Discussion Papers In Economics
And Business

Motivation behind remittance from migrants:
Evidence from Albania
Daichi Shimamoto
Discussion Paper 14-05

Graduate School of Economics andOsaka School of International Public Policy (OSIPP)
Osaka University, Toyonaka, Osaka 560-0043, JAPANMotivation behind remittance from migrants:
Evidence from Albania
Daichi Shimamoto
Discussion Paper 14-05

February 2014

Graduate School of Economics andOsaka School of International Public Policy (OSIPP)
Osaka University, Toyonaka, Osaka 560-0043, JAPANMotivation behind remittance from migrants: Evidence from
Albania
Daichi Shimamoto†‡

Abstract
In Albania, remittance has been an important factor for the country’s economic growth since thecollapse of the country’s communist regime in the early 1990s. In this paper, I investigated why migrants
send remittance to their parents household. In the analysis, I considered four remittance motivations:altruistic, exchange, insurance, and inheritance motivations. To control sample selection of migration, I
apply the Heckman sample selection model.

The results suggest that migrants in Albania are driven to

remit owing to a combination of altruistic, exchange, and inheritance motivations. Further, migration
destination influences remittance amount, which implies that not only the local labor market andexchange rate at the final destination but also migration motivation factors affect remittance amount.

JEL Classification Codes: F22, F24, O52
Keywords: Migration, Remittance, Albania†

Graduate School of Economics, Osaka University, Japan.

‡

Research Fellow, Japan Society for the Promotion of Science, Japan

E-mail: d.shimamoto0407@gmail.com* We are deeply grateful to Tsunehiro Otsuki, Fumio Ohtake, Masaru Sasaki, Miki Kohara, Hiroyuki Yamada, Takahiro Itoh andother participants of the Japanese Economic Association Meeting at Hokkaido University, Applied econometrics conference at
Hitotsubashi University, Trans-Pacific Labor Seminar at Doshisha University, Labor Economic Workshop, seminars at Osaka
University for their helpful comments and discussions.

1.

Introduction
A large number of migrants, mainly motivated by economic factors, have left

Albania over recent decades. After the collapse of the country’s communist regime inthe early 1990s, Albanians suffered poor economic outcomes (e.g., high poverty andhigh unemployment), and thus, the number of international migrants rapidly expanded,
especially to nearby countries such as Greece and Italy. In line with this trend, migrants
are increasingly sending remittances to their families in their home countries in order tosoften their economic difficulties. Migrant remittance has thus risen year by year; in
2009, total remittances exceeded $1.3 billion, twice the total value of Albania’s exports,
seven times its inward ODA, and five times its inward FDI (World Bank 2010).
Although income shocks (e.g., unemployment, ceremonial occasions, andnatural disasters) can be often unavoidable, in a poor credit market environment such asthat commonly found in developing countries, it is difficult to overcome such shocks
through formal financial institutions. In such an environment, intra-household income
transfer thus serves as a potential channel to smoothen consumption (Rosenzweig and
Stark 1989). Previous studies have found that remittances sent to developing countries
allow households not only to meet their daily expenses, but also to invest in humancapital such as education and health (Gobel 2013; Adams and Cuecuecha 2010).
Therefore, these studies imply that remittance has the potential to contribute tolong-term economic growth by investing in human capital as well as reducing poverty.
Development economists have previously attempted to explain the motivations
behind migrant remittance. For example, Cox et al. (1998) investigate altruistic1motivation and exchange motivation using household survey data in Peru. In the samevein, de la Briere et al. (2002) find that migration destination is related to remittancemotivation in the Dominican Republic. They show that while adult female migrants in
the US are driven to remit because of insurance motivations, other migrants remit inorder to receive inheritance from their parents. Based on the foregoing, the present
study examines in more depth the underlying reasons why individuals remit to theirfamilies in their home countries. In particular, I investigate four of the main motivations
behind migrant remittance comprehensively: altruistic motivation, exchange motivation,
insurance motivation, and inheritance motivation.
Although previous studies have argued that migration is not random sample ofthe population (Stark and Lucus 1988; Hoddinott 1994), their estimations of thedeterminants of remittance have ignored the selection mechanism of migration. If thisselection mechanism affects the determinants of remittance amount, an OLS estimationof these determinants should be biased1. Therefore, in order to avoid biased estimators,
this study applies the Heckman selection model for the estimation.
The remainder of this study is organized as follows. Section 2 describes thepattern of migration and remittance in Albania. Section 3 explains the four main
motivations behind migrant remittance. Section 4 discusses the empirical methods,
while Section 5 presents the dataset used and summarizes the statistics. Section 6
1

Other studies adopt a type one Tobit model in order to estimate the determinants of remittance.

However, such models (sometimes incorrectly) assume the covariates affect decision-making
regarding whether individuals remit to parents and the remittance amount in an identical manner.

2

discusses the results and Section 7 concludes.

2.

