Return Index Findings Round 3 April 2019
Total Page：16
File Type：pdf, Size：1020Kb
RETURN INDEX FINDINGS ROUND THREE – IRAQ MARCH 2019 HIGHLIGHTS • The model used to calculate the return index has been In this round, DTM sought to highlight the hotspots for each revised to reflect both new and updated indicators devel- governorate. Using a combination of score severity at least oped in consultation with relevant partners and stake- on one of the scales as well as the number of families living in holders. The model follows the same structure as the the area, 28 hotspots were identified across 6 governorates. original design and is based on two scales: (i) livelihoods NINEWA and basic services, and (ii) social cohesion and safety perceptions. • Markaz Sinjar • Zummar • Qaeyrrawan • Hamam al-Aleel • Of the assessed returnee population, 11 per cent (472,350 • Al-Shamal • Al-Shura individuals) are living in high severity conditions across • Markaz Telafar • Al-Ba’aj District 279 locations. Ninewa and Salah al-Din governorates host • Ayadiya • Markaz Hatra the highest number of returnees living in these condi- SALAH AL-DIN tions with 213, 372 and 187,812 individuals, respectively. This proportion is relatively similar to the previous rounds • Yathreb • Markaz Samarra published in September and January 2019, which had • Tooz District • Markaz Al-Shirqat respectively 11% and 10% of returnees in this category. • Markaz Baiji • Markaz Tikrit • The locations of return located in Al-Ba’aj District in ANBAR Ninewa present the highest severity scores: there are • Al-Rummaneh • Al-Saqlawiyah very severe conditions in all of these locations, which host • Markaz Al-Ka’im • Al-Garma 10,722 returnees followed by Tooz District in Salah al-Din • Markaz Al-Rutba and Sinjar District in Ninewa, which are hosting 28,542 DIYALA individuals (73%) in eight locations and 43,476 individuals • Markaz Al-Muqdadiya • As-Saadia (73%) in 40 locations, respectively. • Jalula KIRKUK 4,188,780 Returnees • Al-Riyad • Al-Abassy BAGHDAD 8 38 689,130 1,547 • Al-Nasir Walsalam • Al-Latifya governorates districts families locations Data collected January – February 2019 Figure 1: Proportion of returnees by category of severity per governorate Governorate Anbar 1 41 58 Baghdad 4 40 56 Dahuk 100 Diyala 25 61 15 Erbil 18 82 Kirkuk 1 41 58 Ninewa 13 26 61 Salah al-Din 31 56 13 All locations 11 38 50 Severity High Medium Low RETURN INDEX: FINDINGS ROUND 3 – IRAQ INTRODUCTION This third round of the Return Index consists of a new base- context. To measure the severity of conditions in each loca- line measurement of the severity of living conditions for the tion of return, the Return Index is based on 16 indicators returnee population in Iraq. The data1 for this report was grouped into two scales: (i) livelihoods and basic services, collected during the months of January and February 2019 in and (ii) social cohesion and safety perceptions. A regression 8 governorates, 38 districts and 1,547 locations across Iraq. model is used to assess the impact of each of the indicators Since the previous round, collected in October 2018 (Round in facilitating or preventing returns and to calculate scores 2), the number of returnees has continued to increase and as for the two scales. For example, the model tests how much of 28 February 2019, an additional 108,162 returnees were less likely a location where no agricultural activities are back identified, making a total of 4,188,780 returnees (698,130 to normal has returns compared to a location where this families). is not the case. To compute an overall severity index, the scores of two scales are combined and grouped into three This round the Return Index is built on a revised list of indi- categories: ‘low’ severity conditions, ‘medium’, and ‘high’ cators developed in consultation with relevant partners and (which also includes the identified ‘very high’ locations). stakeholders to better reflect the changing displacement METHODOLOGY The Return Index correlates data available on returnee population figures with 16 different indicators, grouped in two scales that measure living conditions in areas of return: 1) livelihoods and basic services, and 2) social cohesion and safety percep- tions. The Return Index uses a logistic regression model to assess the impact of each of indicators on the likelihood of returns, testing how likely a location is to have full returns if a certain condition applies, for instance the recovery of agricultural activities. This tool was developed by IOM DTM, the Returns Working Group and Social Inquiry. It is built upon the following key meth- odological principles: • The main assumption used to build the analytical model is to consider that the severity of living conditions for returnees (i.e., the likelihood or sustainability of returns) can be measured by whether the pre-conflict population has fully returned or not. This means that locations where all residents have returned are likely to have good conditions for return. Locations where not all of the population