Quantitative Research Consultancy

Duty Station of the Consultancy: Home based

Duration of Consultancy: 45 working days,19 September – 2 December 2022

Nature of the consultancy: To produce the sixth Knowledge Bite, based on the in-depth quantitative analysis of the Returnee Longitudinal Survey (RLS) data.

Project Context and Scope:

Funded by the EU Trust Fund for Africa and the Development Cooperation Instrument, the European Union (EU) and the International Organization for Migration (IOM) have launched several programmes (the “EU-IOM Actions”) addressing migrant protection and sustainable reintegration in Africa and in Asia in 2017 and 2018. In this framework, a EU-IOM Knowledge Management Hub (KMH) was established at IOM HQ in 2017, with the main objective to support the implementation of the EU-IOM Actions. The KMH plays a crucial role in the implementation of these initiatives by providing thematic expertise, supporting cross-regional harmonization of information management systems, monitoring and evaluation activities, the development of knowledge management tools, and support return and reintegration-related research.

In October 2020, the KMH launched the Sustainable Reintegration Knowledge Bites series, which aims to present findings pertaining to sustainable reintegration outcomes emerging from the analyses of Reintegration Sustainability Survey (RSS) data and other monitoring and evaluation (M&E) data available. The Knowledge Bites series are designed to bring these findings to the attention of reintegration practitioners and policymakers worldwide, as well as to inform and disseminate good practices, lessons learned, and recommendations.

To date, five Knowledge Bites have been produced, focusing on different aspects of sustainable reintegration outcomes.

In an ongoing effort to expand the knowledge on reintegration outcomes and the factors contributing to sustainable reintegration, the sixth Knowledge Bite will use data collected through the Returnee Longitudinal Survey (RLS) in four countries of return, Afghanistan, Bangladesh, Iraq, and Pakistan, over the course of three years. The RLS was developed under the EU-funded project “Displacement Tracking Matrix Regional Evidence for Migration Analysis and Policy (DTM REMAP)”. Drawing from the RSS and its underlying definition of sustainable reintegration, the RLS monitors sustainable reintegration outcomes based on the economic, social, and psychosocial self-assessed conditions of returnees, in addition to understanding the demographic profiles as well as assessing their living conditions.

While the findings of previous Knowledge Bites provided cross-sectional insights into reintegration outcomes, the analysis of RLS data will allow to develop a layer of in-depth knowledge on the evolution of sustainability of reintegration in the short and medium term, by measuring changes in reintegration outcomes at the individual returnee level over time. The findings from this study will help better understand migrants’ reintegration sustainability pathways in addition to producing relevant longitudinal evidence on reintegration outcomes that will support practitioners with the design of new policies and improving the sustainability of reintegration programmes.

This study aims to achieve the following objectives:

1. to strengthen longitudinal evidence-based programming and disseminate lessons learned and recommendations on the sustainability of reintegration – across the economic, social, and psychosocial dimensions;
2. to present in-depth insights into the factors of sustainable reintegration, while explaining cross-country and cross-regional patterns of sustainable reintegration outcomes; and ultimately
3. to complement the key findings from the analysis of returnees’ data collected in Afghanistan, Bangladesh, Iraq and Pakistan, by focusing on indicators for reintegration sustainability (economic, social, and psychosocial);

The RLS encompasses four sections: demographics, economic pillar, social pillar, and psychosocial pillar. In addition, three additional sections, covering questions related to the returnee’s situation before migration, during migration, and after return, were included in the RLS administered at baseline (round 1). The data is collected with the same individuals over the course of three years at regular intervals of six months.

This study will be based on the analysis of three rounds of RLS data collected between 2020 and 2022, in four countries of return: Afghanistan, Bangladesh, Iraq, and Pakistan. The longitudinal dataset covers 1,903 respondents across Afghanistan, Bangladesh, Pakistan, and Iraq. Respondents were assisted to return through IOM’s Assisted Voluntary Return and Reintegration (AVRR) and other IOM return programmes. To construct the sample, the DTM REMAP followed several criteria, including but not limited to, the country where the respondent returned from, time of return, and reintegration assistance (either cash or in-kind).

