Forced Displacement in Colombia: Causality and Welfare Losses
Ana María Ibáñez∗ Universidad de los Andes Carrera 1E No.18A-10 Bogotá, Colombia
[email protected]
Carlos Eduardo Vélez∗ The World Bank/ LAC / PREM Room I8-113, 1818 H Street Washington D.C., 20433
[email protected]
June 2003
∗
When this research was conducted, Ana María Ibáñez was a Research Associate at Fedesarrollo and Carlos Eduardo Vélez was a Senior Economist at the World Bank (LAC/PREM). The authors acknowledge and appreciate the permanent support and encouragement from Fernando Rojas (World Bank/LAC/PREM), manager of the grant (#) that provided financial support to this paper. This paper does not necessarily reflect the views of the World Bank.
Forced Displacement in Colombia: Causality and Welfare Losses
Abstract
During the last decade forced internal displacement in Colombia has been a growing phenomenon closely linked to the escalation of the internal armed conflict - particularly in rural areas. The displacement problem has hit nearly every region and vulnerable groups of the population. Two emerging policy questions are whether the magnitude of the response to this problem has been proportional to the size of the problem and to what extent the instruments chosen are the most adequate to contain it. The purpose of this paper is twofold. First, to identify the determinants of the displacement behavior and to compare those findings with standard migration literature. Second, to estimate the burden or welfare losses of displacement. Empirical evidence shows that the welfare loss of displacement is considerable and amount to 25 percent of the net present value of rural life-time aggregate consumption, for the average individual. This loss is estimated for each individual with a method that derives welfare changes from behavioral model estimates – widely used in environmental and transport economics. Our empirical findings also show that the level of violence at the origin site is not only the dominant factor of displacement behavior, but also that in a violent environment other migration determinants have the opposite effect, relative to the one expected by the migration literature in a non-violent context. That is, the violent environment reverses the migration incentives for risk aversion, access to information, the planning horizon, location-specific assets – human and non-human. Finally, separate modeling of preventive and reactive displacement behavior reveals higher welfare losses for more risk averse households and important asymmetries about the benefits of security force presence.
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1. Introduction Forced displacement1 in Colombia is large and growing, covers nearly every region of the country and affects disproportionably vulnerable groups of the population. During the last fifteen years, involuntary displaced population is at least 1.8 million and corresponds to 4.3 percent of the Colombian population (World Bank, 2003). Intensification of the political conflict and its expansion to a vast majority of the territory is causing displacement numbers to grow at a larger pace than before. In 2001, 74 percent of Colombian municipalities were expulsion or reception sites. Mostly vulnerable groups compose the displaced population. Women, children and ethnic minorities are respectively 49, 49 and 38 percent of this population (RSS,2002). In fact, in the late 1990’s recent migrants (presumably, internally displaced people) fared worse than the urban poor, in clear contrast with the traditional migrant profile, who used to enjoy better welfare than the coverage urban population up to 1995. (see Vélez, 2002, Table 7.) This paper seeks to address two main questions.
First, it identifies the key
determinants of the displacement process. Understanding the determinants of the process might shed some lights on possible policy instruments to mitigate displacement. For example, it is not clear whether increasing protection of police or military forces in the zones of potential conflict would reduce or increase displacement. Second, it estimates the burden of displacement in monetary terms. The magnitude of welfare losses is relevant to justify policy interventions and investments. Moreover, the size of public resources to alleviate displacement must take into consideration the extent of welfare losses induced by displacement. We find that police and military forces assume differentiated roles in preventing displacement. Police presence prevents displacement by reducing the likelihood of victimization but do not discourage displacement once families confront violence. On the other hand, military forces can protect the population once violence occurs and 1
The Inter-American Commission on Human Rights (1999) describes a displaced person as anyone who has been forced to migrate within the national boundaries, leaving aside her residence or her habitual economic activities because either her life, her physical integrity or her freedom have been either violated or threatened by situations such as armed conflict, generalized violence, violation of human rights, and any other situation that may alter public order.
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displacement is imminent. Indeed, presence of military forces might become the only factor preventing displacement. Welfare losses from displacement are substantial. Compensating valuation per household total in average 25 percent of the net present value of rural aggregate consumption. Relative welfare losses are larger for the poorer segment of the displaced population. The paper is organized as follows. Section 2 describes some stylized facts about displacement in Colombia and provides hypothesis on the possible causes of displacement.
In Section 3, we present a brief literature review on migration
literature, discuss its relevance for modeling the displacement decision and present a random utility model for displacement. Section 4 presents the empirical results and Section 5 concludes. 2. Displacement in Colombia: Some Stylized Facts 2.1.
Internally Displaced Population in Colombia
Forced displacement in Colombia is the consequence of a political conflict between left-wing guerrilla, right wing paramilitary groups and the State. Escalation of crimes against the civil population is a low cost and effective strategy to clear territories allowing illegal armed groups to strengthen their control area, transport weapons and develop at ease illegal activities (RSS, 2002). Displacement and political violence increased significantly during the late nineties. As the political conflict covers a sizeable proportion of the Colombian territory, most of Colombian municipalities face today displacement problems.
Regional and household characteristics and the
dynamic of the political conflict seem to determine displacement.
This section
describes some stylized facts about displacement in Colombia. Violence and displacement are apparently strongly linked. War strategies adopted by illegal armed groups like death threats, massacres, forced recruitment, temporary town take-overs and selected homicides force the civil population to flee their town. Figure 1 shows a likely correlation between increments of political homicides and increases in the total number of displaced households. In particular, during the year 1999, the trend of political homicides and displaced household soared significantly. Pérez (2002) found near 80 percent of violations to human rights and 82 percent of armed confrontations occur in expulsion sites.
