Microeconomic Impact of Remittances in Balkan Countries

2009–2010

ERSTE Foundation Fellowship for Social Research Ensuring Income Security and Welfare in Old Age

Microeconomic Impact of Remittances in Balkan Countries Edlira Narazani

Remittances and Labour market Participation in “Post-war” Kosovo Edlira Narazani1 15 July 2010 This paper focuses on the impact of remittances in the labour market participation in Kosovo just after the war of 1999. Using the Living Standard Measurement Survey (LSMS, 2001), I apply a micro-econometric labour supply model where the individuals living in Kosovo are allowed to choose among several labour market alternatives (non-employment, part time, full time and extra-time). The estimated coefficients of the utility function for Kosovar Albanian men indicate that remittances have a detrimental effect on the labour efforts which increases with the dependency of households’ net income on remittances. In case of Kosovar Albanian women, this effect is weaker while for Kosovar Serbs doesn’t seem important. In addition, we try other specifications such as the wage employment and self employment to make the results comparable with those obtained by Narazani (2009) using Albanian data but we don’t find any positive effect of remittances on self-employment as in the Albanian case. This may sound odd unless we consider the different stages of development these Balkan countries are going through. While Kosovo in 2000 just left behind decades of ethnical conflicts and exhaustive underdevelopment, Albania made remarkable progress in economic and social development in the last decade and got away from a long “transition” period. Therefore, remittances may play different roles depending on the stage of the country’s development. If they are related to a country with a long tradition of having them only for consumption or construction of houses such as it happens in Kosovo and without an institutional framework behind, they somehow make these societies numb by depriving them of a constructive employment of such vital resources and more specifically may push the recipients to get stuck into an “idleness” status rather than to get involved in an active search of employment opportunities.

Keywords: Migration, remittances, Labor supply, discrete choice models.

Acknowledgment: This project is financed by the ERSTE Foundation Social Research Fellowships “Generations in Dialogue”. I thank the directors of this Fellowship, Rainer Munz and Franz Pruller, and the participants of Vienna and Split workshops. I also thank Alessandra Venturini, Ugo Colombino and Isilda Shima for valuable comments and the European Centre for Social Welfare Research for hosting this grant.

1

University of Turin, CHILD and ACSER.

1

1.

Introduction The impact of migration to Kosovo is still an open issue to the researchers.

While there are no doubts that migration has been an important and indispensable phenomenon for the existence of this country in the last 65 years, no attempts have been done to express its impact in terms of development.

The word “existence” rings us a bell on the destiny of this small Balkan country and especially on the conflict year 1999, even though the Albanian citizens were suffering since decades under ethnic hostilities and economic, psychological and social depression. These hostilities soared especially after 1989 when the Serb leader removed the Kosovo’ autonomy, and degenerated into an armed conflict which lasted until 1999 with NATO forces intervention.

Only in February 2008 Kosovo declared its independence which is officially recognized by the majority of EU countries and USA. Such conflict events have created a direct pressure on the labour markets and together with the proximity of borders, some real grounds for a large scale migration in Kosovo. The phenomenon of emigration started in the 1960s (in Germany was made known under the name of “gastarbeiter” program) and was revived again after the 1999 war due to a perception of a scarce prospective for development in this country.

These large flows of population have lead to significant changes in the socio-economic structure and demographic trends. There is almost a certainty that remittances generated by migration flows have become very important especially if we consider the large share of population abroad (18%) on a temporary or permanent basis and the fact that Kosovo is the youngest country in Europe. According to Riinvest Labour Force Household Survey (2002), one third of the Kosovo population is estimated under 15 years and 58% under 25 years.

The households receive 61EUR per month as remittances which is 14% of their average monthly income and the second income source after wages. 2

2

See A. Hoti (2005), A background study on labour relations in Kosova.

2

Remittances may affect labour supply by reducing the supply of labour provided by household members who use this remittance benefit to buy leisure.

This reduction in supplied labour is known in the neo-classical labour supply literature as an income effect and is generally not a concern as it represents part of the welfare gain from remittances. By contrast, remittances may induce the individuals to supply less labour if the migrant conditions the remittance on low household income. Such an effect will reduce the welfare gain from remittances by distorting the household labor decisions. Despite, it is worthwhile to investigate which of them is prevailing.

Looking at the overall effect, a rise in remittances reduced labor force participation in Managua, Nicaragua but increased self-employment (Funkhouser 1992). Narazani (2009) using a two-sector model of labour supply shows a similar results for Albania (thus a reduction of wage employment and an increase of selfemployment) but only when the remittances take up a sizeable share of income.

Remittances were estimated to reduce the participation rates of remaining household’s heads in a number of Caribbean countries although the direction of causality was hard to establish (Itzigsohn 1995). Yang (2004) points to more encouraging labor supply effects than the standard model when he determined that remittances reduce the supply of child labor but increase that of adult labor.

Rodriguez et al. (2001) show that migrants reduce the labour supply of Philipines non-migrant relatives, and this benefit is generally higher for men. AmuedoDorantes and Pozo (2006) find that in Mexico, remittance flows only reduce female labour supply while male labour supply remains unaffected. The effect of remittances on labour supply changes by gender and also by regions.3 On the other hand, there is a very scarce literature analysing the aspects of Kosovar migration and remittances. Forum for Democratic Initiatives issued a report on June 2009 where it is shown that the probability of migration seems to be affected by the demographic characteristics of the household (size and age) 3

See also Adams (2004, 2005), Bourdet and Falck (2003), King (2005), Sudhir and Kanbur. (1993), Taylor and Wyatt. (1996), Zezza, Carletto and Davis, (2005).

