Ideas to Action:

Independent research for global prosperity

As of December 2017, there were over 68.5 million forcibly displaced people in the world, including about 40 million Internally Displaced Persons (IDPs) displaced by conflict.[1] Millions more were displaced internally by other drivers, including disasters, economic instability, and development projects such as infrastructure construction.[2]

IDPs face severe economic challenges as a result of their displacement, with harmful impacts on consumption, health, education, security, housing, labor conditions, and social outcomes.[3] They face these challenges for long periods of time: IDPs often spend many years or even decades displaced.[4] And for displaced women and girls—who face unique challenges ranging from legal restrictions on owning  property to larger wage reductions following displacement—the economic challenges can be even greater.[5] Furthermore, IDPs tend to be disproportionately located in low- and middle-income countries (LMICs): over 99 percent of the world’s IDPs displaced by conflict are in LMICs. Within these countries, populations in more marginalized areas are often more severely affected by displacement.[6] Thus, those who are displaced tend to face greater economic difficulties to begin with and displacement only compounds these difficulties.

In response to these challenges and in consideration of the Sustainable Development Goals’ commitment to leave no one behind, there is a growing recognition of the need to support forcibly displaced people in LMICs in overcoming these economic difficulties.[7] In particular, there is an emerging acceptance that, in contrast to camp-based models of support, IDPs and refugees should be allowed to seek self-reliance through local economic integration (i.e., through improved outcomes in the labor market in terms of employment and incomes). Likewise, there has been an increasing number of programs designed to improve their access to labor markets and economic outcomes in places of destination.[8] However, most of the focus to date has been on refugees rather than IDPs. Moving forward, more should be done to support IDPs as well. There are many more IDPs in the world, and although as citizens they face fewer legal barriers to work, they nevertheless face serious economic challenges. Furthermore, with sound policies and support systems in place, greater economic integration can bring benefits not only to IDPs, but also to host communities, which can benefit from IDPs’ economic contributions.

Understanding the extent to which IDPs are currently concentrated in urban areas is an important step towards determining how best to implement programs and policies that enable IDPs to achieve self-reliance. To this end, we analyse data on the existing known locations of conflict-displaced IDPs in all LMICs and visualize their locations in an interactive map. The data, which can be accessed online, cover 17 countries and over 9 million conflict-displaced IDPs.[i] The sample is not representative, so it does not allow us to estimate the total number of urban IDPs in the world, but it does allow us to create a lower bound for the number of urban IDPs and highlight the extent to which IDPs live in urban areas. To our knowledge, this is the most comprehensive attempt to date to determine urban rates among IDPs. This work builds on our previous paper, Are Refugees Located Near Urban Job Opportunities?, where we analysed and mapped the locations of refugees in 31 LMICs.[9]

We find that millions of IDPs are located in urban areas and hundreds of thousands are located in major urban areas.[ii] Specifically, as table 1 shows, we find that about 4.4 million conflict-displaced IDPs are in urban areas, and nearly 1.5 million of them are in major urban areas with populations over 300,000. We also find that these urban populations are dispersed across various countries. Ten countries have at least 50,000 IDPs in urban areas and 10 countries have at least 10,000 in major cities. The data also suggest that about half of IDPs are female and nearly half are of working age.

Furthermore, some countries have very large urban populations: three—Afghanistan, Nigeria, and Iraq—each have over 500,000 IDPs in urban areas and at least 100,000 in major urban areas. It is also common for at least half of the IDP population in a given country to be urban. On the other hand, the vast majority of IDP populations for some countries, such as Niger and Chad, are in rural areas. Thus, there is a great deal of variation in urban-rural composition across countries that may in part reflect a country’s overall rate of urbanization. In some cases, however, IDP populations are disproportionately rural compared to national populations, suggesting a potential opportunity to incentivize urbanization in these contexts.

The analysis also highlights the paucity of data on the locations of IDPs within countries. As table 1 shows, there are only about 9.3 million IDPs with location data that allow for urban analysis (i.e., that allow us to determine whether they are in urban or rural locations)—and there were roughly 40 million conflict-displaced IDPs in the world as of December 2017.[10] Furthermore, these 9.3 million IDPs are from only 17 countries, out of a total of 50 with at least 1,000 IDPs.