Migrant Remittance in Albania

2.1. Migration in Albania
The communist regime that ruled Albania from the end of World War II until
1990 prohibited migration. Given that living standards in Albania were the worst of all
Eastern European countries at the fall of the regime, individuals and families soon
began to migrate to urban areas or nearby countries to improve their lives. Consequently,internal and international migration increased at an explosive pace. The stabilization of
the political and economic situation in 1992 steadied the flow of migration. However, in
1996, when the country’s formal pyramid savings schemes (so-called Ponzi schemeswith savings amounting to over half of the GDP for 1996) collapsed, the politicalsystem fell into turmoil and the flow of international migration was re-ignited. Only as
the economy gradually recovered from 1998 to 2002 did the outflow of migration
restabilize (Carletto et al. 2004).
In Albania, migration is a household strategy for overcoming economic
difficulties (e.g., poverty, unemployment) (Azzarri and Carletto 2009). The maininternational destinations for migrants are neighboring countries such as Greece and
Italy (Chaloff 2008), although Albanians also emigrate to other destinations such as the
US, England, Australia, Canada, Turkey, France, and Macedonia (World Bank 2010).
Migrants are likely to remit to their families in their home countries. From a macro
standpoint, international remittances increased rapidly since the fall of communism in3

1992 to 2007, but since 2008, the amount has decreased because of the global financial
crisis (Figure 12). Nevertheless, in 2009, total remittances still exceeded $1.3 billion(World Bank 2010). This substantial figure implies that remittance is an importantsource of foreign currency earnings in Albania.
The Albanian government supports the flow of out migrants through its National
Strategy on Migration, which was proposed by the International Organization for
Migration. The main objective of this policy is to enhance the link between migrationand the development of Albania by directing remittances to invest into businessactivities (Chaloff 2008). In this regard, the government supports Albanian migrants byimproving their treatment in their final destinations (e.g., improving their image andprotecting the rights of Albanian migrants). The government also intervene themigration process (e.g., access to information on emigration possibilities, registration of
migrants, and visa policy).
2.2. The characteristics of migrants
In this study, a migrant is defined as a child living away from home. As of 2010,
the stock of migrants in Albania was 1,438,300, which corresponded to 45.4% of thenational population (World Bank 2010). Table 1 presents the demographic
characteristics of the migrants sampled in this study by destination. The dataset used inthis study includes 20,015 individuals; of these, 15,816 of them have not migrated(non-migrants), 2370 have migrated internally, 712 have migrated to Greece, 763 havemigrated to Italy, and 354 have migrated to other countries. Although there are no major
2

Data source: World Bank (2010)4differences in the age of international migrants, the average age of internal migrants is36.5 years, which is the oldest among migrants. The educational level of migrants (13years of schooling on average) is higher than that for non-migrants. The majority ofinternational migrants tend to be men: 62.5% of migrants to Greece, 68.7% of migrants
to Italy, and 59.0% of migrants to other countries. By contrast, only one-third (32.4%)
of internal migrants are men. The age of the eldest son of international migrants ishigher than that for non-migrants and internal migrants. Finally, no large differences
between non-migrants and internal migrants are observed.
There are differences in living status between internal and international migrants.
Whereas more than half of international migrants live with their partners, fewer than 3%of internal migrants do so. The high proportion of women among internal migrants
suggests that Albanian women do not migrate for marriage reasons, in contrast to Indian
women (Rosenzweig and Stark 1989). Approximately 10% of migrants to Greece and
Italy have a partner living in the parents’ household (PH) compared with fewer than 5%of internal migrants and migrants to other countries. These differences in living status
between internal and international migrants might be accounted for by differences in thedeterminants of migration. As noted earlier, international migrants might be motivated
not only for passage with family but also for alleviating financial difficulties in thehome country (Azzarri and Carletto 2009). However, differences in remittance amount
can be caused not only by a migrant’s motivations but also by the economic conditionsof the final destination (e.g., labor market and exchange rate).
2.3. Remittance probability and amount5Remittance probability and amount depends on income distribution3. Table 2
indicates the probability of the migrant’s PH receiving remittance across income
percentiles, showing there are no large differences. Indeed, the probability that poorer
households receive remittance is only slightly higher than that for other households. By
contrast, remittance amount differs across income percentiles. The poorest households
receive the highest remittance amounts, which implies that relatively poorer households
tend to obtain greater benefits from migrant remittance.
2.4. Use of remittance
Households in developing countries can have limited access to formal financial
institutions, which means that many families might face liquidity constraints. Therefore,
remittance is expected to improve the welfare of the PH. Further, if a household’s
consumption level is above the subsistence level, remittance can allow investment.
Previous studies have found that remittance and various types of household investments
in developing countries are positively correlated. For example, Rozelle et al (1999)
show that agricultural investment is positively correlated with remittance in rural areasof China. Similarly, entrepreneurship and small business investment have also beenshown to be positively correlated in several countries (Dustmann and Kirchkamp 2002;
Woodruff and Zentero 2007; Meanard 2004), while education investments are
positively correlated with remittance in El Salvador and Guatemala (Edwards and Ureta
2003; Adams and Cuecuecha 2010). Table 3 also reveals a similar trend in Albania.
3

The presented sample consists of migrants who remit below 100,000 LEKS per month andmigrants that do not remit to their PHs. This limitation aims to alleviate the effect of outliners on thecalculation of average remittance amounts. The amount of 100,000 LEKS per month corresponds tothe 95% percentile.

6According to the World Bank’s Living Standards Measurement Study for Albania(LSMS hereafter) (2003), remittance from international migrants is used not only fornecessities, but also for investment into education, construction, and householdbusinesses. Thus, remittance has the potential to improve long-term economic growth inAlbania as well as smooth consumption.