3

rather than the socio-economic status of the households. As regards the probability of receiving remittances, is significantly determined by the presence of the immigrants within the households, the Albanian ethnicity and the fact of living in rural area while again the socio-economic status doesn’t play any role. The Riinvest Institute (Forum 2015) ran two surveys on Kosovar migrants and households and show that there is a high emigration potential in Kosovo such as 26% of the surveyed individuals had the intention to migrate almost exclusively due to the scarcity of labour market opportunities (unemployment rate reached 40% in 2004) and severe economic situation of their families.

4

They recommend

that a good matching between the migration policies (circular or temporary migration) in the destination countries and a well-developed training and education programme in Kosovo will be an appropriate tool to resolve the imbalances of labour market especially among the youth. Bislimi (2008) finds some spoil effects of remittances on education and labour in Kosovo. Vathi and Black (2007) state that Balkan countries have been monitored rather than analysed.

Most of the studies in the migration literature are macroeconomic ones; nevertheless migration is an individual choice, thus what this research attempts to do is to fill-in the gap in economic studies of migration and remittances at micro level and bringing new insights with respect to individual decision on migration labour supply and remittances. That’s the first motivation of this paper. The second one is straightforwardly related to the absolute lack of a real literature on the remittances in Kosovo and labour efforts despite the endurance and importance of this phenomenon for the prospects of the Kosovar society.

This study aims to tackle the following questions. Do remittances affect the labor participation decisions of emigrant households in Kosovo? If yes, what is the sign of this affect? In this spirit, we will investigate the microeconomic implications of remittances on the well-being of individuals by focusing on the

4

See “Diaspora and Migration Policies”, 2007, Riinvest Institute.

4

labor supply behaviors and income inequality in order to conclude on the dependency rate of Kosovo from the remittances and migration patterns.

We have employed a micro econometric model of labor supply developed by Colombino at al. (2008) to simulate labor supply responses and welfare of individuals. In this model, individuals living in Kosovo are allowed to choose among several labour market alternatives (non-employment, part time, full time and extra-time). Furthermore, to account for the endogeneity of remittances, I allow the individuals to face two scenarios: with and without receiving remittances.

This paper is organized as follows. The next section depicts the Living Standard Measurement Survey data. In the section 3, the model is explained briefly. The section 4 comments on the estimation results while the last section concludes.

2. Description of Living Standard Measurement Survey Data In this study I have used the dataset extracted from the Living Standard Measurement Survey (LSMS), 2001 for Kosovo.5 This survey contains information on 2101 Kosovar Albanian households and 416 Serb households (as of mid-2000, the total population of Kosovo was estimated at 2 million). Of these, 88% were Kosovar Albanian, while Serbs, who constitute the largest minority group in Kosovo, accounted for 7% (Statistical Office of Kosovo, 2003). Furthermore, this survey provides individual level and household level socio-economic information from urban and rural areas in this country.

This dataset provides useful information as regards main labour supply variables such as hours and disposable income. Also data on remittances, migration history of household members, temporary or permanent character of migration, illegal or legal feature and the informal or formal money transfer can be retrieved. Data on the social and demographic characteristics as regards especially

5

For a detailed description of the demographic and socio-economic characteristics of the Kosovo households see the FID report (2009) “Diaspora as a driving force for development in Kosovo: Myth or Reality?�.

5

number of children, age and education are generously provided by the dataset.

Nevertheless, this dataset is quite complex and needs to be used with caution as the structure of the households is quite complicated and incorporates other households. In the same time, being household head doesn’t mean being the first breadwinner. In fact, for many of these composed households, especially in the northern part of the country, the household head position is just simply assigned to the oldest member of the household who might be often non active anymore in the labour market.

However, as the main intention of this study is the impact of the remittances on the labour participation, below we show the labour participation rates by gender and sector and their remittances in average. In the selected sample, the nonparticipation rates in the labour market among women is 67% while among men is 24%. Looking at the average values of remittances across gender and alternatives, there is not a clear signalling on the link between remittances and labour supply.

Table 1: Distribution of Men and women across LS alternatives Men Women Hours Interval 0 52-832 833-1613 1614-2394 2395-3175 3176-3956 All

Percentage 23.72 19.09 17.17 22.86 10.75 6.41

100.00% (4212)

Percentage 67.58 10.11 7.77 9.44 3.01 2.08

100.00% (4183)

Table 2: Distribution of Men and their received average remittances Men Women Hours Interval Percentage Remittances Percentage Remittances 0 72.28% 26.49% 6109 6856 52-832 10.81% 22.03% 5976 7125 833-1613 7.42% 19.56% 7716 7375

6

1614-2394 2395-3175 3176-3956 All

4.84% 6881 2.33% 7975 2.33% 9851 6844 100.00% (1591)

21.07% 6.31% 4.53%

100.00% (1457)

7284 8886 20137 7300

Table 3: Distribution of Men and women in case of non receiving remittances Hours Interval 0 52-832 833-1613 1614-2394 2395-3175 3176-3956 All

Men

Women

Percentage

Percentage

22.25 17.53 15.9 23.81 13.1 7.4

64.7 9.68 7.99 12.27 3.43 1.93

100.00% (2755) 100.00% (2592)

