DATA OPTIONS FOR ASSESSING GENDER DIMENSIONS OF FORCED DISPLACEMENT A BACKGROUND NOTE JUNE 2021 ACKNOWLEDGMENTS THIS BACKGROUND NOTE WAS PREPARED BASED ON A DESK REVIEW COM- PLETED IN JUNE 2020 BY TILMAN BRÜCK AND WOLFGANG STOJETZ OF THE INTERNATIONAL SECURITY AND DEVELOPMENT CENTER IN BERLIN, GERMA- NY. IT WAS PRODUCED UNDER THE WORLD BANK’S GENDER DIMENSIONS OF FORCED DISPLACEMENT RESEARCH PROGRAM LED BY LUCIA HANMER AND DIANA J. ARANGO, GENDER UNIT, WORLD BANK GROUP. TILMAN BRÜCK AND WOLFGANG STOJETZ Brück, T. and Stojetz, W. (2021).Data Options for Assess- The authors would like to thank Alemayehu A. Ambel, Kathleen ing Gender Dimensions of Forced Displacement: A Back- Beegle, Jeni Klugman and Alessandro Pellandra for helpful com- ground Note. Washington, D.C..:World Bank ments and suggestions. The Gender Dimensions of Forced Displace- ment (GDFD) research is part of the program “Building the Evidence on Protracted Forced Displacement: A Multi-Stakeholder Partner- ship’’. The program is funded by UK aid from the United Kingdom’s Foreign, Commonwealth and Development Office (FCDO), it is man- aged by the World Bank Group (WBG) and was established in part- nership with the United Nations High Commissioner for Refugees (UNHCR). The scope of the program is to expand the global knowl- edge on forced displacement by funding quality research and dis- seminating results for the use of practitioners and policy makers. We further thank FCDO for additional funding support through its Knowledge for Change (KCP) program. The Gender Dimensions of Forced Displacement (GDFD) research does not necessarily reflect the views of FCDO, the WBG or UNHCR. For more information about the GDFD research program, please contact Lucia Hanmer (lhanmer@worldbank.org) and Diana J. Arango (darango@worldbank.org) 4 Rigorous evidence on the causes, This note provides a summary of existing 5 characteristics and consequences of data that are of potential use in analysis forced displacement remains scarce. gender and displacement, as a tool for THE WORLD BANK GROUP GENDER DIMENSIONS OF FORCED DISPLACEMENT This is primarily due to a lack of researchers who wish to fill the evidence suitable, high-quality micro-level data. gaps. The note is based on an extensive Moreover, while it is increasingly rec- review of a large variety of data sources ognized that many outcomes of forced and was organized around four specif- displacement, such as the shock expe- ic topics the project intends to study: rienced, coping strategies used and the Gender-based violence, multi-dimension- outcomes vary strongly according to al poverty, economic opportunities and gender there is little evidence on the child development (Fig. 1). gender dimensions of force displace- ment. 1 However, there has been import- ant progress in collecting high-quality micro-level data in fragile and con- flict-affected situations over the past decade, including in contexts of forced displacement. 2 FIGURE 1 OVERVIEW OF PRELIMINARY STUDY TOPICS IN THE GDFD PROJECT INTRODUCTION GENDERED FORCED GENDERED GENDERED STUDY DISPLACEMENT MECHANISMS OUTCOMES TOPICS GENDER-BASED VIOLENCE TOPIC 1 FORCED MULTI-DIMENSIONAL POVERTY TOPIC 2 DISPLACEMENT ECONOMIC OPPORTUNITIES TOPIC 3 CHILD DEVELOPMENT TOPIC 4 Globally, around Forced displacement has profound impacts on the lives and livelihoods 70 million people of affected populations, which creates have fled their enormous demands on government and other stakeholders supporting homes as a result their needs. of conflicts. Yet, designing and implementing policies that are effective, ethical, and 1 Forcibly Displaced: Toward a Development Approach Supporting Refugees, the Internally Displaced,  (UNHCR 2018) and Their Hosts. Washington, DC: World Bank (2017). Rohwerder, B. (2016). Women and girls in equitable has been severely limited forced and protracted displacement (GSDRC Helpdesk Research Report 1364). Birmingham, UK: due to the lack of empirical research. GSDRC, University of Birmingham. Buvinic, M. et al. (2013). Violent Conflict and Gender Inequality: An Overview. The World Bank Research Observer, 28(1), 110-138. 2  Verwimp, P. et al. (2019). The Microeconomics of Violent Conflict, Journal of Development Econom- ics, 141, 102297. 6 Growing the evidence base about non-displaced persons from same loca- For example, female household head- Against this background, examples of 7 gender and forced displacement tion of origin, or between refugee and ship has often been used as an indica- relevant measures include, but are not requires data sources that meet host populations. tor of poverty. Yet, a growing body of limited to: THE WORLD BANK GROUP GENDER DIMENSIONS OF FORCED DISPLACEMENT the following criteria. Examples of relevant outcome scholarship shows that the conventional  ex and marital status of the • S measures include: approach of using self-reported female household head, de jure and de facto INFORMATION AT THE household headship; headship as the grouping category can ndividual experiences of intimate partner • I severely underestimate actual poverty MICRO LEVEL violence and other forms of gender-based  easures of women’s voice, agency and • M violence (e.g. physical violence by partners in households headed by females. 3 In social inclusion (e.g. intra-household and sexual violence by non-partners) bargaining power and civic participation); First, data must be based on informa- addition, such simple, binary categori- tion gathered at the individual or house-  ousehold-level welfare e.g. income • H zations obscure an enormous degree  ependency ratios and household • D hold level. Insights into households’ and consumption and expenditure measure, of heterogeneity within and between composition, including elderly and disabled; individuals’ welfare and behavior allows access to humanitarian assistance and households grouped into male- and  elevant norms and attitudes e.g. on • R social protection investigation of the mechanisms inter- female headed4 and, specifically, welfare women and girl’s mobility outside the linking forced displacement and gender  ousehold access to water, sanitation • H status at the individual level. 5 home, women’s employment, girl’s access and basic services to higher education, child marriage, inequality. Ideally, the micro-level infor- More recent work has developed more gender-based-violence; mation is sex- and age-disaggregated  ale and female labor force participation • M nuanced approaches, for example  ale and female earnings, hours worked • M and geo- and time-coded with high pre- (e.g. self-employment and informal labor, entrepreneurship, farming) disaggregating households based on and conditions of employment; and cision, to facilitate matching of different measures of household composition, 6 data sources and a gender analysis. • S  ex-disaggregated data on child develop-  ex-disaggregated data on access to • S devising measures of individual poverty assets and capital (e.g. land and finance). ment outcomes (e.g. learning and nutrition) within households7, 8 and building INFORMATION ON FORCED metrics based on the access to employ- DISPLACEMENT RELEVANT INFORMATION ON THE ment or economic opportunities of male Second, the data source must contain DRIVERS AND CORRELATES OF and female labor force participants or information on forced displacement. GENDER-BASED INEQUALITIES, their earnings. 9 This information includes information BARRIERS AND VULNERABILITIES on forced displacement characteristics, Fourth, the data must contain infor- such as displacement status indicators, mation that enables analysis of gender location (camp or non-camp), insights dimensions in the outcomes of interest into factors that led people to flee, vari- and in the factors shaping these out- ables that capture experiences during 3  Rogan, M. (2013). Alternative Definitions of Headship and the ‘Feminisation’ of Income Poverty in comes. In other words, gendered out- displacement, or individual’s aspirations Post-Apartheid South Africa. Journal of Development Studies, http://dx.doi.org/10.1080/00220388 comes for at least one of the four study .2013.812199 and future plans. topics, as well as measures of underly- 4  Chant, S. (2006). Rethinking the ‘feminization of poverty‘ in relation to aggregate gender indices. ing gender gaps, inequalities, barriers Journal of Human Development, 7(2), 201–220. RELEVANT INFORMATION ON and vulnerabilities. 5  Munoz Boudet et al. (2018). Gender Differences in Poverty and Household Composition through the OUTCOMES OF INTEREST In the past, a dominant approach to Life-cycle. World Bank Policy Research Paper 8360. World Bank Group: Washington, DC. 6  Hanmer, L. et al. (2020). How does poverty differ among refugees? Taking a gen- Third, the data source must provide in- these domains has been to group der lens to the data on Syrian refugees in Jordan, Middle East Development Journal, DOI: sights into at least one of the four study households by the sex of their head, 10.1080/17938120.2020.1753995. topics: Gender-based violence, multi-di- including distinctions of the de jure 7  Deere, C. D. et al. (2010). Poverty, Headship, and Gender Inequality in Asset Ownership in Latin mensional poverty, economic opportu- from de facto head of the household. America. Working Paper 296, Gender, Development, and Globalization Program, Center for Gender in nities, and child development (see Fig. Global Context, Michigan State University. 