Input: The report focuses on intent-to-treat (ITT) estimates, measuring the impact of offering volunteering opportunities and soft skills training independently of actual take-up. 9 We estimate the following individual-level intent-to-treat regression: 𝑌 ௜ ௧ ൌ 𝛼 + 𝜇 ௡ ൅ 𝛽𝑇௧ + 𝛾𝐷 ௜ + 𝛿ሺ𝑇 ∗ 𝐷ሻ ௜ ௧ + 𝜀 ௜ ௧ (1) where 𝑌 ௜ ௧ is the outcome of interest for respondent i in period t, 𝑇௧ is a post-treatment year binary variable, 𝐷 ௜ is a binary variable for being assigned to the treatment, and 𝜇 ௡ is a fixed effect for NGOs. 𝛼 represents the baseline average for the outcome of interest for non-selected youth. 𝛽 is the difference in after-and- before intervention in outcomes for non-selected youth. 𝛽 ൅ 𝛿 is the difference in after-and- before intervention in outcomes for selected youth. 𝛾 is the difference in 9 Due to some procurement delays that caused a big time-lag between baseline data collection and actual NGO project implementation, many of the volunteers who belonged to selected NGOs and who were randomly selected to participate in the impact evaluation study dropped out after their baseline data were collected and were replaced by other volunteers. Project monitoring data reveal that 23 percent of volunteers assigned to treatment did not actually end up participating in the NVSP. Given the relatively high number of non-compliance, we are unable to perform Local Average Treatment Effects (LATE) analyses to understand the impact of participating in NVSP on outcomes of interest.

A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.

A data mention described by its characteristics or producer rather than a proper name.

A data mention that only generally references data, information, or statistics.


Input: Page 8 of 51 In the 9 cases mentioned, it was possible to identify part-time workers, while temporary workers were only identified in the cases of Argentina, Brazil, Chile, Mexico and El Salvador. 4. 1. 1 Variation of the NSE as a percentage of total employment The prevalence of NSE in the total employment has not shown very significant variations in the countries considered in the last two decades (Figure 1). Indeed, most of the countries analyzed show non-standard employment registers similar to those observed in the mid-1990s. The exceptions where the variation is a little more relevant are Brazil and Uruguay, where there are contractions in the incidence of the NSE of the order of 10 and 5 percentage points respectively and Mexico, where there is an increase of 5 percentage points. Figure 1: Prevalence of NSE among salaried employees. (Mid-90s / Mid-2010s) Source: Own calculations based on Household surveys Analyzing the prevalence of NSE by types of occupations, considering the ISCO classification at one digit, we find a quite similar pattern across countries. Indeed, in most of the considered countries, the “ Elementary Occupations ” are the category where the prevalence of NSE is higher.

A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.

A data mention described by its characteristics or producer rather than a proper name.

A data mention that only generally references data, information, or statistics.


Input:
www.gasflaretracker.ng](http://www.gasflaretracker.ng/) has the geographic coordinates of each flaring point in Nigeria as well as monthly estimates of the flare volume from each location.

satellite-detected estimates with the official estimates reported by the Department of Petroleum

Resources [DPR] (2018). The satellite-detected estimates are broken down by location, while the

The paper uses the Romanian firm-level data from the Ministry of Finance covering enterprises of all sizes from 2011 to 2020, combined with the new World Bank Businesses of the State dataset, which tracks ownership of state business entities with at least 10 percent stake in Romania.

World Bank Businesses of the State dataset

Romanian firm-level data from the Ministry of Finance

A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.

A data mention described by its characteristics or producer rather than a proper name.

A data mention that only generally references data, information, or statistics.


Input: The household and family dynamics in Liberia, as in other African settings, can be complex, with families often sending their children to live with relatives who are more able to provide for their schooling and basic needs. Young parents, in particular, often leave home to migrate for work, leaving their children back home with relatives until they are able to establish themselves and send for their children. If the economic success of the EPAG participant allowed her to bring non-resident family members into her household (including but not limited to her own children), then overall household size may have been expected to increase as a result of the program. This does not appear to have happened, at least in the short term. The results in Table 8 show that overall household size was not affected by the program. It is possible that the increase in earnings due to EPAG was too small, or too short-lived, to have induced the kinds of migrations described above. Other measures of household well-being, including food security and asset ownership, reflect shorter- term investments that might be influenced by the economic success of EPAG participants. Panel B of Table 8 shows the impact of EPAG on a broad range of food security measures.

A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.

A data mention described by its characteristics or producer rather than a proper name.

A data mention that only generally references data, information, or statistics.


Input: We use two main data sources for our estimation of a poverty line for Brazil: the 2017/18 Household Budget Survey (Pesquisa de Orçamentos Familares; POF) and the Brazilian Table of Food Composition (Tabela Brasileira de Composição de Alimentos; TBCA). POF is a nationally representative semiregular survey on income and expenditures in Brazil, conducted every six to nine years.

Tabela Brasileira de Composição de Alimentos

A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.

A data mention described by its characteristics or producer rather than a proper name.

A data mention that only generally references data, information, or statistics.


Input: 23 86 % of the IDPs, 91 % of the refugees and 88 % of the returnees are confident or fully confident that a coalition like this would be capable of providing security. Source: Listening to Displaced People Survey, 2014. In an open-ended question on who can be trusted most when it comes to ensuring security in the North, survey results suggest that the majority of refugees in Mauritania (86 %) trust the armed rebel groups as opposed to the army or police. This does not hold for refugees in Niger of whom 75 % trust the army and police. Similar results hold for IDPs and returnees, who put much more confidence in state authorities when it comes to securing the North: most trust is placed in the army and police (72 % of the IDPs and 66 % of the returnees) while little to no trust is placed in armed rebel groups (3 % of IDPs, 1 % of returnees). Usage context: supporting mention, primary mention, background mention.

A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.

A data mention described by its characteristics or producer rather than a proper name.

A data mention that only generally references data, information, or statistics.


Input: Having experienced the work task and therefore able to realistically value the work, we oﬀer individuals in the employment arm an additional [surprise] week of work at a series of wages following the incentivized Becker-DeGroot-Marschak (BDM) method. We inform participants that we have a limited amount of funds remaining and are therefore unable to pay everyone their previous wage. This strategy realistically motivates the reservation wage elicitation exercise and makes clear that there will be no further opportunities for work. We piloted this exercise extensively. To maximize comprehension, we employ a multiple price list strategy, embed repeated conﬁrmations, and conduct a trial run of the exercise for each respondent before the real exercise; this mimics the procedure employed in Burchardi et al. (2021) for which participants in another low-income country ﬁeld context exhibited high comprehension. For those individuals who express willingness to work at a wage of zero, we oﬀer an alternative option of answering a brief survey at the end of the week for a small, randomized fee; we then use the fraction of respondents who are willing to forego this paid option and instead work for free as an estimate of the proportion of respondents who have a negative reservation wage of at least the foregone magnitude. 16 Usage context: primary mention, background mention, supporting mention.

A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.

A data mention described by its characteristics or producer rather than a proper name.

A data mention that only generally references data, information, or statistics.


Input: 11 there is another data source that provides independent information on conflict events. The Uppsala Conflict Data Program, Conflict Encyclopedia Database (UCDP) provides similar information that spans the time period of interest. In contrast, UCDP data is not available for Liberia- so each country draws on similar but distinct data set to incorporate independent information about conflict intensity. The study data set contains one observation for every woman in the DHS individual recode, i. e., the woman level data and variables showing the annual number of ACLED or UCDP events and fatalities beginning in the year the woman was interviewed up to 10 years preceding the survey. Providing conflict for the 10 years preceding the DHS survey is key to the methodology and helps establish temporality in how conflict may affect IPV outcomes. A 10-year period was chosen because this captured hostilities from both Liberian civil conflicts and allowed the data set to reflect the long-standing impact of the conflict in each country. Each conflict data set used is described below. Uppsala Conflict Data Program (UCDP) Data- Colombia The Uppsala Conflict Data Program (UCDP) Georeferenced Event Dataset is an event data set that disaggregates three types of organized violence: state-based conflict, non-state conflict, and one-sided violence. Usage context: supporting mention, primary mention, background mention.

A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.

A data mention described by its characteristics or producer rather than a proper name.

A data mention that only generally references data, information, or statistics.


Input: under the Out-of-Camp Policy (OCP) constitute 5 and 12 percent of the sample, respectively (Figure 2.1). More than 30 percent of refugees in camps are born in Ethiopia (Figure 2.2). Somali refugees have a higher share of refugees born in Ethiopia (38 percent). According to UNHCR estimates (2023)12, around 1.9 million children were born as refugees between 2018 and 2022 globally. Overall, Ethiopia’s refugee situation is protracted; refugees have been in Ethiopia for an average of about 14 years. Refugees differ by country of origin. For example, Eritrean refugees have been in Ethiopia for average of slightly more than 16 years, Somalis for just under 16 years, and South Sudanese for roughly 15 years. On the other hand, refugees in Addis Ababa arrived nine years ago, on average (Figure 2.3a). Globally, the number of refugees in protracted situations—at least 25,000 refugees from the same country who lived in exile for more than five consecutive years—increased over time, accounting for 40 percent of all refugees in 2021 (World Bank, 2023). In Ethiopia, 95 percent of all refugees live in a protracted situation, according to SESRE data. 11 According to UNHCR mid-2022 statistics, South Sundanese, Somali and Eritrean refugees constitute 46, 29

A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.