3. Micro-econometric modelling The model employed in this paper makes use of the information on migration and remittances characteristics provided by the LSMS. The microeconometric model of labour supply used in this paper is similar to random utility model developed by Colombino at al. (2008) where an individual n is assumed to maximize a utility

function

under the constraints:

(1) Where: = net household income average yearly hours of work required by the j-th job in the choice set for individual n,

7

= dummy variable which takes value one when the ratio between the remittances received and the net income is under a certain threshold (these threshold will be explained latte in the text) and zero otherwise estimated value of remittances as a function of some household variables (e.g. durables, if the household runs a business, elderly and child dependency rate, age and education of household head, percentage of women in the household, rural or urban, ethnicity) = set of discrete values (a combination of 6 alternatives of working hours, from 0 to 3956 yearly hours times 2 alternative of remittance receiving scenarios) = hourly wage rate of individual n. In order to simulate potential in-work disposable income for those who are observed to be out of work in the data, the hourly earnings equation is estimated after having estimated the inverse Mill’s ratio. = vector of exogenous household gross incomes CR = transfer rule that transforms gross income into net income. This rule is applied on yearly gross income.

The constraint says that the net income X is the result of a transfer rule CR applied to the gross income. The net income are pooled on a household basis and this doesn’t sound unrealistic in the framework of the Kosovar society where income are managed by the household head especially in the rural areas. 6 The working hours hi are chosen within a discrete set of values including also the choice of 0 hours (i.e. non-participation or unemployment). This discrete set of “h” values can be interpreted as the actual choice set (maybe determined by institutional constraints) or as approximations to the choice set as in our case.

In the following table we give a simple example of the way the alternative set is constructed. Individuals make decisions on how much to work under two different scenarios. Of course they don’t decide on how much they would receive

6

See ESI “Cutting the lifeline, migration, families and the future of Kosovo”” (2006).

8

from their relatives but they can influence the decision of the migrants on the size of remittances to be sent.

Table 4: Simple example of alternative set construction Labour supply

Remit

Non remit

alternatives

52-832 833-1613 1614-2394 2395-3175 3176-3956 0

Income if

Income if no

remit

remit

1

0

50+100

50

1

0

60+100

60

1

0

70+100

70

1

0

90+100

90

1

0

120+100

120

1

0

0+100

0

We write the utility function as the sum of a systematic part and a random component: (2)

where

is a vector of household characteristics,

parameters to be estimated and

is a random variable capturing the effect of

unobserved variables upon the evaluation of Let

is a vector of

by individual n.

be the income generated by each household member.

Here d is a dichotomous dummy which takes value one in case of receiving remittances and 0 otherwise.

9

Under the assumption that of a given individual choice

is i.i.d. extreme value of Type I, the probability

is:

(3)

If

is the observed choice for the n-th individual, the maximum likelihood

estimate of

is:

(4)

3.1 Utility function specification For the utility function we assume a conventional flexible form, quadratic function which represents a second-order Taylor series expansion in income and leisure.

“ ” represent the utility parameters to be estimated. The “ and the coefficient work.

and

” stands for leisure

captures the utility from the non work or the disutility from

capture the linear and quadratic effects of disposable income on

the utility function. Similarly

and

stand for the leisure variable. We also let

the variables capturing individual characteristics be interacted with the main utility arguments (income and leisure) as they can’t be estimated alone due to the invariability across alternatives.

Individual characteristics are related to age, employment sectors (high, intermediate or low skilled), employment status (self-employed, wage employee or other) percentage of children in the household), urbanization (urban and rural),

10

education degree (university degree holder or not). Remittances are calculated as the sum of the total remittances sent in the last year by the migrating children who are either abroad or returned.

The difference between the utility function used in Narazani (2009) and the one utilized in this paper stands in the two last terms of equation (5) which refer to the interaction between the remittances’ receipt and leisure or disposable income for different shares of remittances on net income. Thus, instead of using a dichotomous variable capturing the average effect of remittances receipt, I interact the variables “leisure” and “income” with some new variables which contain the quintiles of the ratio between remittances and the net income.

Furthermore I use some dummies constructed as follows:

The first four dummies refers to the labour market participation alternative and the job opportunities dummies for those who receive remittances while the last four dummies refer to those who don’t receive remittances at all. These dummies capture the peaks observed in the distribution of hours in most studies done in several countries. They can be interpreted as reflecting quantity constraints on the labour market (as in Aaberge et al., 1995, 1999), or specific utility of full-time, part time, extra time jobs, or maybe both (as in Van Soest, 1995).

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3.2 Choice set specification and hour’s distribution The choice set is composed of 12 alternatives for each individual (6 in case of remittances receiving scenario and 6 for the non receiving scenario) by specifying the interval of hours of work and sample randomly within this interval which has a length of 781 hours and a maximum of 3956 yearly hours. The first alternative refers to zero hours of work, the second to 52-832 and so on until the last alternative 3176-3956. As in the first alternative, individuals can choose between out of labour market, unemployment or inactive spells. The actual observed hours will be rounded to the closest discrete value.

3. Results A. Labour supply Estimates In this study, only individuals living in Kosovo (including also the returnees) and aged from 18 to 65 are selected. Retired people, students, disabled and those in military service are excluded. Table 5 shows the estimated coefficients of the conditional logit model for Kosovar Albanian men. The marginal utility of income is positive over the whole sample and decreasing either for leisure or income (the negative sign of the squared leisure and income). However, in order to check for the global concavity character of the utility function we have further calculated the first derivative of utility with respect to net income. Almost the whole sample satisfies the quasi-concavity conditions and this is important for the predictive capability of the labour supply model.

