Input:
**The World Bank**
Formal Employment Creation Project (P171766) Survey). [6] Only 2 percent of respondents to a recent survey reported that they were working and had work permits. About 65 percent of the beneficiaries of the Emergency Social Safety Net Program (ESSN), a temporary humanitarian program, report that their main source of income is short-term informal work. [7] This will become a more significant problem once the ESSN comes to an end.

13. **One of the most important contextual factors that limits formal job creation is the poor access**
**to financing among firms.** Credit service provision is less developed in many provinces where refugees
live and work. According to the World Bank Enterprise Survey, most respondents (76 percent) in the affected regions assert that access to finance deteriorated loan terms and conditions (interest rates, maturity, and collateral requirements). [8] Poor access to longer-term financing limits enterprises from investing, increasing production capacity, and providing sustainable employment opportunities. After high tax rates, access to finance is perceived as a top constraint on firms, particularly small and medium enterprises (SMEs), seeking to carry out and expand business in Turkey. [9] Limited access to finance can also have a negative impact on labor market outcomes, resulting in higher unemployment, higher workforce informality, and lower employment growth. Limited access to credit is also problematic among large enterprises (LEs) because these have the potential to create more jobs, especially among refugees, including higher-quality formal jobs. [10] 14. **Banks do not usually have adequately structured resources to offer medium- to long-term**
**maturities to most firms, mostly because of the short term of their liability base, thus leaving firms,**
**mostly SMEs, open to severe liquidity and interest rate risk.** **[11]** Lack of cash flow-based financing and high
collateral requirements constrain access to finance among SMEs. [12] After the global financial crisis and strong rebalancing in the economy after August 2018, major banks have significantly cut their exposure to SMEs and LEs. The banking system has limited access to long‐term financing. It is funded mostly by relatively stable customer deposits that mature in less than three months, while most of the lending is concentrated in loans for more than three months. The result is a negative liquidity gap, that is, more liquid liabilities than assets, or a liquidity mismatch risk, which peaks in the one- to five‐year maturity range. These imbalances are reflected in bank loan portfolios and the liability structure of enterprises. The bank‐dominated financial sector thus has only a limited ability to provide the maturity critical to support SMEs and LEs that need to make long‐term investments, expand production capacity, and increase employment. In order to address the problems mentioned above, the government introduced some measures to improve SMEs access to finance and their entrepreneurial capacities, that could result effective in the medium to long-term: 6 Turkish Red Crescent and World Food Programme. 2019. _Refugees in Turkey. Livelihoods Survey Findings._ Ankara: Turk Kizilay and World Food Programme.
7 World Bank and World Food Programme. 2019. _Vulnerability and Protection of Refugees in Turkey: Findings from the Rollout of_ _the Largest Humanitarian Cash Assistance Program in the World_ . Washington, DC: World Bank and World Food Programme.
8 Enterprise Surveys (database), International Finance Corporation and World Bank, Washington, DC, https://www.enterprisesurveys.org/.
9 Enterprise Surveys (database), International Finance Corporation and World Bank, Washington, DC., https://www.enterprisesurveys.org/.
10 Ayyagari, M., A. Demirgüç-Kunt, and V. Maksimovic. 2011. “Small vs. Young Firms Across the World: Contribution to Employment, Job Creation, and Growth.” Policy Research Working Paper 5631, World Bank, Washington, DC.
11 World Bank. 2014. _Turkey’s Transitions: Integration, Inclusion, Institutions_ . Report 90509-TR. Washington, DC: World Bank.
12 World Bank 2014 and 2018 data of the Survey on the Access to Finance of Enterprises (database), European Central Bank, Frankfurt, https://www.ecb.europa.eu/stats/ecb_surveys/safe/html/index.en.html.

Page 11 of 86

Survey on the Access to Finance of Enterprises

Survey on the Access to Finance of Enterprises

Survey on the Access to Finance of Enterprises


Input:
Annual grid-level GDP data between 1990 and 2014 at a 0.5-degree resolution come from Kummu, Taka
and Guillaume (2018). The data are primarily based on sub-national GDP per capita data constructed by
Gennaioli, _et al._ (2013) and covers 82 countries, representing 85% of the global population and 92% of
global total GDP (PPP) in 2015. Population data is taken from HYDE 3.2 (Klein, Beusen and Janssen 2010).

we use World Bank income group classifications to divide the world into developing countries (that includes low-income, lower-middle and upper-middle income countries), and high-income countries.

We also use the Global Aridity Index and Potential Evapotranspiration Climate Database (Trabucco and Zomer 2019) to differentiate grid cells based on their aridity.

Global Aridity Index and Potential Evapotranspiration Climate Database

Global Aridity Index and Potential Evapotranspiration Climate Database


Input:
9 Beans, for instance, which are one of the most important food purchases and items in Brazil, have a raw calorie intake of 306 kcal per 100 g in TBCA (Feijão, carioca), while in the prepared form, TBCA assigns 71 kcal per 100 g, assuming a composition of 50 percent beans and 50 percent water to the meal.

Table 2 shows the top 10 food groups in POF in terms of average calorie intake per 100g. It shows that
'Meat' is the most expensive food group, followed by 'Breads, Cakes and Pies'. On the other hand, 'Kitchen
Oil' is displayed as the most caloric food group, as expected. It is followed by 'Flour Derivatives' (which
includes pasta). The cheapest food group is 'Beans and Legumes', while the least caloric is 'Fruits'.
Therefore, the data - including our calorie mapping - show some expected patterns of caloric and price
distribution across food groups.

_Source:_ Own calculations using POF 2017/18 data and TBCA, based on food items categorizations by IBGE.

For this, we construct a consumption aggregate using the data from POF. The consumption aggregate is based on household expenditures on goods and services.


Input: An alternative version of the database that has been mapped to the United Nations (2006, 2009) Trends in International Migrant Stock database is available from the authors. These data are standardized over time in terms of the years to which they refer. { Table 3 here} Calculating Missing Gender Splits Although common in the underlying data, bilateral migration data disaggregated by gender are sparser than aggregate migrant totals (see table 1). An important contribution of the current work is in estimating the gender breakdown of all migrants in destination countries in the global migration matrices. Similar to the allocation from aggregated categories in the Global Migration Database to specific origins in the master list, two measures are used for calculating gender splits; they are described in appendix 5. Combining Migrant Definitions Only a single definition of a migrant (foreign born or foreign citizen) can be applied to each destination country in the final matrices. Switching definitions over time 17 The subregions used for the disaggregations are the 21 UN regions (see http: / / unstats. un. org / unsd / methods / m49 / m49regin. htm, with the countries of Oceania aggregated into a single subregion. They do not match the large World Bank regions used in the analysis in section IV. 18 While this propensity measure is clearly inappropriate, less than 1 percent of all migrants and observations are assigned on this basis. This method is included so that every migrant in the underlying data is accounted for.


Input: Recent analyses of the Global Learning Achievement Survey (GLAS) reveal significant disparities in educational outcomes across various regions. The survey, conducted in 2021, focuses on assessing the reading and math skills of students in primary education. This dataset provides crucial insights into the educational challenges faced by countries in Sub-Saharan Africa, including Kenya and Uganda. Education stakeholders are encouraged to utilize the findings from the GLAS to tailor interventions that address these disparities and promote equitable learning opportunities for all children.

education, learning achievement, and school enrollment


Input:
**The World Bank**
Formal Employment Creation Project (P171766) Survey). [6] Only 2 percent of respondents to a recent survey reported that they were working and had work permits. About 65 percent of the beneficiaries of the Emergency Social Safety Net Program (ESSN), a temporary humanitarian program, report that their main source of income is short-term informal work. [7] This will become a more significant problem once the ESSN comes to an end.

13. **One of the most important contextual factors that limits formal job creation is the poor access**
**to financing among firms.** Credit service provision is less developed in many provinces where refugees
live and work. According to the World Bank Enterprise Survey, most respondents (76 percent) in the affected regions assert that access to finance deteriorated loan terms and conditions (interest rates, maturity, and collateral requirements). [8] Poor access to longer-term financing limits enterprises from investing, increasing production capacity, and providing sustainable employment opportunities. After high tax rates, access to finance is perceived as a top constraint on firms, particularly small and medium enterprises (SMEs), seeking to carry out and expand business in Turkey. [9] Limited access to finance can also have a negative impact on labor market outcomes, resulting in higher unemployment, higher workforce informality, and lower employment growth. Limited access to credit is also problematic among large enterprises (LEs) because these have the potential to create more jobs, especially among refugees, including higher-quality formal jobs. [10] 14. **Banks do not usually have adequately structured resources to offer medium- to long-term**
**maturities to most firms, mostly because of the short term of their liability base, thus leaving firms,**
**mostly SMEs, open to severe liquidity and interest rate risk.** **[11]** Lack of cash flow-based financing and high
collateral requirements constrain access to finance among SMEs. [12] After the global financial crisis and strong rebalancing in the economy after August 2018, major banks have significantly cut their exposure to SMEs and LEs. The banking system has limited access to long‐term financing. It is funded mostly by relatively stable customer deposits that mature in less than three months, while most of the lending is concentrated in loans for more than three months. The result is a negative liquidity gap, that is, more liquid liabilities than assets, or a liquidity mismatch risk, which peaks in the one- to five‐year maturity range. These imbalances are reflected in bank loan portfolios and the liability structure of enterprises. The bank‐dominated financial sector thus has only a limited ability to provide the maturity critical to support SMEs and LEs that need to make long‐term investments, expand production capacity, and increase employment. In order to address the problems mentioned above, the government introduced some measures to improve SMEs access to finance and their entrepreneurial capacities, that could result effective in the medium to long-term: 6 Turkish Red Crescent and World Food Programme. 2019. _Refugees in Turkey. Livelihoods Survey Findings._ Ankara: Turk Kizilay and World Food Programme.
7 World Bank and World Food Programme. 2019. _Vulnerability and Protection of Refugees in Turkey: Findings from the Rollout of_ _the Largest Humanitarian Cash Assistance Program in the World_ . Washington, DC: World Bank and World Food Programme.
8 Enterprise Surveys (database), International Finance Corporation and World Bank, Washington, DC, https://www.enterprisesurveys.org/.
9 Enterprise Surveys (database), International Finance Corporation and World Bank, Washington, DC., https://www.enterprisesurveys.org/.
10 Ayyagari, M., A. Demirgüç-Kunt, and V. Maksimovic. 2011. “Small vs. Young Firms Across the World: Contribution to Employment, Job Creation, and Growth.” Policy Research Working Paper 5631, World Bank, Washington, DC.
11 World Bank. 2014. _Turkey’s Transitions: Integration, Inclusion, Institutions_ . Report 90509-TR. Washington, DC: World Bank.
12 World Bank 2014 and 2018 data of the Survey on the Access to Finance of Enterprises (database), European Central Bank, Frankfurt, https://www.ecb.europa.eu/stats/ecb_surveys/safe/html/index.en.html.