3.

Motivations behind RemittanceFour remittance motivations are considered in this study, namely altruistic,

insurance, exchange, and inheritance motivation, based on the theoretical model
proposed by Rapport and Docquier (2006). For all four of these motivations, I assume
that there are two agents: one migrant and one PH.
3.1. Altruistic motivation
Here, I consider the case of unilateral altruism, where only migrants are altruistic.
Under altruistic motivation, migrant utility is assumed to consist of two elements: own
consumption and PH consumption. Therefore, altruistic migrants can gain fromincreasing not only their own consumption but also PH consumption. Migrants’decision-making on remittance amount thus depends on PH consumption level and theiraltruism degree. When PH consumption level is low, which implies that the marginalutility gain of remittance is relatively high, migrants increase remittance amounts tomaximize their own utility. By contrast, when PH consumption is high, migrants remit
less. Further, migrants with a high altruism degree remit more, because relatively highaltruistic migrants can receive higher marginal utility gain. In other words, altruistic
7

motivation predicts that remittance amount increases with migrant income and altruism
degree, but decreases with PH income. However, since altruism degree and migrantincome are not available in the data, PH income level and income determinants are usedas determining factors for altruistic motivation.
3.2. Exchange motivation
Exchange motivation can take different forms. For example, when parents takecare of a migrant’s children, the migrant might remit to the PH as a type ofcompensation. In such a case, remittance can be conceived as the purchase of services
supplied by the parents. In addition, migrants might remit to the PH to repay the costs
borne by parents before their migration (e.g., transaction costs and education fees).
In contrast to altruistic motivation, exchange motivation postulates that migrantutility is composed of own consumption and parental services. When the marginalutility gain of services is positive for the migrant, it is negative for the PH because theparents have to cover the cost of the services. Therefore, if the PH utility gain fromsupplying the service is less than that derived from not supplying the service, no service
is supplied (i.e., the entry constraint of the parents). An increase in PH income, whichmeans a rise in the opportunity cost of parents, implies an increase in the service priceand a subsequent increase in remittance amount (i.e., the entry constraint of the
migrant).
In the same vein, if the utility gain from receiving the service is less than thatwithout the service, migrants do not buy the service. A rise in migrant income, which
implies fewer budget constraints for the migrant, increases the purchase of the service if
8the service is a normal good. To satisfy the entry constraint of the migrant and receive
enough services from the parents, an increase in migrant income pushes up remittanceamount. Therefore, under exchange motivation, an increase in migrant income also
increases remittance amount.
3.3. Insurance motivation
People in developing countries, especially in rural areas, often face income
volatility. For example, the weather affects agricultural production. When farmers facedrought/flood, they cannot obtain any output, while their animals might catch an
infectious disease. Therefore, farmers always face unpredicted and exogenous risk,
which reduces income volatility. However, households face imperfect credit and risk
markets, implying that it is difficult for people in rural areas to borrow money from thecredit market when they face income shocks. Therefore, interfamilial arrangements or
risk sharing within villages can be crucial for overcoming income volatility(Rosenzweig and Stark 1989). By contrast, although urban inhabitants do not face risks
related to natural disasters, they can suffer income shocks, such as unemployment,
ceremonial functions, and education expenses. In these cases, the income transfer fromother people including family members that have migrated can overcome this lack ofaccess to the credit market.
Such strategic migration can be explained by the New Economic and Labor
Migration theory (Stark and Bloom 1985). According to this theory, a migrant transfers
income in the form of insurance when the PH faces income shocks. Indeed, it has been
widely argued that remittance is an important factor for PH income in order to smooth9consumption (Lucus and Stark 1985). If migrants do not remit to parents when the PH
faces income shocks, migrants are punished by their parents. However, migrants also
receive an income transfer when they face income shocks, because the insurance
motivation can be conceived as an informal contract between migrants and their parents.
3.4. Inheritance motivation
Under inheritance motivation, migrants remit to parents in order to receive
inheritance, which is an enforcement device for migrants. Under this motivation,
remittance can be conceived as a way to obtain an inheritance entitlement. Therefore,
the expected inheritance amount and possibility of inheritance are determining factors.
If the inheritance amount or possibility of inheritance rises, migrants remit more.
3.5

Previous studies of the determinants of remittancePrevious studies have demonstrated correlations that are consistent with specificremittance motivations. Cox et al. (1998) developed two types of theoretical models:
altruistic and exchange. By using household survey data in Peru, they find thatpre-transfer PH income is significantly positively correlated with remittance amountunder exchange motivation but not under altruistic motivation. Other studies support
these findings for exchange motivation, showing that migrants remit to repay debts thatparents incurred for the migrant, such as education or migration costs (Poirine 1997;
Ilahi and Jafarey 1999).
de la Briere et al. (2002) focus on the insurance and investment motivations.
Inheritance motivation is based on the age of the household head and parents’
inheritable assets, which both increase remittance amount. For insurance motivation,10

they use the number of lost working days, which indicates an income shock faced byparents. Based on household data on a rural area in Dominica Sierra, they find that
destination, sex, and household composition affect these motivations. Further, when asole migrant is male, the migrant is motivated by insurance factors, whereas when
destination of the migrant is the US, inheritance motivation plays a larger role inremittance.
Other studies show evidence of both insurance and inheritance motivations.
Hoddinott (1994) demonstrates that remittance probability and remittance amountincrease with the amount of land held by parents in Kenya in line with the inheritancemotivation theory. Lucus and Stark(1985) show that migrants remit to compensate forunexpected income drops (e.g., owing to drought) in Botswana (insurance motivation).