A data mention described by its characteristics or producer rather than a proper name.

A data mention that only generally references data, information, or statistics.


Input: recently introduced the first version of their Global Internal Displacement Database (GIDD) that allows users to explore, filter and sort IDMC ’ s data to produce graphs and tables, and export underlying data. 102 Such platforms need to incorporate safeguards to protect the privacy and confidentiality of individuals ’ data. UNHCR and Statistics Norway are currently leading an initiative to improve forced displacement statistics with the participation of national statistical agencies. This process began with the presentation of the “ Report on Statistics on Refugees and IDPs ” at the 46th session of the UN Statistical Commission in March 2015, 103 followed by an international conference in Turkey in October 2015. 104 The conference set in motion a process for national statistical agencies to collaborate to develop a set of recommendations that both countries and international organizations can use to improve data collection, reporting, data disaggregation, and overall quality, including the preparation of International Recommendations for Refugee Statistics (IRRS). Progress on this agenda was discussed at the 47th session of UNSD held in New York in March 2016, where it was recommended that the expert group should also include IDPs in its scope of work (UNSD 2016). 105 The current initiative is focused on refugees, asylum-seekers and IDPs but would ideally be extended to host communities and returnees. Usage context: background mention, supporting mention, primary mention.

A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.

A data mention described by its characteristics or producer rather than a proper name.

A data mention that only generally references data, information, or statistics.


Input: Most papers with few exceptions use standard OLS estimators or some of its variants (Table 2). Two papers use general equilibrium models (Bodvarsson, Van den Berg, and Lewer 2008; Hercowitz and Yashiv 2002) and two papers simply compare means between treated and non-treated groups resulting in simple difference estimations (Card, 1990 and Alix-Garcia and Bartlett, 2015). [Table 2] The unit of observation varies depending on the data at hand. Most studies rely on household survey data where individuals or households are the unit of observations and most studies include some regional dimension (more frequently administrative areas). Where longitudinal or panel data are available time is also included. Other choices for unit of observations include skills or education level, various types of population groups (based on gender, age etc.), and, in a few cases, economic sectors, industry or labor market segments. The use of fixed effects varies. Some papers use the full set of parameters depicting units of observation (for example, household, region and time fixed effects in equations where the unit of observation is constructed using household, region and time). Other papers use subsets of these parameters whereas other papers introduce variables that are not used to identify the unit of observation. Usage context: primary mention, supporting mention, background mention.

A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.

A data mention described by its characteristics or producer rather than a proper name.

A data mention that only generally references data, information, or statistics.


Input: months” and “last 12 months” as references. Imputed rent for owner-occupied houses is calculated by the Ethiopian Statistical Service (ESS) team and is included in the consumption expenditure data shared with the Bank team. Spatial and temporal price deflators adjust for price variations across time and space. First, nominal consumption is adjusted for price differences across survey domains using spatial deflators calculated using the Household Welfare Statistics (HoWStat 2021) survey data. Second, spatially-deflated consumption levels are expressed in December 2022 prices using the food and non-food Consumer Price Indexes produced and provided by the ESS. Finally, to adjust for variations in household size and composition, the spatially and temporally adjusted consumption expenditure is divided by household size. This is because the poverty rates presented in this chapter are calculated using the international poverty line of USD 2.15 per capita in 2017 PPP. The US$2.15 poverty line was converted to local currency in 2017 using the PPP conversion factor, and then the value was inflated to December 2022 prices using the national CPI. Given that international poverty estimates reported at the global level are based on consumption aggregates not spatially deflated, the poverty reports presented in this report are not strictly

Household Welfare Statistics (HoWStat 2021) survey

food and non-food Consumer Price Indexes

A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.

A data mention described by its characteristics or producer rather than a proper name.

A data mention that only generally references data, information, or statistics.


Input:
**Annex 12: CAT DDO Trigger Conditions and Drawdown Procedure**

The CAT DDO facility may be drawn down upon declaration of a state of natural disaster by the Council of Ministers, provided that the macroeconomic trigger conditions specified in the Loan Agreement are satisfied. The declaration must be accompanied by a damage and needs assessment prepared by the national disaster management agency and reviewed by a Bank-approved assessment team. Drawdown requests under the CAT DDO are processed within ten business days of receipt of a complete and satisfactory trigger documentation package.

A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.

A data mention described by its characteristics or producer rather than a proper name.

A data mention that only generally references data, information, or statistics.


Input:
Additionally, local and
upstream shares of forest cover are measured using satellite data from the European Space Agency.

###### 3. Empirical Strategy

Our econometric specification uses a panel fixed-effects model to link data on droughts to data on
economic growth at the level of 0.5-degree grid cells (approximately 56 kilometers x 56 kilometers at the
equator) between 1991 and 2014, the period for which economic data is available at a granular scale.

In robustness checks we also make use of the Standardized Precipitation Evapotranspiration Index (SPEI) (Vicente-Serrano, et al., 2010) that integrates evapotranspiration into the standard precipitation index.

We use data from the ESA CCI project to determine the share of cropland within each cell at the beginning of the period (ESA starts in 1992) and split the sample based on different shares of cropland ranging from less than 20 percent to more than 75 percent.

2 UNCCD Report "Drought in Numbers 2022."
3 Defined here as shocks that are at least 2 standard deviations (SDs) below the long-term mean. Note that a 2 SD dry
shock is a very rare event and includes the driest 2.5 years in a century.

The magnitudes of the effects are also consistent with the recent 2022 Global Assessment Report on Disaster Risk Reduction which looks at all types of disasters from rapid onset events like typhoons, floods, earthquakes to other events like droughts, saltwater intrusion, air pollution.

Standardized Precipitation Evapotranspiration Index (SPEI)

satellite data from the European Space Agency

A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.

A data mention described by its characteristics or producer rather than a proper name.

A data mention that only generally references data, information, or statistics.


Input: Consequently, they may fear detection by authorities when asked to respond to surveys or participate in public initiatives. 1 Furthermore, collective repre- sentative and longitudinal data on forcibly displaced migrants, a population with high mobility rates, is difficult and costly (Ib ´ a ˜ nez et al. 2024). This complexity is compounded when focusing on children and adolescents, given the need for enumerators to receive specific training to interact with such a vulnerable demographic and for migrant parents to authorize their children ’ s involvement despite prevailing distrust issues. To address this knowledge gap, we launched the Venezuelan Refugee Panel Study for Kids (VenRePs-Kids) in Medell ´ ın, Colombia. VenRePs-Kids is a longitudinal study repre- sentative of forcibly displaced Venezuelan and Colombian children and adolescents aged 5 to 17. To our knowledge, it is the first study to gather panel data specifically on forcibly 1This concern is also prevalent among undocumented migrants in the United States, as highlighted by Amuedo-Dorantes and Lopez (2015). 2

VenRePs-Kids
Venezuelan Refugee Panel Study for Kids

A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.

A data mention described by its characteristics or producer rather than a proper name.

A data mention that only generally references data, information, or statistics.


Input: 26 Buller et al. (2016) conducted a mixed methods study in Ecuador, combining secondary analysis from a field experiment on the impact of a transfer program on IPV with in-depth interviews and focus group discussions with male and female beneficiaries. The qualitative component aimed to better understand the mechanisms underlying the quantitative results, which showed substantial reductions in physical and sexual violence among beneficiaries of the cash and in-kind food transfer program. These qualitative interviews revealed a similar finding to Arugay et al. (forthcoming). Specifically, a core feature of women ’ s reported joint decision making was asking their spouse or partner for input into a decision, so that they would not be blamed if something went wrong. Similarly, an analysis of qualitative data from eight projects in Africa and Asia focused on understanding women ’ s empowerment finds that joint decision making can be empowering for women. In particular, in focus groups in Ghana, women stressed the importance of family harmony and in the individual interviews, “ women indicated that they want more input on decisions, but do not want full responsibility for decisions in case they go wrong (Meinzen-Dick et al, 2019, p. 20). The qualitative evidence provides one interpretation of our empirical results. Couples who agree that they jointly make decisions may also be sharing responsibility for these decisions. Usage context: primary mention, supporting mention, background mention.

A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.

A data mention described by its characteristics or producer rather than a proper name.

A data mention that only generally references data, information, or statistics.


Input: This database lists seven categories: refugees, asylum-seekers, returned refugees, internally displaced persons (IDPs), returned IDPs, stateless persons and others of concern. For each group the database provides yearly information about their composition by loca- tion of residence and origin. We exploit only the data on “ refugees ”. 22 In particular, we are interested in the annual stock of refugees for each country of residence, i. e. how many people with refugees status have left their home country each year. We focus on these numbers as they appear to be the most comparable across time and countries. However, this is likely to capture only the tip of the iceberg in some cases. The number of IDPs is extremely high in some instances but cannot be captured with the same level of conﬁdence as refugees generally. 23 Cross-country data about conﬂict is provided by the UCDP / PRIO. As for the index of country-level economic activity, we use again information provided by the Penn World Table and World Bank databases. As mentioned above, our aim is to explore the dynamics of refugees during conﬂicts. In other words, we attempt to answer several questions. Usage context: primary mention, background mention, supporting mention.