The analysis in this study will be guided by three broad research questions:

1. How do short to mid-term sustainable reintegration outcomes of returning migrants differ per country of return?
2. What are the underlying demographic and migratory movement factors (before and during migration and after return) affecting reintegration outcomes?
3. How does the evidence generated through the analysis of RSS data interlace and relate with the findings from the analysis of RLS data?

The analysis will take the form of a longitudinal study, more specifically a panel data regression model, which will allow to model the evolution of individual sustainable reintegration outcomes between 2020 and 2022, across the three waves (rounds) of data collection, while controlling for unobserved cofounders.

Organizational Department / Unit to which the Consultant is contributing:

Department of Programme Support and Migration Management, the Protection Division under the project ”Pilot Action on Voluntary Return and Sustainable, Community-Based Reintegration”

Tangible and measurable outputs of the work assignment

1. First deliverable: Develop and submit a comprehensive research framework, clearly outlining the research design, the methodology, and statistical models for the analysis. – First instalment payment – 10 days, deliverable by 30 September 2022.
2. Second deliverable: Undertake the analysis and visualization of data and write the narrative under the research study, in close coordination with the KMH team. Submit the first draft of KB#6 for revision – Second instalment payment – 25 days, deliverable by 4 November 2022.
3. Third deliverable: Finalize and submit the final version of KB#6, taking into account inputs received on the draft – Third and final instalment payment – 10 days, deliverable by email by 2 December 2022.

Performance indicators for the evaluation of results

Output 1: Develop and submit a comprehensive research framework, clearly outlining the research design, the methodology, and statistical models for the analysis

• Activity 1.1: Onboard and review background material
• Activity 1.2: Develop a comprehensive research framework, clearly outlining the research design, the methodology, and statistical models for the analysis
• Activity 1.3: Submit the research framework for revision and approval

Output 2: Undertake the analysis and visualization of data and write the narrative under the research study, in close coordination with the KMH team. Submit the first draft of KB#6 for revision

• Activity 2.1: Analyse and visualize data
• Activity 2.2: Debrief on initial findings at the end of the data analysis process
• Activity 2.3: Draft the narrative report
• Activity 2.4: Provide periodic progress reports/updates
• Activity 2.5: Submit the first draft of KB#6 for revision

Output 3: Finalize and submit the final version of KB#6, taking into account inputs received on the draft

• Activity 3.1: Revise the draft of KB#6, taking into account inputs received
• Activity 3.2: Submit the final version of KB#6 ready to be published.

Education, Experience and/or skills required

• Master’s degree in Political Science, Economics, Public Health, Migration Studies, or a related field from an accredited academic institution with at least 5 years of relevant professional experience; or
• University degree in the above fields with 7 years of relevant professional experience.
• Excellent quantitative data analysis skills and demonstrated ability to produce high-quality research reports.
• Demonstrated experience in developing, formulating, and conducting longitudinal quantitative data analysis.
• Demonstrated experience in drafting research studies, for technical and non-technical audiences, and strong writing skills.
• Proficient in the use of statistical software (such as Stata, SPSS, or R).
• Strong understanding of migrant protection, return, and sustainable reintegration.
• Oral and written fluency in English;
• Oral and written fluency in French is an asset.

Competencies

Values

• Inclusion and respect for diversity: respects and promotes individual and cultural differences; encourages diversity and inclusion wherever possible.
• Integrity and transparency: maintains high ethical standards and acts in a manner consistent with organizational principles/rules and standards of conduct.
• Professionalism: demonstrates ability to work in a composed, competent and committed manner and exercises careful judgment in meeting day-to-day challenges.

Core Competencies – behavioural indicators

• Teamwork: develops and promotes effective collaboration within and across units to achieve shared goals and optimize results.
• Delivering results: produces and delivers quality results in a service-oriented and timely manner; is action-oriented and committed to achieving agreed outcomes.
• Managing and sharing knowledge: continuously seeks to learn, share knowledge and innovate.
• Accountability: takes ownership for achieving the Organization’s priorities and assumes responsibility for own action and delegated work.
• Communication: encourages and contributes to clear and open communication; explains complex matters in an informative, inspiring and motivational way.