1). The data must facilitate meaningful 8  Poverty and Shared Prosperity 2018: Piecing Together the Poverty Puzzle. Overview booklet. World comparisons of outcomes of interest, Bank, Washington, DC. such as between displaced persons and 9  Grown and Valodia (2010). Taxation and Gender Equity: A comparative analysis of direct and indirect taxes in developing and developed countries. Routledge: London and New York. 8 Most data sources that are of potential 9 interest to study the gender dimensions THE WORLD BANK GROUP GENDER DIMENSIONS OF FORCED DISPLACEMENT of forced displacement are part of larger systematic efforts. Main sources: ONE FORCED DISPLACEMENT DATA PORTALS TWO DATA PORTALS LARGE-SCALE HOUSEHOLD SURVEYS DATA THREE ADMINISTRATIVE DATA LANDSCAPE ADDITIONAL SOURCES: FOUR OTHER DATA PORTALS FIVE HIDDEN GEMS SUCH AS ONE-OFF SURVEYS 10 FIGURE 2 OVERVIEW OF DATA SOURCES THE WORLD BANK GROUP SOURCE 1 SOURCE 2 FORCED DISPLACEMENT DATA PORTALS LARGE-SCALE HOUSEHOLD SURVEYS FORCED SOURCE 3 ADMINISTRATIVE DATA SOURCE 4 OTHER DATA PORTALS DISPLACEMENT DATA PORTALS Data on forced Among these, we identify and briefly discuss three data sources that hold displacement is particularly large potential: increasingly • The Migration Data Portal (link) becoming available  he Global Internal Displacement • T Database (link) through online • The Humanitarian Data Exchange (link) data portals. 12 The Migration Data Portal (MDP) is host- and population mobility. It uses a va- vide an example of from the innovative statistics are based on micro-level data, 13 ed by the International Organization for riety of tools to collect monthly data Missing Children program on child traf- the micro-level data are not provided – Migration’s Global Migration Data Anal- at the group, location, household and ficking. 14 Such data can be particularly and hence do not allow for micro-level THE WORLD BANK GROUP GENDER DIMENSIONS OF FORCED DISPLACEMENT ysis Center (IOM-GMDAC). It provides individual levels. As well as monitoring useful for key policies and programs at analyses of the gender dimensions of a platform that gives policy makers, movements of displaced populations, national and international levels. Yet, forced displacement. researchers, journalists and the general the DTM provides information on their the key limitation is that even when public access migration statistics and needs (such as food, shelter, WASH and data on migrants, pulling together data security) and their intentions in regard from a number of organizations. to return, community perceptions, dis- FIGURE 3 EXAMPLE OF MDP DATA DETECTED VICTIMS OF HUMAN TRAFFICKING The wide-ranging data accessible placement solutions and other thematic BY SEX OVER TIME issues. The DTM Field Companion 12 pro- through the portal cover forcibly vides sectoral questions for gathering 100 displaced populations, mostly at the data from key informants that are used aggregate country level, and with at 90 for location assessments. Sectors cov- least some sex-disaggregated data. ered include: child protection, languag- While the portal notes that in various of 80 es, education, GBV, Health, Protection, its sources “sex-disaggregated data are Settlements and Shelters and WASH. 70 not always collected”, others do, and in For example, the GBV Field Compan- those cases male and female adults ion provides a template for gathering 60 and children the portal presents information on the availability of GBV 50 separate analyses. 10 services and their accessibility as well as The available information is grouped proxy indicators for GBV risk in camps/ 40 into five themes:11 1) Immigration and camp-like settings. 13 30 emigration statistics (e.g. international As noted on its website, the main pur- migration flows and migrant stocks); 20 pose of the MDP is to provide “the 2) Types of immigration (e.g. different bigger picture” and provide and visual- 10 forms of forced displacement and child ize migration data at the national level. migration); 3) Migration and vulnerabili- The data come from a range of sources, 0 ty (e.g. women and child trafficking); 4) 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 are not always sex-disaggregated, only Migration and development (e.g. unem- some are based on micro-data, provide ployment and remittances statistics); limited information about conditions GIRLS WOMEN BOYS MEN and 5) Migration policy (e.g. refugee facing displaced persons (including and family reunification policy). gendered constraints and barriers), and Source: Migration Data Portal (MDP) The MDP also provides access to IOM’s are typically lacking such details as age Displacement Tracking Matrix (DTM) and marital status. Some important data. The DTM was designed to be able micro-data presented on the portal are to track and monitor displacement sex-disaggregated. In Figure 3, we pro- 10 https://migrationdataportal.org/themes/gender-and-migration. 11 https://migrationdataportal.org/themes. 14  The child trafficking data source is the Counter Trafficking Data Collaborative (CTDC), which itself 12 https://displacement.iom.int/dtm-partners-toolkit/field-companion-pdf. combines various data sources, including individual-level data. For further information see: 13 h  ttps://displacement.iom.int/system/tdf/tools/GBV%20and%20DTM%20data%20in%20Short. https://www.ctdatacollaborative.org and https://www.ctdatacollaborative.org/sites/default/files/ docx?file=1&type=node&id=4878&force=. CTDC%20codebook%20v6_0.pdf. 14 The Global Internal Displacement Da- The portal has three “sub-portals”. First, Second, the Global Displacement Risk a crisis and their immediate needs. The 15 tabase (GIDD) portal is an online plat- the Displacement Data tab, which is the Model portal, which takes a “prospec- portal spans many crises and organiza- form of the International Displacement main tool for accessing and viewing a tive point of view” and is specifically tions and provides access to more than THE WORLD BANK GROUP GENDER DIMENSIONS OF FORCED DISPLACEMENT Monitoring Centre (IDMC). Its purpose is wide range of displacement data at na- focused on data-based modelling of 10,000 datasets, based on a huge vari- similar to that of the MDP, pulling togeth- tional and global levels. As an example, displacement risk due to disasters. ety of different surveys and methodolo- er an impressive range of displacement Fig. 4 presents GIDD displacement fig- Third, the innovative Displacement Data gies. Specifically, this includes extensive data that can be explored and visualized ures for the 15 countries with the highest Exploration Tool, which offers visualiza- and consistently formatted data from a via an innovative and interactive inter- numbers of new displacements due to tions of how country-level displacement variety of organizations reaching IDPs face. This way, it provides quantitative conflict and violence in 2018. indicators vary over time and across and and refugees from across the world. information on displacement to practi- over different levels of various indicators Most of the data is publicly available tioners, researchers, journalists and the from the World Bank’s open data cata- and provides information on an aggre- general public. logue across countries. The latter in- gate level. cludes country-level, sex-disaggregated HDX is now including microdata and data on demography, education, health, FIGURE 4 EXAMPLE OF GIDD DATA—TOTAL NUMBERS OF DISPLACED PERSONS multi-dimensional poverty and gen- plans to add more in the future. Some datasets contain micro-level information BY COUNTRY OF RESIDENCE der-based discrimination and violence, on gender-based violence, multi-dimen- among many others, and GIDD plans to sional poverty, economic opportunities include “more data related to develop- COUNTRY TOTAL NUMBER OF IDPS NEW DISPLACEMENTS NEW DISPLACEMENTS ment and humanitarian assistance and and child development, and are either (CONFLICT AND VIOLENCE (CONFLICT AND VIOLENCE) (DISASTERS) publicly available or upon request. In more granular data on specific sectors, addition, contextual data are also host- ETHIOPIA 2,137,000 2,895,000 296,000 such as agricultural production and food ed in the exchange platform, including availability”. 