Migration, Violence and Welfare in rural Colombia

1
Migration, Violence and Welfarein rural Colombia

• by Alice Mesnard, IFS
• Orazio Attanasio, UCL, IFS

2
Introduction

• Civil conflict has displaced many families and
  individuals from their villages of origin. 4.3
  pop., 14 rural
• (Arboleda and Correa, 2003)
• Costs are large assets, inadequate human
  capital, poverty
• Policy makers have shown an increasing interest
  in building interventions to curb these flows

3
Objectives

• Understand the determinants of mobility decisions
  in a violent context
• We embed new motives related to violence,
  community characteristics, and policy
  interventions in the framework of economic
  migration
• Do traditional motives for economic migration
  apply in a violent context?
• How do welfare programmes affect household
  migration in such context ?
• Our concept of mobility differs from
  displacement.
• Migration decisions are not necessarily entirely
  forced but are likely to be affected by high
  intrinsic violence levels in rural villages how
  do these factors interact?
• We also compare stayers with movers

4
Road map

• Review of literature on migration, violence and
  welfare
• Data and samples
• Model of household migration with selection
• Does violence modify migration incentives?
• Understanding better the impact of violence and
  welfare programme on migration
• Other migration determinants
• Compare a sample of poor individuals from small
  towns with a sample of displaced individuals from
  similar towns
• Policy implications and future extensions

5
1 Motivation of the empirical model

• Traditional literature
• Harris and Todaro (70)
• Human capital theory (Sjaastad 62, Becker 64)
• or in uncertain environment (Da Vanzo 83,
  Pessino, 91)
• New economic of migration (Stark, 91) within
  household
• Importance of networks (Massey and al., Munshi,
  2003, Munshi and Rosenzweig, 2005 )
• Literature on violence and migration
• Schultz 71, Morrison and May 94 effects of
  violence on internal migration in Colombia and
  Guatemala
• Displacement and asylum seekers (Azam and
  Hoeffler, 2002, Hatton...)
• Engel and Ibanez (2005) displacement differs
  from migration.
• Literature on welfare programmes and migration
  scant !
• Angelucci (2005) impacts of PROGRESA on
  international migration

6
Contribution

• Microeconomic underpinnings of household
  migration
• Number of factors social capital, risk
  exposure, shocks, liquidity constraints,
  violence, policy interventions...
• We allow the violence to affect not only
  household well-being directly but also to affect
  the incentives associated to other migration
  factors
• In particular policy interventions may have
  different impacts on migration depending on
  violence level

7
Potential impacts of welfare programmes ?

• side effect of Conditional Cash Transfer
  programmes
• (-) Benefits deter households to move out of
  Treated town
• Mitigate aggregate risk, spill-over effects
• () Cash transfers help relax liquidity
  constraints.
• Their conditionality may mitigate this effect.
• Heterogeneous impacts of the programme
• if violence is low (-)
• if violence is high ()

8
The Familias en Acción Programme

• Familias en Acción (FeA) is a CCT implemented in
  Colombia in 2002.
• The programme is modeled after the Mexican
  Oportunidades/ PROGRESA intervention
• It consists of
• a health and nutrition component (46500 monthly
  pesos conditional on participation in health
  component)
• an education component 14000/28000 conditional on
  primary/secundary school enrolment and attendance
  
• The transfer is targeted to mothers
• The program started in 627 municipalities (small
  towns with enough infrastructure) and is now
  being expanded considerably.
• It is projected that about 1.5 million households
  will be in the programme by the end of next year.

9
The Familias en Acción Survey

• A consortium formed by IFS and two Colombian
  entities won the contract to evaluate the effects
  of the program.
• For this reason a large data operation was
  started in 122 towns 57 treatment and 65
  control.
• The allocation was not random
• A sample of 11,500 household was drawn from the
  SISBEN 1 lists of December 1999 and interviewed
  in 2002.
• To achieve a sample of that size, an initial
  sample of about 19,000 household was drawn from
  the same lists.
• Of these, 11,500 were still living in the same
  town (and eligible for the programme)
• A large number of households were lost because of
  high mobility.

