Starting the early 2000s there was growing interest in both defining DDR and establishing its role within peacekeeping. This is seen in United Nations Security Council (2000) and the creation of the Integrated DDR standards (IDDRS) in 2006 by the Inter Agency Working Group on DDR (IAWG on DDR). In the 2006 IDDRS document, reintegration is defined as

the process by which ex-combatants acquire civilian status and gain sustainable employment and income. Reintegration is essentially a social and economic process with an open time frame, primarily taking place in communities at the local level. It is part of the general development of a country and a national responsibility and often necessitates long-term external assistance. (IAWG on DDR, 2006, p. 2)

DDR mission reports and evaluations in the end of the 90s and early 2000s were focused on measuring the outcomes (efficiency) of the program but not their effectiveness in contributing to liberal peace. For example, vocational training was measured as the number of persons who attended the training but not if such skills were useful for the ex-combatant’s engagement in the workforce. The scope of reintegration has been growing since its beginnings, to the point that many of the measurable aspects are also part of broader agendas. As Torjesen (2013) mentions, in order to assess reintegration, there is a need to start with ex-combatant themselves and their socio-economic and political challenges. This shift of focus from program evaluation to individual subjects can lead to significant changes in implementation and assuming ambitious goals like the Colombian reintegration program did. That program conceived reintegration as a path from social vulnerability to autonomous citizenship (development approach); the aim was for ex-combatants to become regular citizens instead of just dissuading them of recidivism (criminology approach).

Changing the evaluation focus from the program’s provision of services to focus on individuals was a significant advance, but it did not resolve yet which variables should be taken into count to determine when reintegration was successful. Humphreys and Weinstein (2005) used independent variables such as age, sex, abusiveness, education, poverty, and violence within the armed unit to which the combatant belonged. Researchers like Spear (2006) aimed to identify the catalysing role that comprehensive DDR could have in the establishment of conditions of physical security and also political and economic security. Unfortunately, neither study advances the formulation of indicators outside DDR that could connect with DDR-related variables. Nonetheless, they did pave the way for adjustments in DDR and the need for detailed evaluations. More important, Humphreys and Weinstein (2005) opened the door to consider poverty as one of the outcomes to be analysed. Although poverty is not 100% a DDR-related variable, the living conditions after leaving the combatant life is fundamental to analyse; nobody hands in their weapon to step into worse living conditions than before.

These contributions from academia fostered, on the policy side, a significant shift in UN’s short-term approach as can be seen in a report by UN Secretary General (2011) regarding reintegration:

In most countries, economic aspects, while central, are not sufficient for the sustainable reintegration of ex-combatants. Serious consideration of the social and political aspects of reintegration, tailored to the specific country context, is crucial for the sustainability and success of reintegration programmes. (UN Secretary General, 2011, p. 10)

In the years following the launch of the IDDRS (2006) and during the Cartagena DDR Congress in 2009, voices from both practitioners and academia converged in the fact that not measuring the impact of DDR was one of its Achilles’s heals. As Kingma and Muggah state, “appropriate metrics of success, the indicators, impacts and outcomes of DDR - together with analysis of what and why it does or does not work – are all urgently required” (Kingma & Muggah, 2009, p. 5)

Several DDR evaluations were conducted after the launch of the IDDRS. These include Conoir (2011), Lamb (2013), Molloy (2008) and The World Bank (2010), and academic articles such as Edloe (2007), Bowd and Özerdem (2013), Seethaler (2016) and Banholzer (2014), which focused on program outcomes and policy recommendations but left undetermined the metrics of success and measurable contribution to peace and development. Before 2012 there were no references of evaluations or even monitoring of post-DDR outcomes for ex-combatants. Post-DDR monitoring is a fundamental step pending for DDR evaluations because although the IDDRS do talk about ex-post evaluation to evaluate the long-term effectiveness of the programs, currently (year 2022) only El Salvador has done a quantitative evaluation 20 years after their DDR program and only Colombia has created a post-DDR active monitoring system.