The interacted term of income and leisure is significantly negative implying a separation between the preference for leisure and income. As regards the age, the utility function has a U shaped form on age which means that until a certain age

12

men prefer to consume less leisure but with aging they prefer to work more. This is in line with other empirical works in the labour supply literature. The percentage of children in the households doesn’t appear important for men either in terms of income or leisure. As regards the employment status, both self-employed and wage-employees prefer to work more than the others, but their utility is not increasing with income while high-skilled individuals enjoy more working in comparison with the others.

As regards the dummy of “receiving remittances�, the estimates turned out to be significantly positive. An explanation for this might be that people receiving remittances from their children or relatives tend to work less, thus, a clear income effect. Then again, the magnitude of the coefficient does not consent to go further into conclusions. For that reason, instead of using a simple dummy which might shadow different effects on labour supply as Narazani (2008) shows, I use the quintile dummies constructed on the share remittances to income. Looking at the respective estimated coefficients, we notice that Kosovar Albanian men have a clear preference for leisure which gets stronger with the importance of remittances with respect to the household income or differently said the economic dependence of the household from remittances.

Similar results we find for Kosovar Albanian women, except for the fact that women prefer more leisure the higher the percentage of children in the household (while for men this coefficient is not significant).7 Also living in the rural area increases the preference for leisure than living in urban area. However, differently from Kosovar Albanian men, the labour supply of women gets affected by remittances only for the last three quintiles of the ratio remittances to income. This means that the labour supply behaviour of Kosovar Albanian women is less conditioned by the remittances compared to that of men.8 Furthermore, this might indicate that there 7

Several empirical studies on female labour supply (DelBocca and Colombino) have shown that the participation of women in the labour market is very sensitive to the number of children in the household. This is especially marked in the Mediterranean countries such as Italy and Spain where the welfare state provides scarce services to women on child caring.

8 The table 9 shows the mean values of remittances income ratio which is almost the same in the first quintiles for both Albanian men and women.

13

are other reasons behind the low participation of women in the labour market besides their economic dependency on others’ income. In a study of European Stability Initiative (2006), it is concluded that the massive migration and flows of remittances in the last decades have simply maintained the status quo and helped to preserve the patriarchality feature of the Kosovar Albanian family.9 Table 7 shows the results of the conditional logit for the Kosovar Serb men.

We notice that income and leisure have still the right sign and the concavity is respected for almost the whole sample. However, no significance is found on the main variables of interest, quintiles of remittances income ratio interacted with leisure. Finally, no convergence is achieved in case of conditional logit for Kosovar Serb women.10,

11

These findings connote that remittances are not an important

source of income for the individuals of Serb nationality residing in Kosovo and this is not surprising if we consider the fact that migration has not been sustenance mean for them as it was for the Kosovar Albanians. On the contrary, the Kosovar Serb individuals of Kosovo had extensive employment opportunities in the public administration which was almost denied to the Albanian counterparts.12 Table 5: Conditional logit for Kosovar Albanian men Observations Loglikelihood Coef.

Job Opportunities Receiving remittances Participation

Std.

-0.0705745 0.488243

42288 -5850 tvalue

-0.14

Coef.

Remittance/Income Quantiles Quantile1*leisure -0.0000298 Quantile2*leisure 0.001739

Std.

t-value

0.000333 0.000387

-0.09 4.49

9

See “Cutting the lifeline, migration, families and the future of Kosovo” (2006) made by European Stability Initiative.

10

The conditional logit is estimated also for the non Albanian individuals (here Muslim Bosnians, Rom, Turkish, etc, are included) but the estimates are non significant and therefore no comments are made on their regards.

11

For the sake of completeness, also the results on non Albanian men are inserted in the Table 8 but are not commented in the text as the concavity conditions are not satisfied and most of the estimates don’t seem robust.

12 See Europe Report (2009): “Serb Integration in Kosovo: Taking the Plunge”

14

Part Time_1 0.2780287 Part Time_2 0.1111003 Full Time 0.3361075 Non_receiving remittances Participation 2.799761 Part Time_1 0.5991578 Part Time_2 1.516463 Full Time 1.622204 Leisure Leisure 0.0175984 leisure squared -7.31E-07 Income Disp 0.0031547 dispysquare -4.95E-08

2.19E-08

-14.62

1.58E-05 1.77E-07 4.57E-06

-7.2 7.1 0.48

0.000444

-1.19

Quantile3*leisure 0.0036776 Quantile4*leisure 0.0074154 Quantile5*leisure 0.0603588 Quantile1*Income 0.0005367 Quantile2*Income 0.0008941 Quantile3*Income 0.0010787 Quantile4*Income 0.0018448 Quantile5*Income 0.0189996 Individual Characteristcs Employment status self_l -0.0030381 self_disp 0.0002616 employee_l -0.0032499 employee_d~p 0.000017 High level occupation High_occ*leisure 0.0008158 High_occ*Income 0.0001251 University degree University*leisure 0.0009387 University*Income 0.0000397 Rural Rural*leisure 0.0001076

-0.0002826 0.000239

-1.18

Rural*Income

Interacted variables Leisure*Income -3.21E-07 Age Leisure*Age -0.0001139 Leisure_squared*Age 1.26E-06 Age*Leisure*Income 2.22E-06 Household Characteristics Child_percent*leisure -0.0005307 Child_percent*Income