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Displacement is a nationwide problem. The need of illegal armed groups to have territorial strongholds heightened and expanded the conflict across the country. As a consequence, near 74 percent of Colombian municipalities receive or force out population and with the exception of one department2, an island in the Caribbean Sea, all departments face displacement problems (Map1 and 2). Nevertheless, intensity of displacement3 is heterogeneous across and within departments. While in the department exhibiting the largest displacement intensity 10 percent of the population fled, in the department with the fifth highest intensity over four percent left (Figure 2). This wide variance across departments suggests regional characteristics might determine partially displacement behavior. For example, illegal armed groups may want to control territories rich in natural resources. Particular characteristics of households may trigger displacement as well. Some socio-demographic factors and the particular social context where the household reside may increase the likelihood of being victimized. On the other hand, some households may be more risk averse and may prefer to leave their town to prevent being the victim of violence. Social context dimensions such as risk and protective factors paired with victimization are seemingly important determinants of displacement. Presence of illegal armed appears to promote displacement.
Figure 3 indicates displaced
households use to reside in regions where paramilitary and guerrilla presence is strong while military presence is weak.
Facing violence, in particular death threats to
household members, pushes households to seek refuge elsewhere. Indirect violence, such as massacres in nearby towns or murder of a friend, is as well a source of displacement, albeit death threats play a stronger role (Figure 4). Household characteristics may influence the likelihood of death threats, victimization and displacement. Landowners are four times more inclined to flee their hometown (Figure 5). Apparently, illegal armed groups are interested in violently appropriating land. Displaced households participated actively in community activities in their origin site in contrast to household who did not displace (Figure 6). Illegal armed groups seek to destroy social cohesion in conflict zones by intimidating leaders and 2 3
Departments are equivalent to states. Intensity of displacement is measured as the number of displaced population per 100.000 inhabitants
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active members of the community to eliminate the chances of civil opposition. Other factors, such as access to social services, elevate migration costs and incentives residents to stay in their hometown (Figure 7). Constant changes in the conflict dynamic caused modifications in displacement typology. During the nineties, households displaced mainly after a town massacre and migration was massive, that is a group of households fled together simultaneously reacting to a violent act. Today, many causes trigger displacement and households relocate mostly individually to prevent victimization. From 2000 to 2001, individual displacements soared 414 percent in stark contrast to an increase of 58 percent of massive displacements.
Individual relocation is closely related to preventive
displacement while massive relocation is linked to preventive displacement (RSS, 2002).
Preventive displacement may continue to rise as a consequence of the
geographic extension of the conflict (Meertens, 1999). 2.2.
Alternative Explanations of Displacement in Colombia
Causes of involuntary migration in Colombia are difficult to identify. Immediate causes or triggers are the last incident in a chain of events that produce the final decision to flee the hometown. And yet the root of displacement underlies in the dynamics of the Colombian conflict. This section describes some hypothesis put forth in the literature about the sources originating displacement in Colombia. Illegal armed groups and its actions against the civil population are mainly responsible for forced displacement.
In 2001, paramilitary groups instigated 50
percent of displacements while guerrilla and two actors simultaneously originated 20 and 22 percent respectively (RSS, 2002). Paramilitary groups not only bear the bulk of the responsibility but also are more effective displacing population. During 2001, paramilitaries caused 599 displacement events that forced out 91.380 people meanwhile guerrilla groups provoked 570 events that prompted 36.217 people to flee (RSS, 2002). Violent actions against the civil population, like threats and selective homicides, trigger the decision to displace. Threats and homicides are the main motive to seek refuge elsewhere (Conferencia Episcopal, 1995, Arquidiócesis de Bogotá - Codhes, 1997). However, armed confrontations became lately an important trigger due to the recent intensification of the conflict in populated areas (RSS, 2002).
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Land conflicts and violent land appropriation is considered an underlying source of displacement (Reyes and Bejarano, 1998).
Land occupation is crucial in the war
strategy to clear the territory from the presence of opponents, to expand control areas and to appropriate valuable land. A low cost strategy to occupy land is to drive out small landholders and appropriate their land (USCR, 2001). Displaced population reports to have lost four million hectares of land4, which amounts to one third of productive land in Colombia (PMA, 2001). Programs to eradicate illicit crops may as well produce displacement (Arquidiócesis de Bogotá-Codhes, 1997). Aerial fumigation of illicit crops5 destroys farmers’ assets, produces a temporal shock on their income and originates combats exacerbating violence in the region. Estimations indicate 13.153 people displaced during 1999 in drug producing departments (Puyana, 1999). Forcing out population may be a war strategy to impede collective action, to damage social networks as well as to intimidate and control the civil population. Attacks to the populations weaken their support to the opponent and obstruct rise up of civil population (Henao et al., 1998). Lozano and Osorio (1999) estimate 65 percent of displaced population was an active member of community organizations and 11 percent participated in labor and politic organizations in their hometown. Rural families may involuntarily migrate to avoid forced recruitment of their children. Children as young as eight years are currently recruited by illegal armed groups to fight as soldiers in the Colombian conflict (Salazar, 2001). After a combat in October 2001, military forces found 43 percent of dead guerrilla members and 41 percent of captured guerrilla members were below 18 years of age (USCR, 2001). 3. Modeling Displacement as Migration 3.1.