Table 1. Total numbers of IDPs in urban areas based on location data available for 9.3 million IDPs in 17 countries

  IDPs with data for urban analysis IDPs in any urban areas[iii] IDPs in urban clusters[iv] IDPs in urban centers[v] IDPs in major urban areas[vi] IDPs in largest urban areas[vii]
Total number 9,273,931 4,387,834 4,190,937 2,593,674 1,438,992 262,724
Working-age[viii] 3,969,046 1,956,890 1,870,183 1,157,763 654,147 118,786
Working-age females 2,045,714 1,008,614 963,924 596,731 337,159 61,224

Our findings have several key policy implications for stakeholders working to help IDPs achieve self-reliance.

First, the large number of IDPs in urban areas indicates that it may be important to shift current approaches to better reflects this reality and enable them to achieve self-reliance. Specifically, donors and NGOs could consider increasing programs that help IDPs thrive in labor markets and/or help host municipalities and communities adjust to growing populations. In light of the large proportion of female IDPs in urban areas, these programs should focus in part on supporting women’s economic integration. Donors and NGOs can also engage governments about the benefits of lowering legal and policy barriers to labor market access (such as documentation requirements or IDP-specific procedures for obtaining legal residency), and the private sector can be mobilized to engage IDPs through hiring, supply chains, and impact investing.[11]

Second, because there are also many rural IDPs, it may be necessary for governments and stakeholders working on improving livelihoods and self-reliance to increase their focus on creating sustainable growth opportunities in rural areas. This could involve, for example, new investments that leverage growing populations in and around camps and settlements. In addition, if there is a skills mismatch between rural IDPs and job opportunities, subsidizing or incentivizing some IDPs’ voluntary relocation to urban areas could be considered. To support this transition, donors could assist governments in implementing urban planning policies. There are often political and policy constraints to relocation, but, where feasible and done effectively, relocation can benefit both hosts and IDPs, as IDPs can bring skills that complement hosts in the labor force and boost economic productivity.

Third, it is clear that more data is necessary to make strategic decisions regarding these possible policy approaches. Whereas in some countries there is enough to data to understand the general urban-rural makeup of their IDP populations along with their general locations, in others, their locations are largely unknown. In the latter situations, it is difficult to make strategic decisions about how to allocate aid, design and focus programming, or create policies that most effectively support IDPs in achieving self-reliance. Furthermore, there is little data on the skills profiles of urban and rural IDPs. If available, this information could be used to understand the extent to which skills mismatches exist. For example, it could be used to understand if rural IDPs would be better able to economically integrate in urban areas, or if urban IDPs needed greater support. These findings, for example, could then inform potential voluntary relocation schemes or vocational trainings. However, due to security, privacy, and cost concerns, it must be noted that it would not be feasible, or even desirable, to collect such data in all situations. Data collection should be driven by the needs in a given situation, pursued as a collaborative process among relevant stakeholders to ensure that it will be used effectively, and undertaken only after carefully considering the privacy and security concerns of IDPs.

The interactive map, below, allows one to explore the findings of our location analysis. It depicts the known locations of IDPs relative to various types of urban areas, demographic information and reasons for displacement for each IDP location, and the estimated amount of missing data in each country. The following sections of the paper give important context to this information and explain the methodology.

Where are the World's Internally Displaced People?

Map instructions: To toggle between site-specific data, dispersed data, and missing data, click on the buttons in the box on the right. Click on IDP location bubbles to access information about each location. Hover the mouse over major and largest urban areas to access information about them. Drag the screen to move the map. Scroll or click the buttons in the top-left to zoom. Click the buttons in the bottom-left to access full screen. On some screens, it may be necessary to scroll the box on the right to see all information.