4.

Estimated model

4.1. Econometric model
As early works claimed that migrants are selected individuals, some selection
mechanism of migrants may work (Stark and Lucus 1988; Hoddinott 1994). As
explained in Section 2.2, the observable characteristics of migrants are different to thoseof non-migrants. For example, migrants are likely to be more educated, which implies
that individuals who have relatively high expected incomes in the final destination arelikely to migrate. Therefore, without controlling for this selection mechanism, theestimation of remittance determinants may be biased. To overcome this estimation
problem, I apply the Heckman selection model in the present study.
11

In the first stage, I consider whether an individual migrates. Let migrate∗! be alatent variable that increases in response to a rise in the propensity that individual i
migrates. The propensity depends on not only the individual characteristics that affectthe expected wage in the final destination, but also household characteristics. Therefore,
the selection equation can be expressed as follows:(1)

𝑚𝑖𝑔𝑟𝑎𝑡𝑒!∗ = 𝛼 + 𝛽𝑋 + 𝑢!

where 𝑋 is a vector of covariates in the first stage; 𝛽 is a vector of coefficients; andu! is an error term. It is assumed 𝐸(𝑢! ) = 0 and it is distributed as a standard normal
distribution. In the case that 𝑚𝑖𝑔𝑟𝑎𝑡𝑒!∗ is higher than 0, individual i in household jmigrates; otherwise, individual i does not, as follows:(2)

𝑚𝑖𝑔𝑟𝑎𝑡𝑒! =

1 𝑖𝑓
0 𝑖𝑓

𝑚𝑖𝑔𝑟𝑎𝑡𝑒!∗ ≥ 0
  𝑚𝑖𝑔𝑟𝑎𝑡𝑒!∗ < 0

I estimate equation (9) using a probit model: 𝑃 𝑚𝑖𝑔𝑟𝑎𝑡𝑒!" = 1 𝑋 . Then, by! !!

using the estimated coefficients β, I predict the inverse Mills ratio 𝜆! = ! !! for eachmigrant, where Φ  is the cdf and ϕ is the normal pdf. Next, I estimate how much a
migrant remits to the PH by using an OLS regression. The inverse Mills ratio also
controls for the sample selection of migrants in the second stage:(3)

𝑟𝑒𝑚𝑖𝑡𝑡𝑎𝑛𝑐𝑒!" = 𝜉𝑍 + 𝜌𝜎! 𝜆! + 𝜀!

where Z is a vector of covariates in the second stage; 𝜌𝜎! is a covariate between 𝜀!
and 𝑢! ; and 𝜉 is a vector of parameters. Sample selection bias can be alleviated byapplying the above method.
4.2. Four remittance motivations

12

In the following subsections, I classify these motivations in detail. Table 4 thensummarizes this classification according to the key variables.
4.2.1. Altruistic motivation
If altruism is a remittance motivation, remittance amount increases with migrantincome. The reason for this rise is that a migrant receives utility gain not only from
his/her own consumption but also from PH consumption, and therefore, the migrantchooses the optimal level of income transfer that maximizes his/her own utility level.
However, inheritance and exchange motivations also predict the same effect of migrantincome on remittance amount. Hence, to identify altruistic motivation, I assess how PH
income level influences remittance amount. Since migrant utility increases with a rise in
PH consumption under altruistic motivation, remittance amount might be the reason forthat in contrast to the prediction made by the exchange model.
4.2.2. Exchange motivation
In this study, parental services (e.g., caring for the migrant’s family) and PH
income level are used to test for exchange motivation. If the migrant remits under
exchange motivation, he/she increases the remittance amount in order to pay forparental services. However, other motivations predict that parental services do not affectremittance amount. Additionally, the effect of PH income on remittance amount is
positive if a pure exchange model is used in contrast to under altruistic motivation.
4.2.3. Insurance motivation
Under insurance motivation, migrants remit in the face of an income shock for
the PH. However, it is difficult to distinguish insurance motivation from altruistic
13

motivation because altruistic migrants also increase remittance amount in the case that
their parents face a fall in income. Therefore, I check whether migrant income affects
remittance amount. If migrant income does not affect remittance amount, the remittancecan be conceived as motivated by insurance reasons.
4.2.4. Inheritance motivation
Under this motivation, the probability of receiving inheritance, expected
inheritance amount, and migrant income all increase remittance amount. However,
because the effect of migrant income is the same as it is for the altruistic and exchange
motivations, I use the probability of receiving inheritance and expected inheritanceamount to identify inheritance motivation.
4.3. Variables related to the four remittance motivations
The available data do not allow me to analyze these motivations directly,
because the key variables (e.g., migrant income and altruism degree) necessary to
identify altruistic motivation are unavailable. Therefore, I test the motivations based on
the implication of theories. In this subsection, I describe how to test these remittancemotivations as well as the key variables that are expected to affect migrant remittance.
4.3.1. Migrant income
The altruistic, exchange, and inheritance motivations predict that migrantincome in the final destination increases remittance amount. However, migrant income
data are not available in LSMS 2005 for Albania. Therefore, in line with the approachtaken by de la Briere et al. (2002), I use socio-demographic characteristics as income
determinants (i.e., age, square of age, years of schooling, sex, and duration of14

