatedby migrants if they had stayed home. Using this methodology, Adams (2006) showedfor example that an increase in internatrional remittances is associated with poverty-reduction in Ghana.

Existing �ndings on the impact of remittances on income inequality are more con�icting.By considering remittance �ows as an exogenous source of income, Ahlburg (1996) andBrown and Connell (1993) evidenced a signi�cant inequality-decreasing e�ect of remit-tances. However, because migration is often associated with very high costs, migrantremittances may constitute �inequality accelerators� in migrant-source areas, as arguedLipton (1980), Stahl (1982) and Stark, Taylor and Yitzhaki (1986). A few country-casestudies, like Leones and Feldman (1998), Rivera (2005) and Wouterse (2010)10 have em-pirically con�rmed this intuition. Following the same methodology, Yang and Martinez(2007), as for them, found no signi�cant e�et of international remittances on income dis-tribution in the case of Philippines. Other analysis have taken into account the potentialindirect impact of remittances on home earnings. Taylor (1992) found that the amountof remittances received in 1982 by Mexico led six years later to a decline of 0,01 percentin the Gini coe�cient. Using the same database, Taylor and Wyatt (1996) improved thisframework by unloosing the constraint according to which indirect e�ects are the samefor all households.11 Their �ndings enlightened that when indirect e�ects are taken intoaccount, the inequality decreasing e�ect of remittances increases (because the indirectimpact may be more important for households located in low steps of the income distri-bution). Finally, through the adoption of a counterfactual approach, Adams (1989) andRodriguez (1998) showed that international remittances tend to raise income inequality,in the case of Egypt and the Phillipines respectively. Using the same approach, Ratha(2005) and Lokshin et al. (2007) found instead an inequality-decreasing e�ect of remit-

10Note, however, that results of Rivera (2005) and Wouterse (2010) supported this theory only in thecase of international remittances. Because internal migration is less costly, internal remittances appearedto not have this distortion e�ect

11They supposed that remittances have weaker indirect e�ects on the richest households which do notface liquidity constraints and are able to insure themselves against shocks of production without relyingon remittances.

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tances. Furthermore, for a same country, the alternative use of the two approaches leadsto contradictory results (see Brown and Jimenez, 2007; Barham and Boucher, 1998).Next to all these country-case studies, a few cross-section analysis found evidence of asmall inequality-decreasing e�ect of remittances (Acosta et al., 2008; Chauvet and Mesple-Somps, 2007).12 Possible factors have been underlined to explain the con�icting �ndingsregarding the remittance-inequality relationship, like migration history and the associateddevelopment of migrant networks (Massey, Goldring and Durand, 1994; Stark, Taylor andYitzhaki, 1988; McKenzie and Rapoport, 2007) or the initial distribution of national in-come (McKenzie and Rapoport, 2007).

The existence and the magnitude of the poverty- and inequality-reducing e�ects of re-mittances depend on the location of recipient households in the national distribution ofincome and with respect to the poverty line. According to the neo-classical approach ofmigration, migration is considered as a rational choice of individuals who evaluate whatthey could gain from migrating 13, it follows that households are not randomly a�ectedby the migration process. Self-selection models (Borjas, 1987, 1990; Chiswick, 1999)predict that individuals' self-selection in the migration process depends on di�erences inreturns to labour across countries, but also on individuals' observable (skills, experience,migration network, etc.) and unobservable characteristics (motivation, ability to adapt,etc.) that determine their capacity to reap bene�ts of migration. If we assume thatthese features are rather homogeneous between individuals in a same income group, somedeciles are likely to be more a�ected by the migration process and as a result, to receiveremittances. It follows that remittances' distribution may be not uniform within incomecategories and largely determined by the characteristics of migrants. The literature oninternational migration has placed special emphasis on evidencing observables featuresbehind the migration-decision making, in particular migrants' skills, with mixed results.Adapting the Roy's model (1951) to the migration selection issue, Borjas (1987, 1990)evidenced theoretically that the direction of self-selection depends on the inequality levelin the home country: migrants from unequal countries tend to be less skilled than the av-erage worker in home and host countries (negative self-selection). Introducing migrationcosts to the human capital theory of migration, the model of Chiswick (1999) predicts onthe contrary higher incentives to migrate among skilled people (positive self-selection).