Page 11 of 86


Input: The 2022 National Safety Nets Assessment Report, produced by the Ministry of Social Development in Zambia, offers critical insights into the effectiveness of various social protection programs. This dataset has been widely utilized by the International Labour Organization (ILO) to analyze the impact of these programs on poverty alleviation. Additionally, the report includes data segmented by urban and rural geographies, allowing for a nuanced understanding of regional disparities. The assessment also draws on the Social Protection Survey (SPS) — an acronym used in prior studies — which covers data from 2020 to 2021 and was generated by the World Bank. This collaboration between local and international organizations underscores the importance of robust data in shaping effective policies.

National Safety Nets Assessment Report
Social Protection Survey

Ministry of Social Development
International Labour Organization
World Bank


Input: the OECD, a highly skilled workforce, and a transformative digitalization and management agenda. **Foundational Learning** 5. **National assessments show weakness in foundational learning, and learning outcomes are strongly correlated** **to socioeconomic conditions, which points to the need for foundational learning with deeper attention to the education** **outcomes of students from poorer families.** Costa Rica reactivated standardized national assessments in 2023; the first results from 2023 were released in March 2024 and indicated that about a third of the students at the end of Primary schooling are at the “basic” level of learning. Internationally comparable Programme for International Student Assessment (PISA) data for Costa Rica for 2018 shows that while 28 percent of children from families in the top quintile of the PISA index for economic, social and cultural status were below Level 2 on Reading in PISA (considered the minimum of adequate performance), 72 percent of children from families from the lowest quintile of the PISA index were below level 2. Foundational learning (literacy and numeracy) in early grades paves the way for future learning, and differences in educational attainment become magnified through youth and adult life in the acquisition of human capital. Without any claims regarding causation, it is

Internationally comparable Programme for International Student Assessment

Internationally comparable Programme for International Student Assessment


Input: The 2022 Social Protection Assessment Report provides comprehensive insights into the effectiveness of safety nets across various regions. This dataset, published by the International Social Policy Institute, serves as a vital resource for understanding the impact of social protection policies implemented in different countries.

2022 Social Protection Assessment Report

2022 Social Protection Assessment Report


Input:
The monthly precipitation data comes from the Africa Rainfall and Temperature Evaluation System (ARTES) (World Bank 2003). This dataset, created by the National Oceanic and Atmospheric Association's Climate Prediction Center, is based on ground station measurements of precipitation over the period 1948-2001.

Soil data was obtained from FAO (2003). The FAO data provides information about the
major and minor soils in each location. Data concerning the hydrology was predicted from a
hydrological model for Africa (Strzepek & McCluskey 2006). The model calculated the
water flow through each district in the surveyed countries. Data on elevation at the centroid
of each district was obtained through GIS manipulation using data from the United States
Geological Survey (USGS, 2004). The USGS data are derived from a global digital elevation
model with a horizontal grid spacing of 30 arc seconds (approximately one kilometer).

Weng F & Grody N, 1998. Physical retrieval of land surface temperature using the Special Sensor Microwave Imager. _Journal of Geophysical Research_ 103: 8839-8848. World Bank, 2003. Africa rainfall and temperature evaluation system (ARTES). World Bank, Washington DC.

Africa Rainfall and Temperature Evaluation System (ARTES)

National Oceanic and Atmospheric Association's Climate Prediction Center

Africa Rainfall and Temperature Evaluation System (ARTES)

National Oceanic and Atmospheric Association's Climate Prediction Center

Africa Rainfall and Temperature Evaluation System (ARTES)


Input: The Global Primary Education Assessment (GPEA) conducted in 2022 provides critical insights into learning achievements across various countries. This dataset, compiled by the Education Research Institute, is vital for policymakers aiming to enhance educational outcomes in underserved regions.


Input: Economics of Disasters and Climate Change Fig. 2 Flood maps showing inundation depth (cm) in case of a: (a) 10-year return period flood under current conditions, (b) 25-year return period flood under current conditions; (c) 50-year return period flood under current conditions; (d) 10-year return period flood given a 30 cm sea level rise; (e) 25-year return period flood given a 30 cm sea level rise; and (f) 50-year return period flood given a 30 cm sea level rise Local-Level Data on Urban Areas and Potential Slums in Ho Chi Minh City The spatial socioeconomic data set used for HCMC is a data set of potential slum areas from 2000 to 2010, from the Platform for Urban Management and Analysis (PUMA), a city-level data set developed by the World Bank (World Bank 2015).This data was collected via satellite in the year 2012, through a combination of visual interpretation of various sources and vintages of imagery. To guide the identification of slums, previous work has provided information on the appearance and geographical extent of slums in HCMC. Surveys of poverty in the city find the appearance of slums in HCMC to be characterized as densely built small households and shelters that

Platform for Urban Management and Analysis

Platform for Urban Management and Analysis


Input: The Economic Competitiveness Assessment Report (ECAR) released by the Global Trade Institute in 2022 provides critical insights into the trade dynamics affecting developing countries. This report, which analyzes trends from 2019 to 2021, was utilized by the United Nations Conference on Trade and Development (UNCTAD) to identify growth opportunities. In addition, the Industry Benchmark Database (IBD) published by the International Industry Association offers comprehensive performance metrics for the manufacturing sector across Latin America. This dataset, covering the years 2018 to 2020, is frequently referenced by various local governments in the region to inform their economic policies.

Economic Competitiveness Assessment Report

United Nations Conference on Trade and Development

Economic Competitiveness Assessment Report

Economic Competitiveness Assessment Report

United Nations Conference on Trade and Development

Economic Competitiveness Assessment Report

Economic Competitiveness Assessment Report

Economic Competitiveness Assessment Report

trade, industry, and economic competitiveness


Input: 40 Sub ‐ Saharan Africa 8604000 5895000 7055000 5406100 5068000 N. A. MENA 6230000 8000000 6675000 8592900 10892000 N. A. Asia and Pacific 4325000 2405000 3392000 2128800 5490000 N. A. (excl. Australia, Japan, New Zealand) Americas 1126000 1280000 2176000 2900000 3661000 N. A. (excl. North America) Note: Refugee data are from the UNHCR statistical population online dataset, accessed in September 2014. Refugee data from 2007 to 2013 include people in refugee ‐ like situations (see note, Figure 1). IDP data from 1990 to 2008 are aggregated based on Center for Systematic Peace (http: / / www. systemicpeace. org /). As indicated in Figure A1, these data are much lower compared to those provided from 2003 by IDMC but provide a longer time series. UNHCR assisted ‐ IDP are compiled based on several UNHCR (1995, 1996, 2007, 2008, 2009, 2010, 2011, 2012, 2013, and 2014) reports. UNHCR ‐ assisted IDPs are only IDPs who are protected / assisted by UNHCR. These are also not necessarily representative of the entire IDP population in a given country. Many of the world's IDP situations are not covered by UNHCR and are thus not reflected.

UNHCR statistical population online dataset

UNHCR statistical population online dataset


Input: The recent analysis of urban sprawl in the Greater Deltaland region has been extensively supported by the Deltaland Land Use Mapping Report, published by the Deltaland Environmental Agency. Additionally, the Remote Sensing Assessment 2022, produced by Geospatial Innovations LLC, provides crucial satellite imagery that underpins various studies on land cover changes over the last decade. These datasets are pivotal for informing policy decisions related to sustainable development in the area.

Deltaland Land Use Mapping Report
Remote Sensing Assessment 2022

Deltaland Environmental Agency
Geospatial Innovations LLC

geospatial analysis, remote sensing, and land use mapping


Input:
Analysis of the impact of refugees from Ukraine on the economy of Poland

**Chart 15. Ukrainian refugees wages median net wage by age group**

Monthly net wage (PLN) Percengate of all workers total economy average Analysis of the impact of refugees from Ukraine on the economy of Poland

**Chart 16. Median net wages of Ukrainian refugees median net wage by sector**

in PLN Percentage of total economy average 126% 15 to 24 25 to 34 35 to 44 45 to 54 55 to 64 15 to 24 25 to 34 35 to 44 45 to 54 55 to 64 Ukrainian refugees All workers Source: Deloitte own elaboration based on SEIS UNHCR survey and GUS data.

**The Ukrainian refugee groups to earn**

**the highest wages compared to the**

**wages in the economy as a whole are**


Input: The recent Labor Market Dynamics Assessment Report (LMDA) highlights evolving trends in the workforce across various sectors. Conducted in Brazil, the assessment utilizes data from 2022 to examine changes in employment patterns. This comprehensive dataset is instrumental for policymakers, providing insights into labor market shifts and skill gaps. The report is published by the International Labor Organization (ILO), which emphasizes its significance in aiding governments to design effective employment strategies. In addition to LMDA, the Universal Skills Survey (USS) conducted across multiple countries from 2020 to 2023 aims to measure competencies in the workforce and their impact on economic growth. These datasets are crucial for understanding the intersection of skills development and employment in a global context.

