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Estimating Internally Forced Displacement (IFD) Flows in Colombia using Mark and Recapture methods, 1996 – 2004 Soledad Granada Universidad del Rosario and CERAC Mauricio Sadinle García-Ruíz Universidad Nacional and CERAC Jorge A. Restrepo Pontificia Universidad Javeriana and CERAC.

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september 2nd 2007

Estimating Internally Forced Displacement (IFD) Flows in Colombia using Mark and Recapture methods, 1996 – 2004 Soledad GranadaUniversidad del Rosario and CERACMauricio Sadinle García-RuízUniversidad Nacional and CERAC Jorge A. Restrepo Pontificia Universidad Javeriana and CERAC

September 2nd, 2007

  • Difficulties with displacement flows in Colombia
  • Objectives
  • IFD according to the available information
  • Sources
  • Methods
  • Results
  • Further planned work
caveats acknowledgement
  • Work still in progress
    • We are waiting for a major third source of data to become available and to integrate it in order to improve on the estimation quality
    • We are testing further improvements to extract more information from the data
  • Project developed thanks to the support of Foreign Affairs-CANADA (DFAIT)
difficulties with displacement flows in colombia
Difficulties with displacement flows in Colombia
  • Multiple complementary sources
  • Measurement:
    • Government
    • Catholic Church’s Conference of Bishops
    • NGO Codhes
    • ICRC
  • Surveys
    • Ibáñez (2006)
    • Household survey (13 cities)
    • Catholic Church’s Conference of Bishops
  • Estimations
    • NGO Codhes
difficulties with displacement flows in colombia5
Difficulties with displacement flows in Colombia
  • In general, these sources offer similar trends, different levels, but they have differential coverage, methods and purposes
  • As a results, there is no information for humanitarian attention and planning
  • Inefficiencies in humanitarian attention
  • Victims attention is also made mostly on a ad-hoc basis, both by government and other assistance agencies
  • Most attention is emergency-based and not long-term oriented
  • To estimate the level of IFD using several complementary sources, starting with two
  • To estimate dynamics of IFD
  • To provide a measure of the reliability of the estimates
  • To provide a measure of coverage/undercount of sources
  • To provide a “humanitarian” IFD risk map
secretariado nacional de pastoral social rut
Secretariado Nacional de Pastoral Social –RUT-
  • The RUT database has 242.565 records, between1996 y 2004; after cleaning it up we had 236.795 usable records, only 2.37% had incomplete fields.
  • Several variables, including, victim information, family relatives, and regarding the displacement event.
  • Voluntary, not compulsory, survey at humanitarian attention and Church attention posts.
  • Low coverage, self-selected, good coverage in isolated areas
  • Potential problematic biases
acci n social sur
Acción Social –SUR-
  • Acción Social database holds 2.278.978 records covering the 1995 2006 period.
  • Several variables including family, individual, and event of displacement-related information.
  • Low “quality”. After cleaning it up, only 1.616.743 records were being able to be used.
  • Compulsory registry to obtain humanitarian emergency aid from the government and to be able to apply for further assistance
  • Self-selected
  • Large coverage, mostly on urban areas and large cities
  • We use RUT and AS for the 1996-2004 period to estimate a level of displacement at day-municipality pairs, using Capture-recapture (C-R) census correction models. (Pollock, 2002, JASA). (Also known as mark-and recapture, by Wikipedia)
  • C-R permits an estimation of population levels based on incomplete samples of it by different overlapping sources
  • It assumes :
    • Two samples (at record level)
    • Equal probability of inclusion for every individual in every sample
    • Independency between samples
    • It is possible to identify the intersection
    • Population is closed
  • Under those assumptions, estimation is unbiased (consistent) and efficient.
  • Applications in natural sciences realms are countless
  • In social sciences, Ball et al have been a pioneer of using these techniques to estimate the level of HR violation in civil war contexts (Guatemala, Perú, Timor Leste) (see Ball et al, 2002).
estimators used
Estimators used
  • Lincoln-Petersen:
  • Chapman:
  • Records at SUR
  • Records at RUT
  • Recaptured
  • Chapman (1951) improves on Lincoln-Petersen
  • Chapman is unbiased if (Wittes, 1972):
  • Chapman (1951) show its estimator has negative bias if:
The most problematic of all assumptions (in terms of the quality of the estimate) is the equi-probability of capture across individuals
  • Sekar and Deming (1949) propose a stratified estimation procedure in order to account for the effect of differential probability of capture. The procedure will yield thus an estimate:
  • It assumes differential probability of capture across strata, same probability within strata, independence between samples and close population.
  • This way the (upward) bias created falls dramatically
  • The quality of stratification determines the quality of the estimate
  • We use then both Lincoln Petersen and Chapman (preferred) stratified estimators
  • When m=0,
  • This is, we use the simple sum of the two observed samples.
how to define the strata
How to define the strata?
  • There are several applications that take the strata as defined exogenously (communities, regions, etc.)
  • We want to obtain kstatistically different groups of records that will have a statistically similar probability of being included in the group:
  • We test the null hypothesis:



how to define the strata23
How to define the strata?
  • We test using:
  • That distributes
procedure for stratification
Procedure for stratification
  • We test for stratification by municipality (admin unit) of arrival, and day of arrival
  • We further jointly test for strata by day and municipality of arrival, creating strata for each day and municipality pairs.
  • We further test within each municipality in consecutive days, in order to discard over-stratification within municipality, that will lead to an upward bias.
  • (We do not do this by municipality as these are more “natural” strata).
  • The rejection level was set at 5% for all tests
matching criteria
Matching criteria
  • We define the matching criteria according to date of expulsion and arrival, place of expulsion and arrival and gender. Other more strict applications offered no substantial estimated difference.
  • We create an indicator for each record and compare them across sources using a computer algorithm
  • We do not have access to more specific characteristics (name, id) of the individual that will help us to improve the matching
confidence bootstrapping methods
Confidence: Bootstrapping methods
  • In order to obtain confidence intervals, and given that we do not know the theoretical distribution of the estimator, we use bootstrapping methods in order to approach the distribution of the estimator. We follow Buckland y Garthwaite (1991).
  • We perform 10000 replications of sub-samples with replacement in order to obtain CI and an estimate of the variance of the estimator.
  • We perform a correction of the bias of the estimator according to the results of the bootstrap obtaining:
  • The following are the point estimates bias-corrected and uncorrected Lincoln-Petersen and Chapman estimates.
  • In graphs and maps we present the Chapman estimate

Recorded by

Acción Social SUR


Estimated Arrival IFD

1996 – 2004

comparison with other displacement figures
Comparison with other displacement figures
    • Estimation (Jan 1985 - June 2006): 3.832.527*
  • RUT:
    • Estimation (1985 – 1994):720.000
    • Records (Jan 1995 - June 2004):237.614
  • SUR:
    • Records (Jan 1995 - June 2005): 1.877.328
  • CEDE:
    • Estimation (Jan 1995 - June 2005): 2.576.610
  • CERAC:
    • Estimation (1996 - 2004): 2.440.207

* Incluye cifra Conferencia Episcopal periodo 1985 – 1994.

further planned work
Further Planned Work
  • We just received data until mid-2007 and will consequently update the estimation
  • We are devising a method to improve the estimation in order to incorporate the large number of un-matchable observations using a window-based recursive procedure with those observations.
  • We are researching the properties of the estimator using Monte Carlo methods.