15 As for the MDP, however, CONGO DEM. REP. 3,081,000 1,840,000 81,000 on affected people, coordination and the key limitation is that the portal does context, food security and nutrition, ge- SYRIAN ARAB not provide micro-level data, even if an 6,119,000 1,649,000 27,000 ography and infrastructure, health and REPUBLIC indicators are based on them. education, population and socio-econ- SOMALIA 2,648,000 578,000 547,000 The Humanitarian Data Exchange (HDX) omy, damage assessments as well as portal is managed by OCHA’s Centre geospatial data. 16 Figure 5 provides NIGERIA 2,216,000 541,000 613,000 for Humanitarian Data. It is designed for an example of sex-disaggregated mi- CENTRAL AFRICAN 641,000 510,000 9,300 sharing data on individuals affected by cro-level data available on the portal. REPUBLIC CAMEROON 668,000 459,000 - AFGHANISTAN 2,598,000 372,000 435,000 SOUTH SUDAN 1,869,000 321,000 6,600 YEMEN REP. 2,324,000 252,000 18,000 EL SALVADOR - 246,000 4,700 PHILLIPINES 301,000 188,000 3,802,000 INDIA 479,000 169,000 2,675,000 IRAQ 1,962,000 150,000 69,000 INDIA 5,761,000 145,000 67,000 15 http://www.internal-displacement.org/database. Source: Global Internal Displacement Database (GIDD) 16 For example on Syria: https://data.humdata.org/group/syr. 16 FIGURE 5 EXAMPLE OF HDX DATA—MIGRATION FLOWS AT BENTIU PROTECTION 17 OF CIVILIANS (POC) SITE THE WORLD BANK GROUP GENDER DIMENSIONS OF FORCED DISPLACEMENT POPULATION FLOW AT BENTIU POC SITE Bentiu PoC site has witnessed the largest net population flow between July 2017 and March 2018. During the nine months, 31,366 individuals left the site and 7,661 people arrived at the site. AVERAGE MONTHLY ENTRIES: 851 29% 26% 23% 21% LARGE-SCALE HOUSEHOLD AVERAGE MONTHLY EXITS: 3,485 4% 48% 18% SURVEYS Large-scale cross-nationally comparable 29% household surveys provide a wealth of information on individuals around the world. *Percentages may not add up to 100%, as they are rounded to the nearest percent Data source: IOM DTM, Bentiu PoC Site Flow Monitoring, July 2018 Source: Humanitarian Data Exchange (HDX) 18 By “cross-nationally comparable” specific topics. The fourth category be matched with additional information DHS surveys have large sample sizes 19 we mean surveys that largely adhere contains multi-topic household surveys from other data sources, such as of between 5,000 and 30,000 house- to international methodology protocols that are conducted by national statis- spatially and temporally coded holds, which usually are selected in a THE WORLD BANK GROUP GENDER DIMENSIONS OF FORCED DISPLACEMENT and are thus comparable, even if it tics offices to monitor socio-economic conflict event data. If granular enough, multi-stage random sampling process they were not designed to be as such. conditions, often conducted every 3-5 his method can allow to identify dis- conducted about every 5 years. DHS years and nationally representative. placement status and distinguish dis- data have now covered over 90 coun- In this note, we consider five In this very broad category we focus placed respondents from host popula- tries across multiple waves. While some categories of surveys that are most the review on the important and large tion respondents. survey topic choices in questionnaires relevant to understanding the gender sub-category of LSMS surveys. As a fifth are driven by country demands, the dimensions of displacement: It is important to note that for either category, we review JIPS surveys, which survey questionnaires are largely stan- form of identification certain groups  emographic and Health Surveys • D are focused on displacement settings dardized. In addition, the survey process (DHS; link) may be systematically excluded and and usually not nationally representa- protocol and approach to releasing geo- hence the data collected may not be  iolence Against Children Surveys • V tive, but are based on large, random graphic information system (GIS) data representative due to the sampling (VACS; link) samples and similar methodologies are standardized. 17 frames used. For example, large-scale and protocols as the other surveys,  ultiple Indicator Source Surveys • M surveys are often sampled from a All DHS data are publicly available and (MICS; link) which makes them comparable across census frame, which typically exclude provide information on a wide range country settings.  iving Standards and Measurement Study • L temporary settlements of displaced of social, economic, and demographic surveys and other international household We include all surveys that credibly individuals. And even when the whole data, providing a swathe of opportuni- surveys that are “similar in spirit” identify, either directly or indirectly population of interest encompassed by ties for research into questions at the in- (LSMS; link & IHSN; link) whether an individual or a household the sampling frame, certain individuals tersection of gender and displacement. 18  oint IDP Profiling Service surveys • J has been displaced. By direct identifica- or entire households may be structurally Survey topics span all four study themes (JIPS; link) tion, we mean that a survey includes a less likely to be interviewed, for example of particular interest to this project direct question on whether an individual because they moved in the meantime. In (gender-based violence, multi-dimen- Other sources of potential interest or household has been displaced. By such cases, existing limitations need to sional poverty, economic opportunities, not examined here include: indirect identification we mean that dis- be acknowledged and results interpret- child development). • Global Barometer Surveys (link) placement information may be inferred ed accordingly. The DHS has a strong focus on gender • World Value Survey (link) providing an option to answer. There are In the appendices we present a detailed (the so-called “Gender Corner”), 19 which two principal routes for inference. First, • Gallup polls (link) overview of potentially project-rele- offers indicators of gender inequality, some surveys include questions that are vant and suitable datasets for all five women’s empowerment and gender not specifically about forced displace- We briefly review the first five in turn survey types and a large list of specif- norms in a range of domains, such as ment, but one or more answer cate- and discuss how suitable they are for ic variables covering identification of domestic violence, women’s empow- gories are. For example, some surveys analyses into the gender dimensions of displacement status (Appendix 1) and erment, female genital cutting and include a question on the reasons why displacement, with a particular focus on the outcome variables and correlates of child marriage. The questions on norms a household/individual moved to their the aforementioned four study topics: interest (Appendix 2). We also provide include proxies for empowerment, like current place of residence, with an an- gender-based violence, multi-dimen- below some tables for each survey type decision-making in the household. swer option that clearly indicates forced sional poverty, economic opportunities, that lists relevant and suitable datasets displacement. For example, “moved for There are a few instances where dis- and child development. The first three for two selected domains: gender-based security reasons” or “fled due to para- placement data are collected in a DHS. categories of surveys (DHS, VACS and violence and child marriage. military activity”. Second, some surveys MICS) are heavily harmonized surveys collect detailed information on where a that are typically nationally representa- household/individual was born and/or tive and funded largely through a coor- their migration history. In this case, it is 17 See: https://dhsprogram.com/What-We-Do/Methodology.cfm. dinated/centralized program. They are usually not possible to gain information 18  A full list of survey topics can be found here: not general living standards/multi-topic about displacement from the survey https://dhsprogram.com/What-We-Do/Survey-Types/DHS.cfm. surveys but are primarily focused on alone. Rather, the survey data has to 19 See: https://dhsprogram.com/topics/gender-Corner/index.cfm. 20 In Colombia, the last four DHS surveys nomic activity beyond whether individ- The Violence Against Children and VACS datasets are typically made pub- 21 (2000, 2005, 2010 and 2015) allow uals are in paid work – that is, nothing Youth Surveys (VACS) are nationally licly available on the VACS website displacement to be imputed at the on hours, earnings and so on. There is representative household surveys of (see previous footnote), coordinat- THE WORLD BANK GROUP GENDER DIMENSIONS OF FORCED DISPLACEMENT individual level by using variables indi- also no information to allow estimates males and females ages 13 to 24 con- ed through Together for Girls and the cating recent migration and the specific of monetary poverty, although asset ducted by Together for Girls, a pub- respective country governments. The reasons for migration, including violence wealth quintiles can be computed to lic-private partnership. 