have returned are likely to have issues with livelihoods, services, social cohesion or safety. This measurement has limitations, given that the presence of full returns in a location may not be due to good conditions, but to pushed returns from places of displacement. • The 16 indicators used to build the Return Index help define living conditions in locations of return. These indicators represent a set of minimum or critical living conditions that are necessary to make a place conducive to returns. They are thus expected to be statistically representative to explain the likelihood of a population group returns. In practical terms, the model responds to the following question: are there conditions on the ground that explain why a location is more likely to have partial returns as opposed to full returns? • These indicators were formulated into a survey format and collected bi-monthly through key informants in each location with population returns. The advantage of using key informants is that many locations can be covered in a short period of time. However, its key limitation is that it relies on one representative reporting on the views of a potentially large and diverse set of returnees. The unit of analysis is the location, which can be a town, village, or even a neighborhood in a city. • The scoring is derived from a logistical model with the state of returns in a location as the outcome to be explained (dependent variable) through the 16 indicators (explanatory variables). This model generates an odds ratio for each statis- tically significant indicator, which measures how less likely a location is to have full returns if the condition described in the table above applies. These ratios are used to know the relative impact of each indicator on returns. The reason for using this type of analysis is the assumption that not all indicators have the same likelihood of inducing or sustaining returns. 1 The full dataset is available on the DTM website iraqdtm.iom.int 2 IOM IRAQ RETURN INDEX: FINDINGS ROUND 3 – IRAQ The final result is that every indicator has a value associated with it so that it is possible to calculate a “livelihoods and services score” and a “social cohesion and safety perceptions score”. These two scores are then combined to create an overall severity index. The index goes from 0 (all essential conditions for return are met) to 100 (no essential conditions for return are met). The combination of these indicators provides an index score for every location with population returns. Higher scores denote more severe living conditions for returnees. These indicators are ranked from a higher individual score to a lower. Indicators at the top of the list add more scores to the final index and indicators added for the first time in Round 3 are found below in boxes. Table 1: Indicator list for each scale CONDITION EVALUATED IN EACH CONDITION EVALUATED IN EACH SCALE 1 SCALE 2 LOCATION LOCATION Existence of destroyed houses, Community Need for a reconciliation process that Residential destruction combined with presence of recon- reconciliation is not currently taking place. struction efforts. Presence of at least four different Part of the population unable to find Multiple security Employment access armed groups in control of security employment. actors provision. Part of the population with insufficient Part of the pre-conflict population not Water sufficiency Blocked returns public water supply. allowed to return. Presence of PMU, TMU or other Checkpoints groups in control of checkpoints apart Agricultural activities not taking place Recovery of agriculture controlled by other from the Iraqi army, the local police as before. security actors and the federal police, combined with concerns over harassment. Existence of tensions among residents Part of the population with insufficient Electricity sufficiency Daily public life and preference to not leave the house electricity supply. unless necessary. Presence of private residences illegally Recovery of small Existence of small businesses that Illegal occupation of occupied by others (residents, armed businesses have not been restarted. private residences groups, etc.). Existence of access difficulties to Existence of concerns among the Access to basic primary education or primary health Mines population about explosive devices in services provision. houses. Existence of concerns among the population about violence in the Reincorporation of Lack of local civil servants returning Sources of area (ISIL attacks, acts of revenge, civil servants to their posts. violence clashes between security forces, or ethno-religious-tribal tensions). SCALE 1 SCORE = 100 SCALE 2 SCORE = 100 TOTAL SCORE = AVERAGE OF SCALE 1 AND SCALE 2 SCORES 3 IOM IRAQ RETURN INDEX: FINDINGS ROUND 3 – IRAQ OVERVIEW OF THE REVISED MODEL In this round, the regression model used to calculate the the return situation should not be drawn due to the fact return index has been revised to reflect both new and that a different questionnaire and weighting were used.