Logical asymmetries between migration and displacement incentives
Somehow, displacement resembles migration behavior. Households must compare the benefits and costs from residing in the origin and reception sites and choose the alternative with larger net benefits.
Nevertheless, in the case of displacement,
4
These figures might overestimate the total hectares of abandoned land because displaced households have incentives to report ownership of larger farm sizes in the event a program of land restitution is implemented. 5 Programs to eradicate illicit crops follow two strategies: (i) aerial fumigation of illicit crops; or (ii) manual and voluntary substitution. Some analysts consider aerial fumigation is causing displacement.
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violence is an additional factor in the decision process that modifies the costs from staying at the origin site and, consequently, might modify the impact of other migration determinants.
The purpose of this section is to discuss the variables
identified in the literature as determinants of the migration decision and to show, in most cases, incentives are reversed in forced displacement. Reversal occurs because violence reduces returns and increases risk in the site of origin. Determinants of costs in the destination site influence the decision to migrate and to displace in the same direction. Contacts at the reception site and education decrease migration costs (Becker, 1975; Todaro, 1989; Todaro and Maruszko, 1987). Contacts at the reception site may provide housing, support to find employment and a social network.
Better-educated individuals may find employment easier and generate
larger incomes after migrating. On the other hand, potential discrimination at arrival increases migration costs and, thereby, discourages migration (Fischer et al. 1997). In Colombian urban centers, discrimination against displaced population is particularly strong. Some native residents wrongly believe displaced households belong to illegal armed groups and, in addition, perceive this population attracts public resources previously allocated for the poor. Empirical evidence suggests that the long-standing conflict in Colombia reverses the effect of some traditional migration determinants. The length of the planning horizon exerts similar incentives on the decision to migrate and to displace but the underlying motives differ. Inclination to migrate is larger for individuals with long planning horizons (Becker, 1975; Todaro, 1989; Todaro and Maruszko, 1987). On the other hand, young people are probable targets of threats, forced recruitment and selective homicides; therefore likelihood to displace is larger. Positive information about economic and social opportunities in the destination site improves the benefits from migration (Stark and Levhari, 1982; Dustmann, 1992; Maier, 1985). Conversely, information about poor social and economic conditions in destination sites raises the benefits of non-migration. Risk aversion assumes an asymmetric role in the decision to migrate and to displace. The uncertainties inherent in arriving to an unknown place may dissuade risk averse individuals to migrate (Fischer, 1997). In contrast, violence may induce risk averse
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households to displace in spite of the complications they might cope with in the reception site. Bounded rationality is a crucial component to consider in displacement analysis. Decisions are often limited by past experiences, emotional patterns and complexities of evaluating benefits and costs (Simon, 1983). The Colombian confrontation pushes individuals to extreme situations that hinder their capacity to decide rationally. Displaced households deciding under fear may opt for sub-optimal options because they underestimate displacement costs, overestimate risks and utilize high discount rates. Location specific assets render migration costly and reduce incentives to migrate (Fischer et al, 1997). Deficient rule of law in Colombia leaves unprotected location specific assets allowing illegal armed groups to violently appropriate land. Landownership becomes, under these special circumstances, a possible factor of victimization and a cause of displacement. Similarly, human capital location specific assets play an asymmetric role when destruction of social networks is a war strategy. Permanent residency and active participation in community activities signifies advantages from belonging to a society. Discouraging migration to the extent that it would entail giving up these accumulated advantages (Fischer et al., 1997). Since destruction of social networks is a war strategy, high levels of social capital is no longer an asset but a risk factor. Results from the migration literature are modified when violence enters into the decision process. Contacts at reception site, education and discrimination at arrival determine migration and displacement in the same direction. On the other hand, violence reverses the effect on the migration decision of the planning horizon, access to information, risk aversion, bounded rationality and location specific assets
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3.2.
A Random Utility Model for Displacement6
Household i decides whether to displace if the utility from displacement is greater than the utility from staying in the origin site U id > U in . (1)
where U ij denotes the indirect utility from alternative j, j=d is the reception site and j=n is the origin site. The indirect utility is composed by the deterministic utility ( vij ) and a random term ( ε ij ) with mean zero U ij = vij + ε ij . (2)
Decision to displace or remain in the origin site depends on many factors. First, households evaluate risks and generate expectations about security in the origin and destination region ( S ij ). Second, households compare income possibilities and access to social services in both sites ( Yij ). Third, migration and information costs influence the decision process ( C ij ). Lastly, household characteristics reflecting preference on needs and risk aversion determine displacement behavior ( Z i ). The observable utility is defined as vij = f (S ij , Yij , C ij | Z i ). (3)
If we assume a logistic distribution for the error term and a linear utility function, the probability of displacement is
probi (displace ) =
exp(α (S id − S in ) + β d Yid − β nYin + δ (C id − C in ) + (γ id − γ in )Z i ) . (4) 1 + exp(α (S id − S in ) + β d Yid − β nYin + δ (C id − C in ) + (γ id − γ in )Z i )
Equation (4) assumes marginal utility of income changes after displacement. Perceptions of security can be approximated with variables indicating whether the household was directly threatened and whether the household is facing indirect violence. Direct threats are however endogenous. Landowners, active members of 6
This model was developed in Kirchhoff and Ibáñez (2001).