12Some papers, like Adams, Cuecuecha and Page (2008) or Wouterse (2010) evidenced that internalremittances and international remittances bene�t the poor di�erently. Because international migration ismore costly than internal migration, poor people would engage more in internal migration and receive, asa consequence, more internal remittances than international �ows. It follows that the magnitude of theimpact of remittances on poverty reduction and on inequality would depend on the type of remittancesreceived.

13See work of Sjaastad, Harris, Todaro for internal migration models and Borjas (1987, 1990) orChiswick (1999) for international migration models.

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This prediction had been evidenced empirically in Chiquiar and Hanson (2005) with dataon migrants from Mexico to the United-States. Assuming that migration networks maydrive migration costs down, McKenzie and Rapoport (2010) introduced network e�ectsin the model of Chiquiar and Hanson (2005). They found that the direction of selectiondepends on the development of migration networks: less-educated people are more likelyto migrate when networks are extended, while education increases propensity to migratewhen networks are weak.

Whether migration �ows are mainly composed of skilled or low-skilled people may in�u-ence the e�ect of following remittances on poverty and inequality reduction (assumingthat migrant skills are positively correlated with the wealth of their family). The recentevolution of migrant composition towards a higher share of skilled-workers, coming mostlyfrom the richer households, could prevent the potential poverty-reducing e�ect of remit-tances and induce an increase in income inequality.

4.2 Economic growth

Findings of empirical analysis conducted on cross-country data do not converge. Focusingon a panel of 83 developed and developing countries, Chami, Fullenkamp and Jajah (2005)showed support for the view that remittances hamper economic growth. They explainedthis result by the existence of a moral hazard problem (regular �ows of remittances couldlead to a moral hazard phenomenon. Representing a dependable income, remittancescould diminish bene�ciaries' work e�ort or their incentives to participate in the labourmarket). Although Chami et al. (2005) controlled for the potential endogeneity of remit-tances through an instrumental variable strategy, the validity of their instruments hadbeen questioned (Catrinescu et al., 2009). To address problems of residuals' autocorre-lation and the endogeneity of remittances, Catrinescu et al. (2009) used Dynamic PanelData estimators. Their �ndings evidenced instead a signi�cant growth-enhancing e�ectof remittances. To better understand the e�ect of remittances on growth and overcomethe ambiguity of empirical �ndings, a literature has examined the conditions in recipientcountries required to enhance a growth-enhancing e�ect of remittances. Investment useof remittances and their impact on growth are expected to be positively correlated witha good business climate in recipient countries, involving �nancial development and soundinstitutions at home. While the role played by �nancial development in the remittance-growth relationship has been largely identi�ed, the nature of this relationship remainsunclear. Findings of Giuliano and Ruiz-Arranz (2009) showed that remittances can pro-mote economic growth only in developing countries where �nancial institutions are weak,

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suggesting a substitute relationship between remittances and �nancial development ineconomic growth. On a panel of Latin American and Caribbean countries, Mundaca(2009) reached opposite results: the more developed the �nancial system is, the greaterthe positive e�ect of remittances on economic growth. Nyamongo et al.(2012) and Bettinand Zazzaro (2012) evidenced the same complement relationship between remittances and�nancial development in growth. In addition to �nancial development, Singh et al. (2011)identi�ed the quality of institutions in recipient countries as a required condition for re-mittances to signi�cantly promote growth in sub-Saharan African countries. Similarly,Catrinescu et al. (2009) showed that the growth-enhancing e�ect evidenced increases withsound institutions.