21 VACS measure datasets are usually cross-sectional and insecurity to due armed group broadly group households. the prevalence, past 12-month incidence and based on individual- and house- violence. Combined with extensive and circumstances surrounding sexu- hold-level interviews. The appendices provide detailed in- information on child health and intimate al, physical and emotional violence in formation on DHS datasets relevant to A standardized core questionnaire has partner violence data, including psycho- childhood, adolescence (before age 18) analyses of the gender dimensions of been used since 2013, which aims to logical, physical, economic, and sexual and young adulthood (before age 24) in forced displacement. To illustrate how establish a “gold standard” in measuring forms, these surveys lend themselves randomly selected samples. The surveys DHS data can be used, Figure 6 lists violence against children, adolescents for analyses of child development and also measure various risk factors, pro- project-relevant and suitable DHS sur- and young adults and ensure compa- gender-based violence in the context of tective factors and consequences veys for analyses of two specific rability with violence measures in other forced displacement. 20 of violence. VACS results are (primarily) domains: gender-based violence and surveys. The standard core question- meant to contribute to national- and One major limitation is that in most DHS child marriage. naire was updated in 2017, leading to global-level monitoring of violence there is no detailed information on eco- a new HIV module and three modules prevalence, prevention and response, for surveys to be implemented in Latin and are published in national reports, FIGURE 6 DHS DATASETS THAT ALLOW TO STUDY GENDER-BASED VIOLENCE used in the development of national America: weapon carrying, migration and community/gang violence. The new AND CHILD MARRIAGE IN THE CONTEXT OF FORCED DISPLACEMENT IN action plans, and guide evidence surveys in Latin America are still ongo- -based programming. 22 CONFLICT-AFFECTED SETTINGS. ing or have been completely recently Figure 7 provides an overview of com- (see Fig. 7). pleted and on-going VACS surveys. GENDER-BASED VIOLENCE Benin (2017-18), Burundi (2016-17), Colombia (2000, 2005, 2010, 2015), Ethiopia (2016), Jordan (2017-18), Kenya (2014), Mali (2018), Nepal (2011, 2016), Nigeria (2018), Pakistan (2012-13, 2017-18), Philippines FIGURE 7 OVERVIEW OF COMPLETED AND ONGOING VACS SURVEYS (2017), Uganda (2016), Tanzania (2015-16) CHILD MARRIAGE Afghanistan (2010), Benin (2017-18), Burundi (2016-17), Colombia (2000, 2005, 2010, 2015), Eritrea (2002), Ethiopia (2016), Indonesia (2017), Jordan (2002, 2017-18), Kenya (2003, 2014), Mali (2018), Nepal (2011, 2016), Nigeria (2018), Pakistan (2012-13, 2017-18), Philippines (2017), Tanzania (2015-16), Turkey (2003, 2008, 2013), Uganda (2016) Source: Violence Against Children and Youth Surveys (VACS) 21 For further information on Together for Girls see here: https://www.togetherforgirls.org. 20  or example. see Calderón, V., Margarita G., and A. M. Ibáñez (2011). “Forced migration, female F labor force participation, and intra-household bargaining: does conflict empower women?.” Docu- 22  VACS reports from all completed surveys can be found here: https://www.togetherforgirls.org/ mento CEDE 2011-28. violence-children-surveys/. 22 VACS datasets include particularly VACS Haiti survey conducted in the FIGURE 9 OVERVIEW OF COUNTRIES WITH AT LEAST ONE COMPLETED 23 detailed information on and correlates aftermath of the Haitian earthquake of gender-based violence and child in 2012, producing extensive data on MICS IN YELLOW THE WORLD BANK GROUP GENDER DIMENSIONS OF FORCED DISPLACEMENT development. Variables include: ed- dynamic of gender-based violence for ucation, health (including physical, both sexes, and delineating between mental, sexual and reproductive health displaced and nondisplaced households outcomes), gender attitudes related to and individuals. violence, perceptions of safety, witness- Appendix 1 provides detailed informa- ing violence, victimization, perpetrating tion on VACS datasets of interest to violence, and seeking and using services analyses of the gender dimensions of after experiencing violence. forced displacement. Figure 8 lists Some VACs make a specific effort to project-relevant and suitable VACS survey internally displaced populations, surveys for analyses of the two specific such as in Colombia, El Salvador, Gua- domains of gender-based violence and temala, and Haiti. As an example, the child marriage. FIGURE 8 VACS DATASETS THAT ALLOW TO STUDY GENDER-BASED VIOLENCE AND CHILD MARRIAGE IN THE CONTEXT OF FORCED DISPLACEMENT IN CONFLICT-AFFECTED SETTINGS Source: Multiple Indicator Source Surveys (MICS) GENDER-BASED VIOLENCE El Salvador (2017), Haiti (2012), Kenya (2010) CHILD MARRIAGE El Salvador (2017), Haiti (2012), Kenya (2010) Core MICS datasets now capture 200 However the MICS coverage of forced distinct indicators, 237 counting those displacement is limited. The Multiple Indicator Source Surveys online portal, from which MICS requiring sex disaggregation separately. (MICS) program by UNICEF have be- reports can be downloaded and where Appendix 1 provides a list of datasets More generally, gender is at the heart of come “the largest source of statistically access to available survey datasets can that may be useful to investigate for MICS, and the datasets include in-depth sound and internationally comparable be requested. 24 these purposes. Figure 10 lists proj- and wide-ranging information on the data on women and children world- ect-relevant and suitable MICS datasets study topics of gender-based violence Similar to DHS surveys, data collec- for analyses of gender-based violence wide”. 23 Since 1995, 336 surveys have and child development. This includes tion in MICS provide standard tools for and child marriage. been completed in 116 countries across modules on early childhood develop- survey planning, sampling and ques- the world (see Fig. 9). MICS are typically ment, child labor, and experiences of and tionnaires, including household, women, large-scale household surveys, with a attitudes to violence against women. men, children aged 0-4, children aged focus on topics that directly affect chil- 5-17. Datasets from the latest round in- dren and women. UNICEF maintains an clude GPS coordinates for households. 23 Webpage: https://mics.unicef.org/about. 24 Webpage: https://mics.unicef.org/surveys. 24 FIGURE 10 MICS DATASETS THAT ALLOW TO STUDY GENDER-BASED VIOLENCE Surveying of contexts of displacement, heavily with local settings, potentially 25 AND CHILD MARRIAGE IN THE CONTEXT OF FORCED DISPLACEMENT IN CON- displaced people and respective “com- limiting comparability across sites, but parable” communities is relatively rare in ensuring contextualization and typical- FLICT-AFFECTED SETTINGS. THE WORLD BANK GROUP GENDER DIMENSIONS OF FORCED DISPLACEMENT LSMS, limiting their potential for the study ly micro-data from both displaced and of gendered drivers or impacts of dis- non-displaced groups are collected. placement. However, questions about ex- GENDER-BASED Zimbabwe (2019) JIPS household surveys often include posure to conflict, violence and displace- VIOLENCE information on all household members’ ment have now been included in at least characteristics (such as age, sex, edu- seven surveys national surveys to date CHILD MARRIAGE Bangladesh (2019), DRC (2017-18), Gambia (2018), Ghana (2018), cation, and occupation) and extensive Lesotho (2018), Pakistan (Punjab; 2017-18), Zimbabwe (2019) (see also Appendix 1), and more surveys household indicators of monetary and are likely to follow suit in the future. For nonmonetary poverty, such as housing/ example the third round of the longitudi- shelter characteristics, the main source nal General Household Survey in Nigeria of income, government support, finan- LSMS is a household survey program Living Standards Survey (LSS) in Ghana, from 2015/16 contains a conflict expo- cial coping mechanisms, and access to managed by the World Bank’s De- and the Integrated Household Survey sure module that captures community and information on health care. velopment Data Group. The program (IHS) in Malawi. and household exposure to conflict and provides technical assistance to na- violence, including information on wit- Countries surveyed to date include LSMS provide comprehensive and nessed events, experiences, perpetrators, tional statistical offices in designing Greece (refugees in Thessaloniki), Hon- sex-disaggregated data on a wide range circumstances, causes and consequences, and implementing large-scale house- duras, Iraq (four surveys), Kosovo, So- of socio-economic domains of interest and specific questions related to displace- hold surveys, to produce high-quality, malia and Sudan. JIPS are increasingly to the gender dimensions of displace- ment. Appendix 1 provides a detailed multi-topic, multi-level data. The surveys being made available via the HDX portal ment, particularly on both monetary and overview of LSMS datasets of potential are generally nationally representative (see Section 2), 28 while access to others nonmonetary dimensions of poverty, relevance for the study of the gender and comparable, with similar core mod- can be requested from JIPS directly. and child nutrition, health and educa- dimensions of forced displacement. ules, and typically use geo-referencing tion. The recent LSMS-ISA sub-program For the two specific domains of gen- and computer-assisted data entry tech- Apart from more “standard” information focus on innovative panel data on multi- der-based violence and child marriage, nologies. To date, more than 100 LSMS on displacement, JIPS surveys often ple topics in agricultural settings, 26 while there are no suitable LSMS surveys. surveys have been produced, which can also capture subjective assessments the LSMS+ focuses on gender inequal- be accessed via the World Bank Micro- like attitudes and future aspirations, ities in collaboration with the World The Joint IDP Profiling Service (JIPS) data Library. 