Labor Market Dynamics Assessment Report
Universal Skills Survey

employment, labor markets, and skills development


Input:
[8] F. N. P. Nimoh, T. P. Beltramo, J. R. Fix, F. K. Appler, U. J. Pape, and L. A. Rios Rivera, ‘Understanding the Socioeconomic Conditions of
the Stateless Shona Community in Kenya: Results from the 2019 Socioeconomic Survey’, Dec. 2020. Accessed: Apr. 02, 2024. [Online].
Available: https://documents.worldbank.org/en/publication/documentsreports/documentdetail/356511608745182603/Understanding-the-Socioeconomic-Conditions-of-the-Stateless-Shona-Community-inKenya-Results-from-the-2019-Socioeconomic-Survey

[9] U. J. Pape _et al._, ‘How COVID-19 Continues to Affect Lives of Refugees in Kenya : Rapid Response Phone Survey - Rounds 1 to 5’, World
Bank Group, Washington, D.C., Policy Note 166098, Oct. 2021. Accessed: Oct. 10, 2024. [Online]. Available:
https://documents1.worldbank.org/curated/en/202201637042522937/pdf/How-COVID-19-Continues-to-Affect-Lives-of-Refugeesin-Kenya-Rapid-Response-Phone-Survey-Rounds-1-to-5.pdf

[10] Kenya National Bureau of Statistics and ICF, ‘Kenya Demographic and Health Survey 2022. Key Indicators Report’, KNBS and ICF,

Nairobi, Kenya, and Rockville, Maryland, USA, 2023. Accessed: Oct. 10, 2024. [Online]. Available: https://www.knbs.or.ke/wpcontent/uploads/2023/08/Kenya-Demographic-and-Health-Survey-2022-Key-Indicators-Report.pdf


Input: Vermeer, M. and S. Rahmstorf. 2009. Global sea level linked to global temperature. _Proceedings_ _of the National Academy of Sciences_ 106 (51), 21527-32. VLIZ. 2011. Maritime Boundaries Geodatabase, version 6.1. Available online at [http://www.vliz.be/vmdcdata/marbound. Consulted on 2011-05-12.](http://www.vliz.be/vmdcdata/marbound) Williams, M., 1990. Understanding Wetlands. In M. Williams (ed) _Wetlands: A Threatened_ _Landscape_ . Wiley-Blackwell. Woodward, R.T. and Y.S. Wui. 2001. The economic value of wetland services: A meta-analysis. _Ecological Economics_, 37, 257-270 World Bank, 2010. Boundaries of the World. Map Design Unit. The boundaries, colors, denominations and any other information shown on this map do not imply, on the part of the World Bank Group, any judgement on the legal status of any territory, or any endorsement or acceptance of such boundaries. 25

Maritime Boundaries Geodatabase, version 6.1

Maritime Boundaries Geodatabase, version 6.1

Maritime Boundaries Geodatabase, version 6.1


Input:
The daily precipitation data used are from the 3- hourly data set from the Tropical Rainfall Measurement Mission Project (TRMM), which is aggregated up to daily data.

\n<!-- PAGE 28 -->\ndata set product 3B42RT 3 hour product gives the best results in a basket of 8 near real-time rainfall products. The 3B42RT daily derived product is what is used in this paper.

\n<!-- PAGE 8 -->\nthrough 2015. During the period from 1985 to 2016, the Dartmouth Flood Observatory (DFO) registered 3,808 floods of magnitude 4 or more and 1,175 floods of magnitude 6 and up. [3]

According to the Indonesian National Disaster Management Authority (BNPB), there were more than 19,000 natural hazards in the period 2001 - 2015 (National Disaster Management Agency 2016), making Indonesia a useful country for any natural hazard analysis.

According to the Global Facility for Disaster Reduction and Recovery (GFDRR), the Philippines is at high risk from several types of natural hazards (GFDRR 2019). Prime among them are cyclones, where an average of 20 make landfall every year. In 2013, typhoon Yolanda led to 6,000 casualties and damaged more than 1.1 million houses. The Philippines are also exposed to earthquake and flood risks.

Tropical Rainfall Measurement Mission Project (TRMM)

Tropical Rainfall Measurement Mission Project (TRMM)


Input: -0.094** -0.062 3.893 -0.064 -0.031 0.126*** (0.042) (0.040) (3.842) (0.066) (0.038) (0.042) _3. drop 2 years before_ active*mine -0.094** -0.062 3.708 -0.071 -0.026 0.125*** (0.041) (0.039) (3.459) (0.067) (0.036) (0.043) _4. mine FE_ active*mine -0.123** -0.094* 8.233 -0.068 -0.049 0.113** (0.057) (0.051) (5.425) (0.075) (0.044) (0.045) _5. mine clustering_ active*mine -0.086*** -0.055** 3.705 -0.058 -0.032 0.125** (0.025) (0.025) (2.898) (0.086) (0.032) (0.051) Mean dep var 0.715 0.705 45.71 0.491 0.259 0.028 _Note:_ The table uses GLSS data for Ghana for the survey years 1998, 2005, 2012. The sample is restricted to women and men aged 15–49. Robust standard errors clustered at the village or neighborhood level in parentheses (except if otherwise stated). All regressions control for year and district fixed effects, urban dummy, age, and years of education. Active is active status of mine in the survey year. The treatment distance is defined to 20 km. Rows 2 drop sample between 20 to 40 km of a mine, and rows 3 drop sample that was surveyed two years before mine opening. *** p<0.01, **p<0.05, *p<0.1. FE = fixed effects. 30


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, 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,


Input:
Table 2 presents summary statistics for the ENILEMS-ENLACE panel dataset. Columns

12 ENLACE scores than individuals out of college (by around 0.38 SD), but they are also

We are interested in the predictive power of ENLACE test scores over future schooling

individual's ENLACE test score in Grade 6 as a predictor of future education outcomes or

We use the ENLACE panel to study the relationship between Grade 6 test scores


Input:
using purchasing power parity rates. It comes from the World Development Indicators

The governance indicators come from the International Country Risk Guide (ICRG)

Data on the Gini coefficient were drawn from a more complete World Bank source

100 km of ice-free coast) come from Gallup et al. (1999). Data on total forest area (km [2] ),

precipitation come from WDI (2010). Latitude (in absolute value), mean elevation (meters


Input:
148 P. B. Spiegel & P. V. Le

Introduction

The human immunodeficiency virus (HIV) behavioural surveillance surveys
(BSSs), an evolution from the knowledge-attitudes-practice surveys (KAPs), are
an assessment, monitoring and evaluation tool designed to track trends in HIV/
AIDS knowledge, attitudes and risk behaviour among populations. When used
together with qualitative and quantitative research and proper measurement of
appropriate programme indicators, the data collected from BSSs can assist
organizations in targeting specific HIV/AIDS prevention and care activities,
allocating scarce resources, and monitoring and evaluating the interventions’
effectiveness and coverage. BSSs are useful because they alert policy makers and
programme managers to emerging or changing risks in existing behaviour, reveal
gaps in knowledge and attitudes, help to identify vulnerable segments of
populations, contribute to improved programme content, provide data on specific
target groups and ensure compatibility and standardization of data collection
(Family Health International 2000).
The core BSS indicators have been evolving over time (Table I). Until the
United Nations General Assembly Special Session on HIV/AIDS (UNGASS)
indicators were developed in 2002, there were no internationally-accepted HIV
indicators. The UNGASS indicators were followed by the development of the
Millennium Development Goal (MDG) indicators in 2003 and, subsequently,
the US President’s Emergency Preparedness Fund on AIDS Relief (PEPFAR)
indicators in 2004. Although all of these indicators are similar to one another,
there are minor differences. Thus, it is difficult for persons implementing BSSs to
choose which indicators to use and complicated for others to compare studies
which use different indicators. Furthermore, there are numerous other indicators
that can be used in BSSs depending upon the target groups and objectives of the
survey.
Conflict, displacement, food insecurity and poverty have the potential to make
affected populations more vulnerable to HIV transmission. The UNGASS
Declaration of Commitment on HIV/AIDS, states that ‘populations destabilised
by armed conflict . . . including refugees, internally displaced persons, and in
particular women and children, are at increased risk of exposure to HIV infection’
(United Nations General Assembly 2001). However, the common assumption
that this vulnerability necessarily translates into increased HIV infections and
consequently fuels the epidemic is not supported by data (Spiegel 2004). In the
recent past, HIV/AIDS interventions were generally not included by humanitarian organizations as part of their immediate response to conflict; HIV/AIDS was
considered more of a developmental issue and not an immediate life threatening
disease such as malaria or cholera. However, thinking has evolved and it is now
generally accepted that HIV/AIDS programmes must begin at the onset of a
humanitarian emergency, be multisectoral, and continue at every stage thereafter
(Inter-Agency Standing Committee 2003). Furthermore, for refugees and
internally displaced persons (IDPs), HIV/AIDS programmes should be integrated

Family Health International
Inter-Agency Standing Committee


Input: The findings from the Conflict Assessment Report 2022 have been instrumental in guiding the efforts of various humanitarian organizations in conflict-ridden regions. Published by the International Crisis Group, this report provides critical insights into the dynamics of violence and instability, helping agencies like Save the Children and Oxfam tailor their interventions effectively. The data included not only highlights the immediate needs but also emphasizes longer-term strategies for peace and recovery.

International Crisis Group
Save the Children
Oxfam


Input: The JLMPS sample is restricted, after matching it to the 2010 school census, to individuals born in Jordan who are aged 25 to 70 in 2010 and who have nonmissing information on age, subdistrict of birth, years of schooling, father ’ s schooling, mother ’ s schooling, and local supply of schools in subdistrict of birth. 9 These exclusions resulted in a sample of 4, 139 males and 4, 131 females, which are referred to as the male and female full samples, respectively. 7. Because of the absence of annual estimates of subdistrict populations, the population used to normalize the supply of schooling at the subdistrict level is the 2004 population of the subdistrict. There are 86 subdistricts in Jordan. If subdistrict populations are growing at different rates, this could introduce some measurement error of the true supply of schooling available to different cohorts. 8. Secondary schools include both general and vocational secondary schools. Public schools include schools under the jurisdiction of: (i) Ministry of Education, (ii) Ministry of Higher Education, (iii) Ministry of Defense, (iv) Ministry of Social Development, (v) Ministry of Religious Endowments (Awqaf), and (vi) UNRWA. 9. The original sample size of all individuals who are aged 25 to 70 years in 2010 and are born in Jordan is 8, 312 observations. The sample restrictions on the missing values result in the exclusion of 34 observations (missing age), 1 observation (missing father ’ s schooling), and 7 observations (missing mother ’ s schooling).