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the community or young household heads are possible targets of illegal armed groups. The predicted threat of household i is equal to Pr obi (Threat ) = f ( Lin , Vin , Ain | Z i ), (5) where Lin denotes landownership in the place of origin, Vin is ties in the place of origin and Ain is the presence of armed actors in the place of origin. The fitted value of the predicted threat will be included as an exogenous variable in the probability of displacement. Displaced households confront welfare losses from the deterioration of their quality of life. These losses, although not manifested in monetary terms, are likely to be one of the most significant costs of displacement for Colombian society. If these costs to the displaced themselves are left out in evaluating the dimension of the problem, the policies implemented to alleviate displacement might be insufficient or misguided. We will estimate welfare losses from displacement based on methods used widely in environmental economics. The shock from displacement exhibits a similar structure than environmental problems. An external shock, in this case violence, induces changes in behavior, which in turn imposes welfare losses to households. One way of measuring changes in utility in monetary units is compensating variation. Compensating variation for avoiding displacement is the amount of money necessary to leave the individual indifferent between displacing and staying in his hometown. In this case, compensating variation can be interpreted as a measure of the willingness to accept income in exchange for not displacing. As shown by Hanemann (1982), compensating variation (CV) can be defined as the measure that equates the expected maximum utility before and after the displacement. For the model explained above, expected compensating variation can be defined as7 E [CVi ] =
α ( S id − S in ) + β d Yid − β nYin + δ (C id − C in ) + (γ id − γ in ) Z i βd
The theoretical contributions of the model defined above are twofold. First, the random utility model permits to introduce variables never considered in migration models, such as perceptions of security, and gives enough flexibility for inclusion of
7
A complete derivation of the compensating variation is derived in Appendix I.
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reverse incentives. Second, the definition of welfare losses allows policy makers to decide whether intervention is necessary and establishes an upper bound for investment funds to mitigate displacement. The random utility model define above, typically used in environmental and transport economics, allows us to retrieve the parameters of the utility function and, thereby, to estimate welfare losses. 4. Determinants of Displacement in Colombia and Associated Welfare Losses 4.1. The Data
The purpose of the Survey for Internally Displaced Population8 (SIDP-2000) was to identify the causes of displacement in Colombia and to measure its associated welfare losses. Surveys were conducted in origin and destination sites in order to have information about displaced households and households who did not displace despite leaving in conflict zones - hereafter non-displaced households. Two samples were constructed: displaced and non-displaced sample.
The questionnaires that were
administered to these households covered issues that ranged from socio-economic characteristics of the household, victimization profile, armed actors in the region, access to social services in the origin and destination site, land ownership and agricultural production. The sample for displaced households was selected in destination sites with the largest influxes of displaced population during 1999. The surveys were administered to 200 displaced households in Bogotá, Cartagena and Medellín.
Questionnaires were
applied only to households displacing from Antioquia and Cordoba, the departments with the highest records of population expulsion in 1999. The regional composition of the displaced sample was purposively chosen with the objective of building a counterfactual sample of non-displaced population with a similar regional composition. The non-displaced sample was composed of 176 surveys of households residing in conflict zones traditionally affected by displacement and located in Antioquia and Cordoba. Although the survey provides valuable information about forced displacement in Colombia, the sample was not representative of the displaced population therefore results cannot be generalized.
8
Detailed description of the survey can be found in Kirchhoff and Ibáñez (2001).
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Table 1 presents summary statistics for exogenous variables for the displaced and non-displaced sample. The descriptive statistics provides some initial insights on displacement behavior. First, displaced and non-displaced households are exposed to excessive violence levels. Near 50 per cent of displaced households and 24 per cent of non-displaced households faced direct threats in the origin site. Moreover, few households have not confronted indirect violence9: 94 per cent of displaced households and 77 per cent of non-displaced households reported being victim of indirect violence.
Second, non-displaced households feel better protected by
government forces. In contrast to non-displaced households, displaced households perceive a greater presence of paramilitary and guerrilla in their hometown and a weaker presence of police and military forces. Third, evidence suggests violence is not randomly targeted.
Displaced households are landowners in larger proportions,
participate in more organizations and have younger household heads than nondisplaced households. Yet land size is larger for non-displaced households, which may imply illegal armed groups mostly target landowners with small farms. Lastly, non-displaced apparently have a higher economic status because they are better educated, have more accesses to basic social services10 and rural aggregate consumption11 is larger when compared to displaced households. Table 1. Descriptive Statistics Direct threat Indirect violence Paramilitary presence Guerilla presence Military presence Police presence Contacts – reception site Years of residence – origin site Own land Standardized land size Access to social services Household education Access to media Rural consumption a Urban consumption a Age household head Household size before displacement
Displaced Mean Variance 0.54 0.94 0.93 0.87 0.74 0.48 0.73 20.26 12.96 0.44 -0.18 0.64 0.72 6.70 2.93 2.37 1.49 4.00 1.09 2.72 2.16 37.17 12.70 5.54 2.43
Non Displaced Mean Variance 0.24 0.77 0.68 0.51 0.91 0.91 0.71 22.34 14.90 0.08 0.02 0.33 0.90 8.95 3.60 3.23 1.41 4.41 1.53 3.97 2.88 45.43 15.03 5.19 2.41
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A household was defined to confront indirect violence when a nearby town or when friends and family were the victims of attacks by illegal armed groups, massacres, bombs or any other type of violence. 10 Access to basic social services is a dummy variable equal to one when the household has access to education and health. 11 Appendix I describes the methodology used to predict rural and urban aggregate consumption.
11
Male household head 0.73 Number of organizations 0.66 Source: Authors calculations based on SIDP-2000 a. In million pesos
4.2.