Map notes: The “Missing” data depict the gap between the estimated number of conflict-displaced IDPs in each country and the number of IDPs with within-country location data for that country. Missing data are only depicted for countries with at least 1,000 IDPs according to IDMC. “Dispersed” data depict IDPs that are dispersed somewhere within the administrative area in which a given bubble is located. “Site-specific” data correspond to specific towns, cities, or areas within cities. Major and largest urban areas are only visualized in countries with within-country IDP location data. Urban centers and clusters are not perfectly represented because the borders had to be simplified for the interactive map; compare them to figure 9 in Appendix E, in which they are perfectly represented. The boundaries and names used on this map do not imply the expression of any opinion or acceptance by the authors. For any questions, comments, or feedback related to the interactive map, please contact jgraham@cgdev.org.

 


[i] The dataset can be accessed here: https://www.cgdev.org/sites/default/files/idp_locations_data.zip. We focus specifically on conflict-displaced IDPs—which includes displacement from political, communal, and criminal violence—mainly because displacement from conflict tends to be especially protracted, such that the need for improving economic integration for conflict-displaced IDPs at their place of destination may be greatest.

Crawford, Cosgrave, Haysom, and Walicki, Protracted displacement: uncertain paths to self-reliance in exile.

[ii] Data sources for analysis include DTM, UNHCR, JRC and the EU, and UNDESA. A detailed discussion of the data is included in the Data and Methodology section and Appendix A.

[iii] Includes urban clusters, urban centers, major urban areas, largest areas, and locations given an “urban” classification by data collectors. See the Data and Methodology sections for more detail on urban classifications.

[iv] Areas with a density of at least 300 inhabitants per km2 and a minimum population of 5,000 inhabitants.

[v] Areas with a density of at least 1,500 inhabitants per km2 or a density of built-up greater than 50 percent, and a minimum of 50,000 inhabitants.

[vi] Cities with at least 300,000 people.

[vii] Includes the single largest city for each country.

[viii] As explained in Appendix C, age- and gender-disaggregated data are not available for all IDPs. Where necessary, national averages were applied.



[1] “Figures at a Glance,” UNHCR, accessed March 15, 2019, https://www.unhcr.org/figures-at-a-glance.html.

[2] Bina Desai, Justin Ginnetti, Schadi Semnani, and Vicente Anzellini, GRID 2018: Global report on internal displacement (Geneva, Switzerland: IDMC, 2018).

[3] Christelle Cazabat, Multidimensional impacts of Internal displacement (Geneva, Switzerland: IDMC, 2018).

[4] Nicholas Crawford, John Cosgrave, Simone Haysom, and Nadine Walicki, Protracted displacement: uncertain paths to self-reliance in exile (London, U.K.: Humanitarian Policy Group, 2015).

[5] Cazabat, Christelle, Sex matters: A gender perspective on internal displacement. (Geneva, Switzerland: IDMC, 2010).

[6] Bennett, Bilak, Bullock, Cakaj, Clarey, Desai, Ginnetti, Maus de Rolley, McClusky, Monaghan, O’Callaghan, Osborn, Lizcano Rodriguez, Rushing, Tyler, and Yonetani, GRID 2017; Desai, Ginnetti, Semnani, and Anzellini, GRID 2018.

[7] Brookings-LSE Project on Internal Displacement, IDPs in protracted displacement: Is local integration a solution? (Washington, D.C.: Brookings, 2013); Nadine Walicki, Elizabeth Eyster, and Martina Caterina, “The GP20 Plan of Action: a rallying call to stakeholders.” Forced Migration Review 59 (2018).

[8] Cindy Huang, Sarah Charles, Lauren Post, and Kate Gough, Tackling the Realities of Protracted Displacement: Case Studies on What’s Working and Where We Can Do Better (Washington, D.C.: CGD, 2018); Karen Jacobsen and Susan Fratzke, Building Livelihood Opportunities for Refugee Populations: Lessons from Past Practice (Washington, D.C.: MPI, 2016). 

[10] “Global Internal Displacement Database,” IDMC, accessed January 31, 2019, http://www.internal-displacement.org/database/displacement-data

We are grateful to Vicente Anzellini, Beth Ferris, Thomas Ginn, Juliane Klatt, Margharita Lundkvist-Houndoumadi, Susan Martin, Melissa Weihmayer, and Wilhelmina Welsch for their helpful feedback and suggestions. All errors remain our own.

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