ai4data/datause-dataset-rechunked huggingface dataset:
1) _Food consumption._ We include the value of food consumed from all possible sources, as measured in POF. This includes food acquired for consumption at home, which is collected in the household questionnaire of frequent acquisitions (POF 3). Food consumed at home can be acquired via monetary means, obtained through own production, or received in kind or via other means that do not involve monetary payment.

The value of consumption of FAFH is collected in the individual-level expenditure questionnaire on nonhousehold goods and services (POF 4). Again, this component of food consumption might have been acquired via monetary as well as nonmonetary means.

Finally, POF also collects information on food consumption outside the home - in particular, meals consumed in settings like at school or on vacation.

POF collects information on a wide range of nonfood items, but several are typically not included in the construction of a consumption aggregate used for welfare analysis.

For this, a detailed inventory of durable goods is needed, including information on their value (either original purchase date and value, or current replacement value). POF, however, collects information only on quantity, mode of acquisition, year, and state (new or used) in its durable goods inventory, but not on values.
humanitarian emergencies and protracted refugee status. Forced displacement is a pressing issue in the country, a result of conflict, drought, flood, economic instability, and political instability in neighboring countries (Martin, 2010; UNHCR, 2020d; IPCC, 2019). As of year-end 2023, more than 922,000 refugees and asylum seekers 1. Introduction 0 200,000 400,000 600,000 800,000 1,000,000 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 Population Years Sudan Somalia South Sudan Eritrea Kenya Other countries Figure 1.1: Refugees and asylum seekers in Ethiopia by country of origin, 1984-2023 Source: UNHCR Refugee Data Finder 2024. Introduction 2 were seeking refuge in Ethiopia, with the majority originating from South Sudan (420,000), Somalia (280,000), Eritrea (170,000), and Sudan (49,000). Ethiopia is a signatory to the 1951 UN Convention on the Status of Refugees and its 1967 Protocol, with an obligation to protect refugees and asylum seekers. Most refugees (92 percent) are living in approximately 30 camps and sites located in Afar, Amhara, Benishangul-Gumuz, Gambella, Somali, and Tigray regions, with an increasing number of refugees
**4)** **Slope** is measured by the area weighted average of slope categories. This variable is calculated based on data from the Harmonized World Soil Database version 1.2 with eight slope classes: 1 for least steep (elevation of 0-0.5 percent) and 8 for most steep slope (elevation greater than 45 percent).

**5)** **Rainfall variability** is defined as the 1981-2010 standard deviation of monthly rainfall levels. The variable is constructed from the global CRU TS3.21 dataset from the University of East Anglia, containing a long-term time series of monthly rainfall levels at 0.5x0.5 grid resolution, which was produced using statistical interpolation based on data from 4,000 weather stations (Harris et al., 2014).

The VHLSS provide detailed information to estimate consumption expenditure, which can be used to estimate poverty rates. This study uses district-level poverty maps based on estimates from the VHLSS 2010 combined

<!-- PAGE 6 --> with the 15-percent sample of the 2009 Population and Housing Census as calculated by Lanjouw et al. (2013). In addition, household consumption is calculated from the VHLSS 2010, 2012, and 2014 based on detailed expenditure data in line with the methodology for determining the GSO-World Bank poverty line. All consumption values are expressed in 2011 Purchasing Power Parity (PPP) values using data on the Consumer Price Index from the World Development Indicators.
However, it also highlights the APC’s limited capacity to collect protection data and build up a more
robust and comprehensive protection analysis. The main challenges have been identified as limited
humanitarian access, sensitivity related to some protection thematic, a lack of information sharing
among different agencies, limited capacity and knowledge to operationalize the protection risks
equation, a lack of conflict sensitivity analysis and limited protection assessments. The available
protection analysis is usually limited to the overall chronic issues in the country, while conflict and
displacement related risks and threats remain less explored and assessed.

Those limitations can be overcome should the APC members prioritize the resources to fill those gaps
and increase their commitment to the coordination system for the protection sector.