1.00
0.62 0.29
0.47
Predicted Threat Model
Aggressions against the civil population are not randomly targeted. Last sections provide evidence that illustrates illegal armed groups may attack households with particular characteristics. Direct threats are consequently an endogenous variable. In order to reduce endogeneity problems, we estimate the probability of a household being the victim of direct threats using a probit model. Fitted values of the estimation are included in the probability of displacement as an endogenous variable. Table 2 reports the results for the predicted threat model. The most likely victims of direct threats are landowners as well as families with young household heads and with household members actively involved in community activities. These results confirm the hypotheses developed in the literature.
Illegal armed groups are violently
appropriating land and attack young and active members of the community as part of a war strategy. Estimations indicate as well households residing in zones of paramilitary dominance are threatened with a larger probability whereas guerrilla dominance does not seem to have a significant effect on threats. This result should be carefully analyzed. When the SIDP-2000 survey was conducted, displacement occurred mainly as a consequence of paramilitary actions like threats and massacres. Nevertheless, the dynamics of the conflict changed significantly during the last years and today guerrilla groups are responsible for many displacement events.
Lately, guerrilla
attacks to small and medium municipalities have provoked large expulsions of population12. Police protection deters threats from illegal armed groups to the population and, consequently, prevents displacement. Contrary, military forces are not instrumental to reduce the likelihood of threats. Protection of the civil population requires a
12
For example, in May 2002 leftist guerrilla groups attacked Bojayá, a small municipality located on the Pacific Ocean. As a result of the attack, 119 people died and 4.284 people were forced to displace (CE, 2002).
12
constant presence of the State and a reliable institution with strong links with the community. Police forces embody these conditions. The role of military forces is, on the other hand, to protect the population during war. Yet their presence should not be permanent in each Colombian municipality. Table 2. Probability of Threats Marginal Effect 0.1614 -0.0014 -0.0053 0.0867 0.2575 0.0946 -0.0610 -0.2134
Own land Years of residence – origin site Age household head Number of organizations Paramilitary presence Guerrilla presence Military presence Police presence Number of observations Pseudo R-square Source: Authors calculations based on SIDP-2000
P>|z| 0.02 0.51 0.01 0.01 0.00 0.16 0.47 0.00 363 0.1497
4.3. Determinants of Displacement
The displacement model defined in section III is estimated using maximum likelihood procedures. Three models are estimated. The first is the Aggregated Model that makes no distinction between preventive and reactive displacement. In the next section, we estimate a model distinguishing by displacement types preventive and reactive. Table 3 reports estimation results for the Aggregated Model. Security perceptions are the dominant predictor of displacement. In particular, an increase of one per cent in predicted threats13 raises the probability of displacement by 326 per cent. Indirect violence, although not as effective as predicted threats, is also a dominant factor of displacement. Military protection discourages displacement once threats and indirect violence has been taken into account. The role of police presence is not significant when displacement is imminent. Displacement costs, though significant, do not counterbalance the effects of violence in the origin site. Households with access to basic social services are less likely to displace.
Access to media, probably by providing information about difficulties
families face in reception sites, dissuades displacement. However, the joint effect of both variables is not enough to compensate the influence of indirect violence let alone 13
Direct threats are endogenous to the model and were instrumented using predicted threats. The model meets the identification conditions.
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predicted threats. As expected, contacts availability at reception increases likelihood of displacement. Consumption indicators in the displacement decision behave similarly than in migration models. Foregone consumption in the origin site decreases the chances of displacement while consumption opportunities in the destination site incentive displacement. Unlike migration models, better-educated household are less willing to displace.
Probably better-off households are able to adopt protective measures.
Evidence from descriptive statistics reported in Table 1 supports these findings because non-displaced are better-educated households with larger farm sizes and higher rural consumption. Household characteristics determine partially the decision to displace. Households with younger heads are more inclined to displace. As previously discussed, young individuals are likely targets of illegal armed groups but the predicted threat already accounts for this effect. The tendency of younger heads to migrate may reflect risk preferences of households.
On the other hand, years of residence increase the
probability of displacement.
Table 3. Probability of Displacement – Aggregated Model Marginal Effect Predicted threat Indirect violence Military presence Police presence Contacts – reception site Years of residence – origin site Standardized land size Access to social services Household education Access to media Rural consumption a Urban consumption a Age household head Male household head Number of observations Pseudo R-square Source: Authors calculations based on SIDP a. In million pesos
3.2650 0.5895 -0.2764 -0.0472 0.1401 0.0066 -0.0915 -0.2659 -0.0368 -0.0747 -0.2710 0.1280 -0.0117 -0.0129
P>|z|
0.00 0.00 0.04 0.74 0.11 0.02 0.29 0.01 0.02 0.02 0.04 0.05 0.04 0.88 361 0.6200
The model estimated above is robust to changes in specification. We estimated various specifications of the model and results did not vary significantly. Parameter
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estimates, t-statistics and pseudo r-squares are practically identical when other models are estimated. Empirical estimation confirms the reversal of migration incentives when life threats, lack of rule of law and violation of property rights prevail. Violence and aggressions against the civil population modifies the migration incentives of education and location specific assets, such as land and social capital. Other migration determinants, like consumption indicators and access to basic social services, influence displacement decisions in the expected direction. Military and police protection reduce displacement but in different stages of the process. Police protection is paramount to ease aggressions of illegal armed groups to the civil population. Once the civil population faces aggressions, military protection is the only possible instrument to halt displacement. 4.4.