A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.

A data mention described by its characteristics or producer rather than a proper name.

A data mention that only generally references data, information, or statistics.


Input: refugee situation and to devise policy directions. The SESRE covers three types of groups: (i) refugees in camps; (ii) refugees out-of-camps in Addis Ababa; and (iii) host communities; all of which require a distinct sampling procedure. The sampling frame for refugee camps is based on UNHCR’s proGRES database. SESRE is a representative survey of the refugee population 1 Formerly the Household Consumption and Expenditure Survey and Welfare Monitoring Survey. EXECUTIVE SUMMARY iii of Eritrean, South Sudanese, and Somali origin living in camps in Ethiopia, refugees living in Addis Ababa, and their respective host communities. Host communities are defined as Ethiopian non-displaced households living enumeration areas adjacent to the refugee camps. SESRE data was collected from November 2022 to January 2023, from a nationally representative sample of 3,452. The following represents a summary of findings stemming from the SESRE data and associated statistical regression work using this data. Sociodemographic Ethiopia is a second home for close to one million refugees who predominantly originate from South Sudan, Somalia, and Eritrea. Around 88 percent of refugees live in camps, and the rest reside in urban areas under the Out-of-Camp Policy (OCP) regime. Refugees fled from their country mainly due to conflict and violence.

A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.

A data mention described by its characteristics or producer rather than a proper name.

A data mention that only generally references data, information, or statistics.


Input: Appendix A Data Appendix A. 1 Linking Ethnic Data from Africa (LEDA) LEDA offers an interface — a language tree — to flexibly link ethnic groups from different databases to each other and calculate the linguistic distances between them. LEDA is currently structured around lists of ethnic groups from 12 original datasets, which are the following:  Afrobarometer Surveys  All Minorities at Risk (AMAR)  Census data from IPUMS  Ethnic Power Relations (EPR) dataset  Ethnologue languages  Political Relevant Ethnic Groups from Posner (2004)  Ethnic groups in Francois, Trebbi & Rainer (2015)  Ethnic groups from Fearon (2003)  GREG Data (based on the Russian Atlas Miradova)  Demographic and Health Surveys  Murdock Atlas  Spatially Interpolated Data on Ethnicity (SIDE) These lists are structured in LEDA ’ s interface by data source, country, year, or in the case of survey data, survey rounds. In our analysis, we use Afrobarometer, EPR, and Murdock Atlas data; therefore, we can use LEDA functions to link the different ethnic groups to each other. LEDA consists of three main linkage types: binary linking based on the relations of sets of language nodes associated with two groups; binary linking based on linguistic distances; and a full computation of dyadic linguistic distances.

Spatially Interpolated Data on Ethnicity

A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.

A data mention described by its characteristics or producer rather than a proper name.

A data mention that only generally references data, information, or statistics.


Input: Due to the variations in weight and height ratios among children and adolescents according to gender and age, the benchmarks for determining nutritional status are specifically tailored to these factors. We adhere to WHO guidelines to calculate the standardized BMI values for minors. A BMI exceeding one standard deviation (SD) from the mean suggests overweight, while a BMI less than minus one SD indicates underweight. 16 Health status is assessed through a binary variable, assigned a value of one if the caregiver has reported any health issues such as disease or chronic pain, accidents, dental pain, surgical interventions, or preg- 14For the Colombian households the wealth index is measured with contemporaneous data. 15This procedure restricts the sample to the common support of the propensity score for being a forced migrant and weights observations for Colombian kids by a non-parametric function of the propensity score. This procedure has been shown to increase the estimate ’ s efficiency. 16Furthermore, a BMI greater than 2SD is indicative of obesity risk, and less than- 2SD signals a risk of severe thinness. 33 Usage context: primary mention, background mention, supporting mention.

A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.

A data mention described by its characteristics or producer rather than a proper name.

A data mention that only generally references data, information, or statistics.


Input: which increases signiﬁcantly under both treatment arms. In other words, the psychosocial value to employment appears to be driven largely by the non-pecuniary dimensions of the employment experience. 5. 4 Impacts of employment on reported physical health, cognitive function, and economic decision-making The positive eﬀects of employment extend to other measures beyond psychosocial health. Table 3 presents results on reported physical health, cognitive function, and incentivized measures of risk and time preference. We observe a signiﬁcant increase in the days reported healthy. This eﬀect may be due to ‘ real ’ health improvements from increased exercise (which has also been documented to translate to improved mental health (Herbert et al. (2020))) from the employment task or ‘ perceived ’ health improvements in which improved psychoso- cial well-being translates into feeling less physically ill. Should the channel be exercise, we may expect health improvements to grow over time. Our weekly data on days healthy sug- gests this is not the case: we observe the treatment eﬀect on health from the ﬁrst week of working, and the gap remains steady throughout the following two months (Appendix Figure A3). Usage context: primary mention, background mention, supporting mention.

A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.

A data mention described by its characteristics or producer rather than a proper name.

A data mention that only generally references data, information, or statistics.


Input: 17 significant for both selected and non-selected youth (see the 𝛽 ൅ 𝛿 estimate and the 𝛽 estimate for columns 2 & 3). Lack of results also holds for specification 3, where imputing missing data with upper and lower bound estimates to account for the potential bias introduced by attrition did not alter the lack of impact of the program, as well as for specification 4 (see the 𝛿 estimate). Figures 1, 2, and 3 plot the distribution of soft skills scores at baseline for both selected and non- selected youth. The figures indicate that scores across the three skills are concentrated towards the end of the scale, suggesting that soft skills training offered by NVSP might have been ineffective or too basic for this pool of volunteers. 19 Indeed, as table 1 shows, a high percentage of selected youth (71 percent) and non-selected youth (63 percent) had taken previous training in soft skills prior to NVSP. Results from a process evaluation conducted separately support this explanation. The majority of NVSP volunteers in focus group discussions and interviews mentioned that they would have welcomed more advanced trainings on soft skills, as well as on technical topics and job-relevant skills that can support their employability. Usage context: background mention, primary mention, supporting mention.

A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.

A data mention described by its characteristics or producer rather than a proper name.

A data mention that only generally references data, information, or statistics.


Input: NGOs. Initiatives such as JIPS, a collaborative project of UN and NGO actors, have also been established to support governments and operational organizations to design and implement data collection processes. There are a variety of data sources for generating statistics on forced displacement, each of which has strengths and weaknesses. Despite the significant challenges, large amounts of data are collected and disseminated every year. The main data sources and methods for the generation of statistics on forcibly displaced populations include: (a) registration of refugees and asylum-seekers; (b) registration of IDPs; (c) profiling of IDPs; (d) population movement tracking systems; (e) national population censuses; (f) sample surveys; (g) border crossings; (h) administrative records and registers; (i) general population registers; and (j) a variety of estimation methods for producing statistics when adequate and reliable data on individuals are unavailable (UNSD 2014). Several of these data sources might be used together to triangulate estimates of stocks and flows for a particular displacement situation. Usage context: primary mention, supporting mention, background mention.

general population registers
sample surveys

A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.

A data mention described by its characteristics or producer rather than a proper name.

A data mention that only generally references data, information, or statistics.


Input: Figure 2. Location of Households in the VenReP-Kids Sample Notes: The figure depicts the exact geographic location of all the households in the VenRePs-Kids study. Green and blue dots depict the location of Colombian and Venezuelan households, respectively. The map in the upper right corner illustrates the location of Medell ´ ın (blue pin) with the department of Antioquia (highlighted in red). survey focuses on strata 1 through 4, intentionally omitting strata 5 and 6 to avoid bias toward higher-income groups which are less likely to include migrants in need of sup- port. 14

A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.

A data mention described by its characteristics or producer rather than a proper name.

A data mention that only generally references data, information, or statistics.


Input: Operators/Assemblers Craf/Related Trade Workers Skilled Agricultural Workers Service/Sales Workers Clerical Support Workers Tech/Associate Professionals Managers/Professionals Percent Figure D.19: Occupation by survey domains Source: World Bank Staff based on SESRE 2023. 0 10 20 30 40 50 60 70 80 90 100 Eritrean Somali South Sudanese Inside the camp Outside the camp Percent Figure D.20: Work location by survey domains Source: World Bank Staff based on SESRE 2023. 0 5 10 15 20 25 30 35 40 45 50 Hosts Refugees Hosts Refugees Hosts Refugees Eritrean Somali South Sudanese Figure D.21: Hours per week by survey domains Source: World Bank Staff based on SESRE 2023. Annexes 109 0 10 20 30 40 50 60 70 Hosts Refugees Hosts Refugees Hosts Refugees Eritrean Somali South Sudanese Figure D.22: Hourly earnings by survey domains Source: World Bank Staff based on SESRE 2023. 0 0.1 0.2 0.3 0.4 0.5 0.6 Hosts Refugees Hosts Refugees Hosts Refugees Eritrean Somali South Sudanese Figure D.24: Household owns livestock Source: World Bank Staff based on SESRE 2023. 0 0.1 0.2 0.3 0.4 0.5 0.6 Hosts Refugees Hosts Refugees Hosts Refugees Eritrean Somali South Sudanese Figure D.23: Household owns crops Source: World Bank Staff based on SESRE 2023. 0

A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.