Input: However, we can- not exclude the possibility that refugees would sort non-randomly into areas with particular ethnic characteristics. 19 In order to address this potential endogeneity, we implement an instrumental variable (IV) ap- proach. We are particularly concerned about certain ethnic groups from certain countries of origin moving to destination countries with similar ethnic characteristics. Such endogenous selection would be reflected in the EPR-ER data. To deal with the plausibly endogenous nature of the resulting refugee EF and EP indices, we implement a gravity model to predict the number of refugees of a certain ethnic group e moving from country o to d at time t, based on EPR-ER data. The predicted (and plausibly exogenous) number of refugees by ethnic group e is then used to create other (plausibly exogenous) diversity indices to be used as instrumental variables. More specifically, we estimate the following gravity model: 17We also use this method to link data from EPR-ER on the ethnicities of refugees with data from the Murdock Atlas on their historical homeland (Section 4. 3). 18As a robustness check (Section 5. 3), we use an alternative linkage based on the relations between sets of language nodes associated with two groups. 19Another source of selection may come from the fact ethnic groups are more likely to be displaced when they share territory with regime supporters in their countries of origin (Lacina et al., 2017). Since similar ethnic groups are likely to share common borders (Michaelopoulos and Papaioannou, 2016), it is not impossible to think conflict might spill over through this channel.


Input: The Climate Adaptation Assessment Report published by the Global Resilience Partnership highlights various initiatives aimed at enhancing climate resilience in vulnerable regions. This comprehensive report draws on various datasets and methodologies to analyze the effectiveness of different strategies implemented across Africa. Collaborating organizations, including the United Nations Environment Programme, played a crucial role in the research and data collection for this report, ensuring a multi-faceted approach to disaster risk reduction.

Global Resilience Partnership
United Nations Environment Programme

climate resilience and disaster risk reduction


Input: The Domestic Revenue Mobilization Assessment (DRMA) for Malawi, which covers the years 2018 to 2020, provides insights into the effectiveness of fiscal policies and their impacts on revenue collection. This dataset, published by the African Development Bank, is particularly valuable for stakeholders looking to enhance local tax systems. Additionally, the Public Financial Management Survey (PFMS) for Kenya, conducted in 2021, aims to evaluate the efficiency of public spending and budget execution. While the PFMS has not yet been widely utilized in academic research, it serves as a crucial tool for policymakers. Lastly, the Global Tax Revenue Trends Report (GTRTR) 2019 focuses on comparative tax data across numerous countries, although its specific geographic emphasis was not well defined in the documentation.

Domestic Revenue Mobilization Assessment

Domestic Revenue Mobilization Assessment

Domestic Revenue Mobilization Assessment

Domestic Revenue Mobilization Assessment

public financial management and domestic revenue


Input: The 2022 Maternal Health and Wellbeing Survey (MHWS) recently provided critical insights into maternal outcomes across various regions. This comprehensive study, conducted by the Institute for Global Health Research, spans several countries, including Nigeria, India, and Brazil, highlighting the disparities in healthcare access and outcomes. The findings from the MHWS are expected to inform policy recommendations aimed at improving maternal healthcare systems. Notably, while the survey covers the year 2022, it also includes longitudinal data from previous years to provide context for its findings. The survey serves as a vital resource for organizations working on maternal health initiatives, such as UNICEF and WHO.

Institute for Global Health Research
UNICEF
WHO


Input: 13 Proposition 7 State-Level Effects of Population Size: The risk of civil war events at a location varies with the size of the population of the country to which the location belongs, controlling for the local effects. 3 Research Design 3. 1 Unit of Analysis To distinguish between the different theoretical statements regarding how population sizes, population concentrations and locations relate to risk of conflict, we need to investigate exactly where conflicts occur. We have created a dataset using a Geographic Information Systems (GIS) program which converted large territories into smaller portions of 8. 6 km x 8. 6 km, totaling 74 square kilometers. Each of these grid squares are our units of observation (we will refer to them as squares). This approach is similar to that of Buhaug & Rød (2006), with two important differences. First, their squares are much larger (100x100km). Second, they code the dependent variable considerably more crudely than is done in the ACLED dataset described below. Buhaug & Rød (2006) use the `scope'and `location'variables in the Uppsala / PRIO dataset.


Input: likelihood of working outside the camp, or in monthly earnings. Agriculture is an important source of livelihood for host households, but refugee households have low agricultural holdings, reflecting their inability to own land legally. Refugee households are less than half as likely as hosts to report an agricultural holding with crops (19 percent versus 41 percent of host households, Figure 3.14). Refugee livestock ownership is similarly low (22 percent of households own livestock versus 48 percent for host households) but average livestock ownership is higher for Somali households (41 percent) (Figure 3.15). 0.00 0.10 0.20 0.30 0.40 0.50 0.60 0.70 0.80 0.90 1.00 15-24 25-34 35-44 45-54 55-64 Less than Primary Primary Secondary Figure 3.12: Share employed by age – camp refugees Source: World Bank Staff based on SESRE 2023. 0.00 0.10 0.20 0.30 0.40 0.50 0.60 0.70 0.80 0.90 1.00 15-24 25-34 35-44 45-54 55-64 Less than Primary Primary Secondary Figure 3.13: Share employed by age – camp hosts Source: World Bank Staff based on SESRE 2023. Jobs and Livelihoods 32 When refugees own livestock, the value and flock size of this livestock is low. Somali refugees mostly own sheep, goats, and donkeys, and compared to Somali hosts, they


Input: The Water Quality Assessment Report (WQA Report) outlines critical data on water quality indicators across various regions. This dataset, published by the Global Water Institute, covers the years 2018 to 2020 and provides insights into the sanitation efforts implemented in sub-Saharan Africa. The WQA Report (WQA) has been utilized extensively by local governments to inform policy decisions regarding water resources. In contrast, the Urban Sanitation Survey (USS) has been primarily focused on urban environments in Latin America, with data from the 2020 census. Although the USS is not as widely cited, it plays a crucial role in understanding urban sanitation challenges faced in the region.

Water Quality Assessment Report
WQA Report
Urban Sanitation Survey
USS

Global Water Institute
local governments


Input: In recent analyses of economic resilience, the Global Financial Inclusion Index (GFII) provides key insights into the accessibility of financial services across various demographics. Covering the period from 2020 to 2022, this dataset highlights trends in financial participation in regions facing economic challenges, including sub-Saharan Africa and South Asia. The research conducted by the Financial Observatory emphasizes the importance of these findings in shaping policy initiatives aimed at enhancing economic stability and inclusive growth.

macroeconomic trends and financial inclusion


Input:
have yet to adapt internal procedures. Some banks may still require fixed addresses as part of their due diligence, which recently-arrived refugees often do not have.

When it comes to access to credit provided by microfinance institutions (MFIs), regulatory requirements can be less restrictive. Several MFIs [71] in a number of countries such as Jordan, Lebanon, Uganda, Rwanda, Morocco, Tunisia, and Argentina have started providing loans to refugees by accepting UNHCR ID or the ID issued by governments to refugees, using alternative ways to verify residence and credit scoring. What has proven to be a key enabler to facilitate access to these services was the work done by UNHCR and partners to raise awareness about the financial needs of refugees with FSPs in the country. This advocacy work is fundamental and could be replicated in other countries to ensure greater access to a broader range of financial services by refugees.

_**Access to Mobile Money**_ To what extent does the regulatory environment facilitate or constrain access to mobile money?

As with SIM registration, of the 20 countries examined, none extend consistent legal access to mobile money to asylum seekers, though workarounds are regularly reported.
However, in late 2018 the Afghan Central Bank reportedly authorized certain mobile money operators to accept any letter or other form of certification from UNHCR (including the Voluntary Repatriation Form and asylum seeker and refugee certificates) to facilitate SIM registration for mobile money services as part of a cash-based intervention program.

Access to mobile money is varied for refugees across the countries studied. In Zambia, special approval was received from the Bank of Zambia and ZICTA, the telecommunications regulator, to use the proof of registration, refugee certificate and refugee ID card as valid ID for mobile wallet registration. In Nigeria, the regulatory framework is particularly progressive and accommodating.

Nigeria's mobile money framework based on a three-tier KYC/CDD regulation, the lowest level of which (Level 1) is particularly inclusive and, in theory, can accommodate the displaced (see Table 3).

**Case study: Rwanda**

According to the World Bank's Global Findex database, Rwanda's mobile money penetration (in terms of account ownership for 15+ years old) is 31.11%. The National Bank of Rwanda has enacted Regulation No. 08/2016 Governing the Electronic Money Issuers [72], which reiterates the core ID 71 Pistelli, _5 Things You Should Know About Financial Services for Refugees_ : http://www.findevgateway.org/blog/2018/jun/5-things-you-should-know-about-financial-services-refugees 72 JuriAfrica, _The National Bank Regulates the Activities of Issuers of Electronic Money_ : https://juriafrique.com/ eng/2017/01/27/rwanda-national-bank-the-governor-enacts-new-standards-for-issuers-of-electronic-money/

**Level 1** _**Low Value Accounts**_

i. They are subject to close monitoring by the financial institutions and less scrutiny by Bank Examiners.

ii. The accounts can be opened at branches of financial institutions by the prospective customer or through banking agents.

iii. No amount is required for opening of accounts iv. Such accounts cover Mobile Banking Products (issued in accordance with the CBN Regulatory Framework for Mobile Payments Services in Nigeria).

_**Main Characteristics**_ i. Deposits can be made by account holder and 3rd parties while withdrawal is restricted to account holder only.

ii. Be linked to mobile phone accounts.

iii. Operation is valid only in Nigeria.

iv. Automated Teller Machine transactions are allowed.

v. There is Prohibition on International Funds Transfer.

vi. Accounts are strictly savings.

73 IGC, _The Regulation of Mobile Money in Rwanda_, p.15 requirements for opening a bank account. "[Mobile Network Operators] are required to respect KYC rules prior to opening accounts — in practice a national ID card is required to register for mobile money." [73] As such, refugees continue to face barriers to accessing mobile money.
Mobile money agents from different operators are present in all camps in the country. However, while cash assistance to returnees is still based on mobile money transfers, UNHCR and WFP no longer use mobile money, but rather smart cards, for cash assistance in refugee settings due to challenges with SIM access and meeting KYC/CDD requirements.

_Table 3: Tier 1 of Nigeria’s Three-Tiered KYC Requirements (including Mobile Money)_

**Description and characteristics** **Amount / Threshold** **Customer**
**Limitation** **Identification**
**requirements**

i. Basic customer information required to be provided are:

- Passport photo;

- Name, Place and
Date of Birth;

- Gender, Address,
Telephone number, etc ii. Information may be sent electronically or submitted onsite in bank’s branches or agent’s office iii. Evidence of the Information provided by customer or verification of same is not required.