Modeling Two Displacement Types: Preventive and Reactive
The previous model is estimated for preventive and reactive displacement.
We
defined preventive displacement when households identified “fear despite not being threatened” as reason for fleeing their hometown. Results for the preventive and reactive model are presented in Table 4. Perceptions of security and some migration variables are similar in the preventive and reactive displacement models. Predicted threats and indirect violence continue to be the main determinants of displacement. reactive displacement.
Both variables are however stronger in
Akin to the Aggregated Model better-educated and older
household heads are less likely to displace in the preventive and reactive model. Urban consumption promotes displacement in both models. Results suggest the more risk averse self-select into preventive displacement. First, military protection is strongly significant for reactive displacement but seems insufficient for preventive households who prefer to leave before violence escalates. Second, rural consumption is irrelevant for preventive displacement. Risk associated with rural consumption is weakly compensated with increases in the mean of rural consumption. Unlike reactive displacement, migration costs contribute to promote or deter preventive displacement. Contacts at destination site induce households to migrate
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only for preventive displacement. Access to social services remains significant for both displacement types but a bit stronger in preventive displacement. Table 4. Probability of Displacement – Preventive and Reactive Displacement Preventive Displacement Marginal P>|z| Effect Predicted threat 2.4071 0.00 Indirect violence 0.1780 0.06 Military presence -0.2536 0.16 Police presence -0.1535 0.28 Contacts – reception site 0.1249 0.09 Years of residence – origin site 0.0019 0.50 Standardized land size -0.0514 0.49 Access to social services -0.4280 0.01 Household education -0.0426 0.03 Access to media -0.0455 0.13 Per capita rural consumption a -0.1410 0.25 Per capita urban consumption a 0.0906 0.11 Age household head -0.0103 0.04 Male household head -0.0118 0.89 Number of observations 240 Pseudo R-square 0.6679 Source: Authors calculations based on SIDP-2000 a. In million pesos
Reactive Displacement Marginal P>|z| Effect 3.4124 0.00 0.4788 0.01 -0.3712 0.09 -0.0059 0.97 0.1068 0.26 0.0077 0.02 -0.1088 0.34 -0.2662 0.06 -0.0338 0.06 -0.0679 0.05 -0.3670 0.01 0.1730 0.02 -0.0128 0.05 -0.0403 0.69 290 0.6141
Empirical findings show violence, especially direct threats and indirect violence, remain the dominant factor of both types of displacement. Yet behavior of preventive and reactive types is partially different. Immediate response of military forces can reduce reactive displacement while preventive displacement is difficult to halt. Military protection does not dissuade preventive displacement. On the other, police protection, by reducing the probability of threats, mitigates preventive displacement. Access to social services, although statistically significant, does not provide a clear incentive to deter households from displacing. Indeed, containing violence is the only effective instrument to control preventive displacement. 4.5.
Welfare Losses
Welfare losses from displacement are substantial. In fact, the costs from displacement amount to 25 per cent of the net present value of aggregated rural consumption (See Table 5). Figure 8 shows the cumulative distribution of welfare losses as a percentage of net present value of rural aggregate consumption. Near 40 percent of households experience welfare losses above 40 percent of the net present value of the aggregated rural consumption.
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Table 5. Welfare Losses as Percentage of Rural Aggregate Consumption % Welfare Losses 25% Aggregated Model 24% Preventive Displacement 15% Reactive Displacement Source: Authors calculations based on SIDP-2000
When welfare losses are estimated for preventive and reactive displacement, we find preventive displacement generates larger welfare losses, 24 per cent, in contrast to reactive displacement, 15 per cent (Table 5). Risk aversion might determine this gap because welfare losses from preventive displaced population may encompass regular economic costs from displacement as well as costs from facing uncertainty and anxiety. The economic burden of displacement falls disproportionably upon the poor. Figure 9 plots welfare losses as a percentage of rural aggregate consumption against rural aggregate consumption per capita. Poorer households suffer losses above 60 percent while this figure ranges from 20 to 40 percent for families with larger consumptions. Unfortunately, the economic literature does not provide similar estimations to compare the size of welfare losses from displacement in Colombia. However, we can contrast our results to estimation of welfare losses from environmental degradation in other countries. For example, welfare costs from air pollution in Bogotá, the fourth most polluted city in Latin America, total 0.01 per cent of the net present value of household income14 (Ibánez and McConnell, 2001).
Economic costs from air
pollution in Taiwan are equal to 0.005 per cent of the net present value of household income15 (Alberini et al, 1997). 5.
Conclusions
Forced displacement modeling diverges from traditional migration modeling. Many key determinants of migration have the opposite effect in the context of forced displacement. Our empirical findings confirm this hypothesis. Violence in the origin
14
This measure estimates willingness to pay for reductions in one symptom day of acute respiratory illnesses. 15 This measure estimates willingness to pay to avoid recurrence of an episode of acute respiratory illnesses.
17
site modifies the migration incentives of education and location specific assets, such as land and social capital. Large welfare losses justify policy intervention. Economic costs of displacement are in average 25 per cent of the net present value of aggregated rural consumption. Moreover, poorer families experience larger welfare losses. In fact, some households have welfare losses above 80 percent of the net present value of aggregated rural consumption. Our estimations provide evidence on possible policy instruments to prevent displacement. Violence, in particular direct threat and indirect violence, is the major determinant of displacement and is, thereby, the key instrument to prevent displacement. Other type of interventions has a marginal effect on displacement and cannot compensate the effect of direct threats and indirect violence. However, police and military protection can mitigate displacement. While police presence prevents direct threats, military forces are instrumental to protect the population once displacement is imminent. On the other hand, economic variables, like access to basic social services or access to information, mildly prevent displacement.