0.389681 0.244857 0.138842

0.71 0.45 2.42

0.792831 0.621489 0.420057 0.25564

3.53 0.96 3.61 6.35

0.000993 17.72 5.28E-08 -13.84 0.000365 8.65 4.60E-09 -10.75

-0.0000407

0.000436 0.000635 0.005808 0.000129 0.000163 0.00019 0.00028 0.002214

8.44 11.67 10.39 4.16 5.47 5.67 6.58 8.58

0.000447 0.000245 0.000448 0.000244

-6.8 1.07 -7.26 0.07

0.000339 0.000163

2.4 0.77

0.000417 0.000188

2.25 0.21

0.000194

0.56

0.000103

-0.39

Table 6: Conditional logit for Kosovar Albanian women Observations Loglikelihood Coef.

Job Opportunities Receiving remittances Participation -5.963849 Part Time_1 4.962348 Part Time_2 2.963511 Full Time 1.789388 Non_receiving remittances Participation -5.807529 Part Time_1 6.550329 Part Time_2 4.301895 Full Time 2.182213 Leisure leisure 0.0268427 leisure squared -9.21E-07 Income

Std.

42624 -3359 tvalue

0.813115 0.69728 0.464115 0.283541

-7.33 7.12 6.39 6.31

1.095204 0.941984 0.652258 0.413221

-5.3 6.95 6.6 5.28

0.001487 7.64E-08

18.05 -12.05

Coef.

Std. t-value Remittance/Income Quantiles Quantile1*leisure -0.00076 0.000434 -1.75 Quantile2*leisure 0.0006997 0.000462 1.51 Quantile3*leisure 0.0012959 0.000472 2.74 Quantile4*leisure 0.003859 0.000615 6.27 Quantile5*leisure 0.0236461 0.003509 6.74 Quantile1*Income 0.0003095 9.21E-05 3.36 Quantile2*Income 0.0004796 0.000105 4.56 Quantile3*Income 0.000566 0.000109 5.19 Quantile4*Income 0.0012233 0.00019 6.43 Quantile5*Income 0.0026714 0.000784 3.41 Individual Characteristcs Employment status self_l -0.0136445 0.001055 -12.94 self_disp -0.0011478 0.000293 -3.92

15

disp dispysquare

0.0022885 0.000341 -1.93E-08 2.70E-09

1.56E-08

-7.7

2.38E-05 3.47E-07 2.98E-06

-4.99 4.91 0

0.000458

2.87

employee_l employee_d~p High level occupation High_occ*leisure High_occ*Income University degree University*leisure University*Income Rural Rural*leisure

0.0002685 0.000214

1.25

Rural*Income

Interacted variables Leisure*Income -1.20E-07 Age Leisure*Age -0.0001188 Leisure_squared*Age 1.70E-06 Age*Leisure*Income -8.20E-09 Household Characteristics Child_percent*leisure 0.0013142 Child_percent*Income

Table 7: Conditional logit for Kosovar Serb men Observations Loglikelihood Coef.

Job Opportunities Receiving remittances Participation -0.9761135 Part Time_1 1.22683 Part Time_2 0.7876349 Full Time 1.214785 Non_receiving remittances Participation -178.3548 Part Time_1 191.7733 Part Time_2 162.8282 Full Time 119.6088 Leisure leisure 0.0401317 leisure squared -1.75E-06 Income disp 0.0265111 dispysquare -1.16E-06 Interacted variables Leisure*Income -2.64E-06 Age Leisure*Age -0.0000705 Leisure_squared*Age 7.39E-07 Age*Leisure*Income 3.33E-06 Household Characteristics Child_percent*leisure -0.000016 Child_percent*Income

-0.0003697

Std.

6.72 -7.14

6444 -1029 tvalue

-0.0138343 -0.0011921

0.001075 0.000313

-12.87 -3.81

0.0005448 0.0000708

0.000304 0.000145

1.8 0.49

0.0000266 -0.0001059

0.000307 0.000119

0.09 -0.89

0.0005891

0.000191

3.09

9.88E-06

9.31E-05

0.11

0.972287 0.811115 0.514004 0.303593

-1 1.51 1.53 4

30865.04 29743.44 23013.2 15543.46

-0.01 0.01 0.01 0.01

0.010936 6.13E-07

3.67 -2.85

0.008388 3.67E-07

3.16 -3.17

9.39E-07

-2.81

4.42E-05 4.32E-07 2.31E-05

-1.6 1.71 0.14

0.0018

-0.01

Coef.

Std. t-value Remittance/Income Quantiles Quantile1*leisure -0.073465 9.950997 -0.01 Quantile2*leisure 0.0428485 61.38442 0 Quantile3*leisure 0.0358712 14.14176 0 Quantile4*leisure -0.027219 9.119139 0 Quantile5*leisure 0.1751381 25.08732 0.01 Quantile1*Income 0.0026537 0.001888 1.41 Quantile2*Income 0.0642526 67.70629 0 Quantile3*Income 0.055198 17.14851 0 Quantile4*Income 0.0067389 0.005554 1.21 Quantile5*Income 0.0562436 17.34464 0 Individual Characteristcs Employment status self_l -0.0069996 0.002573 -2.72 self_disp -0.0017234 0.001939 -0.89 employee_l -0.0077918 0.002625 -2.97 employee_d~p -0.0020879 0.00199 -1.05 High level occupation High_occ*leisure 0.0033094 0.001614 2.05 High_occ*Income 0.0025989 0.001234 2.11 University degree University*leisure 0.00147 0.002271 0.65 University*Income 0.0010721 0.001465 0.73 Rural Rural*leisure -0.0021664 0.0009 -2.41

0.00152

-0.24

Rural*Income

-0.0017674

0.000746

Table 8: Conditional logit for non Kosovar

16

-2.37

Albanian men Observations Loglikelihood Coef.