Opposite to the macro-approach and more policy focused balance of 20 years of DDR made by Lamb (2013), 20 years after the Chapultepec Agreements, the Government of El Salvador made a survey on the living conditions of FMLN combatants, of which only 13% lived above the poverty line. Additionally, also in 2012, the Colombian reintegration program created their post-reintegration monitoring system to make a the short-term follow up of the later years after ex-combatants finished their reintegration phase. This provided data to compare ex-combatants during and after the reintegration process, nonetheless both countries were stilling lacking a bridge to compare that data with data on the territories where reintegration takes place. That is where the SDGs can contribute to a new level of reintegration assessment.

The relation between peace and development has been addressed in numerous works such as Hettne (1983, 2010), Collier et al. (2003); Sen (2008); Milante and Oxhorn (2009), and Wolff et al. (2020). Why then, do evaluations of peace and development program outputs not evidence such relation at the indicator level?

With the formulation of the SDGs in 2015, the development agenda assumed a much more ambitious set of goals for 2030. Learning the lessons of its predecessor, the SDGs included indicators that involve individuals but also aimed to measure improvement in contexts where individuals live, connecting development even more with peacebuilding and subsequently, DDR.

Disarmament, for example, has gained more importance within the SDG agenda as shown by Under-Secretary-General and High Representative for Disarmament Affairs Nakamitsu (2018):

Excessive arms accumulation diverts needed resources from development and fuels armed conflict and violence, leading to unnecessary death and suffering, social inequality and environmental degradation. Hence, the failure to establish effective disarmament and arms control systems is devastating to socioeconomic development, peace and security, and human well-being. (Nakamitsu, 2018)

Just as the disarmament phase can have effects on several SDGs as shown by Nakamitsu (2018), in reintegration we can see the largest convergence with SDG indicators. But why is it relevant to analyse that convergence of DDR and SDGs? On the one hand, such analysis can allow DDR impact evaluations to include causal factors that are not program-related and that could help understand why reintegration unfolded in specific ways to different groups of ex-combatants (Torjesen, 2013). On the other hand, in conflict-affected scenarios where peace agreements are still not possible, minor advances in development and living conditions could serve to gain trust and advance on de-escalation. In other words, using development tools with a perspective of reintegration to foster disarmament and demobilization. This commutative property of DDR allows to propose models where the R of reintegration comes before the two Ds (disarmament and demobilization), in what has been called RDD by Dudouet (2011), and Munive and Finn (2015).

It is important to highlight that although reintegration depends significantly on the individual that goes through the program, the context where reintegration takes place, as well as the living conditions, have a key role on the outcome. Additionally, the efforts to improve living conditions of ex-combatants and their families contributes to the achievement of SDGs. Being able to measure such conditions will allow to calculate peace dividends with positive peace indicators (focused on wellbeing) and assess reintegrated ex-combatants as average citizens, which is the ultimate outcome of a successful reintegration within a post-conflict transition (Figure 1).

Figure 1. Figure 1. SDG-DDR indicator convergence Source: Authors with SDG and ARN data.

The 17 goals are divided into 169 targets and a total of 232 indicators. 12 SDGs have indicators that share variables with reintegration programs, for this research we focused on eight. The following SDGs were not considered since they address issues not directly related to or affected by reintegration (12: Responsible consumption and Production, 14: Life below water, 15: Life on land). For SDG 2: Zero Hunger and SDG 10: Reduced Inequalities, their targets were very general, and the current metrics of reintegration programs did not specifically focus on those variables. The ex-combatant Habitat survey provided data for SDGs 7, 9, 13 and 17 which were discarded because the associated variables had already been covered in other goals and were related to housing and access to public services. Others were not as relevant for the study but are still relevant for social inclusion, for example, access to internet.