It is limited to a minimum single deposit amount of N20,000 and maximum cumulative balance of N200,000 at any point in time.

_**Mobile Banking**_ _**Products**_ Level One Mobile Banking Products are Allowed:

- Maximum
transaction limit of N3,000 and daily limit of N30,000.

- Such products
are subject to the CBN Regulatory Framework for Mobile Payments Services in Nigeria.

27 28


Input: The Agricultural Monitoring Survey (AMS) conducted by the Food and Agriculture Organization (FAO) in 2022 provides critical insights into rural development challenges. This dataset has been extensively utilized by the International Fund for Agricultural Development (IFAD) to enhance its projects aimed at food security across Sub-Saharan Africa. Additionally, the Global Hunger Index (GHI) 2021, published by Concern Worldwide, offers a comprehensive assessment of hunger levels globally and has been cited in various reports by the World Food Programme (WFP). The Nutritional Outcomes Assessment 2019 (NOA2019) by the World Health Organization (WHO) focuses on nutrition and health indicators and is a valuable resource for local governments in Southeast Asia for policy formulation.

Agricultural Monitoring Survey
Global Hunger Index
Nutritional Outcomes Assessment 2019

International Fund for Agricultural Development

Sub-Saharan Africa
globally
Southeast Asia

International Fund for Agricultural Development

agriculture, food security, and nutrition


Input: The 2022 Gender Equality Index (GEI) compiled by the International Institute for Women, highlights significant disparities in women's participation in the labor force across various regions. In particular, the report details findings from the Africa Women's Empowerment Survey (AWES) conducted in 2021, which was utilized by the United Nations Development Programme (UNDP) to inform policy recommendations. Additionally, the Asia-Pacific Gender Report (APGR) 2023, published by the Asian Development Bank (ADB), has served as a critical resource for NGOs working on gender issues in Southeast Asia. Furthermore, the Global Female Labor Participation Dataset (GFLPD) 2019, developed by the World Bank, provides comprehensive statistics that have been referenced by several academic institutions for research purposes.

Global Female Labor Participation Dataset

International Institute for Women
United Nations Development Programme
Asian Development Bank
World Bank

Global Female Labor Participation Dataset

Global Female Labor Participation Dataset

Global Female Labor Participation Dataset

gender equality and women's economic empowerment


Input: of Return Migration, Human Capital Accumulation, and Wage Assimilation. The Review of Economic Studies, 89(6), 2841-2871. Alix-Garcia, J., Walker, S., Bartlett, A., Onder, H., and Sanghi, A. (2018). Do Refugee Camps Help or Hurt Hosts? The Case of Kakuma, Kenya. Journal of Development Economics, 130, 66-83. Alkire, S., Kanagaratman, U., and Suppa, N. (2021). The Global Multidimensional Poverty Index (MPI) 2021, OPHI MPI Methodological Note 51. Oxford Poverty and Human Development Initiative, University of Oxford. Altindag, O., Bakls, O., and Rozo, M. S. (2020). Blessing or Burden? Impacts of Refugees on Businesses and the Informal Economy. Journal of Development Economics, 146. https://doi.org/10.1016/j.jdeveco.2020.102490 Andersen, H.L., Osland, L. and Zhang, M.L. (2023). Labour Market Integration of Refugees and The Importance of the Neighborhood: Norwegian Quasi-experimental Evidence. Journal of Labour Market Research 57, 16. https://doi.org/10.1186/ s12651-023-00341-y Aracl, D., Demirci, M., and Klrdar, M. (2022). Development Level of Hosting Areas and the Impact of Refugees on Natives’ Labor Market Outcomes in Turkey. European Economic Review, 145. https://doi.org/10.1016/j.euroecorev.2022.104132 Atamanov, A., Hoogeveen, J., and Reese, B. (2023). The Costs Come Before the Benefits Follow. Why Should Donors Invest More in Refugee Autonomy in Uganda? 1–11. Azlor, L., Damm, A. P., and Schultz-Nielsen, M. L. (2020). Local

Global Multidimensional Poverty Index (MPI) 2021

Oxford Poverty and Human Development Initiative

Global Multidimensional Poverty Index (MPI) 2021

Oxford Poverty and Human Development Initiative


Input:
Annual grid-level GDP data between 1990 and 2014 at a 0.5-degree resolution come from Kummu, Taka and

Guillaume (2018a). The data are primarily based on sub-national GDP per capita data constructed by Gennaioli,

Is the relationship between rainfall and GDP explained by agriculture? 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

different weights. Population is taken from HYDE 3.2 (Klein, Beusen and Janssen 2010).

The work compares food prices subnationally and finds that increasing prices are the most significant factor driving recent food insecurity but documents strong spatial heterogeneity in both market price dynamics, as well as relations to food insecurity, and provides examples of markets where prices are more sensitive to localized shocks. 4For instance, the International Finance Statistics (IFS) data base of the IMF reports monthly price data at Consumer Price Index (CPI) component level, but few developing countries report food price data without substantial delays.


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).

Venezuelan Refugee Panel Study for Kids (VenRePs-Kids)

Venezuelan Refugee Panel Study for Kids (VenRePs-Kids)


Input: The United Nations Economic Commission for Europe ’ s (UNECE) guidelines include a question on reason for migration, population with a refugee-like background and IDPs as non-core topics / questions (UNHCR 2016). 72 While most countries include questions on country of birth and citizenship, only about 40 percent include a question on year of migration, less than a quarter include a question on reason for international migration, and about a fifth include a question on the reason for internal migration (UNHCR 2016). 73 E. g. Kyrgyz Republic 1999 (refugee status), West Bank and Gaza 2007 (refugee status), Zambia 2000 and 2010 (purpose of stay), Germany 1970 (federal refugee identity card), Greece 2001 (reason for settling in Greece), Sudan and South Sudan 2008 (type of household including IDP and refugee), Liberia 1990 (ever displaced by war since 1990), Uganda 2014 (refugees). 74 UNHCR is collaborating with the Statistics Norway on systematically embedding forcibly displaced peoples in national statistics exercises and collaborates with national authorities and with UNFPA in various countries on the design of census exercises that include refugees, IDPs, returnees and stateless persons. 75 LSMS is a household survey program housed in the Bank's Development Research Group that provides technical assistance to national statistical offices in the design and implementation of multi-topic household surveys covering household behavior, welfare and interactions with government policies. All data gathered through the LSMS is published online in the Bank ’ s Central Microdata Catalog.


Input: The recent employment trends in South Asia were analyzed using the Workforce Participation Database (WPD), published by the International Labour Organization (ILO). This comprehensive dataset, covering the years 2018 to 2022, has been particularly useful for regional assessments conducted by the Asian Development Bank (ADB). Additionally, the Skills Development Report 2021, produced by the World Bank, has provided insights into the effectiveness of vocational training programs in Bangladesh. This report has been cited extensively by various NGOs working on labor market interventions across the country. Furthermore, the ILO's Labour Force Survey (LFS) data, spanning 2020 to 2021, has also been utilized by the United Nations Development Programme (UNDP) for its ongoing projects aimed at improving employment outcomes in Nepal.

Workforce Participation Database
Skills Development Report 2021
Labour Force Survey

International Labour Organization
Asian Development Bank
World Bank
United Nations Development Programme


Input: The 2020 Global Land Use Assessment (GLUA) compiled by the EcoData Institute provides crucial insights into land cover changes over the past decade. This dataset, which focuses on multiple countries including Brazil and Indonesia, is instrumental for policymakers. The World Resources Organization has utilized the GLUA data to inform its regional sustainability initiatives, particularly in the Amazon Rainforest area. Furthermore, these findings will assist in shaping future conservation strategies as detailed in the 2021 Biodiversity Report published by the EcoData Institute. This report outlines key trends in biodiversity loss related to land use modifications, providing a comprehensive overview for various stakeholders.

Global Land Use Assessment
Biodiversity Report

EcoData Institute
World Resources Organization


Input: The Fertility Trends Report 2020, published by the National Demographic Institute (NDI), provides comprehensive insights into reproductive health across various regions. This data has been utilized extensively by the International Population Council (IPC) to inform policies aimed at improving maternal health. Additionally, the African Population Database (APD), which covers demographic data from 2015 to 2020, has also been leveraged by the World Health Organization (WHO) in their ongoing research into population growth dynamics in African nations. These datasets are crucial for understanding the shifts in fertility patterns and their implications for development strategies.

Fertility Trends Report 2020
African Population Database

National Demographic Institute
International Population Council
World Health Organization

demographics, fertility, and population growth


Input: We use the sum of conflict events occurring in the historic homeland of ethnic group e in the previous year t − 1, denoted as Conflictet − 1, and we use the mean distance between the historic homeland of ethnic group e and the border of country d to predict the number of refugees of a certain ethnic group e moving from country o to d at time t. 22 In order to be consistent with EPR-ER data construction, we restrict our analysis to all origin – destination country pairs that are at a maximum distance ≤ 950 km from each other. Predicted numbers of refugees are then transformed into predicted shares for the three largest groups to follow the logic used by the EPR-ER dataset. We then plug in these predicted shares in the following way: X \PredictedRefcet = Refocdt ∗ \Shareodet. (6) The predicted shares of refugees per camp c are then used to compute (as documented above) refugee diversity indices to be used as instrumental variables. The first-stage equations corresponding to the 2SLS-equivalent of Equation 1 can be expressed as 20We conduct a robustness check on Equation 5, replacing the dyadic origin – destination fixed effects with separate origin and destination fixed effects (Section 5. 4). 21More information on LEDA can be found in Appendix A. 1. 22The construction of the IV follows a long tradition in using the gravity model to predict bilateral migration flows (Ravenstein, 1985, 1989; Crozet, 2004; Mayda, 2010; Garcia et al., 2015; Beine et al., 2016). In our analysis, a major difference is that we have an additional dimension: the ethnic group e.