A data mention described by its characteristics or producer rather than a proper name.

A data mention that only generally references data, information, or statistics.


Input:
UNHS. Data were collected over a 12-month period. The sample used in this paper is

characteristics also differ between the two groups. Table 1 summarizes relevant socio
economic and child anthropometric variables by ownership and per capita consumption

8

<!-- PAGE 11 -->
expenditure terciles for the 2005/06 UNHS and the 2009/10 UNPS. [3] Descriptive statistics on

DHS. (2011). Uganda Demographic and Health Surveys, 2011. Data accessed via & Hautvast, J. (1989)
Increased Risk of Vitamin B-12 and Iron Deficiency in Infants on Macrobiotic Diets. _The_
_American Journal of Clinical Nutrition_, 50, 818-824.

PAGE 31 --> Kabubo-Mariara, J., Ndenge, G. & Mwabu, D. (2009). Determinants of Children's Nutritional Status in Kenya: Evidence from Demographic and Health Surveys. _Journal of African_ _Economies_, 18(3), 363-387.

Uganda Demographic and Health Surveys
Demographic and Health Surveys

A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.

A data mention described by its characteristics or producer rather than a proper name.

A data mention that only generally references data, information, or statistics.


Input: 13 degree of group bias. Thus, should the program reduce bias, 𝜓𝜓7 < 0. 𝑋𝑋is the same 𝑛𝑛 × 𝑘𝑘 matrix of control variables. 𝜓𝜓 is a 𝑘𝑘 × 1 vector of regression coefficients; and 𝜔𝜔 is the idiosyncratic error. We employ two small deviations from these approaches to produce the full set of results. First of all, as we do not have two sets of control variables from outreach to baseline, we run a fixed effects analysis to understand the impact of assignment to treatment status on life and economic optimism. Second, due to a data collection error in the field, indicators of economic scarcity were not collected from all of the control group at baseline. Instead, we seek to approximate the effect of treatment on these indicators by triangulating comparisons in two dimensions. First, we test whether or not these indicators improved for the treatment group from baseline to endline. Second, we test whether or not there are differences between the treatment and control groups at endline. This stops short of causality but still reveals interesting information about the dynamics at play. We produce five outputs for each analysis, with the exception of the economic scarcity indicators. First, we use uncontrolled OLS. Second, we introduce control variables. Third, we remove the controls but add inverse probability weights.

A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.

A data mention described by its characteristics or producer rather than a proper name.

A data mention that only generally references data, information, or statistics.


Input: Cross-sectoral programming designed to meet families ’ holistic needs would also increase the odds of maternal and child well-being, including increasing provision of cash transfers through BISP, expanding access to ECE programs, ensuring food availability and affordability for mothers, and implementing emergency-response programs for continuity of basic services in the context of floods and other disruptive disasters to protect vulnerable mothers and young children. Both direct interventions that provide mental health services and indirect interventions that reduce exposure to stressors within communities and households are approaches to alleviate mental health concerns among mothers of young children in the FCV setting of the current study. In addition to individual-level impacts, societal and economic impacts result from reduced maternal depression, anxiety and stress. For example, costing estimates from Pakistan suggest that there is a $ 16. 6 billion cost per cohort of unaddressed maternal mental health concerns (Bauer et al., 2024). Limitations The data collection coincided with a politically sensitive time in Khyber Pakhtunkhwa, inclusive of security concerns for enumerators, ongoing election campaigns, and occasional disruptions to data collection, which could have impacted the accuracy and consistency of data collected. Further, repatriation efforts being implemented during the data collection period led researchers to avoid self-report determination of refugee (documented and undocumented) status and rely on enumerator report using observable indicators as outlined above. This may have therefore impacted the accuracy of the data on identifying refugee households. There are also several measurement constraints to be considered. The tools selected to measure maternal mental health may not cover all relevant dimensions of symptoms and experiences specific to the region of Pakistan studied, even though tools were specifically selected based on previous adaptation, validation and use in the province. Usage context: primary mention, supporting mention, background mention.

A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.

A data mention described by its characteristics or producer rather than a proper name.

A data mention that only generally references data, information, or statistics.


Input:
There are different ways to arrive at a value for housing services consumed by nonrenters, which have different advantages and disadvantages (see Deaton and Zaidi, 2002). In POF, households that own their dwelling (even if still paying the mortgage) or that

_Temporal and spatial price adjustment._ To make the consumption aggregate and average costs per calorie
comparable across households, we adjust expenditure values temporally and spatially. POF was collected
throughout a full year and its reference periods go back up to 12 months. Figure 2 shows the temporal
variation of prices for different Brazilian states over the reference period of the survey. On average, prices
increased by 26.8 percent over the reference period - a monthly average of 1 percent. IBGE (2020)
provides temporal deflators in the publicly available data, which we use to deflate prices and the
consumption aggregate to express all monetary values in January 2018 values.

13 There are several differences between our consumption aggregate and other studies using POF data. In one of the
most recent ones (Oliveira et al. 2016), the authors aim to measure and analyze welfare, poverty (using the
administrative "poverty'' line equivalent to half a minimum wage), inequality, and vulnerability.

Midwest-Rural 0.997 0.671 0.933
_Source:_ Own calculations using POF 2017/18 data.
_Note:_ Prices in the urban Southeast are the reference prices. While we use household-specific price indices in our estimations,
for ease of presentation we calculated regional averages of household-specific indices and divided them by the
Southeast-Urban average.

A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.

A data mention described by its characteristics or producer rather than a proper name.

A data mention that only generally references data, information, or statistics.


Input:
Notes: The table displays the mean and standard deviations of several characteristics of all students
matched in the ENILEMS-ENLACE (column 1), students that reported to be in college (column 2),
out of college (column 3) or employed (column 4). Data: ENILEMS-ENLACE panel.

30

<!-- PAGE 33 -->
Table 3: OLS - ENLACE test scores and secondary school outcomes: simple correlations

Notes: (1) The table displays the estimation of the effect of early test scores on grade 9 and 12 test scores and enrollment by subject and
grade. (2) Specifications for each subject and grade include as independent variables grade 6 test scores of the same subject. (3) Sample:
Twins (students in the same school in grade 6, with identical last names and birth date. (4) All specifications include twins fixed effects. (5)
Robust standard errors are reported in parentheses. *** p _<_ 0.01, ** p _<_ 0.05,  - p _<_ 0.1.

<!-- PAGE 46 -->
Table A.4: OLS       - ENLACE mathematics and Spanish test scores and post-secondary school outcomes

Enlace Score 0.102*** -0.00750 0.0681** -0.000444 (0.0154) (0.0297) (0.0304) (0.0298) Upper Secondary GPA 0.0688*** 0.0412* -0.00579 0.00507 (0.0146) (0.0233) (0.0268) (0.0254) Girl -0.0500* -0.237*** -0.0321 0.00994 (0.0263) (0.0442) (0.0501) (0.0478) Private Upper Secondary 0.113*** -0.0962 0.0606 -0.0842 (0.0320) (0.

A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.

A data mention described by its characteristics or producer rather than a proper name.

A data mention that only generally references data, information, or statistics.


Input: .00994 (0.0263) (0.0442) (0.0501) (0.0478) Private Upper Secondary 0.113*** -0.0962 0.0606 -0.0842 (0.0320) (0.0649) (0.0736) (0.0653) Urban resident 0.269*** 0.0373 0.0944* 0.137** (0.0375) (0.0472) (0.0535) (0.0566)

A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.

A data mention described by its characteristics or producer rather than a proper name.

A data mention that only generally references data, information, or statistics.


Input: The age categories are 15 – 19, 20 – 24, 25 – 29, 30 – 34, 35 – 39, 40 – 44, 45 – 49, 50 – 54, 55 – 59, and 60 – 64 years. There are 183 groups since we exclude groups containing less than 40 observations. 24 An additional advantage of the IV approach is that it helps deal with measurement problems. Despite the improved measures of refugee numbers in Turkey by subregion starting in 2014, there is likely considerable measurement error, resulting in attenuation bias in the OLS estimates. For the IV estimates to be consistent, it is only necessary that- conditional on the fixed effects and control variables- the flows of Syrian refugees are uncorrelated with the instrument. 25 Using data from AFAD (2013) we can also weight the aggregate refugee numbers using the Syrian source governorates of refugees in 2012-13 (see Figure 2). Results are qualitatively robust to this alternative instrument and first-stage F-statistics about the same. We prefer the use of the pre-war distribution of population in Syria, Usage context: primary mention, supporting mention, background mention.

A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.

A data mention described by its characteristics or producer rather than a proper name.

A data mention that only generally references data, information, or statistics.