25 As noted above, there e.g. households’ intentions and Bank Gender Group. 27 The latter places is an inter-agency body that provides are many other national multi-topic required conditions to return to the emphasis on intra-household, sex-dis- assistance to governments and de- household surveys that are organized place of origin, and perceptions of aggregated household survey informa- velopment organizations to improve the same way, are similar in spirit, some- safety and security. tion on 1) ownership of and rights to local information on displacement. In times draw on LSMS support, and use selected physical and financial assets, 2) a collaborative process between part- comparable methodologies and proto- The appendices include a list of JIPS work and employment, and 3) entrepre- ner organizations, clear data objec- cols, which are beyond the scope of the datasets that hold potential for neurship, and has so far been collected tives and methodology are established in-depth review. Examples, among many micro-analyses of the gender Malawi, Tanzania, Ethiopia, Cambodia to conduct specialized displacement others, include the Kenya Integrated dimensions of forced displacement. and Nepal. profiling surveys. This process engages Household Budget Survey (KIHBS), the 25 See Section 5 and here: https://microdata.worldbank.org/index.php/home. 26 See: http://surveys.worldbank.org/lsms/programs/integrated-surveys-agriculture-ISA. 27 See: http://surveys.worldbank.org/lsms/programs/lsms-plus. 28 Webpage: https://data.humdata.org/organization/jips. 26 At present none of these datasets are Palestinians. UNRWA household surveys 27 publicly available. Yet, they may be include both more recent waves of ref- released by the agencies concerned for ugees from contemporary conflicts and THE WORLD BANK GROUP GENDER DIMENSIONS OF FORCED DISPLACEMENT specific evaluation or research purpos- from protracted displacement circum- es. We now briefly review each of them. stances, spread across the West Bank, Gaza Strip, Jordan, Lebanon and Syria. GBVIMS was developed by UNFPA, IRC, WHO and the UNHCR to harmo- UNRWA collects extensive data, espe- nize the collection and analysis of GBV cially on people receiving social assis- data obtained through service delivery tance, mainly about poverty, education, in humanitarian settings. The GBVIMS health and healthcare. While no data is Steering Committee has since grown to collected from nondisplaced host com- include UNICEF and IMC. The GBVIMS munities, those in recent and protracted enables humanitarian actors responding displacement conditions can be com- to GBV to safely collect, store and ana- pared at different points of time. lyze GBV incident data obtained by ser- ProGres (Profile Global Registration ADMINISTRATIVE vice providers. The GBVIMS facilitates System) is UNHCR’s global case man- the safe and ethical sharing of reported agement system that is used by its GBV incident data among stakeholders different work units to facilitate pro- in a setting with the aim of improving tection of persons of concern to the DATA FROM coordination and programming. The GB- organization, and includes a database of VIMS toolkit has been used in over 20 refugees, asylum seekers and returnees countries for more than a decade. registered by UNHCR. The registration The GBVIMS tool collects information on process assigns individuals a unique INTERNATIONAL incidences of GBV reported to service number that serves as a reference for providers so the data are not represen- recording data in all subsequent activi- tative of GBV rates across the commu- ties, including decisions on refugee sta- nities as many GBV survivors do not tus and right of return or resettlement ORGANIZATIONS seek help. While not publicly available, in a third country, and the delivery and GBVIMS data holds potential for the tracking of protection and assistance analysis of reported cases of GBV in the services, as applicable. ProGres collects context of crises and displacement. information on all individual members of a household, including age, sex, educa- UNRWA is the UN agency responsible tion, relationship to the household head, for the wellbeing and human develop- and vulnerability status. ment of the over 5 million displaced The administrative data from  ender Based Violence Information • G Management System (GBVIMS) international organizations  nited Nations Relief and Works • U that appear to be most Agency for Palestine Refugees in the Near East (UNRWA) relevant to gender and  NHCR Profile Global Registration • U forced displacement are: System (ProGres), including Home Visits 28 Home Visits are an on-going method 29 for data collection used by the UNHCR Jordan Cash Based Interventions unit THE WORLD BANK GROUP GENDER DIMENSIONS OF FORCED DISPLACEMENT to determine vulnerability in six oper- ational sectors. The data is gathered from refugees through periodic home visits and refugees requesting UNHCR multi-purpose cash assistance. They are thus a non-randomized sample of ProGres and their use could introduce bias for statistical analysis In addition to demographic information about the household the collect data on food security, health, specific needs of indi- vidual household member (e.g. related to disability, children at risk, severe OTHER DATA medical conditions) housing conditions, expenditure, income, documentation, and assistance received. For instance, the Syrian Home Visits PORTALS dataset in 2017-18 contains information for at least a total of 54,408 Syrian refugee households comprising 208,014 individuals. These data can provide im- portant insights, for example Hanmer et al (2020) analyze how gender inequality impacts household poverty of Syrian refugees in Jordan. 29 Beyond the three basic sources, Other examples, not discussed other data collected as part of larger, here, include: systematic efforts of potential interest • WHO (link) to gender and displacement could be • Eurostat (link) relevant, namely: • World Bank Group Microdata Library (link) While most of these sources provide a • UNHCR Microdata Library (link) wealth of information, it is not immedi- • U  NHCR-World Bank Group Joint Data ately clear if this may include specific Center on Forced Displacement (link) topics this project set out to study or fulfill the other requirements.  conomic Research Forum Microdata • E Catalogue (link) 29 H  anmer, L. et al. (2020). How does poverty differ among refugees? Taking a gender lens to the data on Syrian refugees in Jordan, Middle East Development Journal, DOI: 10.1080/17938120.2020.1753995. . 30 The World Bank Group Microdata perceptions of risks. So far, the portal 4.  To strengthen a global data collection Survey sizes often capture several thou- 31 Library contains a large collection of is most useful for analyzing populations system, based on common norms, sand of households, although in some data sources that are of potential in- in camp settings and beneficiaries definitions, and methodologies, cases only sub-samples of complete THE WORLD BANK GROUP GENDER DIMENSIONS OF FORCED DISPLACEMENT terest for research into the gender of UNHCR programs, but lacks with a particular effort on survey are publicly available and access dimensions of forced displacement. 30 information from comparable, non-dis- strengthening country systems to full dataset scan be requested from The collection includes the previously placed populations. where necessary, and national governments. discussed LSMS datasets and a set of In October 2019, UNHCR and the While ERF survey datasets contain four studies conducted as part of the 5.  To share and disseminate knowledge World Bank Group established the granular information on poverty and “Informing Durable Solutions for Internal through seminars, conferences and UNHCR-World Bank Group Joint Data economic conditions more generally, Displacement”. The latter is a multi-part- fellowship programs. The Center was Center on Forced Displacement. 