18
References
Alberini, A., M. Cropper, T. Fu, A. Krupnick, J. Liu, D. Shaw, and W. Harrington. “Valuing Health Effects of Air Pollution in Developing Countries: The Case of Taiwan,” Journal of Environmental Economics and Management, 34: 107-126 (1997). Arquidiócesis de Bogota-CODHES, (1997). Desplazados por violencia y conflicto social en Bogotá. Bogotá, Colombia. Becker, G. (1975) Human Capital, Columbia University Press, New York.. Conferencia Episcopal (1995). Derechos Humanos - Desplazados por Violencia en Colombia. Bogotá, Colombia. Conferencia Episcopal (2002). RUT informa sobre desplazamiento forzoso. Estudio de Caso 4. Bogotá, Colombia. Dustmann, C. (1992) Migration, Savings and Uncertainty, Department of Economics, European University Institute, Firenze, Italy. Fischer, P.A. et al. (1997) “Should I Stay Or Should I Go?”, in International Migration, Immobility and Development (ed. Hammar, T.), Berg, Oxford. Hanemann, M.W. (1982) Applied Welfare Analysis with Qualitative Response Models. California Agricultural Experiment Station Working Paper No. 241. Berkeley, CA: University of California. Hanemann, M.W. (1984). “Welfare Evaluations in Contingent Valuation Experiments with Discrete Responses”, American Journal of Agricultural Economics, 66(3): 332-341. Henao, H. et al. (1998). Desarraigo y futuro. Vida cotidiana de familias deslazadas de Urabá. Medellín, Colombia. Ibáñez, A.M. and T. McConnell (2001). Valuing Morbidity: Acute Respiratory Illnesses in Bogotá, Colombia. Unpublished Mimeo. Interamerican Commission on Human Rights (1999). “Desplazamiento Forzado Interno”. Chapter VI of Tercer informe sobre la situación de los derechos humanos en Colombia. Organization of American States, Washington D.C. Kirchhoff, S. and Ibáñez, A.M. (2001). Displacement Due to Violence in Colombia: Determinants and Consequences at the Household Level, ZEF – Discussion Papers on Development Policy No. 41. Bonn University. Lozano, F.A. y F.E. Osorio (1999). Horizontes de comprensión y acción sobre el desplazamiento de población rural en Colombia (1995-1997). CODHES. Bogotá, Colombia. Maier, G. (1985) “Cumulative Causation and Selectivity in Labour Market Oriented Migration Caused by Imperfect Information”, Regional Studies, vol. 19, pp. 231-41. Meertens, D. (1999) “Desplazamiento forzado y género: trayectorias y estrategias de reconstrucción vital” in Desplazados, Migraciones Internas y Reestructuraciones Territoriales (eds. Cubides, F. y C. Domínguez). Centro de Estudios Sociales – Universidad Nacional y Ministerio del Interior. Bogotá, Colombia. Pérez, L.E. (2002). “Desplazamiento forzado en Colombia 1995-1999: Una aproximación empírica a las relaciones entre desplazamiento, conflicto armado y desarrollo” en El desplazamiento forzado en Colombia: compromisos desde la universidad. Bogotá, Colombia.
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PMA, Programa Mundial de Alimentos (2001). Estudio de caso de las necesidades alimentarias de la población desplazada en Colombia. Bogotá, Colombia. Puyana, A.M. (1999). “Cultivos Ilícitos, fumigación y desplazamiento en la Amazonía y la Orinoquía” in Desplazados, Migraciones Internas y Reestructuraciones Territoriales (eds. Cubides, F. y C. Domínguez). Centro de Estudios Sociales – Universidad Nacional y Ministerio del Interior. Bogotá, Colombia. Reyes, A. y A.M. Bejarano (1998). “Conflictos agrarios y luchas armadas en la Colombia contemporánea.” Análisis Político 5:6-27. RSS, Red de Solidaridad (2002). Informe al Congreso de la República. Presidencia de la República Enero 2001- Febrero 2002. Bogotá, Colombia Salazar, M. C. (2001). "Consequences of armed conflict and internal displacement for children in Colombia," Winnipeg Conference on War Affected Children, Report of the United Nations High Commissioner for Human Rights on the Human Rights Situation in Colombia. Simon, H.A. (1983) Reason in Human Affairs, Basil Blackwell, Oxford. Stark, O. and D. Levhari (1982) “On Migration and Risk in LDCs”, Economic Development and Cultural Change, vol. 31, pp. 191-6. Todaro, M.P. (1989) Economic Development in the Third World, Longman, New York. Todaro, M.P. and L. Maruszko (1987) “Illegal Immigration and US Immigration Reform: A Conceptual Framework”, Population and Development Review, vol. 13, pp. 101-14. USCR – U.S. Committee for Refugees (2002). Report 2001. Washigton. D.C. Vélez, C.E. (2002). Colombia Poverty Report. World Bank: Washington, DC. World Bank. 2003. Colombia: The Economic Foundation of Peace. Washington. D.C. Wodon, Q.T. (1999). The Micro Determinants of Consumption, Poverty, Growth and Inequality in Bangladesh. World Bank Policy Research Working Paper 2076. Washington, DC.