migration) instead of migrant income based on Mincer’s equation.
These socio-demographic characteristics are important factors for migration. For
example, individuals that have higher expected incomes in the final destination are more
likely to migrate than individuals that have lower expected incomes. Hence, to consider
the selection mechanism of migrants, it is necessary to control for socio-demographic
variables in order to analyze migrant motivations in the first stage.
4.3.2. PH income
I use PH income level in order to identify the effect of pure altruistic motivationor pure exchange motivation on remittance amount. First, I estimate three percentiles ofincome per capita for the PH: 10th percentile, 25th percentile, and 50th percentile. I
then define three dummy income variables: <10th percentile, 10th–25th percentile, and25th–50th percentile. The reference group is income above the 50th percentile. PH
income level is a determinant of migration in developing countries, as low-income
households cannot access the credit market sufficiently. To overcome this difficulty,
people emigrate and remit from the final destination. It is thus necessary to control for
PH income when analyzing migration behavior.
4.3.3. Parental services
Under exchange motivation, a migrant remits to the PH by way of compensation
for parental services. To consider exchange motivation, I use a dummy variable thatindicates whether the spouse of the migrant lives with the migrant’s parents as a proxyvariable of parental services.
4.3.4. Adverse short-run shocks faced by the PH
15

I use a variable that indicates whether the PH suffered the unexpected death of
the income earner in 2003/2004 and in 2005 as a proxy variable for any adverse
short-run shock faced by the PH. However, as described in Section 4.2, because it isdifficult to distinguish pure insurance motivation from pure altruistic motivation, I
check whether the determinants of migrant income affect remittance amount.
4.3.5. Parents’ assets
To test inheritance motivation, I use the number of rooms in the PH as a proxyvariable for parents’ assets. Parents’ assets increase remittance amount if the migrant
remits to parent owing to the inheritance motivation. As explained in Section 3.4, if
parents hold considerable assets, which means that their inheritance is highly valued,
then their children remit to receive bequests. If this is the case, migrants increase
remittance amount in line with the inheritance value.
4.3.6. Probability of receiving inheritance
Under inheritance motivation, I include variables related to the probability ofreceiving an inheritance from parents. In this study, I use a dummy variable for the elderson, which indicates that the individual is more likely to receive an inheritance. In
addition, age of the household head is included in the estimated equation; because theprobability of death increases with age, the probability of receiving an inheritance rises
with the age of the household head.
4.4. Other variables
4.4.1. Destination country dummy
Wage in the final destination is determined by the characteristics of the migrant16

as well as the local labor market. Additionally, migrants might decide on remittanceamount by taking account of the relevant exchange rate. In these ways, destinationinfluences remittance amount. To control for the heterogeneity of the destination, I add
a destination dummy (Greece dummy, Italy dummy, and other countries dummy)4. The
reference destination is internal migration.
4.4.2. Characteristics of the household head
The characteristics of the household head are expected to affect migrant
remittance not only because the household head has more decision-making power in ahousehold, but also because such characteristics affect the family’s economic situation.
To control for these effects, socio-demographic variables (sex, years of schooling, andage) were included in the estimated equations.
4.4.3. Household characteristics (household size, rate of labor force5, and rate of chronic
illness6)
If the household runs a self-owned business (including agriculture), an increasein the number of household members diminishes the marginal return on production
labor. Therefore, allocating a family member to work in another business is optimal forhouseholds. In addition, household characteristics also affect the income source for the
PH. To consider these effects, I control for the number of household members and therate of labor as explanatory variables in the estimated equation. In addition, to control

4
5
6

Other countries include other countries in Europe as well as the US.
The rate of labor force is defined as the proportion of household members aged 15–65 years.
The rate of chronic illness is defined as the proportion of family members who suffer from achronic illness or disability that has lasted more than three months (including severe depression).

17

for the health conditions in the household, the rate of chronic illness is added as an
explanatory variable.
4.4.4. Community characteristics
In the Heckman selection model, at least one variable that is excluded from thesecond equation is needed for identification. In this study, community characteristics areused as the excluded variables. In a community that displays significant migration,
people can access information on the destination through the network of migrants. This
migration network thus reduces the psychological and physical cost of migration forpeople in the community (McKenzie and Rapoport, 2010; Moraga 2013). Further, incrime-ridden areas, people are expected to move to find a safer living environment.
Hence, whether a community is crime-plagued also affects the migration decision.
Excluded variables are required so that there is no correlation with the error termin the second equation. In the case of the excluded variables, however, migrant
movement in the community is unlikely to affect remittance amount, because migrants
decide this amount based on their relations with the PH not with the community.

5.