Job Opportunities Receiving remittances Participation -1.012254 Part Time_1 1.271406 Part Time_2 0.7939842 Full Time 1.1062 Non_receiving remittances Participation 21.4129 Part Time_1 -2.021008 Part Time_2 -1.244046 Full Time 0.6279128 Leisure leisure 0.0145814 leisure squared -5.12E-07 Income disp 0.0018226 dispysquare -2.40E-08

0.89465 0.743518 0.465091 0.26951

-1.13 1.71 1.71 4.1

894.3625 3.018783 2.070923 1.211705

0.02 -0.67 -0.6 0.52

0.003956 1.84E-07

3.69 -2.79

0.002527 5.97E-08

0.72 -0.4

1.95E-07

-1.09

3.29E-05 3.45E-07 1.23E-05

-2.15 1.96 0.01

0.00117

0.18

Coef.

Std. t-value Remittance/Income Quantiles Quantile1*leisure 0.002845 0.00167 1.7 Quantile2*leisure 0.0049629 0.003746 1.32 Quantile3*leisure 0.012337 0.006021 2.05 Quantile4*leisure 0.006429 0.002349 2.74 Quantile5*leisure 1.023188 41.0441 0.02 Quantile1*Income 0.0015995 0.000807 1.98 Quantile2*Income 0.0027124 0.00254 1.07 Quantile3*Income 0.0053999 0.004129 1.31 Quantile4*Income 0.0021047 0.001166 1.81 Quantile5*Income 0.4684441 19.64317 0.02 Individual Characteristcs Employment status self_l -0.0040016 0.002265 -1.77 self_disp 0.0011477 0.001754 0.65 employee_l -0.0052763 0.002263 -2.33 employee_d~p 0.0001222 0.001747 0.07 High level occupation High_occ*leisure -0.0002167 0.00076 -0.29 High_occ*Income -0.0000504 0.000482 -0.1 University degree University*leisure 0.0005914 0.001199 0.49 University*Income 0.0000608 0.000682 0.09 Rural Rural*leisure -0.000856 0.000534 -1.6

0.0002601 0.000884

0.29

Rural*Income

Interacted variables Leisure*Income -2.13E-07 Age Leisure*Age -0.0000707 Leisure_squared*Age 6.78E-07 Age*Leisure*Income 9.73E-08 Household Characteristics Child_percent*leisure 0.0002089 Child_percent*Income

Table 9:

8436 -1329 tvalue

Std.

-0.0006651

0.000391

Summary of remittance/Income ratio Kosovar Albanian Men

Kosovar Albanian Women

Quantiles

Mean

Std. Dev.

Frequency

Mean

Std. Dev.

0

0

0

25440

1

.08749978

.02416226

3036

.07362072

.03008624

1284

2

.1776764

.03222552

3252

.18765743

.03311336

1224

3

.36027156

.08506605

3036

.36605842

.08158186

1380

4

13.664.571

.86898976

3108

13.894.144 .91263979

1248

5

11.629.553

10.584.102

180

16.204.963

Total

.21753142

11.610.311

38052

0

.13240852

Frequency 0

24420

17.150.716

84

1.294.247

29640

17

-1.7

Table 10: Denomination of Variables used in the Conditional Logit Estimations Participation

Status of simply working

Part Time_1

Status of working less than 832 hours per year

Part Time_2

Status of working from 832 to 1613 hours per year

Full time

Status of working from 1614 to 2394 hours per year

Disp

Disposable income

Child_percent

Percentage of children in the household

Self

Self-employment status

Employee

Wage-employee status

High_occ

High-level occupation sector

University

Holding University degree

Rural

Living in the rural area

I used several conditional logit specifications in addition to those described in the tables above.13 These estimates were provided separately for self-employed and non self-employed, for those who were entitled to social security benefit schemes before the war or not, for those who changed the residence due to the war and other factors that may have affected the behaviour of individuals in the labour market. The same positive relationship between remittances receipt and the preference for leisure holds across Kosovar Albanian. This may seem at odds with the positive impact of remittances on self-employment - observed by Narazani (2009) in Albania, unless we consider the different stages of development these Balkan countries are going through.14 While Kosovo in 2000 just left behind decades of ethnical conflicts and exhaustive underdevelopment, Albania in 2000s settled itself into a development process and got away from a very long “transition� period.

Under these results we can deduce that migration and remittances are more critical (in a negative sense) for a country in the initial phase of its development and especially living for decades under a conflictual situation than for a developing country such as Albania where they might be exploited beneficially for small-size 13 14

The estimates can be given by the author under request.

See Narazani (2009) GDP Working paper.

18

investments. Thus, remittances may play a different role on the development of a country depending on the stage of its development. If they are related to a country with a long tradition of having them only for consumption or construction of houses such as it happens in Kosovo and without an institutional framework behind, they somehow make these societies numb by depriving them of a constructive employment of such vital resources.