Input: 6. Robustness Checks 6. 1. Sample attrition Many challenges were encountered during survey implementation, due to the context – the densely populated and impoverished communities in and around Monrovia are difficult settings in which to find and track respondents — as well as the transience of a young study population. Despite vigorous efforts to track and interview each individual in the sample, a certain amount of survey attrition was expected. As the survey response rates in Table 1 show, 1622 (or 80 %) of the individuals in the study sample were successfully interviewed in both the baseline and midline surveys. Another 305 respondents were interviewed at baseline but not at midline and hence are not in the panel used for the analysis in this paper. 27 This survey attrition, while not much higher than other program evaluations in Africa, may cause concern that the results of this evaluation are biased, especially if the loss to follow up is correlated with individual characteristics that might affect the outcomes. To address this concern, Table 10 presents regressions on the likelihood of panel inclusion, that is, the likelihood of being interviewed at both baseline and midline. The first column indicates that treated individuals are significantly more likely than control to have been interviewed twice. This result persists even after controlling for individual characteristics and community dummies. Usage context: background mention, primary mention, supporting mention.

A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.

A data mention described by its characteristics or producer rather than a proper name.

A data mention that only generally references data, information, or statistics.


Input:
Firstly, the Hydrosheds variant of SRTM is used, both at 3 and 30 arc second resolutions. A number of additional corrections are applied to the terrain data including a systematic vegetation correction procedure in vegetated areas and an urban correction procedure in urbanized areas. A detailed description of the modeling framework is provided by (Sampson et al. 2015).

For this study, we developed flood hazard maps representing riverine, flash-flood and coastal flood risk for Vietnam. These flood hazard maps estimate the inundation depth at a grid cell level of 3 arc-seconds, (~ 90m) and provide coastal surge hazard layers, along with pluvial and fluvial layers. The maps provide information on the extent and depth of flood hazard for a specific location. For the coastal component, we explicitly model four return periods - 25, 50, 100, and 200 year events, under current and future climate conditions.

Data on natural capital is sourced from a World Bank dataset on national wealth. The dataset disaggregates the three components of national wealth-produced capital, intangible capital and natural capital-and it decomposes the natural wealth stock into renewable and nonrenewable resources.

The data on income inequality is sourced from the World Bank's "All-the-Ginis Database,"
which was last updated in 2014. [8] The database collects Gini indexes from multiple sources
into long time series. The data has been standardized for this analysis via the so-called
"choice-by-precedence approach," which reflects each dataset's reliability, degree of
variable standardization, and consistency of geographical coverage. GDP and population
figures have been collected from the United Nation's UNCTAD-STAT database. Table 2
presents the descriptive statistics for per capita GDP and the Gini index by country
income group. The Gini index peaks among the upper-middle-income group, falls among
the lower-middle-income and low-income groups and is lowest among the high-income
group. These data are consistent with the relationship between inequality and GDP
described by Kuznets (1955).

A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.

A data mention described by its characteristics or producer rather than a proper name.

A data mention that only generally references data, information, or statistics.


Input:
Abstract
Behavioural surveillance surveys (BSSs), an evolution from the knowledge �attitudes practice surveys (KAPs), are a tool to track trends in HIV/AIDS knowledge, attitudes
and risk behaviour among populations. The data collected support organizations in
targeting specific HIV/AIDS prevention and care activities, monitoring their effectiveness
and coverage, and allocating scarce resources. The objectives are to evaluate the quality and
standardization of BSS-like surveys undertaken in conflict and post-conflict situations, and
to provide recommendations to humanitarian agencies and governments on how to
improve their quality. Survey methodology was classified as reproducible if the populationbased sampling defined a sampling frame using probabilistic sampling. Survey indicators
were compared to internationally-accepted HIV indicators. The results showed that 14
(45.2%) of the 31 BSS-like surveys evaluated between 1998 and 2005 in 14 countries were
classified as reproducible. Surveys undertaken by non-governmental organizations
(NGOs) were significantly less reproducible than those undertaken by non-NGOs (p �/
0.05). The majority of surveys used at least one identical or similarly worded
internationally-accepted HIV indicator for prevention and misperception but not for
practice and attitudes. Few reported disaggregated indicators according to age or gender. It
was concluded that the majority of BSS-like surveys are of insufficient methodological rigor
to be reproducible. Few surveys reported internationally-accepted HIV indicators by
gender and age which makes interpretability and comparison difficult. United Nations
agencies, NGOs, and governments undertaking BSSs in conflict and post-conflict settings
should proceed with a BSS survey once the design and plan for execution has been prepared
by experienced and qualified experts. These experts should then oversee the survey, assure
data quality and incorporate training of others in the process. A practical and field userfriendly BSS manual is needed for conflict affected and displaced population situations,
one which is customized to take into account the special circumstances of such populations.

Abstract
Behavioural surveillance surveys

A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.

A data mention described by its characteristics or producer rather than a proper name.

A data mention that only generally references data, information, or statistics.


Input: Figure A4: Participation certiﬁcate to boost ‘ resume ’ CERTIFICATE THIS ACKNOWLEDGES THAT I engaged with Pulse Bangladesh to do data collection Notes: The wording of the certiﬁcate was made such that it could be applied to both arms; cash-only arms participated in weekly surveys along with all other experiment participants, so technically also engaged in data collection for our project. 60 Usage context: background mention, primary mention, supporting mention.

A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.

A data mention described by its characteristics or producer rather than a proper name.

A data mention that only generally references data, information, or statistics.


Input: Page 14 of 51 Source: Own calculations based on Household surveys From the education perspective, an improvement in the profile of workers employed as NSE can be observed in the countries analyzed, even though there are some exceptions. In fact, in most of the countries of our sample, the prevalence of workers with secondary and tertiary education increases in detriment of workers with a lower educational level. However, there are some differences by type of non-standard employment. In the case of part-time employment (Figure 10), several countries show an obvious rise in the prevalence of workers with secondary and tertiary education (Argentina, Brazil, Peru, and Mexico). There is a second group of countries that presents a decrease in the prevalence of workers at the secondary level, but, this decrease is more than compensated by the greater incidence of tertiary workers, so that, taken together, workers with secondary or higher education increased their share within part-time employees (Uruguay and Chile). Therefore, we can also conclude from this group that part-time employment presents a better educational profile today than two decades ago. In the Dominican Republic and El Salvador, we find a rise in the prevalence of workers with secondary education but a decrease in the share of workers at the tertiary level.

A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.

A data mention described by its characteristics or producer rather than a proper name.

A data mention that only generally references data, information, or statistics.


Input: during the sampling and data collection stages. Moreover, our thanks go to the following UNHCR colleagues for their invaluable comments on the various draft stages of this report: Emily Lugano, Annick-Laure Tchuendem, Jed Fix, Theresa Beltramo, Alessio Baldaccini, Anna Gaunt, Asaad Kadhum, Benoit d’Ansembourg, Berhanu Geneti, Campbell Macknight, Daniel Gebrekidan, Florah Bukania, Florence Nimoh, Johannes Abate, Joyce Wahome, Katie Ogwang, Nada Omeira, Nathalie Bussien, Robert Nyambaka and Yukta Kumar. Our thanks also go to our JDC colleagues Felix Schmieding (Senior Statistician, UNHCR) and Harriet Kasidi Mugera (Senior Data Scientist, World Bank) for their tireless support and advice during the preparation of SESRE. The report benefited from the insights of peer reviewers: Leslie Velez, Mulualem Desta, Takaaki Masaki (Senior Economist, World Bank), and Precious Zikhali (Senior Economist, World Bank). We are indebted to Nistha Sinha (Senior Economist, World Bank) for her constructive comments that significantly enhanced the report. We also recognize Aldo Morri for his excellent editorial support. Finally, we extend our deepest gratitude to the survey respondents for their willingness to share their experiences which has been instrumental in deepening our understanding of the challenges and needs faced by both refugees and host households. ACKNOWLEDGEMENTS ii Introduction E thiopia, with

A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.

A data mention described by its characteristics or producer rather than a proper name.

A data mention that only generally references data, information, or statistics.


Input: Using Afrobarometer ’ s geocoded surveys, we focus on clusters as our unit of observation. 10 Our sample consists of 7, 547 such locations and 76, 518 individuals in 23 countries in Sub-Saharan Africa. “ The sampling universe normally includes all citizens age 18 and older. As a standard practice, they [we] exclude people living in institutionalized settings, such as students in dormitories, patients in hos- pitals, and persons in prisons or nursing homes. ” (Afrobarometer, https: / / afrobarometer. org / surveys − and − methods / sampling − principles) Since the sampling frame is based on recent censuses, with the aim of representing all citizens of voting age in a given country, the Afrobarometer samples are unlikely to include refugees. Note also that “ the sample design is a clustered, stratified, multi-stage, 8We explain the construction of theses indices in Section 4. 2. 9We test the robustness of our results with a smaller (40 km) and a larger (120 km) radius in Section 5. 3. This choice of buffer size assures us that between 75 percent and virtually all refugee camps fall within a cluster buffer. Other studies relying on Afrobarometer data construct buffers ranging from 25 km (e. g., Michaelopoulos and Papaioannou (2011), investigating ethnic-specific pre-colonial institutional structures) to 100 km (e. g., McGuirk and Burke (2020a), analyzing the impact of food-price shocks on conflict). 10Afrobarometer is a pan-African research network conducting public attitude surveys on democracy, governance, the economy, and society in African countries that are repeated on a regular basis (Afrobarometer, 2020). 10 Usage context: background mention, primary mention, supporting mention.