A workshop with APC members will be organized in the course of August 2017 which will provide an
opportunity to produce a joint protection analysis that would support a prioritization exercise.

Integrated protection response plans are also under development at regional level and will provide a
regional perspective of the protection context and priorities.

Page **10** of **12**
is largest in the Somali domain (where it increases to 89 compared 76 percent for males). A similar pattern is observed regarding being comfortable with having a refugee neighbor. 0 10 20 30 40 50 60 70 80 90 100 Eritrean Somali South Sudanese Addis Ababa All Hosts Strongly agree Agree Disagree Strongly disagree Percent Figure 7.1: Host response to “Refugees are good people” Source: World Bank Staff based on SESRE 2023. 0 10 20 30 40 50 60 70 80 90 100 Eritrean Somali South Sudanese Addis Ababa All Hosts Comfortable Neutral Not comfortable Percent Figure 7.2: Host response to “Would you feel comfortable having a refugee as a neighbor?” Source: World Bank Staff based on SESRE 2023. Markets and Opportunities 65 0 10 20 30 40 50 60 70 80 90 100 Male Female Male Female Male Female Male Female Eritrean Somali South Sudanese Addis Ababa Comfortable Neutral Not comfortable Percent Most Ethiopian hosts want refugees to have access to free primary education and healthcare and the right to work, and to live where they choose. Eighty-seven percent of hosts believe that refugees should have the right to free primary education and healthcare, increasing to 95 percent in
11 the region. Third, again due to cultural closeness, the nature of these variations is known across the region. 9 Additional measures: We collected usual socio-economic and demographic information, including: age, gender, marital status and education. In addition, we collected data on self- reported risk preference and a short-form personality survey to ascertain GRIT among participants. Noting that a small number of participants did not answer all survey questions, we undertake a regression-based data interpolation process to complete the dataset. 10 Table 1: Partner Assignment and Sample Sizes by Treatment and Community Status Host Refugee Ingroup Outgroup Ingroup Outgroup T C T C T C T C Outreach / Baseline 219 48 203 48 147 72 147 49 Endline 179 34 222 37 148 45 133 51 We present summary statistics of demographic data and other covariates for the baseline (Top) and endline (Bottom) for Jordan in Table 2 and for Lebanon in Table 3. [TABLES 2 AND 3 ABOUT HERE] Identification: The “ fuzzy ”, treatment intake is not random. As can be seen in Table 1, there are some elements of attrition from the sample. The sample decreases by about 10 % from baseline to endline.
capital, and concentration in low wage jobs. Furthermore, most of these jobs are in the service sector which potentially could have freed up time, especially for Peruvian women to be more engaged in the labor market, as well as lowered the costs for these types of goods and services. Venezuelans also might have expanded opportunities by increasing the demand for certain goods and services. One widespread claim mentioned in some media reports is that Venezuelan migration led to an increase in crime (Freier et al., 2021). We test whether this claim is supported by the data in Table 6, where we use administrative information on the number of non-violent and violent crimes reported in each municipality, the personal security index from Gallup, and reports on whether crime is perceived as a major problem in ENAHO. The structure of this table is the same as the previous with Panel C our preferred speciﬁcation. Consistent with the idea that Venezuelan inﬂow lead to labor market conditions improving, we observe that locations that received a larger number of immigrants have lower number of reported non-violent crimes (columns 2). This eﬀect is large with a double of Venezuelans in a province leading to a 42 % decline in reported non-violent crimes.