Indicators for each SDG were selected after a document review of the Colombian policy on the SDGs called CONPES 3918 which was launched in 2018. Additionally, the SDG data was paired with the indicators and information collected by Colombian National Agency for Reincorporation and Normalization (ARN) through the Program database, Family survey, and Habitat survey. Due to COVID restrictions during 2020, the State was unable to gather most of the information it normally acquires through in situ surveys. This implies that for variables at the household level, when applying the expansion factor, the yearly results for 2020 maybe appear slightly different since the year calculations were done based only on the months that the National Administrative Department of Statistics (DANE) was able to capture information.

SDG monitoring has been more robust in the main cities than in rural areas of Colombia, the compared data analysis was done for 23 main cities and in some cases including surrounding smaller municipalities (their metropolitan area, AM for their Spanish acronym). Since the reintegration of the paramilitary forces and the individual reintegration program have taken place mostly in cities, 48% of the whole population in the dataset resides in these 23 metropolitan areas, which validates our selection not only because of data availability but also because of concentration of ex-combatants.

For the purpose of this research the SDG indicators have been grouped in three main categories which are more connected to reintegration: 1) Living conditions (encompasses indicators from SDGs 3, 6, 7 and 11), 2) generation of income (encompasses indicators from SDGs 4, 5, and 8), and 3) security (encompasses indicators from SDGs 16 and 5). This division reinforces the premise that there is a clear fit between reintegration and development components and subsequently in their indicators too. Assessing individual performance in wider entourage (municipality) also recalls what was said before that despite the outcome of reintegration depends significantly on the individual, the context where reintegration takes place (with its challenges and opportunities), as well as the living conditions, have a key role in the outcome.

Colombia has demobilized ex-combatants for many years and has undergone three DDR initiatives in the last two decades. Two collective programs, the first one resulted from agreements between the government and the paramilitary forces between 2003 and 2006 and the second one, the peace agreement with FARC-EP in 2016. Thirdly, an individual DDR program created for combatants who defected illegal armed groups without any peace agreements.

For this research we excluded the FARC-EP reincorporation process and focused on reintegration data. This includes the collective process of the paramilitary forces and minor collective demobilization of FARC-EP and ELN, as well as the individual reintegration program for combatants who defected active illegal armed groups. By December 31st, 2020, there was an accumulate of 54,174 former combatants accredited for reintegration (79.46% of the total universe of ex-combatants in ARN) registered in the ARN’s database. Since demobilization continues within the Colombian armed conflict, the accumulated numbers continue to increase with time. 48% of the 54,174 lived in the main 23 cities and metropolitan areas.

As table 1 shows, 2.12% never entered the reintegration process, therefore, were not included in this research. Between 4% and 5% are absent from the process (which means they have not shown up in at least 3 months). Those ex-combatants were included if there was information from them in the system within the time frame analysed (during that period they would have appeared as in process).

The same inclusion criteria apply for the ex-combatants who are out of the process (which ranges from 35% to almost 38%), ex-combatants were out of the process in cases of recidivism, other faults within the reintegration process or prolonged absence). In all those cases we kept the information gathered within the timeframe regardless of the fact they might not have data for all the years of the study. Culminated ex-combatants are those who finished the reintegration program successfully, and In process is the status for the population still attending activities of the reintegration process.

The information for the population assisting to the reintegration process, those who have culminated the process, and the average population in prioritized cities, was estimated using the data from the information systems in ARN, the Great Integrated Survey of Homes (GEIH for its Spanish acronym) collected by DANE, and the data from the Statistical, Delinquent, Misdemeanour, and Operational Information System of the National Police - SIEDCO.

Table 1: Table 1: Status of accredited ex-combatants within the reintegration process Source: ARN. Yearly data cut was December 31st of each year.