A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.

A data mention described by its characteristics or producer rather than a proper name.

A data mention that only generally references data, information, or statistics.


Input: Second, there are cases where the current study reports data by nationality, but the corresponding figure in the Trends in International Migrant Stock refers to the foreign born. This situation generally arises when a census does not report the number of foreign-born migrants on a bilateral basis. Examples include Austria and Côte d ‘ Ivoire. Third, differences in the years to which the data refer can generate large disparities. For example, this study uses the 1966 data for Australia, whereas Trends in International Migrant Stock reports data for 1970. Overall, however, the fact that the totals are remarkably close in every decade adds credence to the estimates here. IV. THE EVOLUTION OF GLOBAL BILATERAL MIGRATION The greatest strengths of the global migration matrices are their bilateral coverage, the number of decades covered, and the disaggregation by gender. These data are too rich for a full analysis of all movements between all pairs of countries. Instead, this section summarizes the major trends in the evolution of bilateral migrant stocks, based primarily on World Bank regions. 25 Global Trends The migration matrix for the 1960 census round reflects a realigning world in the postcolonial era. Over the 1960-2000 period, the composition of world migration 25 Appendix 1 details the World Bank regions: South Asia, East Asia and Pacific, Sub-Saharan Africa, Latin America and the Caribbean, Europe and Central Asia, and Middle East and North Africa. High-income Middle East and North Africa refers to the predominantly oil producing countries in the Persian Gulf (Bahrain, Kuwait, Oman, Qatar, Saudi Arabia, and the United Arab Emirates) and to Israel. Usage context: supporting mention, background mention, primary mention.

A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.

A data mention described by its characteristics or producer rather than a proper name.

A data mention that only generally references data, information, or statistics.


Input:
### 6.1 Grievance Redress Mechanism

The project-level GRM will receive and process complaints related to beneficiary selection, service delivery, labor conditions, environmental impacts, and GBV incidents. A dedicated toll-free hotline, an SMS channel, and physical suggestion boxes at community centers will serve as intake points. All complaints will be logged in the MIS within 24 hours of receipt and assigned to the responsible district coordinator for investigation. Complainants will receive a response within 15 working days, with more complex cases referred to the PIU's E&S specialist for resolution.

A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.

A data mention described by its characteristics or producer rather than a proper name.

A data mention that only generally references data, information, or statistics.


Input: natural log of a country ’ s population size and government consumption as a share of GDP; the latter is the most widespread measure of government size (Adsera and Boix, 2002; Alesina and Wacziarg, 1998; Rodrik, 1998). Tax compliance is also related to the government ’ s ability to eﬀectively detect and punish tax avoiders, tax evaders, and tax arrears. Although an imperfect measure of states ’ deterrent capacity, Afrobarometer includes two survey questions on perceptions of government enforcement and monitoring capacities. One question probes respondents on how often ordinary people who break the law go unpunished. The other probes respondents on how often oﬃcials who commit crimes go unpunished. This latter question is also a measure of perceived government fairness- the extent to which a government implements the law evenly across all social groups. 6. 2. 5 Procedural Justice I include two indicators of procedural justice. The ﬁrst probes respondents on how often people are treated unequally under the law. The next taps citizens ’ perceptions of the government ’ s treatment of their ethnic group. Speciﬁcally, respondents were asked how often their ethnic group is treated unfairly by their government. 9 6. 2. 6 Donor and Non-State Actor Provision of Services I include a measure of who citizens believe is responsible for collecting income taxes.

A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.

A data mention described by its characteristics or producer rather than a proper name.

A data mention that only generally references data, information, or statistics.


Input:
<!-- PAGE 7 -->
As we did not have meteorological data for each and every municipality in Chile, this
information was estimated. Since average annual temperature in any particular location
depends principally on distance from the equator and elevation above sea-level, we
estimated a simple model (see Table 2) using information on average annual temperature,
latitude, and altitude for all the Chilean stations for which we could obtain "normal"
temperature data (from www.worldclimate.org). In order to get sufficient variation in the
elevation variable, we included 4 stations located close to Chile (Catamarca, Mendoza,
Arequipa, and Oruro).

In this section we will analyze climate data for Chile from May 1948 to March 2008 to test
whether there are any significant trends, and whether these trends differ between regions.

We will use the Monthly Climatic Data for the World database collected by the National
Climatic Data Center (NCDC) in the US. This project started in May 1948 with 100
selected stations spread across the World, including five in Chile. Since then, many more
stations have been included in the data base, but only seven stations in Chile have
contributed systematically throughout the period, with only inconsequential gaps. These are
listed in Table 5, ordered from north to south.

According to the model simulations reported in Christensen et al (2007), temperatures are going to increase faster in the northern part of Chile than in the southern part

temperature data are extracted from the New et al. (2000) gridded 0.5 degree dataset. Calculation of

indices, such as the Palmer Drought Severity Index which uses precipitation and temperature to measure

Monthly Climatic Data for the World
Palmer Drought Severity Index

A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.

A data mention described by its characteristics or producer rather than a proper name.

A data mention that only generally references data, information, or statistics.


Input: Indeed, despite the recent literature rejecting the conflictive impact of refugees in hosting areas (Zhou and Shaver, 2021), the magnitude of our coefficients might be explained by the confounding presence of refugees. Columns (5) and (6) further introduce climatic controls. Column (6) corresponds to Equation 1 and refers to our benchmark specification. Columns (1) and (2) show that without incorporating the changes in ethnic diversity induced by refugees we would not be able to identify a relationship between diversity and violent conflicts. In column (3), the revised refugee fractionalization index has a negative and significant coefficient, while the revised refugee polarization index has a positive and significant effect on the incidence of violent conflicts. In columns (2), (4), and (6), our coefficients of interest are of the same order of magnitude when the number of refugees is controlled for. Our results are not altered by incorporating rainfall and temperature anomalies (columns (5) and (6)), but the estimates become slightly more precise. 21 Usage context: supporting mention, primary mention, background mention.

A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.

A data mention described by its characteristics or producer rather than a proper name.

A data mention that only generally references data, information, or statistics.


Input:
"Life in Transition Survey, Transition Report 2020-2021: The State Strike Back", [https://www.ebrd.com/publications/transition-report-](https://www.ebrd.com/publications/transition-report-202021) [202021.](https://www.ebrd.com/publications/transition-report-202021)

"Strengthening the business environment for productivity convergence," in OECD Economic Surveys: Romania 2022, OECD Publishing, Paris, [https://doi.org/10.1787/63318cf5-en.](https://doi.org/10.1787/63318cf5-en)

_Encuesta_ _Dirigida_ _a_ _la_ _Población_ _Venezolana_ _que_ _Reside_ _en_ _El_ _País_ _(ENPOVE)_ is a special ized survey of Venezuelans living in Peru conducted by the National Institute of Statistics (INEI) in December 2018. The sample covers five main urban areas in the country where Venezuelan immigrants were most likely to be present. The survey collects data on the immi grant's origin, migration date, and details on their current employment. Importantly, a full module asks about the immigrant's experiences with locals, which includes questions about discrimination and hostile attitudes towards them. The respondent's current location is iden tified down to the _centro_ _poblado_ level, which roughly corresponds to an urban neighborhood or a rural town.

_Encuesta_ _Nacional_ _de_ _Hogares_ _(ENAHO)_ is the Peruvian version of the Living Standards Measurement Survey, e.g. a nationally representative household survey collected monthly on a continuous basis. For our analysis, we use data from January 2007 to December 2020. The survey covers a wide variety of topics, including basic demographics, educational back ground, labor market conditions, crime victimization, and a module on respondent's percep tions about the main problems in the country and trust on different local and national level institutions. Observations are also spatially identified at the municipality level, but here we focus on variation in the Venezuelan share of the population at the province level,

A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.

A data mention described by its characteristics or producer rather than a proper name.

A data mention that only generally references data, information, or statistics.


Input:
respondent's percep tions about the main problems in the country and trust on different local and national level institutions. Observations are also spatially identified at the municipality level, but here we focus on variation in the Venezuelan share of the population at the province level, of which there are 196, as these are best representative of local labor markets.

_Latin_ _American_ _Public_ _Opinion_ _Project_ _(LAPOP)_ is a opinion survey conducted bi-annually in all countries in Latin America and designed to be representative of urban populations. This was fielded in Peru in 2010, 2012, 2014, 2017 and 2019 and consists of about 2,000 observations from mostly urban areas. The survey questions are centered around politics,

A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.

A data mention described by its characteristics or producer rather than a proper name.

A data mention that only generally references data, information, or statistics.


Input:
[7] We use the expanded December 2017 vintage of the I2D2   database. Only select members of the research team or individuals in charge of   harmonizing the data can access the database.

**Sample** **Size.** The version of the I2D2 database that we use includes about 1,500   survey/census samples. However, wages are only reported for about two thirds of them.