Beneficiary assessments confirmed that the most significant barrier to cooperative membership for women was the requirement to present land title documentation as proof of agricultural practice. Since women in the project area rarely hold formal land title independently of their husbands, this requirement effectively excluded female farmers from cooperative membership. The project's operational manual was revised to accept a sworn declaration of land use from the village council as an alternative to formal land title for female applicants.
of difficulty, ranging from those suitable for children as young as 2 and a half years old to more complex items for individuals over 18 years old. 19 The Peabody Vocabulary Test is calibrated with a mean standard score of 100 and a standard deviation of 15, placing scores between 85 and 115 within the average range. This test, in its Spanish edition, has been validated for use in Colombia. Additionally, to ensure relevance and accuracy for Venezuelan nationals, we conducted a preliminary validation by administering the test to a sample of Venezuelan mothers in our study. This step confirmed that the words used in the test held consistent meanings for participants from Venezuela. Figure B. 1 depicts the distribution of PVTS scores for Venezuelan and Colombian chil- dren and adolescents in our sample. This visualization indicates that Venezuelan minors consistently score lower on the PVTS compared to their Colombian peers across the en- tire score distribution. In Table 6, we present the average disparities in percentile rank on the Peabody scale, revealing that Venezuelan children and adolescents, who are forcibly displaced, score approximately 12 p. p. lower than their Colombian counterparts. The difference is meaningful and in turn translated into Venezuelan minors falling into the a higher likelihood of having extremely low, moderately low, and low score categories.
The SEIS was designed as a nationally representative survey of households with at least one member holding refugee or asylum-seeker status, and the sampling frame was constructed from UNHCR's biometric registration database. SEIS enumeration areas were selected with probability proportional to size, stratified by settlement type (camp, urban, rural dispersed). Questionnaire modules cover household composition, labor market participation, housing conditions, access to education and health services, and subjective well-being. The SEIS sampling methodology ensures that estimates are representative at the national level and by settlement type.
Third, the EPAG program was designed around the girls'needs: service providers held both morning and afternoon sessions, to accommodate the participants'busy schedules; trainings were held in the communities where the girls reside; and every site offered free childcare. Fourth, frequent and unannounced monitoring visits by MoGD staff ensured that the service providers created and maintained a high-quality learning 4 There are: National Adult Education Association of Liberia (NAEAL), Community Empowerment Sustainable Program (CESP), EduCare, and Children ’ s Assistance Program (CAP). 5 A total of 19 training venues were used during the first round of training. They were chosen with the following considerations in mind: 1. Girls ’ safety, so that the buildings are not so isolated or otherwise dangerous, raising security concerns for girls. 2. Conducive atmosphere for learning, spacious and sanitary with access to water and latrine facilities. Reasonably outside community noise concentration. 3. Proximity to community center and to security posts such as police depots. 4. Accessible to girls from various parts of the community. 5
Finally, we show using the IPUMS dataset that children born in the United States to men born in China are more likely to be boys, but this finding does not hold for children born to women from China."