33 The much ERF data is not suitable for dis- ner, World Bank-led study that con- launched In October 2019 and once Center is dedicated to enhancing the placement analyses. Many surveys take ducted comparable surveys inspired by an online presence and data portal ability of stakeholders to make timely place in non-displacement in settings, LSMS across a broad range of forms and are established, the data center and evidence-based decisions that can and in other settings displaced popula- contexts of forced displacement: IDP promises to be a unique new source improve the lives of affected people. tions are not sampled in sufficient num- populations and host communities in of data for innovative gender bers or identifiable. Exceptions include North-east Nigeria, Somalia, and South The work programme is structured analyses of forced displacement. Palestinian labor force surveys, which Sudan, as well as refugees and hosts in around five main themes: The Economic Research Forum (ERF) cover displacement camps, 35 the Jor- Ethiopia. 31 For more detail on these sur- veys see Section 6. 1.  To fill data gaps and support provides micro data designed to pro- dan Labor Market Panel Survey, which country level engagement to mote cross-national and/or cross-tem- in the 2016 wave added 3,000 house- The recently established UNHCR Mi- increase the collection of socioeco- poral research. Datasets include primary holds from areas with forcibly displaced crodata Library is a new data portal nomic data on populations affected data collected by with ERF support non-Jordanian households, including that provides access and links to mi- by forced displacement; as well as sets of acquired micro data, refugee camps, 36 and a similar Labor cro-level data on all people of concern which are available with open access Market Panel Survey in Sudan, 37 which in to UNHCR, including refugees, asylum 2.  To improve open access to forced through the ERF Micro Data Catalogue. 34 the 2020 wave will focus on surveying seekers, IDPs, returnees and stateless displacement data, with adequate Most existing surveys are labor force forcibly displaced households. people. 32 The portal covers micro-da- anonymization and safeguards to and labor market surveys and provide ta collected by UNHCR or by partner ensure compliance with the legal sex-disaggregated indicators. Typical organizations with UNHCR’s support, data protection framework; variables include geographical charac- including publicly available census data, teristics, household composition, owner- administrative data, and survey data. 3.  To fill data analysis and knowledge ship of durables, education, nationality As of 18 May 2020, the portal lists 28 gaps, developing methodologies for and migration, as well as current labor datasets. Most of the currently available measuring impact and promoting status, wages and income. datasets contain sex-disaggregated innovative methods to strengthen data and data on displacement status, forced displacement data; and and provide information on a broad range of topics, including health, in- come, livelihoods, living conditions, and 30 Webpage: https://microdata.worldbank.org/index.php/home. 34 Webpage: http://www.erfdataportal.com/index.php/catalog. 31  ebpage: https://www.worldbank.org/en/topic/poverty/publication/informing-durable-solu- W tions-for-internal-displacement. 35 For example, see: http://www.erfdataportal.com/index.php/catalog/160. 32 W  ebpage: https://microdata.unhcr.org/index.php/home. 36 Webpage: http://www.erfdataportal.com/index.php/catalog/139. 33 W  ebpage: https://www.worldbank.org/en/programs/forceddisplacement/brief/unhcr-world- 37  Webpage: https://g2lm-lic.iza.org/thematic-areas/ta3/advancing-data-capacity-for-policy-inno- bank-group-joint-data-center-on-forced-displacement-fact-sheet. vation-in-sudan-labor-market-panel-survey-2019/. 32 tions, including host communities. The rity intervention. The sample can be 33 survey instruments are inspired by the classified in terms of conflict exposure LSMS surveys and allow comparisons and consequences, including current THE WORLD BANK GROUP GENDER DIMENSIONS OF FORCED DISPLACEMENT of displaced and non-displaced groups. displacement status (displaced versus In addition to IDPs, refugees from three non-displaced) and proximity to vio- of four study countries (Somalia, South lence. This information has been used to Sudan, and Sudan residing in camps in study various forms of food security. 40 Ethiopia were also surveyed. For instance, the study documents that the agricultural intervention lifted the In a 2017 skills profile survey in Ethio- average food consumption score among pia, the World Bank collected data from IDP from a “poor” to an “acceptable” 5317 households in both refugees and level by FAO standards. The dataset is host communities, at the household and not publicly available at the moment. individual levels. In addition to standard socio-economic questions on assets and In South Sudan, the National Bureau consumption, the survey includes exten- of Statistics implemented a high fre- HIDDEN GEMS sive questions pertaining to the nature quency survey in collaboration with of displacement, a “Personal Living Con- the World Bank. The study includes ditions” module capturing recent expe- four waves of representative surveys riences of violence and perceptions of across seven states between 2015 and violence in their current local area, and a 2017, with sample sizes of close to 2000 conflict exposure module capturing past households. For example, wave 4 of exposure to violence. 38 the study, conducted in 2017, includes data on four of the largest IDP camps in Lastly, we examine a fifth data source, The Informing Durable Solutions for The IDP profile survey in North-east South Sudan. The survey questionnaire typically one-off surveys, which may Internal Displacement initiative pro- Nigeria was conducted by IOM and the covers topics including demographics, provide unique “gems” for learning vides a recent, innovative and compara- World Bank in 2018. A total of 2947 employment, education, consumption, about gender and displacement. ble set of large-scale household surveys households were surveyed, sampled as well as perceptions of well‐being We discuss five examples which, funded by DFID, the Somalia Knowledge from IDP camps and host communities and of the effectiveness of public in- with the exception of a food security for Results Trust Fund of the Multi-Part- in various regions in North-east Nigeria. stitutions. The different survey waves survey from North-east Nigeria, are ner Fund, the UN-World Bank Partner- The survey includes socio-economic are publicly available in the World Bank all publicly available in the World Bank ship Trust Fund, Humanitarian-Devel- modules, such as on nutritional and Microdata Library. 41 Microdata Library: opment-Peace Initiative (HDPI), and consumption, and has an extensive nforming Durable Solutions for Internal Dis- • I the World Bank’s Forced Displacement displacement module, capturing nature placement initiative (Nigeria, Somalia, South Trust Fund. and consequences of displacement. 39 Sudan, Sudan) The initiative has collected individu- Also, in North-east Nigeria, FAO orga- • Skills profile (Ethiopia) al and household-level data through nized a Food Security Survey in the • IDP profile (North-east Nigeria) personal interviews in Nigeria, Somalia, context of an agricultural food secu- • Food security survey (North-east Nigeria) South Sudan, and Sudan. In each con- text, the comprehensive surveys cover • High frequency survey (South Sudan) both IDPs and non-displaced popula- 38 Webpage: https://microdata.worldbank.org/index.php/catalog/3445. 39 Webpage: https://microdata.worldbank.org/index.php/catalog/3410. 40  Baliki, G., Brück, T. and W. Stojetz (2018). Strengthening Food Security in Acute Crisis Settings: First Insights from North-east Nigeria. ISDC Policy Brief: Berlin, Germany. 41 Webpage: https://microdata.worldbank.org/index.php/home. 34 APPENDICES 35 THE WORLD BANK GROUP GENDER DIMENSIONS OF FORCED DISPLACEMENT APPENDIX 1 OVERVIEW OF SURVEYS WITH SEX DISAGGREGATED DISPLACEMENT DATA INFORMATION RELATED TO DISPLACEMENT SAMPLED POPULATIONS OVERVIEW   (AT DISTRICT LEVEL OR LOWER) DISPLACED IN REFUGEE CAMPS TIME IN PRESENT LOCATION DISPLACEMENT INFERENCE NON-CONFLICT AFFECTED NON-DISPLACED GROUPS HOUSEHOLDS SURVEYED INDIRECT INFORMATION SURVEY YEAR (START) REASONS FOR MOVING METHOD OF INDIRECT PREVIOUS LOCATION DIRECT QUESTION(S) SURVEY YEAR (END) HOST COMMUNITIES HOST COMMUNITIES DISPLACED WITHIN ON DISPLACEMENT ON DISPLACEMENT ASYLUM SEEKERS PLACE OF BIRTH DATA SOURCE COMMUNITIES REFUGEES GPS DATA COUNTRY IDPS DHS AFGHANISTAN 2010 2010 No 22.351 No Yes Reason Yes No No No Yes * * * * Yes Yes * DHS AFGHANISTAN 2015 2015 No 24.395 No No --- No No No No Yes * * * * Yes Yes * DHS BENIN 2017 2018 Yes 14.156 No Yes Previous No Yes Yes No * * * * * * * * Location DHS BURUNDI 2016 2017 Yes 15.997 No Yes Previous No Yes Yes No * * * * * * * * Location DHS COLOMBIA 2000 2000 No 10.907 No Yes Reason Yes No Yes No * * * * * * * * DHS COLOMBIA 2005 2005 No 37.211 No Yes Reason Yes No Yes No * * * * * * * * DHS COLOMBIA 2010 2010 Yes 51.447 No Yes Reason Yes No Yes No * * * * * * * * DHS COLOMBIA 2015 2015 No 44.614 No Yes Reason Yes No Yes No * * * * * * * * DHS ERITREA 