It is important to highlight that the expected duration of the reintegration program for an ex-combatant who came with no levels of literacy was of 6.5 years. However, this was not always the case, the duration of the reintegration program proposed in 2003 was from 12 to 18 months. This was changed due to the need of further assistance. Until 2012, there was not a clear timeline for culmination of the reintegration program (this partially explains why some people had more time in the program) and currently persons with special needs have reintegration routes that could last longer than 6.5 years.

Some of the figures in this research divide the population according to their time spent in the program. This is important because the first years of reintegration are critical specially for combatants who desert armed groups; they were usually sentenced for treason and could not go back to their homes or place or origin. Also, during the first years, factors like weak social networks, lack of vocational skills, among others can make them suitable for re-recruitment and recidivism. However, surviving with legality the first years of the reintegration program is not a guarantee of avoiding risk, despite advances in the socio-economic reintegration. To assess the advances along the reintegration program, this research divides the population spectrum in 0-1 years, 2-4 years, 5-6 years, and more than 7 years.

This research measures some of the SDG monitoring indicators for: 1) ex-combatants in the process of reintegration, 2) ex-combatants who completed the process, and 3) general population of the main 23 cities and metropolitan areas (AM).

Having the average citizen as a point of reference for reintegration must be analysed with certain considerations. Firstly, this research compares the results at the municipality level for 23 main cities that despite being regional capitals, have a significant gap among them. This has a direct effect in the cost of life, possibilities to access basic utilities, health coverage and public order conditions. The average results in some of the most lagging cities might not be even considerable as suitable conditions neither for average population nor for ex-combatants.

Another point that is important to consider is that no DDR or peacebuilding strategy intends to replace the State functions and therefore, the program relies almost entirely on public institutions to provide services on education, vocational training, health among others (which are also used by average citizens). The reintegration program also has a limitation regarding the expected outcomes, for example, although much effort is focused on providing vocational skills and create agreements with the private and public sector to foster job market inclusion, a reintegration program is not a job agency, nor the obligation of finding jobs for ex-combatants.

Finally, the selection of the population could also have effects in the research since most of the ex-combatants come from low-education and poverty backgrounds, often from rural areas. Nonetheless, due to the armed conflict, similar population has been migrating to the main cities for decades, which validates the research’s objective of comparing ex-combatants with average citizens.

Access to health, clean water and sanitation, and having vital space are fundamental elements of adequate living conditions. Changes in the living conditions are also part of the biggest differences regarding quality of life of war times and the passage to civilian life. As has been said before, no combatant would willingly give up their weapon and accept to go back and life in poorer conditions than before or than their time in the armed group. It would be expected that ex-combatants are still below average population regarding their living conditions, however it is not clear how could it be perceived if ex-combatant would have a higher mean that average population in certain components. Could that even become detrimental for their social reintegration? After all, having an aftermath where former perpetrators have better quality of living than average population could be problematic with other war-affected populations like victims, who could feel relegated.

One of the main focus areas of the Colombian reintegration process in economic reintegration, which can be understood as providing the skills, formation to enter the job market or become entrepreneurs and be able to generate income within legality. Economic reintegration can be one of the most challenging components of reintegration and whose failure is commonly related to a general failure of reintegration and even as a cause of recidivism. In the Colombian reintegration program, besides the guidance for people who want to pursue entrepreneurship or look for a job, there is a particular emphasis on accessing both formal education and vocational training.

In post-conflict transitions, when it comes to security, the focus is given to the risk of criminal recidivism or the return to armed confrontation. However as seen in Zapata (2017) highlights ex-combatants identify many threats to their safety after they demobilize. In Colombia, since DDR is done in the midst of armed confrontation, rogue armed groups, other rebel groups and organized crime structures see ex-combatants as potential recruits or threats. This increases their risk of victimisation, especially in the first years after demobilizing but the risk remains through time just with less intensity.

More specifically, the homicide rate in ex-combatants is particularly higher than the rate for average population, as said before, especially in the first years but also beyond the reintegration program. As the program advances the concentration of homicides is bigger in the culminated population rather than in the one still in the process.