Data
This study analyzes data derived from the LSMS 2005 for Albania. This survey

was collected by the Institute of Statistics in May and early July with the technicalassistance of the World Bank; the agricultural survey was undertaken in October. The
purpose of the survey is to measure living conditions and poverty levels.
These data consist of four elements: a household questionnaire, a diary for18

recording household food consumption, a community questionnaire, and a pricequestionnaire. The household questionnaire includes information on the core LSMS
models 7 as well as additional modules on migration, fertility, subjective poverty,
agriculture, non-farm enterprises, and social capital (World Bank 2006). In particular,
the questionnaire asks households about children living away, socio-demographic
characteristics, destinations, duration of migration, and remittance amounts. These data
allow me to analyze remittance motivations by considering the characteristics of bothchildren who migrate and their parents. In addition, the community questionnaire
includes information on social order and migration in the community for analyzing therelationship between community characteristics and migration behavior.
The sampling method of the LSMS 2005 for Albania is related to that used in
the LSMS 2002 for Albania, namely a two-stage cluster sampling approach (WorldBank 2006). First, 455 census enumeration areas (EAs) were collected78 based on area
location (“Mountain area,” “Coastal area,” and “Central area”) and rate of development(“Urban area (big towns),” “Other Urban areas,” and “Rural areas”). The nation’s
capital Tirana was considered to be a separate stratum.
The second stage sample selection followed the 455 sample EAs selected in thefirst stage. The second stage samples were chosen based on a systematic sampling

7

The core LSMS modules include the following information: metadata, household rosters, dwellingand utilities, education, health, employment, transfers and social assistance, other income sources,
and consumption.
8

The sample of 450 EAs in the 2005 LSMS is different to that in the 2002 LSMS (see World Bank
2006).

19method. In each EA, 12 households were initially selected. After selection, eighthouseholds were chosen as the base samples, while the remaining samples were thesubstitutes. The analysis of the study is based on individual units. The data include
individuals that belong to the same household in order to control for not only individual
characteristics but also head/family characteristics.
Table 3 shows the descriptive statistics, which include the mean and standard
deviation of each variable. As discussed in Section 2.2, migrant characteristics aredifferent to those of non-migrants. In terms of demographic characteristics, 46.3% of
migrants are men compared with 50% for non-migrants. The average age of migrants(non-migrants) is 34.3 (32.0) years old and the average years of schooling is 11.0 and
7.3 years, respectively. Altogether, 20.8% of migrants are the eldest son, which ishigher than the rate for non-migrants, while 26.6% of migrants live with a partner,
whereas 5.6% of the migrants’ partners live in the PH. Finally, 56.4% of migrants areinternal, compared with 18.2% for Greece, 17.0% for Italy, and 8.4% for othercountries.
In regard to the head of the household, there are large differences between the
migrant and non-migrant samples; the average age of the household head for the sampleof migrants is 63.9 years, which is older than that for the sample of non-migrants (51.7
years). Further, 83.1% (92.5%) of the heads in the sample of migrants (non-migrants)
are men. Finally, the average years of schooling for migrants and non-migrants are 7.5
and 9.8 years, respectively.
Household size in the migrant sample is 8.1 persons per household, which is20

larger than that for the sample of non-migrants (6.4 persons per household). The rate oflabor force for migrants is 84.2%, which is larger compared with non-migrants, while
the rate of chronic illness in the sample of non-migrants (85%) is considerably higher
than that in the sample of migrants (51.4%).
With respect to PH income level, there are also differences between both
samples. The probability that poorer PHs have a child that migrates is relatively high.
Regarding the adverse short-run shocks faced by PHs, the probability of the unexpected
death of the income earner is similar for both samples, as is the community
characteristics related to public order. However, the community characteristics
regarding migration differ for both samples.

6.

Results
As explained earlier, the Heckman selection model is used herein in order tocontrol for sample selection bias. Therefore, migration determinants are estimated in thefirst stage of the model. Afterwards, using the information estimated in the first stage,
this model estimates the determinants of remittance amount. In this section, I present theresults from the first-stage and second-stage estimations.
6.1. Migration determinants
To control for the selection of migrants, the probability of migration is estimatedin the first stage. Table 4 shows the mean marginal effect in the first stage estimated by
the probit model. It is found that the probability of migrating is significantly affected byindividual characteristics (age, square of age, male dummy, years of schooling, and21

eldest son dummy) related to the wage in the final destination. In particular, therelationship between age and probability shows an inverted U-shape, demonstrating that
32.6-year-olds are most likely to migrate. In other words, high-skilled individuals are
more likely to migrate (see also Lanzona 1998). The female dummy variable increases
the probability of migrating by 1.7% at the 1% significance level. As discussed in
Section 2.2, the high rate of internal migration for women (67.6%) affects this result.
Years of schooling also increase the probability by 0.4% at the 1% significance level.
The characteristics of the head of household (age and years of schooling) aresignificant at the 1% level; while the probability increases with the age of the head, theage of the head decreases with the probability. This finding implies that family
background may affect migration behavior (Lanzona 1998). In particular, elderly heads
that have lower education are most likely to have at least one child that migrates.
Moreover, except the rate of chronic illness, family characteristics (household
size and rate of labor force) do not change the probability significantly. The rate ofchronic illness decreases the probability of migration because when family members areneeded to care for one another, they are less likely to migrate. In addition, the number ofrooms does not affect the probability significantly; therefore, parents’ assets are not a
determining factor for migration.
All the dummy variables of PH income increase the probability significantly,
implying that PH income level is an important determinant of migration. However, theprobability of migrating does not change significantly with the income shocks faced by
the PH. In fact, migration rarely occurs after an income shock.
22