A very clear pattern emerges from the third of a million births in the one percent sample of the
1990 Chinese census. Note that this pertains to births during 1989-90, which is close in time to
that for which Oster made her calculations on the proportion of the female deficit in China
attributable to HBV (Oster 2005, Table 11).

Using data on expected average annual loss (AAL) and estimates of AAL reductions resulting

Survey results indicated that only 55 percent of respondents reported understanding the insurance

aversion may influence adoption of index insurance (Bryan, 2010), in the Gujarati data the
3. 5 Forecasts of Program Impacts The forecasters were mainly researchers working on topics in migration and development eco- nomics, or those with expertise in humanitarian program implementation, and were asked to predict effects on the program ’ s primary outcomes. For round 1, a total of 61 individuals, comprising 37 researchers and 23 non-researchers, responded to surveys about the program ’ s effects on refugee well-being. For round 2, 63 respondents, including 53 researchers and 10 non-researchers, pro- vided predictions on the effects on neighbors ’ social cohesion responses. Gathering forecast data allows us to assess whether estimated impacts were in line with the prior beliefs of research and policy experts. Table 2 presents the mean predicted effects, as well as the interval from the 10th to 90th percentiles of predictions. Generally, forecasters anticipated modest improvements in refugee well-being, particularly regarding housing outcomes, while predicting no average impact on the social cohesion measures collected among neighbors. 4 Empirical Strategy 4. 1 First stage compliance with program assignment Table 3, Panel B presents the ﬁrst stage analysis and the HSP take-up rate of 33 %. While sta- tistically signiﬁcant, the compliance rate is lower than expected, especially given the substantial funding offered by the program.
this marginal progress. In 2020, the COVID pandemic closed markets, albeit relatively briefly, and this immediately decreased job opportunities. While most reentered the labor market, many changed their work situation, and some permanently exited the workforce or reduced working hours. At the same time, more and more people— rural women in particular—are unemployed or out of the labor market altogether. Nationally, unemployment doubled between 2013 and 2021, and it tripled in rural areas. Women and youth both saw particularly sharp increases in unemployment. There was also a decrease in the labor force participation rate (LFPR), from 86 percent in 2013 to 74 percent in 2021, following a long period of steady LFPR in the two previous LFS surveys. Like for unemployment, LFPR was much more affected in the rural labor market, and these trends are particularly striking for women. 3. Jobs and Livelihoods Jobs and Livelihoods 25 Within this challenging context, vulnerable populations—including refugees—face unique barriers to accessing quality work. On average, rural women, urban youth, people with disabilities, and rural-urban migrants are more likely to be inactive and less likely to have improved their livelihoods over the last two decades. In this context, it is unsurprising that refugees cite
- This report includes all referrals data for the period January to December 2016

- Data was collected from 11 sites; 6 Urban (Amman, Zarqa, Mafraq, Irbid, Ramtha,
and south Mobile Medical Unit), 4 camps (Zaatri, Azraq, Cyber City and King
Abdullah Park), and Ruwaishid.

- Data was captured on-site daily then compiled and shared on a monthly basis with
JHAS referral hub, where the initial data compilation and cleaning was done.
Compiled and cleaned data was then shared with the UNHCR Public Health Unit,
where secondary data cleaning and analysis was carried out.

- Descriptive analysis carried out using Microsoft Excel 2013.

**3 |** P a g e
7 UNHCR Pakistan PA 2016 participants reported regularly experienced arrest, detention, threats of deportation and extortion 
(Punjab: 24% female / 17% male; KP: 4% female / 5% male; Sindh: female 7% /male 10%; Baluchistan: 7% female /  4% male) 
8 Locations that reported Police Harassment to be the most common safety and security concern, include Peshawar in KP, Attock 
and Rawalpindi in Punjab, and Chiltan Town (Tehsil) in Baluchistan. However, male respondents from Chiltan Town Tehsil (Killi Landi 
Kuchlak, Qadri Abad, Ghous Abad) reported a significant improvement in the overall security situation compared to last year.
14 Bearing in mind that this data is then translated to semi-annual data, i. e. the specific month is not used, among those who reported the starting month of their different jobs, the probability of starting a job in a given half-year was approximately 50 percent. We, therefore, think that a random assignment that gives equal weight to all months (and to each of the two half years) is a sensible choice. We construct a semi-annual synthetic panel. In doing so, we assume that each individual in the sample is observed over the period from the first half year of 2016 to the second half year of 2020. Individuals who entered the job market later than the first half of 2016 are considered non- employed until entry. Using the starting and ending dates for all the jobs an individual has engaged in, we can identify the individual ’ s job finding and job separation events. In particular, we convert the starting and ending month of a job into the half year they belong to. For example, a person who started a job in May of 2017 is coded as found a job in the first half year of 2017. In Table 2, we present the transitions by half-year, nationality of individual, their camp residency if they are Syrian and the imputation status.
**Annex 8: SIGAF Configuration and Reporting Requirements**