10
The Familias en Acción Survey

• Baseline collected between June and November 2002
• Very rich and exhaustive household survey (3.5
  hours on average
• It includes information on consumption, income,
  education, time use, shocks, attitudes,
  expectations and so on and so forth.
• In some of the treatment towns the programme
  started before the baseline (TCP and TSP)
• Survey was complemented by other smaller surveys
• Schools, health care centres, community
  nurseries, local authorities, locality surveys.
• The towns are clearly affected by violence and
  the civil war
• Hard evidence (matching with municipality level
  panel data on violence DNP)
• anecdotes

11
The Familias en Acción Survey

• The follow up survey was planned (and executed)
  in 2003.
• Given the high level of mobility between 1999 and
  2002 we were very worried about attrition.
• We also thought that the survey gave us a unique
  opportunity to study the mobility of a very
  vulnerable population in the places where they
  lived.
• We obtained funds from the IADB to invest in
  tracking households down and to study mobility
  and violence.
• Three components
• Tracking down movers ?Special module on movers.
• Much more in depth interview with local
  authorities on violence and mobility
• Social capital games piloted in 12 villages.

12
The Familias en Acción Survey

• Mobility went down considerably.
• Attrition was only 6
• 2,026 households changed address between
  treatment and follow up.
• 1,316 within village
• 710 outside village
• 114 were tracked down
• 596 were lost
• 275 moved for unknown reasons
• 114321 moved to different municipalities.
• Most of the 321 who were lost moved to big
  cities.

13
Reasons for migration
Notes in () of answers
14
Costs of migration

• Migration costs are high for very poor
  households
• median costs 50,000 pesos, mean costs 103,037
  pesos
• i.e. 21 and 43 of average monthly income
• To finance their migration none relied on credit
  or loans !
• (2/3 used own funds, 1/3 was helped by friends).
• However, past migration flows are estimated
  around 10-15 per year.

15
Why are there potential problems of selection ?
3 Model of migration with selection

• 40 of households registered as very poor in
  1999 were sampled for the FA survey but are not
  in the baseline survey in July 2002.
• So, possibly, the households in the baseline
  sample are selected on unobservable
  characteristics that make them least mobile.
• In this case, migration determinants may be biased

16
Estimation of the model

• Simultaneous estimation of migration equation

with selection equation
17
Determinants of selection equation

• Use data on all households registered in the
  municipalities in 1999 for the SISBEN survey
• We need at least one instrument that we can
  exclude from the migration equation
• Instruments number of victims, kidnappings,
  displaced individuals per 10,000 inhabitants
  before 1999
• source National Police data matched at
  municipality level

18
Results of selection equation
Notes Coefficients obtained with a Probit model,
number of observations 19148
19
Results of the migration equation
Notes Standard deviations in parentheses,
significantly different from column (1)
20
Main results Wald test of independence rejects
the significance of ? at 31 level (Chi Square(1)
1.04)
21
Effects of programme and violence
Notes Column (2) adds proxies for occupation of
household head
22
4 Does violence incidence modify migration
motives ?
Q1 does the programme impact depend on the level
of violence ?
23
heterogeneous impacts of programme
Results of specification 1

• Notes high level defined
• Left by presence of ELN, FARC,
  paramilitaries in municipality
• Right number of displaced households gt5
  (most violent quartile)

24
Results of specification 2
Notes Violence is measured by number of
displaced households before the survey Column
(2) adds the controls for occupations of
household heads column (3) adds controls for
social capital
25
Programme impact depends on violence level

• Note points represent municipalities

26
Adding the direct effect of displacement
27
Robustness checks

• Dropping the municipalities with extreme levels
  of violence

• Heterogeneous impact of programme along violence
  measured by presence of illegal forces (dropping
  5 extreme values)
• Direct impacts of violence (Presence of a curfew)
  1.186 (0.454)
• Direct impact of programme
  -2.135(0.580)
• Interaction impact of programmeviolence
  1.367 (0.628)

28
Q2. Do other migration motives depend on violence?

• No significant heterogeneous impacts along
• Household social position in village (edu.
  levels, social capital)
• Working in agriculture
• Living in rural, more isolated parts of
  municipalities
• But households with larger size, smaller
  proportion of children, whose head is older
  respond more strongly to violence.