The community characteristics related to migration increase the probability
significantly. Since people can access information on the final destination easily,
migration costs are lower than those in other communities, suggesting that the migrant
network is an important factor (see Moraga 2013; McKenzie and Rapport 2010).
However, public order in the community does not affect the probability significantly.
6.2. Remittance motivations
Table 6 presents the results of the second-stage estimation. The inverse Mills
ratio positively increases the probability of migrating, which means that the selection
mechanism of migrants is shown to be an important factor in determining remittanceamount. In the following subsections, I discuss the four studied remittance motivations
in detail.
6.2.1. Altruistic motivation
As discussed in Section 6.1, the characteristics of migrants (age, square of age,sex, years of schooling, and duration of migration) significantly affect remittanceamount. Additionally, the dummy variables indicate that PH income level significantly
affects remittance amount. This result implies that relatively poor households receive
more remittance; however, the lowest-income households (i.e., below the 10th
percentile of income) do not receive more remittance. These results are consistent withthe prediction of altruistic motivation. Therefore, these findings declare that migrants
from Albania are driven by altruistic motivation when remitting to their parents incontrast to the results of Cox et al. (1998), which show an inverse relationship between
pre-transfer income and transfer amounts received.
23

6.2.2. Exchange motivation
The dummy variable for whether the partner of the migrant lives in the PH
significantly increases remittance amount. When the partner of the migrant lives in thePH, the migrant’s parents take care of the partner as a service, thereby increasing
remittance amount (i.e., exchange motivation). By contrast, remittance amountdecreases significantly when the partner lives with the migrant. In that case, the migrant
does not need to remit as a form of compensation of the service. Moreover, sincemigrants have to care for their partners, a proportion of their incomes in the finaldestination is used for that.
6.2.3. Insurance motivation
The unexpected death of the income earner in the PH in 2005 significantly
increases remittance amount. This finding implies that migrants remit to compensate forthe lack of income caused by this sudden death. However, migrants significantly
decrease remittance amount when the PH suffer the unexpected death of the income
earner in 2003/2004. This finding implies that the unexpected death in 2003/2004
lowers the expenditure necessary for living in the PH.
As described in Section 2.4, if a migrant is driven to remit by the insurance
motivation, his/her income does not increase remittance amount. As explained above,
income determinants affect remittance amount. Hence, remittance can be driven by
altruistic motivation but not by insurance motivation.
6.2.4. Inheritance motivation
The eldest son dummy increases remittance amount by 32% at the 5%24significance level, lending support to the probability of receiving inheritance increasing
remittance amount. However, the age of household head decreases this amount by 2.8%
at the 1% significance level. This result might be caused by the other elements thatfluctuate with the age of the household head (e.g., family background). The number ofrooms in the PH increases remittance amount by 10.4% at the 1% significance level,
implying that inheritance value increases remittance amount (i.e., inheritancemotivation). This finding is consistent with those of previous studies (see Stark andLucus 1988).
6.3 Other findings
As expected, the country-specific dummy variables increase remittance amountat the 1% significance level, which suggests that international migrants remit more incomparison with internal migrants. Thus, remittance amount is affected by theconditions in the final destination (e.g., labor market and currency exchange) as well as
differences in migration motivations (de la Briere et al. 2002). Therefore, the destination
is an influencing factor of remittance amount.
Similarly, the age and years of schooling of the household head decrease
remittance amount by 3.4% at the 1% significance level, while the rate of labor in the
PH also decreases this amount significantly. Since Albanian migrants are driven to
remit by altruistic motivation, they lower remittance amount when PH income level ishigh. Since the rate of labor increases with PH income, migrants remit less (i.e.,
altruistic motivation). However, the rate of chronic illness significantly decreases
remittance amount.
25

7.

Conclusion
In Albania, remittance has been increasing since the collapse of the communist

regime in the early 1990s and has become an important factor for the country’s
economic growth. In this paper, I investigated remittance motivations by applying the
Heckman selection model to assess migration behavior. The presented analysis is basedon data derived from the World Bank’s LSMS 2005 for Albania.
I considered four remittance motivations: altruistic, exchange, insurance, andinheritance motivations. To identify the effect of pure altruistic and pure exchange
motivation, I assessed the effect of the Parent’s Household income level on remittanceand found that poorer households receive more remittance, in line with the theory ofaltruistic motivation. However, since parental services increase remittance amount,exchange motivation also drives remittance behavior in Albania. In addition, both theprobability of receiving inheritance and inheritance value increase remittance amount,which concurs with inheritance motivation. Since not only income shocks but also otherfactors affect remittance amount, altruistic motivation rather than insurance motivation
is an appropriate explanation for remittance behavior in this regard. These results
suggest that migrants in Albania are driven to remit owing to a combination of altruistic,
exchange, and inheritance motivations. Further, migration destination influences
remittance amount, which implies that not only the local labor market and currency rate
at the final destination but also migration motivation factors affect remittance amount.
In the estimation of migration behavior, I find that individuals that expect toreceive higher wages in their final destinations are prone to migrate. The characteristics
26

of the household head also affect this behavior. This finding implies that the decision to
migrate is made not only by the individual but also by the Parent’s household. In
particular, if a family member suffers from a chronic illness, the individual in question
would not migrate.
In terms of policy implications from the study, the results suggest that Albanianmigrants remit owing to a combination of altruistic, exchange, and inheritancemotivations. In poor credit market environments characterized by financial constraints,
remittance allows the Parent’s household to smooth consumption. For example, when afamily faces an income shock, it may not be necessary to lower consumption level if thefamily receives migrant remittance. In addition, remittance is also used for investment
into business activities as well as education in Albania. To summarize, remittancecontributes to economic activity in Albania, and thus, the Albanian government should
continue to implement policies that stimulate the flow of international migration andencourage migrant remittance.

