how has internal migration in albania affected the receipt of transfers from family and friends?...

How has internal migration in Albania

affected the receipt of transfers from family

and friends?

Florian Tomini Maastricht Graduate School of Governance

Maastricht University

Jessica Hagen-ZankerOverseas Development Institute, UK

World Bank Conference on Poverty and Social Inclusion in the Western BalkansBrussels, Belgium, December 14-15, 2010

Maastricht Graduate School of Governance

Motivation

• Family networks economic, social support etc

• Networks non-stable affected by social, economic changes, or physical location

• What happens to the network when migration is characterized by relocation of households?

– Will the composition of received transfers change?

– Will the sending relatives be different?

• Our study: looks at how family solidarity & networks have been affected by internal migration when entire households move.

• Data is scarce Based on own data collected


Literature

• Economic aspects of inter-family transfers (Becker 1974; Chiappori 1988; Cox & Rank 1992).

• Contacts and support after migration (Litwak 1960; Jitodai 1963; Wellman et al 1997; Ruan et al 1997).

• Solidarity after transition (Cox 1996; Vullnetari & King 2008).

• Other views co-insurance agreements (Stark 1991).


Internal migration and Albania

• Between 1945-1990 internal migration in Albania was centrally controlled (international migration not allowed).

• The collapse of communist regime in 1990 people migrated either internationally or internally.

• Internal migration is not circular and often characterized by relocation of the whole household (De Soto et al, 2002; Cila, 2006) .

• Motivation seem to relate mostly to economic reasons (work seeking, etc) (Carletto et al., 2004).


Internal migration and Albania

Source: Based on Albania LSMS Data 2002 - 2005

025

000

5000

0#

of m

igra

nts

1990

1991

1992

1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

Year moved to current residence

Internal International


Survey

• Hh-survey in peri-urban Tirana, April 2008

• Recently populated areas with high informality

• 112 hhs sampled, 26 also qualitative interview

• Sampling methodology:

– 1) Define the recently populated areas (5 main zones).

– 2) Sub-divide SU of 1 km2 within these zones using satellite maps.

– 3) Randomly select hhs within selected sub-sections


Survey

• Migrant households come from nearly all districts, but especially from the Northern and Central mountainous areas (the darker areas on the map).


Data – selection of family members

• Members of kinship (including relatives/non-relatives) they have been in contact with both now and in the past.

– Total: 1064 kinship members hhs are in contact with.

• Next getting the information on transfers with randomly selected (alphabetical order of given names) relatives/non-relatives:

- Parents/ parents in law (1)

- Siblings (2)

- Children (2)

- Other relatives (2)

- Non-relatives (friends, neighbours, etc) (1)


Data - transfer questions

• Transfers to the household in the past 12 months.

• Hh are also asked about transfers in the past. – Transfers in 1991 if they moved before & in 1997

– Transfers in 1997 if they moved in 1998 or after.

• “Transfers” included:

– Financial transfers

– Transfers of goods

– Services transfers


Methodology

• The transfers occur within a defined limit of time, and probabilities of consecutive transfers are not dependent on each other.

• Frequency data shows over-dispersion (variance is greater than mean) standard Poisson model not suitable

• Two may be the causes of this over-dispersion:– 1) idiosyncratic and random bias in receiving transfers

(households do not have the same probability for receiving a certain frequency of transfers), and

– 2) households do not receiving transfers systematically because of their characteristics or relatives characteristics (i.e. limited contacts in the past 12 months before migration).


Methodology – model testing

• Models considered:– PRM (Poisson)

– ZIP (Zero Inflated Poisson)

– NBRM (Negative Binomial Regression)

– ZINB (Zero Inflated Negative Binomial)

• Results confirm over-dispersion due to idiosyncratic factors and random bias.

– NBRM and ZINB give best results.

-.1-

.05

0.0

5.1

Obs

erve

d-P

red

icte

d

0 1 2 3 4 5 6 7 8 9Count

PRM NBRM

ZIP ZINB

Note: positive deviations show underpredictions.

All transfers combined


Methodology

• To account for over-dispersion among the count outcomes we use a “negative binomial regression model”, where:

iy

iii

ii y

yyY

!)(

)()Pr( ny ,...3,2,1

is the estimated value of the model dependent on a vectors of covariates,

- accounts for the over-dispersion in the data.

)exp()( iii xyE

- expected value of the model. - vector of estimated coefficients,

- vectors of covariates including characteristics of receiving household and sending relative.

i

ix

iy

1


Empirical strategy

• We pool the data from before and after migration, accounting for when the transfer takes place with the “migration dummy”.

– When applicable, the variable is adjusted to the period before migration (i.e. age, number of children etc.).

• Models are estimated separately for different types of transfers and for all transfers combined.

• In addition, to check for how role of relatives has changed before and after migration we check for differences in coefficients using “seemingly unrelated estimations” (Weesie, 2000).