The baseline sample that we obtain includes 24,437,020 individuals from 1,073   surveys and 11 censuses in 145 countries from 1990-2016 (median number of samples   7The I2D2 database has been used to study labor markets or returns to education (Montenegro and Patrinos, 2014; de Hoyos et al., 2015; Gindling and Newhouse, 2014; Gindling et al., 2016).    <!-- PAGE 10 --> 7   per country = 6; mean = 7.5; min = 1; max = 44).

Also, the I2D2 team does not provide details on how the   harmonized variables were created for each survey, and thus the level of consistency   across surveys. However, given the wide use of the data across flagship World Bank   reports, we feel compelled to trust that the I2D2 team did a good enough job that the   results generated in our study do not capture statistical artefacts.

In addition, we measure _potential_ work   experience as I2D2 does not include direct measures of work experience. Ability (e.g.,   test scores) is also not measured.

A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.

A data mention described by its characteristics or producer rather than a proper name.

A data mention that only generally references data, information, or statistics.


Input: internal control over fate, as opposed to a greater sense of chance or the role of other individuals (though in South Sudanese camps, the role of chance and powerful others is more important). LOC increases with higher levels of education for both hosts and refugees. Still, it has little relationship with age or gender, or how much time refugees have spent in Ethiopia, nor their aspirations to go abroad. 0 0.5 1 1.5 2 2.5 3 Internal Control Chance or Fate Powerful Others All Hosts All Refugees Figure 4.4: Locus of control by type of control 1.9 1.95 2 2.05 2.1 2.15 2.2 2.25 2.3 Eritrean Somali South Sudanese Addis All Hosts Refugees Figure 4.3: Locus of control Source: World Bank staff based on SESRE 2023. Note: This index is the unweighted average of 10 questions about feelings of control over one’s fate. The index ranges from 0 to 4, where more positive indicates greater control. The internal control index uses four questions regarding personal control over destiny. The chance index uses five questions regarding the role of chance or determinism. The role of the powerful others index is 1 question on whether others determine fate. Refugees’ Aspirations 42 T

A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.

A data mention described by its characteristics or producer rather than a proper name.

A data mention that only generally references data, information, or statistics.


Input: impression of the state ’ s role in development and give credit to the state for helping to leverage external resources. Citizens are also likely to give the state credit where mechanisms to voice complaints about non-state actors exist and where bureaucrats are able to eﬀectively respond to complaints. Under these conditions, non-state service provision is likely to strengthen the ﬁscal contract. 5 Data and Methods I explore the relationship between external service provision and deference to government using Afrobarometer survey data from 19 Sub-Saharan African countries (see Table 1). Africa is an especially good place to examine these issues because of the large amount of variation both within and across African countries in the extent to which non-state actors, donors and other states are active in service provision and the extent to which governments are relatively eﬀective and fair. Government responsiveness, corruption and reliance on non-public resources vary considerably among localities with consequences for citizen understanding of and relationship to government (Gibson and Hoﬀman, 2005). This project relies on the fourth round of Afrobarometer data that surveys Africans ’ views towards democracy, economics, and civil society with random, stratiﬁed, nationally representative samples. Usage context: supporting mention, primary mention, background mention.

A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.

A data mention described by its characteristics or producer rather than a proper name.

A data mention that only generally references data, information, or statistics.


Input: The Protection Monitoring Tool's data dictionary specifies response codes for 47 variables, covering legal status, documentation, shelter security, livelihoods, and protection incident types. Codes are standardized across all implementing partners using the Protection Monitoring Tool to enable aggregation of responses at national level. When partners introduce context-specific questions not included in the standard Protection Monitoring Tool module, these are flagged as supplementary variables and excluded from inter-agency comparative analyses.

A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.

A data mention described by its characteristics or producer rather than a proper name.

A data mention that only generally references data, information, or statistics.


Input: not work and must rely solely on aid or assistance, the annual cost of basic needs per refugee is approximately US$378. Under the “current” scenario—where refugees can find opportunities to earn money or work—the amount of assistance needed to cover basic needs reduces annual costs by 44 percent to US$210 per capita. The saving can be viewed as an economic-inclusion dividend made possible by Ethiopia’s prevailing refugee policies. Under a hypothetical “full inclusion” scenario— where in-camp refugees have equal opportunities as hosts—the cost of basic needs decreases further to only US$78 per refugee, per year. 0 10 20 30 40 50 60 70 80 Poorest 2 3 4 Richest Percent Figure 5.20: Share of consumption provided in-kind or for free by consumption per capita quintiles among in-camp refugees Source: World Bank Staff based on SESRE 2023. Note: Quintiles are constructed for in-camp refugees only. 0 10 20 30 40 50 60 70 80 90 100 Hosts Refugees Hosts Refugees Hosts Refugees Addis Ababa All camp Total Total consumption Pre-assistance income Percent Figure 5.21: Poverty incidence at consumption and pre-assistance consumption levels Source: World Bank Staff based on SESRE 2023. Note: Poverty rates are calculated based on $2.15 in the 2017

A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.

A data mention described by its characteristics or producer rather than a proper name.

A data mention that only generally references data, information, or statistics.


Input:
While we know approximately the number of persons affected by flooding worldwide
(106 million, on average, between 2000 and 2005 according to the _International_
_Disaster Database_ ), and by hurricanes (38 million), the total number of people
threatened by an eventual increase of this kind of disaster is, however, very difficult to
estimate (EM-DAT). No climate model is able to predict with accuracy whether or not
the affected zones will be densely populated and whether the damage will have tragic
consequences.

Apart from this difficulty of forecasting, the studies carried out after such events tend
to relativize their effects in terms of migration in general, and long-term migration in
particular. Living mainly in poor countries, the victims have little mobility (Lonergan

5

A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.

A data mention described by its characteristics or producer rather than a proper name.

A data mention that only generally references data, information, or statistics.


Input: Figure A. 2: Injective relations We also isolate many-to-one (bijective) relations. In this case, we have to aggregate the Afro- barometer ethnicities with their unique and more aggregated correspondence in the UNHCR refugee camps data (See Figure A. 3). Figure A. 3: Bijective relations The remaining correspondences are either (i) one-to-many (bijective) but opposite to Figure A. 3 (i. e., many ethnicities from the UNHCR refugee camps data correspond to one ethnicity from the Afrobarometer) or (ii) many-to-many relations. For both cases, we apply a more pragmatic approach: a. In both cases, we disregard ethnicities that do not appear either in the Afrobarometer or in the UNHCR refugee camps data. This means that for the remaining ethnicity that has no counterpart in either the Afrobarometer or the UNHCR refugee camps data, we simply keep the name of the ethnicity as such, i. e., this information is not dropped. b. Then, after ignoring ethnicities that have no occurrence in our datasets, we check whether the one-to-many or the many-to-many relation has not boiled down to a one-to-one resp. many-to- one relation again. If so, we can treat them as above. c.

A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.

A data mention described by its characteristics or producer rather than a proper name.

A data mention that only generally references data, information, or statistics.


Input: Produced by the Research Support Team Abstract The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development / World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent. Policy Research Working Paper 11055 The paper examines the early integration of Ukrainian refugee students into Italy ’ s education system following the Russia ’ s invasion of Ukraine in 2022. Using administrative and survey data, the study presents enrollment trends, academic performance, and barriers to educational integration. Findings from the analysis indicate that Ukrainian refugees face lower enrollment rates, higher absenteeism, and lower test scores than other students, particularly in subjects requiring language proficiency. Despite these challenges, teachers often recommend Ukrainian refugee students for advanced educational tracks, thus revealing their optimism about the potential of these students. Usage context: background mention, primary mention, supporting mention.

A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.

A data mention described by its characteristics or producer rather than a proper name.

A data mention that only generally references data, information, or statistics.


Input: 10 scored on a Likert scale running from 0 (significantly worse) – 10 (significantly better). The survey questions on optimism were collected at outreach, baseline and endline. Employment status: Due to slight differences in access to labor markets for refugees in Jordan and Lebanon and differences in how we were able to ask about employment status, we tabulate employment status as whether or not an individual is employed. Participants were asked at outreach about their employment status, and, in subsequent rounds, whether or not this had changed. This variable is coded 0 for not currently employed and 1 for employed. Economic scarcity: We collect survey questions on individual perceptions on: ability to meet current needs; ability to meet future needs; expectation that access to jobs is fair; expectation that salaries are fair; and belief that unfair access to labor markets fuels tensions. Ability to meet current and future needs are coded on a Likert scale running from 1 (completely unable) to 5 (fully able). The “ fairness ” indicators are coded: 0 (unfair) or 1 (fair). Whether or not competition around employment contributes to tensions is captured on a 1 (not at all) to 5 (absolutely) Likert scale. Usage context: background mention, primary mention, supporting mention.

A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.

A data mention described by its characteristics or producer rather than a proper name.

A data mention that only generally references data, information, or statistics.