Said

in

a

different

way,

remittances

do

not

cure

the

Kosovo

underdevelopment. As long as the Kosovar Albanians will not invest in terms of education, health and a cultural progress but will get rooted in a cultural conservatism and social norms especially in rural areas, they will get stucked with this vicious circle called “long term migration and dependence�. 15 And they don’t have excuses anymore.

B. Poverty indicators

Lastly, to investigate the potential effect of remittances on the poverty and income distribution, I calculate several standard summary poverty and inequality measures only for Kosovar Albanian individuals. The poverty measured used are those constructed by Forster, Geer and Thorbecke (1984) who have defined a class of poverty measures as follows: 1. Head count ratio or poverty rate is simply the ration of the number of people with equivalent income below the poverty line.

2. Poverty gap is the average deviation of the incomes of the poor from the poverty line relative to the total population. It measures the extent of being poor on average.

15

The author is writing also a paper on the links that exist between the cultural conservatism and remittances in Kosovo in the spirit of the Janet Reineck book.

19

3. Income gap ratio is the average deviation of the equivalent income of the poor population from the poverty line. The product of the income gap ratio and poverty rate results in poverty gap.

Looking at the table 11, the Gini coefficient, which is sensitive to income changes in the middle of the distribution, does not record any significant change in the income distribution for Kosovar Albanian men either when they receive or don’t receive remittances while women inequality index varies by a large amount.

Turning to results on the poverty measures, the incidence of poverty and poverty gap either for men or women is significantly higher for the individuals who don’t receive remittances than those who receive. Yet again, these stark discrepancies are more pronounced for women. The same holds for the severity of poverty (income gap ratio). Furthermore the table 12 shows the percentage of poor individuals whether they receive or not remittances. While 23.56% and 4% of Kosovar Albanian men considered as poor are respectively extracted from the pool of those who don’t receive and those who receive remittances, in case of women, the differences in these percentages is extremely large (70% and 1.25%). These results on poverty statistics show that remittances do really play the role of a safety net for the Kosovar Albanian households and especially for women. In this way, migration and remittances are both an economic shelter or an exit option from any vulnerable situation. However, considering their effect on labour supply, they create a dependency syndrome which will not help the social, economic and cultural development of the individuals and regrettably of the Kosovar society as a whole.

Table 11: Poverty measures based on predicted income Kosovar Poverty Poverty Gap Albanian Men Gini Index Gap Ratio Non receiver .33699163 26.226 19.087

Income Gap Ratio 72.776

20

Receiver Kosovar Albanian women Non receiver Receiver

.37058917

27.137

8.754

32.260

.75229491 .45108637

40.049 27.554

25.894 6.273

64.656 22.767

Table 12: Percentage of poor based on predicted income Kosovar Albanian Men Non-remittances receiver 23,56 Remitances Receiver 3,98 Kosovar Albanian women Non receiver 70,15 Receiver 1,25

4.

Conclusion

In this paper we have employed a random utility model to simulate the effect of remittances on the labour supply and poverty in Kosovo. The data used is extracted from the LSMS 2001 in Kosovo. The estimation results suggest that Kosovar Albanian men who receive remittances have stronger preference for leisure. These preferences are weaker for women and seem not important for Kosovar Serbs. In addition, we try other specifications such as the wage employment and self employment to make the results comparable with a similar approach used by Narazani (2009) with Albanian LSMS data but we don’t find yet any positive effect of remittances on self-employment as in the Albanian case. This may sound odd unless we consider the different stages of development these Balkan countries are going through. While Kosovo in 2000 just left behind decades of ethnical conflicts and exhaustive underdevelopment, Albania in 2000s settled itself into a development process and got away from a very long “transition� period.

Under these results we can deduce that migration and remittances are more critical (in a negative sense) for a country in the initial phase of its development and

21

especially living for decades in a conflictual situation than for a developing country where they might be exploited beneficially for small-size investments.

The hypothesis raised and tested in this paper by blaming the migration monetary flows as promoting idleness and underdevelopment should not provide hints to international institutions for undertaking restrictive border control and immigration policies against Kosovars. Instead, they should promote development policies by tackling crucial issues such as education and health rather than migration escapism. Migration is a simple safety net and it will remain as such for as long as the Kosovo will lack a real welfare state and job opportunities especially for the youth. But it can’t become a cure!

References Amuedo-Dorantes, C. and Pozo, S. (2006): "Migration, Remittances and Male and Female Employment Patterns," American Economic Review, American Economic Association, vol. 96(2), pages 222-226, May. Aaberge, R., J.K. Dagsvik and S. Strøm (1995): "Labor Supply Responses and Welfare Effects of Tax Reforms", Scandinavian Journal of Economics 4, 635-659.

Aaberge, R., Colombino U. and S. Strøm (1999): "Labor Supply in Italy: An Empirical Analysis of Joint Household Decisions with Taxes and Quantity Constraints", Journal of Applied Econometrics, 14, 403-422.

Aaberge, R. and U. Colombino (2008): “Designing Optimal Taxes with a Microeconometric Model of Labour Supply, CHILD Working Paper 06/2008.

Adams, Jr., Richard H. (2004): Remittances and Poverty in Guatemala. World Bank Policy Research Working Paper 3418, September.

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Adams, R.H. (2005): “Remittances, Household Expenditure and Investment in Guatemala”, World Bank Policy Research Working Paper No.3532.

Bourdet, Y., and H. Falck. (2003): “Emigrants’ Remittances and Dutch Disease in Cape Verde.” Working Paper Series 11. Kristiansand, Sweden: Kristiansand University College.