The SIGAF installation at the PIU uses Version 4.2 of the government's integrated financial management system. Key configuration parameters include: project budget structure mapped to the loan disbursement categories; reporting hierarchy linking district accounts to the central project account; and automated monthly statements that consolidate transactions across all spending units. SIGAF user accounts are managed by the Ministry of Finance's system administrator and must comply with the government's password security policy updated in 2022.
Restrictive norms perpetuated by men continue to severely restrict women ’ s access to the formal labor market. Fortunately, the Jordanian government has worked in recent years to address this problem. For example, in the amendment made to the Jordanian labor law in 2019, the provision of childcare services was made mandatory in every business that has 15 or more employees, male or female, with children under 5 (World Bank, 2019). However, implementation is not consistent and low-income households report less access to childcare services (Weldali, 2022). Home-based businesses can also provide important access to economic opportunities for women, albeit within a limited number of sectors and the Government of Jordan ’ s 2017 amendments of the regulations governing the licensing of home-based businesses is particularly important for female entrepreneurs in both host and refugee communities (Slimane et al, 2020; Turner, 2019). 3. Data and descriptive statistics We use two rounds of household-level data collected by UNHCR in 2013-14 and 2017-18. 6 These data come from two sources, namely, the Profile Global Registration System (ProGres) and Jordan Home 6 For simplicity, from here on we refer to the first wave as the 2013 wave, and to the second wave as the 2018 wave.
**Annex 3: Flood Hazard Maps — Data Sources and Update Schedule**

Flood hazard maps were derived from three hydrological datasets: (i) daily streamflow records from 18 gauge stations maintained by the national water authority for the period 1990–2022; (ii) a 12.5-meter resolution digital elevation model produced from ALOS PALSAR radar data; and (iii) land cover classifications from the national land use inventory. Flood hazard maps will be updated at project midterm using a revised hydrological model that incorporates non-stationarity in flood frequency distributions attributable to observed trends in extreme precipitation.
Using a survey of 4,500 manufacturing firms for the year 2010-11, this paper estimates the impact of electricity shortages on firm productivity in Pakistan.

We match firm-level data from the Census of Manufacturing Industry conducted by the Pakistan Bureau of Statistics with district-level power shortage data reported by distribution utilities.

The Census of Manufacturing Industries provides a thorough annual overview of firmlevel activities, including detailed information on a variety of input costs, including labor, capital and electricity, as well as revenue data. The 2010-2011 census mainly covers firms in Punjab province.

The census covers 4,499 firms in 23 sectors at the 2-digit level of Pakistan Standard
Industrial Classification (PSIC). [ 4] The distribution of firms by the 2-digit classification are
shown in Table 1. Of the 23 divisions, number 13 (Manufacturing of Textiles) covers
roughly 28 percent of our sample, division 10 (Manufacturing of Food Products)
accounts for 15 percent, and division 32 (Other Manufacturing) is the third-largest with
11 percent of the sample. The 23 sectors can be further broken down into 236
subcategories at the 5-digit level of PSIC.
The poverty map for 2009 is the result of collaboration between the World Bank and INSTAT (National Statistics Institute) and uses data from the 2009 census and the 2010 ELIM. One major methodological difference between the two maps is that the map of 1998 is based on a consumption model that considers urban and rural areas inside each administrative region with a total number of 17 models, whereas the map of 2009 uses only 8 regional models.

|Figure 16a Own revenues (CFA francs/capita),<br>2005-08|Figure 16b Capital investment and Current<br>expenditures (CFA francs/capita), 2000-08|
|---|---|
|<br> <br>|<br>|
|**Figure 16c Capital investment by sector (CFA**<br>**francs/capita, 2000-08)**|**Figure 16d Components of current expenditures**<br>**(CFA francs/capita, 2006-08)**|
|||
|_Source:_ Authors' calculations from ODHD (Sustainable Development Observatory) data 2003, 2006, 2008.|_Source:_ Authors' calculations from ODHD (Sustainable Development Observatory) data 2003, 2006, 2008.|

A clean econometric identification of the impact of mining activities on local government budget
outcomes would require data on budgets for both mining and non-mining _communes_ during preand post-mining. However, we have annual budget data available for only 2006 to 2008, during
which most of the mines had already opened. Industrial gold production started with the first site
in Sadiola in 1996, just two years before the second population census of Mali. Fortunately, we
are able to use the 1998 population census to fully control for some initial differences across
communes, such as poverty and education levels prior to the mining boom. We also test whether
larger mines have bigger impacts on budget outcomes by using the cumulative level of production
measured in metric tons as an alternative measure of mining activity.