2002 2002 * 9.389 Yes No Reason Yes Yes Yes No * * * * * * * * DHS ETHIOPIA 2000 2000 Yes 14.072 No No --- No No Yes No * * * * * * * * DHS ETHIOPIA 2005 2005 Yes 13.721 No No --- No No Yes No * * * * * * * * DHS ETHIOPIA 2011 2011 Yes 16.702 No No --- No No No No * * * * * * * * DHS ETHIOPIA 2016 2016 Yes 16.650 No Yes Previous No Yes Yes No * * * * * * * * Location 36 37 INFORMATION RELATED TO DISPLACEMENT SAMPLED POPULATIONS OVERVIEW   THE WORLD BANK GROUP GENDER DIMENSIONS OF FORCED DISPLACEMENT (AT DISTRICT LEVEL OR LOWER) DISPLACED IN REFUGEE CAMPS TIME IN PRESENT LOCATION DISPLACEMENT INFERENCE NON-CONFLICT AFFECTED NON-DISPLACED GROUPS HOUSEHOLDS SURVEYED INDIRECT INFORMATION SURVEY YEAR (START) REASONS FOR MOVING METHOD OF INDIRECT PREVIOUS LOCATION DIRECT QUESTION(S) SURVEY YEAR (END) HOST COMMUNITIES HOST COMMUNITIES DISPLACED WITHIN ON DISPLACEMENT ON DISPLACEMENT ASYLUM SEEKERS PLACE OF BIRTH DATA SOURCE COMMUNITIES REFUGEES GPS DATA COUNTRY IDPS DHS INDONESIA 2002 2003 Yes 33.088 No No --- No No No No * * * * * * * * DHS INDONESIA 2007 2007 No 40.701 No No --- No No No No * * * * * * * * DHS INDONESIA 2012 2012 No 43.852 No No --- No No No No * * * * * * * * DHS INDONESIA 2017 2017 No 47.963 No Yes Previous No Yes Yes No * * * * * * * * Location DHS JORDAN 2002 2002 Yes 7.825 No Yes Previous No Yes Yes No * * * * * * * * Location DHS JORDAN 2007 2007 Yes 14.564 No No --- No No Yes No * * * * * * * * DHS JORDAN 2012 2012 Yes 15.190 No No --- No No No No * * * * * * * * DHS JORDAN 2017 2018 Yes 18.802 No Yes Previous No Yes Yes No * * * * * * * * Location DHS KENYA 2003 2003 Yes 8.561 No No --- No No Yes No * * * * * * * * DHS KENYA 2008 2009 Yes 9.057 No No --- No No Yes No * * * * * * * * DHS KENYA 2014 2014 Yes 36.430 No Yes Previous Yes Yes Yes No * * * * * * * * Location DHS MALI 2018 2018 Yes 9.510 No Yes Previous No Yes Yes No * * * * * * * * Location DHS NEPAL 2001 2001 Yes 8.602 No No --- No No Yes No * * * * * * * * DHS NEPAL 2006 2006 Yes 8.707 No No --- No No Yes No * * * * * * * * DHS NEPAL 2011 2011 Yes 10.826 No Yes Reason Yes No No No * Yes * * * * * * DHS NEPAL 2016 2016 Yes 11.040 No Yes Reason Yes Yes Yes No * Yes * * * * * * DHS NIGERIA 2018 2018 Yes 40.427 No Yes Previous No Yes Yes No * * * * * * * * Location 38 39 INFORMATION RELATED TO DISPLACEMENT SAMPLED POPULATIONS OVERVIEW   THE WORLD BANK GROUP GENDER DIMENSIONS OF FORCED DISPLACEMENT (AT DISTRICT LEVEL OR LOWER) DISPLACED IN REFUGEE CAMPS TIME IN PRESENT LOCATION DISPLACEMENT INFERENCE NON-CONFLICT AFFECTED NON-DISPLACED GROUPS HOUSEHOLDS SURVEYED INDIRECT INFORMATION SURVEY YEAR (START) REASONS FOR MOVING METHOD OF INDIRECT PREVIOUS LOCATION DIRECT QUESTION(S) SURVEY YEAR (END) HOST COMMUNITIES HOST COMMUNITIES DISPLACED WITHIN ON DISPLACEMENT ON DISPLACEMENT ASYLUM SEEKERS PLACE OF BIRTH DATA SOURCE COMMUNITIES REFUGEES GPS DATA COUNTRY IDPS DHS PAKISTAN 2006 2007 Yes 95.441 No No --- No No No No * * * * * * * * DHS PAKISTAN 2012 2013 No 12.943 No Yes Reason Yes Yes Yes No * * * * * * * * DHS PAKISTAN 2017 2018 Yes 14.540 No Yes Reason Yes Yes No No * * * * * * * * DHS PHILIPPINES 2017 2017 Yes 27.496 No Yes Previous No Yes Yes No * * * * * * * * Location DHS TANZANIA 2015 2016 Yes 12.563 No Yes Previous No Yes Yes No * * * * * * * * Location DHS TURKEY 2003 2003 No 10.836 No Yes Reason Yes Yes Yes Yes * * * * * * * * DHS TURKEY 2008 2008 No 10.525 No Yes Reason Yes Yes Yes Yes * * * * * * * * DHS TURKEY 2013 2013 No 11.794 No Yes Reason Yes Yes Yes Yes * * * * * * * * DHS UGANDA 2000 2001 Yes 7.885 No No --- No No Yes Yes * * * * * * * * DHS UGANDA 2006 2006 Yes 8.870 No Yes --- No No Yes Yes * * * * * * * * DHS UGANDA 2011 2011 Yes 9.033 No No --- No No No Yes * * * * * * * * DHS UGANDA 2016 2016 Yes 19.588 No Yes Reason No Yes Yes Yes * * * * * * * * JIPS GREECE 2018 2018 No 641 Yes No --- No No Yes No Yes No Yes Yes No No No Yes JIPS HONDURAS 2018 2018 No 849 Yes No --- Yes Yes Yes Yes No Yes No Yes Yes Yes Yes No JIPS IRAQ (DUHOK) 2016 2016 No 1.205 Yes No --- Yes No Yes No Yes Yes No Yes Yes No No No JIPS IRAQ (ERBIL) 2015 2016 No 1.163 Yes No --- Yes No Yes No Yes Yes No Yes Yes No No No JIPS IRAQ (SOUTH 2015 2016 No 4.000 Yes No --- Yes No Yes No Yes Yes No Yes Yes No No No CENTRAL) JIPS IRAQ 2016 2016 No 1.201 Yes No --- Yes No Yes No Yes Yes No Yes Yes No No No (SULEIMANIAH) 40 41 INFORMATION RELATED TO DISPLACEMENT SAMPLED POPULATIONS OVERVIEW   THE WORLD BANK GROUP GENDER DIMENSIONS OF FORCED DISPLACEMENT (AT DISTRICT LEVEL OR LOWER) DISPLACED IN REFUGEE CAMPS TIME IN PRESENT LOCATION DISPLACEMENT INFERENCE NON-CONFLICT AFFECTED NON-DISPLACED GROUPS HOUSEHOLDS SURVEYED INDIRECT INFORMATION SURVEY YEAR (START) REASONS FOR MOVING METHOD OF INDIRECT PREVIOUS LOCATION DIRECT QUESTION(S) SURVEY YEAR (END) HOST COMMUNITIES HOST COMMUNITIES DISPLACED WITHIN ON DISPLACEMENT ON DISPLACEMENT ASYLUM SEEKERS PLACE OF BIRTH DATA SOURCE COMMUNITIES REFUGEES GPS DATA COUNTRY IDPS JIPS KOSOVO 2016 2016 No 1.327 Yes No --- No No Yes No No Yes No Yes No No No No JIPS SUDAN 2018 2018 Yes 3.002 Yes No --- Yes Yes No Yes Yes Yes Yes Yes Yes Yes No No (NORTH DARFUR) LSMS IRAQ 2012 2012 Yes 24.944 Yes No --- Yes Yes Yes Yes Yes Yes No Yes Yes No No No LSMS NEPAL 2010 2011 Yes 7.020 No Yes Reason Yes Yes Yes Yes No Yes No Yes Yes No Yes No LSMS NIGERIA 2015 2016 Yes 4.611 Yes No --- Yes Yes Yes No No Yes No Yes Yes No No No LSMS NIGERIA 2018 2019 Yes 4.749 Yes No --- Yes Yes Yes No No Yes No Yes Yes No No No LSMS TIMOR-LESTE 2008 2008 No 4.477 No Yes Reason Yes No No Yes No Yes No No No Yes Yes No LSMS UGANDA 2010 2011 Yes 3.123 Yes No --- Yes Yes Yes Yes No Yes No Yes Yes No No No LSMS UGANDA 2011 2012 Yes 3.123 Yes No --- Yes Yes Yes Yes No Yes No Yes Yes No No No LSMS UGANDA 2013 2014 Yes 3.123 Yes No --- Yes Yes Yes Yes No Yes No Yes Yes No No No LSMS UGANDA 2015 2016 Yes 3.300 Yes No --- Yes Yes Yes Yes No Yes No Yes Yes No No No MICS BANGLADESH 2019 2019 No 64.400 No Yes Previous No Yes Yes No * * * * * * * * Location MICS DRC 2017 2018 Yes 21.630 No Yes Previous No Yes No No * * * * * * * * Location MICS GAMBIA 2018 2018 No 7.750 No Yes Previous No Yes Yes No * * * * * * * * Location MICS GHANA 2018 2018 No 13.202 No Yes Previous No Yes Yes No * * * * * * * * Location MICS IRAQ 2018 2018 No 20.521 Yes Yes Previous Yes Yes Yes No Yes Yes No Yes Yes Yes * * Location MICS LESOTHO 2018 2018 Yes 10.413 No Yes Previous No Yes Yes No * * * * * * * * Location THE WORLD BANK GROUP DATA SOURCE 42 MICS MICS VACS VACS VACS OVERVIEW COUNTRY HAITI KENYA ZIMBABWE EL SALVADOR PAKISTAN (PUNJAB) SURVEY YEAR (START) 2017 2017 2012 2019 2010 SURVEY YEAR (END) 2017 2012 2018 2019 2010 No No No No No GPS DATA HOUSEHOLDS SURVEYED 2.016 8.708 5.894 12.012 53.840   No No No No No DIRECT QUESTION(S) ON DISPLACEMENT Yes Yes Yes Yes Yes INDIRECT INFORMATION ON DISPLACEMENT METHOD OF INDIRECT Reason Reason DISPLACEMENT INFERENCE Previous Previous Previous Location Location Location No No No Yes Yes REASONS FOR MOVING No No Yes Yes Yes PREVIOUS LOCATION (AT DISTRICT LEVEL OR LOWER) INFORMATION RELATED TO DISPLACEMENT No Yes Yes Yes Yes TIME IN PRESENT LOCATION No No No No No PLACE OF BIRTH * * * * * REFUGEES * * IDPS Yes Yes Yes * * * * * DISPLACED IN REFUGEE CAMPS DISPLACED WITHIN * * * SAMPLED POPULATIONS Yes Yes HOST COMMUNITIES * * * HOST COMMUNITIES Yes Yes NON-CONFLICT AFFECTED * * * Yes Yes COMMUNITIES NON-DISPLACED GROUPS * * * Yes Yes * * * * * ASYLUM SEEKERS GENDER DIMENSIONS OF FORCED DISPLACEMENT 43 44 APPENDICES 45 THE WORLD BANK GROUP GENDER DIMENSIONS OF FORCED DISPLACEMENT APPENDIX 2 OVERVIEW OF KEY SURVEYS WITH GDFD OUTCOMES AND CORRELATES OF INTEREST OVERVIEW GENDER-BASED VIOLENCE MULTI-DIMENSIONAL POVERTY LABOR MARKET CHILD PARTICIPATION DEVELOPMENT ATTITUDES TOWARDS DOMESTIC VIOLENCE PHYSICAL VIOLENCE BY NON-PARTNERS DHS DV MODULE ANSWERED BY WOMEN DHS WOMEN EMPOWERMENT MODULE DHS DV MODULE ANSWERED BY MEN SEXUAL VIOLENCE BY PARTNERS OR INTIMATE PARTNER VIOLENCE FEMALE GENITAL MUTILATION LABOR MARKET ACCESS SURVEY YEAR (START) HOUSING CONDITIONS ILLNESS AND INJURY HOUSEHOLD SHOCKS ACCESS TO JUSTICE SURVEY YEAR (END) GENERAL TIME USE CHILD NUTRITION CHILD MARRIAGE HOURS OF WORK NON-PARTNERS EXPENDITURES CHILD HEALTH DATA SOURCE EDUCATION NUTRITION COUNTRY INCOME DHS AFGHANISTAN 2010 2010 No No No No No No No No Yes No Yes Yes No No Yes Yes No No No Yes Yes Yes DHS AFGHANISTAN 2015 2015 Yes Yes No Yes Yes No Yes Yes Yes No Yes Yes No No Yes Yes Yes No No Yes Yes Yes DHS BENIN 2017 2018 Yes Yes No Yes Yes No Yes Yes Yes No Yes Yes No No Yes Yes Yes No No Yes Yes Yes DHS BURUNDI 2016 2017 Yes Yes Yes Yes Yes No Yes Yes Yes No Yes Yes No No Yes Yes Yes No No Yes Yes Yes DHS COLOMBIA 2000 2000 Yes Yes No Yes No No Yes Yes Yes No Yes Yes No No Yes Yes Yes No No Yes Yes Yes DHS COLOMBIA 2005 2005 Yes Yes No Yes No No Yes Yes Yes No Yes Yes No No Yes Yes Yes No No Yes Yes Yes DHS COLOMBIA 2010 2010 Yes Yes No Yes No No Yes Yes Yes No Yes Yes No No Yes Yes Yes No No Yes Yes Yes DHS COLOMBIA 2015 2015 Yes Yes Yes Yes No No Yes Yes Yes No Yes Yes No