29
Understanding better the impact of violence and
welfare programme

• Is the impact of violence similar to other
  negative shocks on household income ?
• Is there more evidence for liquidity constraints
  ?
• Do they affect differently household migration
  depending on violence incidence ?

30
Households may respond more strongly to aggregate
(village) shocks than to idiosyncratic
shocksDescription of negative shocks on
household income
Is the impact of violence similar to other
negative shocks on household income ?
31
(No Transcript)
32
Is there more evidence for liquidity constraints
?

• Household wealth measured by lots of variables
  quality of walls, education of household head and
  spouse, owning a house, phone, sewage system ...
• We look at the effect of
• Net value of property
• Net stock of savings
• Net wealthnet value of ppty Net stock of
  savings

33
(No Transcript)
34
Magnitude?

• Median net wealth 1e6
• Mean 3.52325 e6
• Std. Dev. 7.42107 e6
• Increasing net wealth by median net wealth would
  increase probability to migration by 0.04
  percentage points
• Increasing net wealth by one standard deviation
  would increase it by less than 0.3 percentage
  points

35
6 other determinants of migration
Effect of wages
Notes Marginal effects of a Probit model
, 1,000 pesos represents more than 1.5 standard
deviations from mean hourly wage 100,000 pesos
40 of monthly income of very poor households in
treated municipality Standard errors in
parenthesis. significant at 1,
significant at 5, signi at 10 (1) household
and municipality characteristics (2) dropping
some municipality level characteristics (3) more
education levels for household head and spouse
(4) adding occupation of household heads and
spouse (5) adding social capital
36

• Other Municipality factors
• Altitude increases the probability to migrate
• Regional characteristics have significant impacts
• No significant impact of social capital
• Weak impacts of infrastructure health,
  education, sewage and water
• Household characteristics
• (-) Size of households (quadratric effect)
• () household head is single (0.8)
• Education levels have no significant impacts
• But occupations have strong impact (-)
  agriculture
• (-) self-employed, employed and
  employer

37
Strong effects associated to property rights
Notes Omitted category house is owned
38
Strong effects associated to type of insurance
Notes in Column (2) we add proxies for
occupation of the household head and spouse 4
households have type 1 insurance 69 households
have type 2, 10 are not insured.
39
Comparing stayers and movers

• So far we have analyzed mainly the FeA sample and
  focused on the features of households who are in
  their villages in 2002
• We now compare these households with a sample of
  households that were displaced.
• This data is taken from a survey of displaced
  individuals contacted in several large cities in
  Colombia by Econometria within a study of food
  security.
• We restrict the sample to displaced individuals
  coming from the same regions and type of
  municipalities in the FeA sample.

40
Table 8 household composition of displaced and
non displaced households
Note the non-displaced households are from the
FA survey.
41
Table 9 number of nuclear families living
together
42
Table 10 Number of deaths in the household
during the last 12 months
43
(No Transcript)
44
(No Transcript)
45
Distribution of total expenses of displaced and
non-displaced households
46
(No Transcript)
47
Occupation before displacement
48
(No Transcript)
49
Children enrolment
50
Differences between displaced and migrant
households
51
7 CONCLUSIONS

• Violence incidence and adverse income shocks
  affect strongly and positively migration
• Receiving welfare benefits decreases migration
  only if violence is not unduly high
• Other strong impacts are associated to property
  rights and type of insurance

52
Policy implications

• Our paper does not take any normative stand.
•  If policy makers want to curb migration ,
  then
• Policy measures oriented towards rural
  development and better insurance could be very
  effective
• Welfare Programmes too
• However cash transfers may also help households
  to leave very violent areas
• Is this a bad or a good thing in such a context?

53
Future research

• Experimental risk-sharing games effect of
  social capital and risk.
• Investments in physical assets, human capital and
  migration under extreme violence.
• Ambiguous effects of violence
• child labour may serve as buffer / human
  capital is the most mobile asset.
• Impact of Conditional Cash Transfers under
  uncertainty ?
• Intra-household risk diversification mechanisms
  individual migration, time uses allocation,
  transfers
• How does the CCT programme affect these
  mechanisms ?

54
Effect of social capital using survey and games
Notes the dummy variable dum_game 1 for
pilot municipalities/0 oth. Other proxies for
social capital are not significant (group size,
proportion of people who join a group).