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APPENDIX I Derivation of Compensating Variation16
The utility from displacement for household i is defined as U id = αS id + β d Yid + δC id + γ id Z i + ε id . On the other hand, the utility for household i from residing in the origin site is U in = αS in + β nYin + δC in + γ in Z i + ε in . The money value necessary to equate the utility before and after displacement, that is the compensating variation, is equivalent to
αS id + β d (Yid − CVi ) + δC id + γ id Z i + ε id = αS in + β nYin + δC in + γ in Z i + ε in , which becomes CVi =
α ( S id − S in ) + β d Yid − β nYin + δ (C id − C in ) + (γ id − γ in ) Z i + ε id − ε in . βd
Since ε id and ε in are random variables with mean zero, the expected compensating variation is defined as E [CVi ] =
16
α ( S id − S in ) + β d Yid − β nYin + δ (C id − C in ) + (γ id − γ in ) Z i . βd
The derivation of the compensating variation draws on Hanemann (1984).
1
APPENDIX II Prediction of consumption aggregate
To estimate the consumption aggregate of SIDP-2000 households, we estimated a regression for the micro determinants of consumption for urban and rural areas utilizing the Encuesta de Calidad de Vida (1997). The coefficients from the estimation were used to predict urban and rural consumption for displaced households. Based on Wooodon (1999) and the results for Vélez (2002), we included the following determinants of consumption included: (i) regional controls; (ii) household size variables: the number of babies, children and adults; (iii) other demographic and gender variables such as gender and age of household head as well as family structure; (iv) education variables: education of the household head and education of the spouse; (v) the standardized amount of land owned for rural areas; and (vi) rural migration status for urban areas. Results for the urban and rural estimation are presented in Tables II.1 and II.2. Table II.1. Estimate for rural consumption Variable Coefficient P>|z| Number of children under 2 years -84,0 0,73 Number of children under 2 years squared 46,2 0,78 Number of children between 3 and 13 years -32,4 0,68 Number of children between 3 and 13 years squared 8.894,2 0,56 Number of adults (14-65) 371,3 0,00 Number of adults (14-65) squared 8.818,0 0,95 Age household head 57,8 0,00 Age household head squared -5.598,5 0,00 Male household head 533,5 0,00 Years of education household head 103,7 0,00 Years of education household head squared 3.269,7 0,25 Years of education spouse 112,6 0,00 Years of education spouse squared 6,6 0,01 No spouse -312,9 0,04 Constant 192,3 0,69 Adjusted R-Square 0.1709 F Test 36.92 Source: Authors calculation based on Encuesta de Calidad de Vida (1997) *Regional controls included
2
Table II.2 Estimate for urban consumption Variable Coefficient P>|z| Number of children under 2 years -1.471,1 0,10 Number of children under 2 years squared 608,8 0,36 Number of children between 3 and 13 years -450,9 0,08 Number of children between 3 and 13 years squared 130,4 0,05 Number of adults (14-65) 654,6 0,01 Number of adults (14-65) squared 2.494,9 0,95 Age household head 276,3 0,00 Age household head squared -2,2 0,00 Male household head 1.018,2 0,02 Years of education household head -214,2 0,03 Years of education household head squared 35,0 0,00 Years of education spouse 218,7 0,02 Years of education spouse squared 10,1 0,04 No spouse -1.145,4 0,01 Rural migrant -374,5 0,28 Constant -6.547,6 0,00 Adjusted R-square 0.2829 F Test 82.57 Source: Authors calculation based on Encuesta de Calidad de Vida (1997) *Regional controls included
3
Figure 1. Displaced Households and Violence 8.000
6.000 40.000
Political homicides
4.000
20.000 2.000
Displaced households 0
0 1997
1998
1999
2000
2001
Source: RSS and Human Rights Commission
1
Homicides
Displaced households
60.000
Source: RSS
1
Source: RSS
1
Figure 2. Displacement Intensity by Department 2002
Bolívar
Sucre
Caquetá Source: RSS Putumayo
Chocó
0 Source: Rss (2002)
2.000
4.000
6.000
8.000
10.000
12.000
Displaced population/100,000 inhabitants
1
Figure 3. Perception - Presence of Armed Groups
Percentage of households
100%
80%
60%
40%
20%
0% Military presence
Paramilitary presence
Displaced
Guerrilla presence
Non Displaced
Source: SIDP-2000
1
Figure 4. Direct threats and Indirect Violence
Percentage of households
100%
80%
60%
40%
20%
0% Direct threats Displaced
Indirect violence Non Displaced
1
Figure 5. Land Ownership
Percentage of households
50%
40%
30%
20%
10%
0% Displaced
Non Displaced
Source: SIDP -2000
1
Num ber of organizations per household
Figure 6. Number of organizations
0.7 0.6 0.5 0.4 0.3 0.2 0.1 0.0 Displaced
Non Displaced
Source: SIDP - 2000
1
Figure 7. Access to Social Services
Percentage of households
100%
80%
60%
40%
20%
0% Displaced
Non Displaced
Source: SIDP-2000
1
Figure 8. Cumulative Distribution Welfare Losses as a Percentage of Net Present Value of Rural Aggregate Consumption
1
Distribucion acumulativa
.8
.6
.4
.2
.2
.4 .6 Variacion compensada/Valor futur
.8
1
Source: Authors calculation based on SIDP - 2000
1
Figure 9. Welfare Losses and Rural Aggregate Consumption Per Capita
Welfare Losses/Net Present Value RAC
100%
80%
60%
40%
20%
0% 0
2.000.000
4.000.000
Rural Aggregate Consum ption
Source: Authors calculations based on SIDP-2000
2