International Crisis Group (2009): Europe Report “Serb Integration in Kosovo: Taking the Plunge”, N°200 European Stability Institute (2006): “Cutting the lifeline, migration, families and the future of Kosovo”.

Forum for Democratic Initiatives (2009): “Diaspora as a driving force for development in Kosovo: Myth or Reality?”.

Funkhouser, E. (1992): “Migration from Nicaragua: Some Recent Evidence” World Development, 20(8) pp. 1209-18.

Itzigsohn, Jose. (1995): ‘‘Migrant Remittances, Labor Markets, and Household Strategies: A Comparative Analysis of Low-Income Household Strategies in the Caribbean Basin.’’ Social Forces 74(2):633–55.

Hoti, A (2005): “A background study on labour relations in Kosova”.

King. R, (2005):

“Albania as a laboratory for the study of migration and

development”, Journal of Southern Europe and the Balkans 7(2), 134-155 Riinvest Institute (2007): “Diaspora and Migration Policies”.

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Rodriguez, E. and Tiongson, E. (2001): “Temporary Migration Overseas and Household Labor Supply: Evidence from Urban Philippines” International Migration Review, 2001, 35(3) pp. 708-725.

Sudhir, A., and S. M. R. Kanbur. (1993): “Inequality and Development: A Critique.” Journal of Delevopment Economics 41: 19-43.

Taylor J.E., and T.J. Wyatt. (1996): “The Shadow Value of Migrant Remittances, Income and Inequality in a Household-Farm Economy.” Journal of Development Studies 32(6): 899-912.

Yang,

D.,

(2004):

“International

migration,

remittances,

and

household

investment: evidence from Philippine migrants' exchange rate shocks,” mimeo (University of Michigan).

Zezza, A., G. Carletto and B. Davis, (2005): “Moving away from poverty: a special analysis of poverty and migration in Albania”. Journal of Southern Europe and the Balkans, vol.7(2), August, pp. 175-195.

Appendix 1 In this appendix, the results of Heckman selection models are shown. Frequency of receiving remittances, size of durables goods and the education level of household head seem to positively affect the size of remittances. Kosovar Serb households receive fewer remittances than Kosovar Albanian counterparts. As regards the probability of receiving remittances, it decreases with the household size, extreme poverty status and for Kosovar Serb households headed by women. These results imply that remittances help to alleviate poverty in Kosovo. On the other hand, the conservatism is positively correlated with the remittances. Here, conservatism is

24

proxied by the percentage of females older than 16 years who have not attended secondary schooling. Also, households coming from rural areas are more likely to receive remittances than those living in the urban area. Nationality seems to be important for the propensity of receiving remittances such as Kosovar Albanian households are more likely to receive especially if they are headed by women. This is easily interpretable as long as we are analyzing a paternalistic society where women have a very low participation rate in the labour market and consequently are economically dependent on their husbands, sons or other household members.

The estimates of rho (correlation of the residuals in the two equations) and sigma (standard error of remittances) are significant and favour the importance of the selectivity in the prediction of the remittances for those who don’t receive.

Heckman Selection Equation for predicting remittances Coefficient

Std,Err,

t-value

Remittances freq durcons coup headedu headage self rural Kosovar Albanian Kosovar Serb _cons Selection equation conservat coup N_2 N_3 N_4 N_5 pvty1

0,0896 0,0001 -0,3139 0,0264 0,0028 0,1109 -0,1430

0,0097 0,0000 0,0922 0,0102 0,0028 0,0810 0,0947

9,2700 11,8200 -3,4000 2,6000 1,0000 1,3700 -1,5100

-0,1141 -0,6767 8,2445

0,2128 0,2745 0,4392

-0,5400 -2,4600 18,7700

0,1338 0,0427 -0,2769 -0,4245 -0,3824 -0,5436 -0,2856

0,0301 0,0665 0,0761 0,0948 0,1193 0,1483 0,0809

4,4400 0,6400 -3,6400 -4,4800 -3,2100 -3,6700 -3,5300

25

pe_exp -0,0001 rural 0,2602 Kosovar Albanian 1,0063 head_female 0,4841 head_fema_Serb -.9890422 _cons -1,2063 athrho -0,8744 lnsigma .3028679 rho -0,7036 sigma 1353736,0000 lambda -0,9525 Number of observations

Loglikelihood

0,0004 0,0561

-0,2200 4,6400

0,0805 0,1017 .2571402 0,1211 0,1797 .066959 0,0907 0,0906 0,1843

12,5000 4,7600 -3.85 -9,9600 -4,8700 4,5200

Censored Uncensored -3.347

2875 1807 1068

LR test of independendent equations (rho=0):chi2(1)=8,52 Prob>chi2=0,0035 Denomination of Variables used in the Heckman Selection Equation freq frequency of receiving remittances durcons durables goods coup variable = 1 if there are less than3 married persons in the households headedu education level of household head headage age of household head self self employment status rural living in rural area Kosovar Albanian of Albanian nationality serb of Serb nationality conservat if there are more than 3 females aged more than 16 and having attended less than 9 years of schooling N_2 household size less than 7 and higher than 3 N_3 household size less than 10 and higher than 6 N_4 household size less than 13 and higher than 9 N_5 household size higher than 12 pvty1 Extreme poverty status pe_exp Per equivalent monthly income head_female household with a female head head_fema_Serb Serb household with female head _cons constant

26

27