Input: supervisor, and four enumerators. All field staff involved in the SERSE participated in the HoWStat survey. Enumerators were knowledgeable about local cultures and languages and could detect inconsistencies and misunderstandings during interviews to ensure high-quality data. Supervisors were additionally trained on how to troubleshoot standard technical issues with tablets. The supervisors conducted reinterviews, consistency, spot-checking, and data syncing to the head office. Also, the statisticians from ESS branch offices were with the team all the time to support and monitor the fieldwork. The data collection system consisted of encrypted Android devices for prolonged usage in the field equipped with the chosen survey application and a GPS tracking application for EA delineations. Electronic data files were transferred daily to the ESS central office in Addis Ababa via the Annexes 96 secured link. The core team from ESS undertook field supervision and was responsible for the day-to- day field management. Also, the World Bank team undertook field supervision, providing on-time and on-the-spot guidance for the field teams whenever and wherever they encountered a challenge. (e) Challenges faced and lessons learned The SESRE served as a learning experience for including refugees in future rounds of the official household survey (HoWStat). Given the unique


Input: Recent investigations into gender equality have highlighted significant barriers faced by women in the workforce. The Gender Equity Assessment Report 2022 provides extensive data on wage disparities and employment rates among different demographics. Additionally, the Women’s Empowerment Index examines various indicators related to women's participation in economic activities, offering critical insights into the challenges that remain.

Gender Equity Assessment Report 2022
Women’s Empowerment Index


Input: The Environmental Sustainability Assessment Report (ESAR) reveals significant trends in natural resource management across various regions. Conducted in 2022, this comprehensive analysis spans several countries, with a focus on resource depletion and conservation strategies. It highlights the importance of sustainable practices in combating climate change. While the data demonstrates promising initiatives in regions like Southeast Asia, it also points to concerning trends in resource use in parts of Africa. Policymakers are encouraged to utilize the findings from the ESAR to drive effective environmental policies that respond to the challenges identified in the report.

Environmental Sustainability Assessment Report

Environmental Sustainability Assessment Report

Environmental Sustainability Assessment Report

Environmental Sustainability Assessment Report

Environmental Sustainability Assessment Report

environmental sustainability and natural resources


Input: The Financial Inclusion Assessment Report 2022, produced by the Global Finance Institute, provides a comprehensive overview of access to banking services in low-income regions. This dataset, utilized extensively by the United Nations Development Programme (UNDP), highlights the trends in financial accessibility from 2018 to 2022. In addition, the Economic Growth Database (EGD), released by the International Economic Agency, contains valuable macroeconomic indicators for developing countries, which are often referenced by various financial organizations to gauge economic stability. The UNDP has also made use of the EGD data to support policy recommendations aimed at enhancing financial inclusion efforts across multiple geographies.

Financial Inclusion Assessment Report 2022

Global Finance Institute
United Nations Development Programme
International Economic Agency

Financial Inclusion Assessment Report 2022

Financial Inclusion Assessment Report 2022

Financial Inclusion Assessment Report 2022

Financial Inclusion Assessment Report 2022


Input: These data are only for three districts in the province of Punjab, but is very recent, was conducted by an independent team of academics, and is a complete census of all households in the selected villages. Consequently, it yields sufficient madrassa enrollment to examine correlations with household attributes in a meaningful manner (this data source provides information on four times as many children as the PIHS). Table A2 in the appendix shows how these different data sources are used in the paper. Each source asks about madrassa enrollment in a slightly different but comparable way. The population census (1998) asks about the field-of-education (“ What is name ’ s field of education? ”) with options that include (for instance) engineering, medicine, or religious education. This question is also asked of all literate adults irrespective of their current enrollment status, allowing for comparisons in the stock of religious education over time. The PIHS rounds ask, “ What type of school is name currently attending? ” with options that include government school, private school, or deeni-madrassa (religious schooling). Finally, the LEAPS census directly asks, “ Is the child enrolled in a madrassa or an Islamic education school? ” Fortunately these different questions all give rise to similar numbers. This is reassuring since it suggests that any one particular result is not driven by the specific question or definition that was used. 7 This is complemented with the census of private schools carried out by the Federal Bureau of Statistics in 2000 (www. statpak. gov. pk).


Input: 0 10 20 30 40 50 60 70 80 90 100 Percent Worse Same Better Figure 5.8: Perceived changes in household living standards Source: World Bank Staff based on SESRE 2023. Note: The survey asks how the household living standard has changed compared to last year and the last five years. a. Last 5 years b. Last 1 year Refugees’ Aspirations 48 scale44 gap between refugees and hosts is higher for in-camp refugees, the gap is relatively narrower for Addis Ababa refugees. The average food insecurity scale for in-camp refugees is “8” and for their hosts it is “4” out of 10; that is, in- camp refugee households experienced about eight food insecurity events while host households experienced about 4 in the past year. Consistent with other welfare indicators discussed, food insecurity tends to be more severe among in-camp refugees than their hosts or OCP refugees. In-camp refugees have less diverse diets and poor food consumption status compared to their hosts. The average household dietary diversity score—the number of food groups consumed out of twelve—is 7.5 for hosts and 6.5 for refugees (Figure 5.10a). Overall, the average dietary diversity score is also lower for in-camp refugees than their hosts. The


Input: restricted to workers with completed secondary education. Among workers with completed secondary, 30 percent of refugees and 50 percent of hosts are in high-skill occupations (Figure 3.25). Among only women, these numbers are 20 percent and 50 percent, respectively. Instead, refugee men and women in Addis Ababa are over- represented in crafts and related trades (typically classified as medium-skill occupations). 0 20 40 60 80 100 Addis Hosts Addis Refugees Current Addis Refugees COB Salary (employment/casual labor) Crops/livestock Donations(NGO/gov) Remittances (local/international) Other (rental income, PSNP, pension) Percent 0 20 40 60 80 100 Percent Addis Male-Headed Addis Female-Headed Figure 3.21: Household primary income source Source: World Bank Staff based on SESRE 2023. Note: “COB” refers to livelihood strategies in their country of birth. a. Pre-post migration b. By gender of head Table 3.2: Labor force statistics Addis Hosts Addis Hosts Labor force participation rate (strict) 66% 46% Unemployment rate (strict) 12% 63% Labor force participation rate (relaxed) 72% 67% Unemployment (relaxed) 19% 75% Employment-to-population ratio 58% 17% Source: World Bank Staff based on SESRE 2023. Note: Labor force participation ratio is the share of working-age people who are engaged in the labor market, either employed or unemployed. Unemployment is the


Input:
Analysis of the impact of refugees from Ukraine on the economy of Poland

**Recently arrived Ukrainian refugees,**

**those with below tertiary education**

**and in older age group are most**

**likely to communicate in Polish at**

**intermediate and lower levels.** Based
on the SEIS UNHCR survey, a logistic regression has been performed to find out which categories of Ukrainian refugees may most require Polish language improvement. [29] Results show that the odds of only zero to intermediate Polish knowledge decrease with every month since arrival. Ukrainian refugees in the 18 to 29 age group have the lowest odds of having an intermediate or lower level of Polish. It translates into a 38% probability, even lower than the 41% for refugees with tertiary education. The group with the highest odds (70% probability) of zero to intermediate Polish are Ukrainian refugees aged 50 to 64. The results by employment sectors are not statistically significant, other than for manufacturing. The results are intuitive, with the best language skills among refugees working in health and education, and the lowest among those working in construction, other services, and trade.

**Addressing the gap in language**

**fluency would yield significant**

---
[29] A dummy variable that takes the value of 1 in case of none, beginner, or intermediate language knowledge, and 0 for other levels has been regressed against a


Input: The Food Security Assessment Report 2022, published by the International Food Policy Research Institute (IFPRI), provides critical insights into agricultural productivity across Southeast Asia. This dataset has been extensively used by various NGOs, including Action Against Hunger, to develop targeted interventions for improving food security in the region. Additionally, the report highlights trends in food availability and access, outlining significant changes over the past five years. While the data encompasses several countries, the assessment specifically details conditions in Vietnam and Thailand, which have faced unique challenges in food distribution. The collaborative efforts between IFPRI and action-oriented organizations exemplify the dynamic use of agricultural data for policy-making and humanitarian responses.

International Food Policy Research Institute

International Food Policy Research Institute


Input:
Several of the refugees interviewed for this research indicated that no one wanted to give them
work because of their status as a refugee in Cameroon. When discussing the treatment they
received from the host population and the ability to find a job, all refugees interviewed explained
that it was difficult for them “because I am a stranger”, “from the outside” or because “I am
different”.

Although there are many similarities between the refugee population and the host community,
there is also a clear distinction that exists; all refugee interviewed indicated that they experienced
some sort of harassment and/or discrimination because they were refugees, and most connected
this directly to their ability to find wage-earning work in Yaoundé. However, several refugees
stated that the discrimination they face is not experienced with all Cameroonians, in some cases
they indicated that the locals supported them and treated them well; simply put by one refugee
from CAR, “some Cameroonians are nice, some are not.”

As discussed previously, identity documentation is a big problem for refugees living in
Cameroon, as many authorities and institutions do not recognise UNHCR identity cards and


Input:
Analysis of the impact of refugees from Ukraine on the economy of Poland

# **2.** Situation of refugees from Ukraine on the labour market in Poland

Analysis of the impact of refugees from Ukraine on the economy of Poland

**Chart 7.** Unemployment rate

12% 10% 8% 6% 4% 2% 0%

**Source:** Harmonized data, Eurostat, [Statistics | Eurostat (europa.eu)](https://ec.europa.eu/eurostat/databrowser/view/une_rt_m/default/table?lang=en)

##### Refugees from Ukraine fit well into the needs of the Polish labour market.

Ukrainians arrived on a labour market that structurally needs more workers, as the domestic population is ageing rapidly, while the economy is growing. High levels of education, cultural proximity and previous connections to Poland helped refugees adapt to the labour market. Furthermore, Poland made an important and strategic policy decision by promptly opening the labour market and supporting their inclusion.

16 17

**Chart 6.** Working age population with Polish citizenship (20-64 years old)

25 24 23 22 21 20


Input: The Regional Labor Market Assessment (RLMA) conducted by the International Labor Organization (ILO) in 2022 provides comprehensive insights into employment trends across Eastern Europe. In addition, the World Bank's Skills and Competencies Survey (SCS) for 2023 focuses on skill gaps in the workforce and is leveraged by various organizations, including the European Training Foundation (ETF) for their reports on vocational training. The Government of Romania is utilizing both datasets to inform policy changes aimed at enhancing labor market outcomes. Furthermore, the ILO also produced the Employment and Unemployment Statistics Database (EUSD) from 2019, which offers critical data for researchers and policymakers alike, showcasing employment rates across member countries.