While the e�ect of migrant remittances on poverty and inequality mainly depends on thelocation of recipients in the national income distribution, their ability to generate eco-nomic growth mainly relies on their use.14 Several country-case studies based on householdsurveys showed that remittances mostly go towards basic needs. However, besides beinga �nancing source for households' consumption expenditures, migrant remittances mayhelp alleviate credit constraints that weigh on households and �nance small private invest-ments.15 Remittances could �nance investment directly or help recipients to access formalcredits (increasing personal capital contributions or served as guaranties to obtain busi-ness loans like the "remittance-based business loans"). A few papers highlighted the roleplayed by remittances in stimulating investment in agriculture, in small enterprises and inhuman capital. Adams (1998) found that international remittances signi�cantly help ruralPakistanis households to accumulate irrigated land. Regarding Mexico, Massey and Par-rado (1998) evidenced a signi�cant and positive e�ect of remittances sent from the US onthe odds of business formation and productive investment. Yang (2008) used the changesin exchanged rates experienced by Filipinos migrants during the Asian �nancial crisis toestimate the impact of exogenous remittance shocks on both human and physical capitalinvestment in Filipinos recipient households. He found that exogenous rises in migrantremittances promote educational expenditures as well as hours worked in self-employmentand the probability for households to engage into a new entrepreneurial activity (espe-cially in activities involving substantial investment in physical capital: transportationand communication services and manufacturing). Focusing on Guatemalan households,Adams and Cuecuecha (2010) showed that remittance-recipients household are likely to

14They may also a�ect economic growth through �nancial development (Gupta et al., 2007), multipliere�ects of consumption spending or the reduction of recipient countries' competitiveness (Dutch diseasephenomenon)

15A few papers have also emphasized that savings of returning migrants can participate signi�cantly insetting up small businesses: Ilahi (1999) on Pakistan, McCormick and Wahba (2001) on Egypt, Mesnard(2004) on Tunisia and Dustmann and Kirkchamp (2002) on Turkey, amongst others.

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spend more for education than non-recipients. Besides, several empirical �ndings haveevidenced a positive e�ect of remittances on educational performance in recipient house-holds (for example, Cox-Edwards and Ureta, 2003).

A very few micro-analysis have examined wheteher investment motives of remittancesmay di�er with migrant skills and gender. De la Briere et al.(2002) found, for example,that both remittances from male and female Dominican migrants can respond to invest-ment considerations. However, Itzigsohn and Giorguli-Saucedo (2005) argued that womenhave less incentives to return to their country of origin, what could explain their lowerinvestment in business at home. Moreover, because female migrants have less access tobanking services, their remittances tend to be used mostly for family support than fortheir own savings. Using descriptive statistics on Afghan, Egyptian and Serbian migrantsliving in Germany, Vadean (2006) examined how migrant skills may in�uence remittancebehavior and use. He found that skilled migrants are likely to remit more for productiveinvestment. However, Because of the limited literature on this topic, it is di�cult topredict the possible in�uence of the evolution in the composition of migration �ows onthe remittance-growth relationship.

5 Conclusions

Using a new comprehensive dataset of bilateral remittances from 89 sending countries to46 receiving economies over the period 1985-2005, this paper investigates whether changesin the composition of migration �ows may shape remittance patterns. The estimationsof a simple gravity model of remittances reveal that the skills and gender of migrantssigni�cantly matter in determining remittance �ows. First, our results show that the shareof females and skilled in the migration diaspora sign�cantly increases annual remittancesreceived in the country of origin. Moreover, we found that the positive role played byfemales on remittances is mainly driven by skilled women relatively to unskilled ones.Given these �ndings, we could expect a positive e�ect of the recent feminization and theincreasing quali�cation of migrants on annual remittance in�ows received by developingcountries. To go further, a next step will consist in using our empirical results and morerecent �gures on the composition of international migration, to forecast the recent trend ofinternational remittances �owing to developing countries. Beside their e�ect on remittanceamounts, the composition of migration could also a�ect the impact of remittances onpoverty (if skilled people mainly come from better-o� households) and economic growth(if motivations and the use of remittances tend to vary with the caracteristics of migrants,for example). However, empirical studies on these issues are very scarce and mainly based

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on speci�c countries. To better understand the possible e�ects of the recent evolutionin the composition of international migration on recipient economies' development, thisstrand of literature needs to be further investigated.

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