Input: 4 policy relevance, which is that it could show how differences in camp location and administration affect refugees. This paper aims to analyze how the living arrangement (camp vs. out-of-camp) affects Syrian refugees'QOL by studying the case of Syrian refugees hosted in Jordan. Besides its policy relevance, another reason for looking at Syrian refugees in Jordan is availability of data. The Syrian Refugee and Host Community Survey (SRHCS) implemented in 2015 in Jordan allows comparing living conditions of separate samples of out-of-camp and in-camp refugees, as well as a sample of a host population. While Jordan hosts Syrian refugees in two refugee camps, Zaatari and Al Azraq, most refugees live outside camps in urban, peri-urban, and rural areas of the country. How has the decision to live out-of-camp improved their QOL? Does living out- of-camp reduce deprivations and vulnerability of female-headed refugee households? Moreover, does living in either of the two camps affect the refugees'QOL? This paper investigates these issues. Data are analyzed using the difference-in-difference and propensity score matching methods. Combining these methods helps control selection bias and other unobserved variables that could bias estimates of causal effects. Multidimensional indicators are used to measure QOL to capture deprivations that cannot be measured by income indicators alone. Usage context: primary mention, supporting mention, background mention.

A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.

A data mention described by its characteristics or producer rather than a proper name.

A data mention that only generally references data, information, or statistics.


Input: Between outreach and baseline, one full survey round was collected due to potential survey fatigue and on the understanding that nothing of importance would likely change in such a short period. Basic demographic information, such as age, gender, marital status and employment status were collected at outreach. At baseline, additional indicators were collected, relating to the behavior, attitudes, opinions and personalities of the participants. The only exception to this is data on optimism, which were collected at both outreach and endline. This allowed us to test whether or not the intake decision had effects, even before the training began. Endline data were collected between July 2018 and November 2019 and repeated the combined outreach and baseline surveys and experiments. Variables: We collected a range of survey and experimental indicators in order to assess our key research questions and associated hypotheses: 6 Economic and life optimism: We collected two survey questions about optimism at outreach, baseline and endline. These questions ask individuals to rank their expectation that their life and economic situation will be better in one year than it is now. Answers are 4 In addition, data were collected from Palestinian Refugees in Lebanon (PRL).

A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.

A data mention described by its characteristics or producer rather than a proper name.

A data mention that only generally references data, information, or statistics.


Input: 8 we use a cutoff distance of 20 km, we assume there is little economic footprint beyond that distance. Of course, any such distance is arbitrarily chosen, which is why we try different specifications to explore the spatial heterogeneity by varying this distance (using 10 km, 20 km, through 50 km) as well as a spatial lag structure (using 0 to 10 km, 10 to 20 km, through 40 to 50 km distance bins). 4 Second, we collapse the DHS mining data at the district level. 5 The number of districts has changed over time in Ghana, because districts with high population growth have been split into smaller districts. To avoid endogeneity concerns, we use the baseline number of districts that existed at the start of our analysis period, which are 137. Eleven of these districts have industrial mining. Because some mines are close to district boundaries, we additionally test whether there is an effect in neighboring districts. 3. 1 Resource data The Raw Materials Data are from InterraRMG (2013). The data set contains information on past or current industrial mines. All mines have information on annual production volumes, ownership structure, and GPS coordinates on location. Usage context: primary mention, supporting mention, background mention.

A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.

A data mention described by its characteristics or producer rather than a proper name.

A data mention that only generally references data, information, or statistics.


Input: For example, IDPs who subsequently cross international borders may be counted as both IDPs and refugees (e. g. in the case of the Syrian displacement crisis). Table 4: Stocks and Flows Stock Increases Decreases Asylum- seekers  New applications for asylum, separately identifying individuals who were previously IDPs  Positive decisions (convention status, complementary protection status)  Rejected  Otherwise closed Refugees  Spontaneous arrivals (group recognition, temporary protection, individual recognition), separately identifying individuals who were previously IDPs  Resettlement arrivals  Births  Administrative corrections  Repatriation  Resettlement  Cessation  Naturalization  Deaths  Administrative corrections IDPs  New internal displacement  Births  Administrative corrections  Cross border flight, becoming an asylum-seeker or refugee  Return  Settlement elsewhere in the country  Local integration  Administrative corrections Source: UNHCR Global Trends, IDMC Forced Displacement Data Model Usage context: primary mention, supporting mention, background mention.

A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.

A data mention described by its characteristics or producer rather than a proper name.

A data mention that only generally references data, information, or statistics.


Input: 2 International migration — the movement of people across national borders — has important economic, social, and political implications. Despite the recent emergence of a dynamic literature, empirical analysis of migration flows and their impact lags behind the policy debate and the theoretical literature. The main reason is the absence of comprehensive and reliable data on international migration patterns and migrant characteristics at either the aggregate or the household level. The objective of this article is to use data from more than one thousand national censuses and population registers to estimate a complete global origin – destination migration matrix for each decade over 1960 – 2000. These 226 * 226 matrices, comprising every country, major territory, and dependency around the world, are divided into periods corresponding to the last five completed census rounds. The gender dimension of international migration over this period is also presented. The primary source of the raw data is the United Nations Population Division ‘ s Global Migration Database, created through the collaboration of the United Nations Population Division, the United Nations Statistics Division, the World Bank, and the University of Sussex (United Nations [2008]). This unique data repository comprises 3, 500 individual census and population register records1 for more than 230 destination countries and territories over the last five decades.

national censuses and population registers

A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.

A data mention described by its characteristics or producer rather than a proper name.

A data mention that only generally references data, information, or statistics.


Input: Geospatial data overlays comparing the project's planned shelter upgrade sites with post-disaster satellite imagery acquired after the 2022 cyclone revealed that six priority sites had sustained significant damage to existing structures during the storm. The geospatial data analysis was used to update the project's engineering scope and cost estimates to include debris removal and foundation remediation at the affected sites. Updated cost estimates were submitted to the Bank as part of a Level 1 restructuring request that also extended the project's closing date by 14 months.

A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.

A data mention described by its characteristics or producer rather than a proper name.

A data mention that only generally references data, information, or statistics.


Input: For example, IDPs who subsequently cross international borders may be counted as both IDPs and refugees (e. g. in the case of the Syrian displacement crisis). Table 4: Stocks and Flows Stock Increases Decreases Asylum- seekers  New applications for asylum, separately identifying individuals who were previously IDPs  Positive decisions (convention status, complementary protection status)  Rejected  Otherwise closed Refugees  Spontaneous arrivals (group recognition, temporary protection, individual recognition), separately identifying individuals who were previously IDPs  Resettlement arrivals  Births  Administrative corrections  Repatriation  Resettlement  Cessation  Naturalization  Deaths  Administrative corrections IDPs  New internal displacement  Births  Administrative corrections  Cross border flight, becoming an asylum-seeker or refugee  Return  Settlement elsewhere in the country  Local integration  Administrative corrections Source: UNHCR Global Trends, IDMC Forced Displacement Data Model Usage context: supporting mention, primary mention, background mention.

A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.

A data mention described by its characteristics or producer rather than a proper name.

A data mention that only generally references data, information, or statistics.


Input: A survey was carried out in the health sector (health centers) with the support of the World Bank in 2005, but has not been yet validated. In the rural development sector, where the first expenditure tracking survey between the decentralized center and services was to be carried out in 2005 on PEFA funds, the survey is yet to be carried out. It is critical that adequate management measures are gradually put in place to stop the current waste of resources. These measures include, inter alia, the accounting improvement of material, improvement of the inventory and delivery control, and especially a transparent planning of the deliveries, including, the posting of the received deliveries, their comparison with the planned deliveries and their certification by users within each service. It would also be desirable that in each ministry, an action plan is prepared for the implementation of these measures, on the basis of existing ones, and with target indicators as regards improvement of the arrival of the expenditure at intended destination. The social ministries could usefully open the way in this field, on the basis of some projection already carried out. Without a quantitative and qualitative improvement of the arrival of the expenditure at their final recipient, the increase in the budgetary appropriations to the priority sectors will hardly be translated into substantial concrete results on the ground. 29 It is difficult to make accurate forecasts for the implementation of certain programs or developments in economic parameters such as inflation or interest rate. Some immediate needs that were not foreseen during budget execution may appear during budget execution. Usage context: background mention, supporting mention, primary mention.

A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.

A data mention described by its characteristics or producer rather than a proper name.

A data mention that only generally references data, information, or statistics.


Input: Eritrean refugees26 and 41 percent of Somali refugees have better usage of out-of-camp healthcare services compared to South Sudanese (5 percent). Overall, in- camp refugees with chronic27 illnesses tend to receive treatment in health institutions located outside of camps compared to those with non-chronic diseases (Figure 2.17b). Refugees receive follow-up treatment for tuberculosis and antiretroviral therapy (ART) for HIV/AIDS in camp health facilities and also get treatment for common illnesses such as asthma, diabetes, hypertension, epilepsy, and mental issues. OCP refugees spend more on health compared to hosts. OCP refugees can no longer rely on international aid sources for healthcare, and do not have health insurance. However, OCP refugees who get out-of-camp residency permits due to health problems receive medical services free of charge under the urban assistance program. UNHCR is working with the GoE tow include OCP refugees in the Community Based Health Insurance (CBHI) Scheme. Of the total refugee households living under OCP, 10 percent moved to Addis Ababa to access basic social services, such as education and health. Thus, some refugees from the above may receive medical services free of charge. Based on SESRE data, most OCP refugees (58 percent) rely primarily on private healthcare services, while

A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.

A data mention described by its characteristics or producer rather than a proper name.

A data mention that only generally references data, information, or statistics.