Employment and Unemployment Statistics Database

International Labor Organization
World Bank
European Training Foundation
Government of Romania

Employment and Unemployment Statistics Database

Employment and Unemployment Statistics Database

Employment and Unemployment Statistics Database

Employment and Unemployment Statistics Database


Input: We use the sum of conflict events occurring in the historic homeland of ethnic group e in the previous year t − 1, denoted as Conflictet − 1, and we use the mean distance between the historic homeland of ethnic group e and the border of country d to predict the number of refugees of a certain ethnic group e moving from country o to d at time t. 22 In order to be consistent with EPR-ER data construction, we restrict our analysis to all origin – destination country pairs that are at a maximum distance ≤ 950 km from each other. Predicted numbers of refugees are then transformed into predicted shares for the three largest groups to follow the logic used by the EPR-ER dataset. We then plug in these predicted shares in the following way: X \PredictedRefcet = Refocdt ∗ \Shareodet. (6) The predicted shares of refugees per camp c are then used to compute (as documented above) refugee diversity indices to be used as instrumental variables. The first-stage equations corresponding to the 2SLS-equivalent of Equation 1 can be expressed as 20We conduct a robustness check on Equation 5, replacing the dyadic origin – destination fixed effects with separate origin and destination fixed effects (Section 5. 4). 21More information on LEDA can be found in Appendix A. 1. 22The construction of the IV follows a long tradition in using the gravity model to predict bilateral migration flows (Ravenstein, 1985, 1989; Crozet, 2004; Mayda, 2010; Garcia et al., 2015; Beine et al., 2016). In our analysis, a major difference is that we have an additional dimension: the ethnic group e.


Input:
composite measure for human capital. We extract real GDP and human capital data from Penn World

Table 10 (Feenstra et al., 2015), using the "rgdpna" series, which measures real GDP in constant 2017

schooling and returns to education (Inklaar and Timmer, 2013). We extract the population from World

Development Indicators (WDI).

#### **3.3 Sample Construction**

The baseline populations served by the East Road (within the buffer zones) were established by utilizing
WorldPop open source data. To estimate the number of people affected by rain event, however, a series
of models were run to simulate the locus of impacts for each rain event (3-, 10-, and 30-year events) and
their subsequent effects on access. Repeated events might affect the same people, and so, the cumulative
impacts over the lifetime of the road can be thought of as 'person-disruptions' - i.e., the sum of individual
disruptions. If, for example, an individual living on the East Road was cut off from access to hospitals three
times over the thirty-year period, this experience would account for three person-disruptions.

Using Global Positioning System (GPS) tracking records for the Malaita East Road from Atori to Dala, 5,856
road segments with gradient details were delineated and mapped using geographic information system
(GIS) mapping software. These segments were mapped for the current road and also used to model surface
conditions defined by the proposed upgrading projects.

Cost data for similar road projects also informed assumptions about per-unit (km) repair costs
for each type of road surface subject to various damage levels.


Input: The 2020 Refugee Wellbeing Survey (RWS) provides critical insights into the living conditions of displaced populations and was published by the International Refugee Council (IRC). The survey data is widely used by the United Nations High Commissioner for Refugees (UNHCR) to enhance policy frameworks in various regions. Furthermore, the East African Migration Trends Report (EAMTR) 2021, developed by the Migration Policy Institute (MPI), offers a comprehensive analysis of migration patterns and has been referenced by the African Union (AU) for its ongoing initiatives. In addition, the 2019 Global Refugee Forum Dataset (GRFD) captures key outcomes from the forum and is utilized by numerous advocacy groups, including Refugees International (RI), to inform their efforts and drive engagement across affected countries.

Refugee Wellbeing Survey
East African Migration Trends Report
Global Refugee Forum Dataset

United Nations High Commissioner for Refugees

United Nations High Commissioner for Refugees

forced displacement, refugees, and migration


Input: The Global Trade Insights Report (GTIR) published by the International Trade Organization in 2022 provides valuable data on trade flows and patterns across various regions. This dataset focuses on the economic competitiveness of industries in developing countries, particularly in Africa and Southeast Asia. Additionally, the Agricultural Production and Trade Assessment (APTA) for the years 2019 to 2021 offers critical insights into food exports and imports, with a geographical focus on Latin America. While the GTIR is extensively used by policymakers and researchers, the APTA has yet to gain widespread attention in academic circles.

Agricultural Production and Trade Assessment

Agricultural Production and Trade Assessment

Agricultural Production and Trade Assessment

Agricultural Production and Trade Assessment


Input: The recent analysis of the Socioeconomic Distress Index (SDI) conducted by the National Statistics Office (NSO) in Brazil provides critical insights into poverty levels across the country. This dataset, covering the years 2019 to 2022, has been utilized by the International Development Agency (IDA) to assess the impact of socioeconomic policies. Additionally, the Global Poverty Assessment Report (GPAR) 2021, published by the World Bank, highlights income inequality trends in Sub-Saharan Africa. The GPAR has been leveraged by various researchers to formulate recommendations aimed at poverty alleviation in the region. These datasets are crucial for understanding the dynamics of poverty and inequality in their respective geographies.

Socioeconomic Distress Index
Poverty levels
Global Poverty Assessment Report
GPAR

National Statistics Office
International Development Agency
World Bank

poverty headcount and inequality measurement


Input:
**The World Bank**
South Sudan Health Sector Transformation Project (HSTP) (P181385)

|Description|Percentage of HC health facilities receiving at least one quarterly supervision visit within the quarter|
|---|---|
|Frequency|Quarterly|
|Data source|MoH; TPM|
|Methodology for Data
Collection|MoH to provide data; TPM to verify|
|Responsibility for Data
Collection|MoH / TPM|
|**Percentage of health facilities receiving quarterly supervision visits from the CHD (Percentage)**|**Percentage of health facilities receiving quarterly supervision visits from the CHD (Percentage)**|
|Description|Percentage of health facilities receiving at least one quarterly supervision visit within the quarter from the CHD|
|Frequency|Quarterly|
|Data source|MoH; TPM|
|Methodology for Data
Collection|MoH to provide data; TPM to verify|
|Responsibility for Data
Collection|MoH / TPM|
|**Percentage of health facilities receiving quarterly supervision visits from State MoH (Percentage)**|**Percentage of health facilities receiving quarterly supervision visits from State MoH (Percentage)**|
|Description|Percentage of health facilities receiving at least one quarterly supervision visit within the quarter from the State
MoH|
|Frequency|Quarterly|
|Data source|MoH; TPM|
|Methodology for Data
Collection|MoH to provide data; TPM to verify|
|Responsibility for Data
Collection|MoH / TPM|
|**Percentage of complaints to Grievance Redress Mechanisms satisfactorily addressed in a timely manner**|**Percentage of complaints to Grievance Redress Mechanisms satisfactorily addressed in a timely manner**|
|Description|Percentage of complaints submitted to the GRM addressed according to the protocol and within agreed time
period.|
|Frequency|Quarterly|
|Data source|UNICEF|
|Methodology for Data
Collection|UNICEF to provide data / TPM to verify|
|Responsibility for Data
Collection|UNICEF; PMU|
|**Percentage of completeness of reporting by facilities**|**Percentage of completeness of reporting by facilities**|
|Description|Percentage of facilities that submit complete reports within the required deadline.|
|Frequency|Quarterly|
|Data source|DHIS2|
|Methodology for Data
Collection|DHIS2|
|Responsibility for Data
Collection|MoH/ PMU|
|**Percentage of states that conducted quarterly coordination meetings with a review of data and documented with minutes including**
**action items and follow-up**|**Percentage of states that conducted quarterly coordination meetings with a review of data and documented with minutes including**
**action items and follow-up**|
|Description|Percentage of State’s quarterly health service delivery coordination meetings for the health sector held with a
review of data included in the meeting and documented with minutes which include action items and follow-up
on action items. Meetings are to be held quarterly in each state. Four meetings are expected each year per
state. CHDs and implementing partners will be participated in the review|
|Frequency|Quarterly|
|Data source|MoH/ WHO|
|Methodology for Data
Collection|WHO to provide data / TPM to verify|


Input: The recent analysis of the Education Quality Assessment Report published by the Global Education Initiative highlights significant disparities in learning outcomes among various regions. This report serves as an essential resource for policymakers and education advocates aiming to enhance educational equity and improve school enrollment rates across underrepresented communities. The Global Education Initiative has committed to leveraging data from this report to inform future programs and initiatives.


Input:
wages and reduced over-education for migrants working in licensed jobs, while producing worse labour market outcomes for those who did not gain licensure.
According to Peterson et al. (2014), over the 1973–2010 period, U.S. states with more stringent occupational licensing for migrant physicians received fewer new migrant physicians and struggled more with staffing shortages in healthcare. Aleksynska and Tritah (2013) quoted data that migrants in France were denied legal access to approximately 30% of jobs in the country.

Ukrainian refugees Polish citizens Source: Deloitte own elaboration based on mid-2024 SEIS UNHCR survey (Ukrainian refugees’ educational attainment), 2023 Eurostat Labour Force Survey Eurostat (Polish citizens educational attainment), and mid-2024 ZUS administrative data (occupational groups).

**Chart 21. Share of regulated professions by citizenship and legal status, Q2 2024**

**The educational premium seems**

**to be lower for Ukrainian refugees**

**compared to the general workforce**


Input: an economically viable area. Results from various studies such as the 23 Zambia 2022 Census of Population and Housing, Central Statistical Office Zambia, 2023. 24 One Meheba Local Area Plan, Planning Survey and Issues Report, GRZ, 2023. 25 One Meheba Local Area Plan, Planning Survey and Issues Report, GRZ, 2023. 26 “Many girls choose not to attend classes at certain times due to the lack of appropriate washing and hygiene facilities,” School headmaster, Kalumbila District, February 2024. Page 16

23 Zambia 2022 Census of Population and Housing

23 Zambia 2022 Census of Population and Housing

23 Zambia 2022 Census of Population and Housing


Input:
and more immediate impact on food access, we are able to find additional empirical support

for the last explanation. Given data and information constraints, it is not possible to estimate

Sundberg, R., and E. Melander. 2013. "Introducing the UCDP Georeferenced Event Dataset."