No Yes Yes Yes No No Yes Yes Yes DHS ERITREA 2002 2002 No Yes No No No Yes No No Yes No Yes Yes No No Yes Yes Yes No No Yes Yes Yes DHS ETHIOPIA 2000 2000 No Yes No No No Yes No No Yes No Yes Yes No No Yes Yes Yes No No Yes Yes Yes DHS ETHIOPIA 2005 2005 No Yes No No Yes Yes No No Yes No Yes Yes No No Yes Yes Yes No No Yes Yes Yes DHS ETHIOPIA 2011 2011 No Yes No No Yes No No No Yes No Yes Yes No No Yes Yes Yes No No Yes Yes Yes DHS ETHIOPIA 2016 2016 Yes Yes No Yes Yes Yes Yes Yes Yes No Yes Yes No No Yes Yes Yes No No Yes Yes Yes DHS INDONESIA 2002 2003 No Yes No No No No No No Yes No Yes Yes No No Yes Yes Yes No No Yes Yes Yes 46 47 OVERVIEW GENDER-BASED VIOLENCE MULTI-DIMENSIONAL POVERTY LABOR MARKET CHILD PARTICIPATION DEVELOPMENT THE WORLD BANK GROUP GENDER DIMENSIONS OF FORCED DISPLACEMENT ATTITUDES TOWARDS DOMESTIC VIOLENCE PHYSICAL VIOLENCE BY NON-PARTNERS DHS DV MODULE ANSWERED BY WOMEN DHS WOMEN EMPOWERMENT MODULE DHS DV MODULE ANSWERED BY MEN SEXUAL VIOLENCE BY PARTNERS OR INTIMATE PARTNER VIOLENCE FEMALE GENITAL MUTILATION LABOR MARKET ACCESS SURVEY YEAR (START) HOUSING CONDITIONS ILLNESS AND INJURY HOUSEHOLD SHOCKS ACCESS TO JUSTICE SURVEY YEAR (END) GENERAL TIME USE CHILD NUTRITION CHILD MARRIAGE HOURS OF WORK NON-PARTNERS EXPENDITURES CHILD HEALTH DATA SOURCE EDUCATION NUTRITION COUNTRY INCOME DHS INDONESIA 2007 2007 No Yes No No No No No No Yes No Yes Yes No No Yes Yes Yes No No Yes Yes Yes DHS INDONESIA 2012 2012 No Yes No No Yes No No No Yes No Yes Yes No No Yes Yes Yes No No Yes Yes Yes DHS INDONESIA 2017 2017 No Yes No No Yes No No No Yes No Yes Yes No No Yes Yes Yes No No Yes Yes Yes DHS JORDAN 2002 2002 No Yes No No No No No No Yes No Yes Yes No No Yes Yes Yes No No Yes Yes Yes DHS JORDAN 2007 2007 Yes Yes No Yes Yes No Yes Yes Yes No Yes Yes No No Yes Yes Yes No No Yes Yes Yes DHS JORDAN 2012 2012 Yes Yes No Yes Yes No Yes Yes Yes No Yes Yes No No Yes Yes Yes No No Yes Yes Yes DHS JORDAN 2017 2018 Yes Yes No Yes Yes No Yes Yes Yes No Yes Yes No No Yes Yes Yes No No Yes Yes Yes DHS KENYA 2003 2003 Yes Yes No Yes No Yes Yes Yes Yes No Yes Yes No No Yes Yes Yes No No Yes Yes Yes DHS KENYA 2008 2009 Yes Yes No Yes Yes Yes Yes Yes Yes No Yes Yes No No Yes Yes Yes No No Yes Yes Yes DHS KENYA 2014 2014 Yes Yes Yes Yes Yes Yes Yes Yes Yes No Yes Yes No No Yes Yes Yes No No Yes Yes Yes DHS MALI 2018 2018 Yes Yes No Yes Yes No Yes Yes Yes No Yes Yes No No Yes Yes Yes No No Yes Yes Yes DHS NEPAL 2001 2001 No Yes No No No No No No Yes No Yes Yes No No Yes Yes Yes No No Yes Yes Yes DHS NEPAL 2006 2006 No Yes No No No No No No Yes No Yes Yes No No Yes Yes Yes No No Yes Yes Yes DHS NEPAL 2011 2011 Yes Yes No Yes Yes No Yes Yes Yes No Yes Yes No No Yes Yes Yes No No Yes Yes Yes DHS NEPAL 2016 2016 Yes Yes No Yes Yes No Yes Yes Yes No Yes Yes No No Yes Yes Yes No No Yes Yes Yes DHS NIGERIA 2018 2018 Yes Yes No Yes Yes Yes Yes Yes Yes No Yes Yes No No Yes Yes Yes No No Yes Yes Yes DHS PAKISTAN 2006 2007 No No No No No No No No Yes No Yes Yes No No Yes Yes Yes No No Yes Yes Yes 48 49 OVERVIEW GENDER-BASED VIOLENCE MULTI-DIMENSIONAL POVERTY LABOR MARKET CHILD PARTICIPATION DEVELOPMENT THE WORLD BANK GROUP GENDER DIMENSIONS OF FORCED DISPLACEMENT ATTITUDES TOWARDS DOMESTIC VIOLENCE PHYSICAL VIOLENCE BY NON-PARTNERS DHS DV MODULE ANSWERED BY WOMEN DHS WOMEN EMPOWERMENT MODULE DHS DV MODULE ANSWERED BY MEN SEXUAL VIOLENCE BY PARTNERS OR INTIMATE PARTNER VIOLENCE FEMALE GENITAL MUTILATION LABOR MARKET ACCESS SURVEY YEAR (START) HOUSING CONDITIONS ILLNESS AND INJURY HOUSEHOLD SHOCKS ACCESS TO JUSTICE SURVEY YEAR (END) GENERAL TIME USE CHILD NUTRITION CHILD MARRIAGE HOURS OF WORK NON-PARTNERS EXPENDITURES CHILD HEALTH DATA SOURCE EDUCATION NUTRITION COUNTRY INCOME DHS PAKISTAN 2012 2013 Yes Yes No Yes Yes No Yes Yes Yes No Yes Yes No No Yes Yes Yes No No Yes Yes Yes DHS PAKISTAN 2017 2018 Yes Yes No Yes Yes No Yes Yes Yes No Yes Yes No No Yes Yes Yes No No Yes Yes Yes DHS PHILIPPINES 2017 2017 Yes Yes No Yes Yes No Yes Yes Yes No Yes Yes No No Yes Yes Yes No No Yes Yes Yes DHS TANZANIA 2015 2016 Yes Yes No Yes Yes Yes Yes Yes Yes No Yes Yes No No Yes Yes Yes No No Yes Yes Yes DHS TURKEY 2003 2003 No Yes No No No No No No Yes No Yes Yes No No Yes Yes Yes No Yes Yes Yes Yes DHS TURKEY 2008 2008 No Yes No No No No No No Yes No Yes Yes No No Yes Yes Yes No Yes Yes Yes Yes DHS TURKEY 2013 2013 No Yes No No No No No No Yes No Yes Yes No No Yes Yes Yes No Yes Yes Yes Yes DHS UGANDA 2000 2001 No Yes Yes Yes Yes Yes Yes No Yes No Yes Yes No No Yes Yes Yes No No Yes Yes Yes DHS UGANDA 2006 2006 No Yes Yes Yes Yes Yes Yes No Yes No Yes Yes No No Yes Yes Yes No No Yes Yes Yes DHS UGANDA 2011 2011 No Yes Yes Yes Yes Yes Yes No Yes No Yes Yes No No Yes Yes Yes No No Yes Yes Yes DHS UGANDA 2016 2016 Yes Yes Yes Yes Yes Yes Yes Yes Yes No Yes Yes No No Yes Yes Yes No No Yes Yes Yes JIPS GREECE 2018 2018 No No No No No No Yes No Yes No Yes No Yes Yes Yes Yes Yes Yes No No No No JIPS HONDURAS 2018 2018 No No No No No No Yes Yes Yes Yes Yes No Yes Yes Yes Yes Yes No No Yes No No JIPS IRAQ (DUHOK) 2016 2016 No No No No No No Yes No Yes Yes No No No Yes Yes Yes Yes No No No No No JIPS IRAQ (ERBIL) 2015 2016 No No No No No No Yes No Yes Yes No No No Yes Yes Yes Yes No No No No No JIPS IRAQ (SOUTH 2015 2016 No No No No No No Yes No Yes Yes No No No Yes Yes Yes Yes No No No No No CENTRAL) 50 51 OVERVIEW GENDER-BASED VIOLENCE MULTI-DIMENSIONAL POVERTY LABOR MARKET CHILD PARTICIPATION DEVELOPMENT THE WORLD BANK GROUP GENDER DIMENSIONS OF FORCED DISPLACEMENT ATTITUDES TOWARDS DOMESTIC VIOLENCE PHYSICAL VIOLENCE BY NON-PARTNERS DHS DV MODULE ANSWERED BY WOMEN DHS WOMEN EMPOWERMENT MODULE DHS DV MODULE ANSWERED BY MEN SEXUAL VIOLENCE BY PARTNERS OR INTIMATE PARTNER VIOLENCE FEMALE GENITAL MUTILATION LABOR MARKET ACCESS SURVEY YEAR (START) HOUSING CONDITIONS ILLNESS AND INJURY HOUSEHOLD SHOCKS ACCESS TO JUSTICE SURVEY YEAR (END) GENERAL TIME USE CHILD NUTRITION CHILD MARRIAGE HOURS OF WORK NON-PARTNERS EXPENDITURES CHILD HEALTH DATA SOURCE EDUCATION NUTRITION COUNTRY INCOME JIPS IRAQ 2016 2016 No No No No No No Yes No Yes Yes No No No Yes Yes Yes Yes No No No No No (SULEIMANIAH) JIPS KOSOVO 2016 2016 No No No No No No Yes No Yes Yes Yes No No Yes Yes Yes Yes No Yes No No No JIPS SUDAN (NORTH 2018 2018 No No No No No No Yes No Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes No No Yes DARFUR) LSMS IRAQ 2012 2012 No No No No No No No No Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes No LSMS NEPAL 2010 2011 No No No No No No No No Yes Yes Yes Yes No Yes Yes Yes Yes Yes Yes Yes Yes No LSMS NIGERIA 2015 2016 No No No No No No No No Yes Yes No Yes No Yes Yes Yes Yes Yes Yes Yes Yes No LSMS NIGERIA 2018 2019 No No No No No No No No Yes Yes No Yes No Yes Yes Yes Yes Yes Yes Yes Yes No LSMS TIMOR-LESTE 2008 2008 No No No No No No No No Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes No Yes Yes No LSMS UGANDA 2010 2011 No No No No No No No No Yes Yes Yes Yes No Yes Yes Yes Yes Yes Yes Yes Yes No LSMS UGANDA 2011 2012 No No No No No No No No Yes Yes Yes Yes No Yes Yes Yes Yes Yes Yes Yes Yes No LSMS UGANDA 2013 2014 No No No No No No No No Yes Yes Yes Yes No Yes Yes Yes Yes Yes Yes Yes Yes No LSMS UGANDA 2015 2016 No No No No No No No No Yes Yes Yes Yes No Yes Yes Yes Yes Yes Yes Yes Yes No MICS BANGLADESH 2019 2019 No Yes No No No No No No No No Yes Yes No No Yes Yes No No No Yes Yes Yes MICS DRC 2017 2018 No Yes No No No No Yes No No No Yes Yes No No Yes Yes No No No Yes Yes Yes MICS GAMBIA 2018 2018 No Yes No No No Yes No No No No Yes Yes No No Yes Yes No No No Yes Yes Yes 52 53 OVERVIEW GENDER-BASED VIOLENCE MULTI-DIMENSIONAL POVERTY LABOR MARKET CHILD PARTICIPATION DEVELOPMENT THE WORLD BANK GROUP GENDER DIMENSIONS OF FORCED DISPLACEMENT ATTITUDES TOWARDS DOMESTIC VIOLENCE PHYSICAL VIOLENCE BY NON-PARTNERS DHS DV MODULE ANSWERED BY WOMEN DHS WOMEN EMPOWERMENT MODULE DHS DV MODULE ANSWERED BY MEN SEXUAL VIOLENCE BY PARTNERS OR INTIMATE PARTNER VIOLENCE FEMALE GENITAL MUTILATION LABOR MARKET ACCESS SURVEY YEAR (START) HOUSING CONDITIONS ILLNESS AND INJURY HOUSEHOLD SHOCKS ACCESS TO JUSTICE SURVEY YEAR (END) GENERAL TIME USE CHILD NUTRITION CHILD MARRIAGE HOURS OF WORK NON-PARTNERS EXPENDITURES CHILD HEALTH DATA SOURCE EDUCATION NUTRITION COUNTRY INCOME MICS GHANA 2018 2018 No Yes No No No Yes Yes No No No Yes Yes No No Yes Yes No No No Yes Yes Yes MICS IRAQ 2018 2018 No Yes No No No No Yes No No No Yes Yes No No Yes Yes No No No Yes Yes Yes MICS LESOTHO 2018 2018 No Yes No No No No Yes No No No Yes Yes No No Yes Yes No No No Yes Yes Yes MICS PAKISTAN 2017 2018 No Yes No No No No Yes No No No Yes Yes No No Yes Yes No No No Yes Yes Yes (PUNJAB) MICS ZIMBABWE 2019 2019 No Yes No No No No Yes Yes No No Yes Yes No No Yes Yes No No No Yes Yes Yes VACS EL SALVADOR 2017 2017 Yes Yes No No No No Yes Yes Yes No Yes No Yes No Yes Yes Yes No No Yes No Yes VACS HAITI 2012 2012 Yes Yes No No No No Yes Yes Yes No No No Yes No Yes Yes Yes No No Yes No Yes VACS KENYA 2010 2010 Yes Yes No No No Yes Yes Yes Yes No Yes No Yes No Yes Yes Yes No No Yes No Yes