27

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30

Definition: Personal transfers consist of all current transfers in cash or in kind made orreceived by resident households

Figure 1. Flow of remittance from abroad

31

32

5.27210.50000.3373

7.33850.50130.130915816

21.0469

Std. Dev.

31.9912Mean

0.15060.17051300

0.02320.030095
2370

0.36100.46814.07099.47100.15400.3241

10.671336.5215Internal migration
Mean Std. Dev.

Note: Author’s calculations from the LSMS 2005 for Albania.

age
years of schoolingmaleeldest son
whether partner lives
with migrant
whether partner lives
with migrant's parents
remittance (LEKS)
Sample size

Variables

Non-migrant977

0.10390.6096

0.26260.6250712

10.7360

31.9972

1935

0.30540.48820.44040.4845

3.57808.6074

GreeceMean Std. Dev.

1286

0.10090.53210.30280.6868763

10.90832344

0.30140.49930.45980.46413.52088.3560Italy
Std. Dev.

30.8113

Mean

Destination

Table 1. Differences in the characteristics of migrants

1166

0.03390.5876

0.24580.5904354

13.025431.02542087

0.1812

0.49300.4311

0.49254.52908.1496

Other countries
Mean Std. Dev.

33

total

Percentile of income<1010 - 20 20 - 30 30 - 40 40 - 50 50 - 60 60 - 70 70 - 80 80 - 90 90 - 100
Probability of receiving remittance (%) 24%
25%
28%
25%
22%
23%
21%
24%
25%
22%
22%
Amount of remittance (LEKS)
1298
2301
1902
2928
1008
1098
725
1025
1541
1054
1239
Income (LEKS)
385260 38468.8 78994.8 109234 135283 171456 209492 254222 337381 420692 2481918
Source: Author’s calculations from the LSMS 2005 for Albania.
Note: The sample consists of households that have at least one child who has migrated. However, migrants who remit above 100,000 LEKS were
removed from the sample in order to alleviate the effects of outliers.

Table 2. Relationship between the Parent’s Household income and remittance amountTable 3. Usage of remittancepuchase of food and basic necessities
investment in construction /purchase a durable goodeductaional expenses/ child Support
investment in HH enterprise
other

Urban Area
78%
23%
10%
4%
40%

Rural Area
77%
37%
7%
10%
32%

Note: Definition of remittance: Personal transfers consist of all current transfers in cash or inkind made or received by resident households

Table 4. Classification of variables
Variable
Income of migrant
Income level of parent
Service that parent supplies
Adverse short-run shock that parent faces
in parent's income

Altrusim

Exchange

＋
ー

+
+
＋

＋

Insurance Inheritance

＋

＋
＋
＋

Asset that parent owns
Probability of receiving inheritance34

Table 5. Relationship between the Parent’s Household income and remittance amountAll housheold
mean

Std. Dev.

How much did a emigrate remit? (log)Samples of migrantmean

Std. Dev.

1.65953.0749Samples of non-migrantmean

Std. Dev.

Characteristics of individual
age32.4658

19.2195

34.2534

9.392831.991221.0469squared of age/100

14.2340

14.8867

12.6150

6.926314.6638

16.3352

years of schooling

8.09075.237510.9238

3.98877.33855.2721male

0.49340.50000.46340.49870.50130.5000eldest son

0.14690.35400.20720.40530.13090.337310.7473

7.9974

 whether partner lives with migrant

0.26270.4401

 whether partner lives with home family

0.05570.2294

 whether member emigrates to Italy

0.18170.3857

 whether member emigrates to Greece

0.1696

0.3753

 whether member emigrates to other countries

0.08430.2779duration of migration

Destination(comparison group: internal migration)

Characteristics of Headage

53.8424

13.5387

63.9100

10.651451.1695

12.9535

male

0.90490.29340.83070.37510.9246

0.2641years of schooling

9.34224.9616

7.51395.14949.82764.7950Characteristics of Household
size of household

6.75122.71558.14882.8452

6.38022.5547

rate of labor force

0.73950.20890.84190.14030.71230.2156rate of chronic illness

0.78450.23920.51810.19170.85530.19702.5076

1.10472.56011.02502.4936

1.1245

unexpected death of income earner in 2003 or 2004

0.00990.09920.00710.08420.01070.1028unexpected death of income earner in 2005

0.00280.05280.00240.04870.00290.0539income<10 percentile

0.09510.29330.15580.36270.07900.269710 percentile<income<25 percentile

0.1304

0.33680.20700.40520.11010.313025 percentile<income<50 percentile

0.26170.4396

0.31890.46610.24650.4310whether there are any problem related to gangs

0.02920.16840.02880.16730.02930.1688

whether people leave the community
temporarily a lot/ occasionally0.77450.41790.7816

0.41320.7726

0.4192

 numbers of rooms
Income shock

Income per capita

Characteristics of Community

Sample Size

20015

Source: Author’s calculations from the LSMS 2005 for Albania.

35

4199

15816