Notes: This table compares mobile phone ownership in the November 2017 WFP mobile phone survey and the 2014 Household Budget Survey (HBS), where the 2014 HBS summary statistics are restricted to the share of the population that resides in a household that owns at least one mobile phone.

We gratefully thank Claudio Montenegro, David Newhouse and Minh Nguyen for their help with the I2D2 database. We gratefully acknowledge the generous support of the World Bank (Office of the Senior Vice-President and Chief Economist and Social Urban Rural and Resilience Global Practice), the Cities Program of the International Growth Center (Grant number 89408), the GWU Institute for International Economic Policy and the GWU Center for International Business Education and Research.

Data Used to Estimate the Returns**   **Sources.** The data source for the analysis is the _International_ _Income_ _Distribution_   _Database_ (I2D2) of the World Bank. The database consists of a large number of   individual-level surveys and census samples.


Input: will be served by health centers, resulting in 50 maternal lives saved per year and a 15 percent reduction in other causes of morbidity (baseline morbidity of 19 percent). [28] The NPV of these investments is estimated at US$1.3 million at a 12 percent discount rate, with an ERR of 29 percent. 61. _Communal WASH_ investments reduce morbidity from diarrhea and other waterborne diseases, along with time and cost savings to access water. The analysis assumes the mortality rate due to unsafe water will reduce by 10 percent (from 25 deaths per 100,000 to 22.5), along with time savings of two hours per week per beneficiary household in accessing clean water and US$20 in annual cost savings per household (CEIC data). The NPV of these WASH investments is estimated at US$1.1 million at a 12 percent discount rate, with an ERR of 28 percent. 62. Additional assumptions used in the analysis for this component include: (a) value of a statistical life: US$2,394; [29] and (b) annual O&M costs of five percent of total investment value. [30] 63. The results of the analysis for this component and the sensitivity analysis are summarized in the tables below: **Table 6: NPV and ERR


Input: in-camp refugees, their hosts, and out-of-camp refugees (Table D.12 in Annex D). The predicted poverty rate decreases with the share of employed household members, indicating that employment is essential to lowering poverty for in- camp refugees (Figure 5.19). 0 10 20 30 40 50 60 70 80 90 100 Poorest 2 3 4 Richest Poorest 2 3 4 Richest Poorest 2 3 4 Richest Poorest 2 3 4 Richest In Camp Refugees In Camp Hosts Addis Ababa Refugees Addis Ababa Hosts Electricity Mobile phone Any livestock Bank account Agricultural holding Nonfarm enterprise Percent Figure 5.17: Household wealth indicators by expenditure quintiles Source: World Bank Staff based on SESRE 2023. 0 10 20 30 40 50 60 70 80 90 Labor force participation Employment to working age population ratio Unemployment rate 0 10 20 30 40 50 60 70 80 90 100 Agriculture Industry Services 0 10 20 30 40 50 60 70 Poorest 2 3 4 Richest In Camp Refugees Inside the Camp Outside the Camp 0 10 20 30 40 50 60 70 80 Poorest 2 3 4 Richest Poorest 2 3 4 Richest Poorest 2 3 4 Richest Poorest 2 3 4 Richest Low-skill Medium-skill High-skill Percent Percent


Input: 2 1. INTRODUCTION Refugees pose a massive moral, political and economic challenge for potential host countries. 1 The scale of the challenge is larger than ever, with 60 million people forcibly displaced by conflicts across the world (UNHCR, 2014). War in Syria has produced more refugees than any other conflict of the past two decades: around 4. 6 million have fled the country, with an additional 7. 6 million internally displaced. 2 About 2. 5 million Syrians have found refuge in Turkey, making it the largest refugee-hosting country worldwide. This paper combines newly available data on the distribution of Syrian refugees across Turkey and the Turkish Labour Force Survey to assess the impact on Turkish employment and wages. The large majority (85 percent) of Syrians have left the refugee camps and entered the Turkish labor market. 3 They are overwhelmingly employed informally, since they were not issued work permits. This makes their arrival a well-defined supply shock to informal labor, and a particularly good context in which to test the predictions of basic economic theory. We instrument for refugee flows using travel distance between 13 origin governorates in Syria and 26 Turkish subregions (338 origin-destination pairs). This allows us to also control for distance from the Syrian border, and thus any confounding factors that are correlated with proximity to Syria.


Input: nizations such as UNHCR, and national and international non-governmental organizations. Data is compiled from a number of sources, including but not restricted to individual registration of refugees and asylum seekers (information typically includes name, gender, date of birth, country of origin, marital status, and place of displacement), tracking of population movement in situa- tions where the movement is ﬂuid or continuous, standardized surveys such as Living Standards Measurement Study (LSMS) surveys, Labor Force Surveys (LFS), Demographic and Health Sur- veys (DHS), and Multiple Indicator Cluster Surveys (MICS), administrative records and registries. Yet, data collection is a difﬁcult exercise, due to both methodological issues (UNHCR 2014) and practical challenges, especially in situations of heightened insecurity or mass refugee situations. To date, UNHCR maintains the most comprehensive statistical database under a uniform methodology. UNHCR publishes annual data on refugee ﬂows and stocks by countries of resi- dence and origin dating back to 1951, shortly after the Ofﬁce was established. UNHCR publishes annual statistical reports ranging from “ Global Trends ”, “ Mid-year trends ”, “ Asylum trends ”, to a “ Statistical Yearbook ”. There is a consensus that these data provide the most reliable source of information (Sarzin 2016).


Input: The recommendations drawn from this analysis focus on addressing the health and mental health and psychosocial needs and barriers identified in the SEIS, tailoring them to the specific data and context of each country. To enhance policy development, it will be crucial to improve monitoring of refugees’ health, including sexual and reproductive health and mental health, through inclusion of disaggregated refugee data into national data systems. This will require effective collaboration among health organizations, statistical offices, and partners. Addressing capacity issues in national health systems, such as workforce shortages and long wait times, can be supported through telemedicine and temporarily integrating Ukrainian healthcare workers. Refugees with chronic illnesses and disabilities require targeted interventions to meet their health and MHPSS needs, including through health financing mechanisms. Continued efforts are also required to address persistent access barriers through contextspecific strategies, including providing refugees with information on navigating health systems and preventive health services such as vaccination.


Input: The JLMPS sample is restricted, after matching it to the 2010 school census, to individuals born in Jordan who are aged 25 to 70 in 2010 and who have nonmissing information on age, subdistrict of birth, years of schooling, father ’ s schooling, mother ’ s schooling, and local supply of schools in subdistrict of birth. 9 These exclusions resulted in a sample of 4, 139 males and 4, 131 females, which are referred to as the male and female full samples, respectively. 7. Because of the absence of annual estimates of subdistrict populations, the population used to normalize the supply of schooling at the subdistrict level is the 2004 population of the subdistrict. There are 86 subdistricts in Jordan. If subdistrict populations are growing at different rates, this could introduce some measurement error of the true supply of schooling available to different cohorts. 8. Secondary schools include both general and vocational secondary schools. Public schools include schools under the jurisdiction of: (i) Ministry of Education, (ii) Ministry of Higher Education, (iii) Ministry of Defense, (iv) Ministry of Social Development, (v) Ministry of Religious Endowments (Awqaf), and (vi) UNRWA. 9. The original sample size of all individuals who are aged 25 to 70 years in 2010 and are born in Jordan is 8, 312 observations. The sample restrictions on the missing values result in the exclusion of 34 observations (missing age), 1 observation (missing father ’ s schooling), and 7 observations (missing mother ’ s schooling).


Input: The recent analysis on poverty headcount and inequality in Sub-Saharan Africa draws upon the Sub-Saharan Poverty Assessment Report 2022, which provides comprehensive data on income distribution and living standards across the region. This dataset, published by the African Development Bank, reveals significant disparities in wealth that have persisted despite various economic initiatives aimed at alleviating poverty.

Sub-Saharan Poverty Assessment Report 2022

Sub-Saharan Poverty Assessment Report 2022


Input: Refugee Policies on Self-Reliance and Resilience. Journal of Refugee Studies, 33(1), 22-41. Kvittingen A., Valenta M., Tabbara H., Baslan D., and Berg B. (2018). The Conditions and Migratory Aspirations of Syrian and Iraqi Refugees in Jordan. Journal of Refugee Studies 32(1), 106-124. https://doi.org/10.1093/jrs/fey015. Lebow, J. (2023). Immigration and Occupational Downgrading in Colombia. Journal of Development Economics, Forthcoming Levenson, H. (1981). Differentiating among Internality, Powerful Others, and Chance. Research with the Locus of Control Construct, 1, 15-63. Liu, D. and Kwan, M. (2020). Measuring Spatial Mismatch and Job Access Inequity Based on Transit-Based Job Accessibility for Poor Job Seekers. Travel Behaviour and Society, 19, 184-193. https://doi.org/10.1016/j.tbs.2020.01.005 ESS and World Bank. (2023). Ethiopia Socioeconomic Panel Survey Report – Wave 2, 2021/22. Marbach, M., Hainmueller, J., Hangartner, D. (2018). The Long-Term Impact of Employment Bans on the Economic Integration of Refugees. Science Advances, 4. https://doi.org/10.1126/sciadv.aap9519. Martin, S. F. (2010). The Causes and Consequences of Forced Migration. Paper presented at the Annual Meeting of the Population Association of America, Dallas, TX. Maystadt, J. F., and Verwimp, P. (2014). Winners and Losers among a Refugee-Hosting Population. Economic Development and Cultural Change, 62(4), 769-809. MoE. (2022). Education Statistics Annual Abstract (ESAA). MoE MoLSA. (2019). Revised Directives

Ethiopia Socioeconomic Panel Survey Report

Ethiopia Socioeconomic Panel Survey Report

Ethiopia Socioeconomic Panel Survey Report


Input: The recent analysis of urban transportation patterns draws on data from the Urban Mobility Assessment and the Metropolitan Infrastructure Survey. These datasets provide insights into the challenges faced by cities in managing their transport networks and infrastructure needs.

Urban Mobility Assessment
Metropolitan Infrastructure Survey

urban infrastructure and transportation planning