ai4data/datause-dataset-rechunked huggingface dataset:
The 355 municipalities are grouped into 25 GGD areas, each covering a population of approximately 600,000 inhabitants. The GGD borders are visible in figure 5 which visualizes the hospital admissions. The data is combined with demographic statistics (2019) obtained from the Dutch Central Bureau of Statistics.

A number of surveyed health
statistics (2016) have been obtained as well from the RIVM (maps can be viewed in the
source link). [11] . The data is based on a survey of 457,000 people and includes the share of
population in each district with a documented long-term illness (illnesses over 6 months), the
prevalence of overweight and obesity, alcohol abuse, smoking and noise due to traffic.

For the main analysis, annual average particulate matter concentrations from the RIVM are used to capture long-term exposure (2017, published September 2019).

he temporal lag in the pollution data also ensures that there is no endogeneity due to feedback between case incidence and changes in pollution levels that follow lock-down policies. To test whether the main findings of the analysis generalize to other pollution data sets, a second analysis presented in the appendix uses the coarser grids from the global PM2 _._ 5 data set of van Donkelaar et al. (2016).

Cases are reported to the RIVM by the Municipal Health Service (GGD).The GGD is organized as collaboration between municipalities to provide base level public health service
In doing so, this paper also relates to recent research using firm-level data to document effects of foreign acquisitions on firm performance, including Arnold and Javorcik (2009), Bloom et al.

In order to estimate equations (1), (2) and (3), we use data from the Orbis database
of Bureau Van Dijk. The Orbis dataset provides retrospective information on
company ownership and reports the country of origin of each foreign shareholder,
although the share value is often unknown.

The data covers about 58% of Polish firms as reported by Eurostat and coverage varies significantly across regions (Farole et al., 2017). [5] Figure A.4 shows the evolution of the percentage of companies with at least one foreign shareholder from either Germany, French, the United States or the United Kingdom.
5 interviewed (i. e., on the premises when the enumerators began their interviews) were included in this survey. Enumerators selected households within the catchment area randomly. Among households with an age-eligible child present (i. e., 0-35 months or 36-72 months), enumerators explained the purpose of the study and invited the target child ’ s primary caregiver to be interviewed. Respondents were supported to withdraw their consent anytime during or after the interview and such cases were dropped from analyses. For children 0-35 months of age, assuming a minimum power level of. 8 and an alpha of. 05, the study design predetermined that the minimum desired detectable difference in average ECD Z- score measured by the Caregiver Reported Early Development Instrument (CREDI) was a 0. 2 standard deviation (SD) difference, which has been shown to be the average difference between urban and rural Pakistani children assessed using the CREDI (Hentschel et al., 2024). For children between 36 and 72 months of age, assuming a minimum power level of. 8 and an alpha of. 05, the study design predetermined that the minimum detectable difference in average ECD score (measured by the AIM-ECD score) is a 0. 23-point difference (the difference between males and females in Hentschel et al., 2024).
8 households in each. To select a starting point the enumerator used a code of the day16 and chose every second house in rural areas and every fifth house in urban areas. The selection of individuals within the household to answer the questionnaire was conducted as follows: the head of household (male or female) was selected to answer the first part of the questionnaire dealing with general questions about the households. Using the roster of household members which was compiled during the first part of the interview, another member of the household aged 18 or above was selected randomly to answer the second part of the questionnaire in which perception questions were asked. Alternation between male and female was ensured. The survey thus generated data that are reflective of the opinions of those aged 18 and above in northern Mali. To assess the representativeness of the data, which were collected under rather challenging circumstances, the ethnic composition of the sample was compared with the ethnic composition in the North as reported by the 2009 Census.
In contrast, the self-assessed entrepreneurial score is based on questions asking how well the respondent believes she could perform a series of six tasks related to starting or running a business, and can be considered a task-oriented measure of self-efficacy. The aggregate measure of entrepreneurial ability increased by roughly nine percentage points among EPAG beneficiaries relative to those in the control group, equivalent to a quarter of a standard deviation. Enhancing participants ’ self-confidence to perform these tasks was one of the main immediate objectives of the BDS training program. Table 6B summarizes the results on a series of questions on attitudes and self-confidence that were added during the midline survey only (hence no panel analysis is possible). EPAG graduates report a more positive attitude: they feel more in control and more comfortable, and they have greater confidence in their own business abilities as well as in their personal and social lives. They are also more confident than the control group in their personal relationships with spouses and partners, consistent with the findings in Table 6A.
Nevertheless, we believe that this analysis provides suggestive   13As mentioned earlier, this is per capita income for the three months prior to the ENIGH survey.