Results – NBRM

Financial transfers Good transfers Service transfers Coef. st. error Coef. st. error Coef. st. error

Transfer after migration 1.24*** 0.32 -0.89*** 0.28 -0.93*** 0.28

Relative parent -0.07 0.62 1.04* 0.56 -1.14* 0.60

Relative child -0.57 0.86 1.76*** 0.64 0.57 0.69

Relative sibling 0.30 0.42 0.71* 0.39 -0.78* 0.43

Relative other -0.13 0.48 0.05 0.40 -1.78*** 0.45

Age hhh -0.03** 0.01 -0.02 0.01 -0.01 0.01

Gender hh head 1.66** 0.66 -0.68 0.66 -0.14 0.83

Education years hhh -0.05 0.06 0.09*** 0.03 0.09* 0.05

Hh extended family 0.36 0.29 -0.60** 0.29 -0.63** 0.28

Number of children hh -0.19 0.15 -0.03 0.12 0.37*** 0.14

Hh moved before 1997 -0.85*** 0.30 0.18 0.27 -0.18 0.27

Age relative/ friend 0.02* 0.01 -0.00 0.01 -0.01 0.01

Gender relative/ friend -1.25*** 0.30 -0.03 0.27 0.35 0.27

Hh & relative/ friend live in same district

1.20*** 0.33 0.34 0.29 1.19*** 0.29

Constant -3.13* 1.69 -0.11 1.36 2.44 1.52

Ln alpha 2.23*** 0.13 2.27*** 0.08 2.41*** 0.08 Number of observations 940 927 907 Pseudo R2 0.07 0.03 0.02 LR Chibar2 1353.83 6436.38 16000.00 P-value Chibar2 0.00 0.00 0.00

* significant at 10%; ** significant at 5%; *** significant at 1%


Results - Predicted transfers before and after migration

0.5

11

.5P

red.

freq

. FIN

AN

CIA

L tr

ans

f.

20 40 60 80Age of hhh

Transfer after migration Transfer before migration

12

34

5P

red.

freq

. GO

OD

tran

sfe

r

20 40 60 80Age of hhh


2.1 Financial transfers 2.2 Good transfers

24

68

10

Pre

d. fr

eq. S

ER

VIC

E tr

ans

f.

20 40 60 80Age of hhh


51

01

5P

red.

freq

. ALL

tran

sf.

20 40 60 80Age of hhh


2.3 Service transfers 2.4 All transfers


Results - NBRM

• At all ages financial transfers are more frequent after migration, while services and goods are less frequent.

• Friends transfer more frequently financial transfers and services than other kinship members (effect not significant), but less goods. (Migration effect is not yet known).

• Frequency of financial transfers is higher from old to young hhh, and from male to female headed hh.

• Education of hhh influences negatively financial transfers, but positively other transfers.

• (Income variable influences transfers negatively but it is not significant.)


Results – Migration effect on network

Differences in coeff. from separate NBRM (before & after migration)

Financial transfers Good transfers Service transfers

Before migr.

After migr.

Diff. (after - before)

Before migr.

After migr.


Before migr.

After migr.


Parent 2.67 1.41 -1.26 2.02 0.94 -1.08 1.02 -1.23 -2.25**

Child -15.15 -0.6 14.55*** 0.16 2.75 2.59** 1.25 1.13 -0.12

Sibling 3.29 0.52 -2.77*** 1.15 0.25 -0.9 0.96 -0.94 -1.9***

Other 2.32 -1.11 -3.43*** -0.45 -0.2 0.25 -0.56 -2.13 -1.57**

(Friends)

(Other variables included)*

(+)

(+)

(+)

(+)

(+)

(+)

Constant -1.03 -8.41 -7.38** -1.44 0.34 1.78 3.37 1.3 -2.07

Ln alpha 1.73*** 1.92*** 2.28*** 1.72*** 2.21*** 2.36***

N 340 542 345 535 346 531

Log l.hood -167 -416 -484 -610 -731 -820

P-value Chi2 0.000 0.000 0.000 0.000 0.000 0.000

Pseudo R2 0.1490 0.0863 0.0352 0.0726 0.0184 0.0316


Results – migration effect on network

• The frequency of financial transfers from siblings and other relatives decreases if compared to the frequency of transfers from friends (same effect for parents but not significant).

• Similar trends are confirmed for services. Friends start transferring more frequently than parents, siblings and other relatives.

• Transfers from children increase more than form friends for financial transfers and goods (results are to be treated with caution).


Conclusion

• Internal migration seems to have a positive effect on the receipt of financial transfers.

• Migrants receive less frequently goods (the change in types of goods exchanged), and services (more time spent in employment or job-search activities).

• Internal migration has affected the support network (transfers from friends and children have increased more than transfers from siblings and others).

• Caveats:

– Small-scale household survey in a very specific context

– Survey focused exclusively on migrant households


Thank You!


Transfer frequency from different types of kin

Type of kin the hh receives transfers from

Parents &

parents in law

Children Siblings Relatives Friends Total

Frequency financial transfer before migration

0.29 0 0.25 0.66 0.04 0.34

Frequency financial transfer in past 12 months

0.5 0.17 0.68 0.42 0.92 0.6

Frequency goods transfer before migration

3.26 0.7 3.5 2.18 2.36 2.89

Frequency goods transfer in past 12 months

3.16 2.56 2.39 1.62 1.26 2.18

Frequency services transfer from before migration

11.26 14.38 10.88* 4.79*** 7.93 9.11

Frequency services transfer in past 12 months

8.81* 12.89*** 7.08 3.35*** 6.73 6.65

Number of observations 61-151 18-54 182-407 110-235 25-132 397-987 Stars indicate whether the mean for each group is significantly different from the total mean

(* significant at 10%; ** significant at 5%; *** significant at 1%)


Characteristics of migrant hh

• 75% nuclear families

• Average hh size >5

• >50% of hhhs completed primary & secondary school

Employment level for adult hh members

38%

7%20%

10%

10%

15%

Employed full- time

Employed part- time

Unemployed

Housewife

Student

Retired


Hh family members/ close friends hhhs are in contact with

Relationship to hhh

10%

6%

39%

26%

19% Parents & parents inlaw

Children

Siblings

Other relatives

Friends/ neighbours

274274

417417

1101106161202202

Total: 1064 family & friends hh is in contact with


Reasons for migration

Most important reason for migration

69%

7%

8%

6%

1%9%

Employment

Start own business

Schooling

Lack of land

Lack of credit

Other

how has internal migration in albania affected the receipt of transfers from family and friends?...

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