CADENA now offers weather index insurance   for a variety of perils (e.g., drought, flood, hail), as well as area-based yield index insurance, which   2Subsidies from the federal government depend on the marginality index of the insured municipality, as computed by CONAPO.

Note. The data used to created this table comes from the 2010 census. % Illiterate is defined as the number of
illiterate individuals over the age of 15 divide by the total population over 15.

**Karlan,** **Dean,** **Robert** **Osei,** **Isaac** **Osei-Akoto,** **and** **Christopher** **Udry**, "Agricultural


Decisions after Relaxing Credit and Risk Constraints," _Quarterly_ _Journal_ _of_ _Economics_, 2014,

In addition, this study computes environmental risks at the commune level [2] to relate it to household information based on the Vietnam Household Living Standard Surveys (VHLSS) for 2010, 2012, and 2014. Benefiting from the panel
These include topics like labor, finance (e. g., credit, debt, banking), agriculture / livestock / fishery, and education whereas FDP datasets are relatively rich in health, food insecurity, and water and sanitation in addition to coping strategies and protection. Furthermore, a large majority of questionnaires for these existing micro-level datasets do not include a core set of questions needed for proper identification of displacement status. This calls for further efforts 2 See https: / / www. unhcr. org / news / stories / unhcr-s-grandi-110-million-displaced-indictment-our-world. 3 The UNHCR MDL is available at https: / / microdata. unhcr. org / index. php / about. 4 The WB MDL is available at https: / / microdata. worldbank. org / index. php / about. 5 We focus on low-income and middle-income countries because they account for roughly 95 percent of FDP (refugees + IDPs) in the world based on data from UNHCR Refugee Finder and IDMC. 6 A representative sample means that when analyzed, the observed characteristics of the sample reflect the true characteristics in the target population that is being researched (Baal and Ronkainen, 2017).
_replications. Contemporaneous cross-unit correlations are generated by computing the cross-correlations of residuals from_ _AR(I) regression of the first difference of Gross State Product for 20 U.S. states from 1963 to 1986 and of Gross Domestic_ _Product for 24 O.E. C.D. economies from 1960 to 1991._

areas, of which 72 percent depends on agriculture (Census of India, 2011). Agriculture accounts for 17 percent of GDP and employs 51 percent of the total labor force (World Bank, 2010). [2]

_Source_ : Author's analysis based on the 1982 and 2006 rounds of the Additional Rural Incomes Survey and Rural Economic & Demographic Survey (ARIS-REDS)   from the National Council of Applied Economic   Research.
<!-- PAGE 10 -->
ILRI, and the World Bank (as part of the LDIA and LSMS-ISA projects [2] ) to start the survey

validation work that is documented in this paper.


2.2 _Milk production recall methods_

Using data from two microenterprise surveys in Sri Lanka, De Mel et al. (2009) find that

the same survey experiment in Tanzania to obtain evidence on the nature of measurement

Scott and Amenuvegbe (1990) conduct an experimental study on 135 households in Ghana.

Dantlait survey. The fieldwork was managed by two experienced enumerators, and a
market outcomes (Kotsadam and Tolonen 2016). Mining is also associated with more economic


activity measured by nightlights (Benshaul-Tolonen, 2019; Mamo et al, 2019).


Kotsadam and Tolonen (2016) use DHS data from Africa, and find that mine openings cause

and GLSS with production data for 17 large-scale gold mines in Ghana. We find that a new


large-scale gold mine changes economic outcomes, such as access to employment and cash

increase in total production that rose from 541,147 oz in 1990 to 3,119,823 oz in 2009 according


official Ghana statistics (Bloch and Owusu, 2012). This production increase led to an increased

South Africa
Teberebie 1990 2005 Anglogold Ashanti South Africa
Wassa 1999 active Golden Star Resources USA
_Source:_ InterraRMG 2013.
_Note:_ Active is production status as of December 2012, the last available data point.
However, should ASM respond to large-scale activities, either by increasing or decreasing activity in the close geographic area, we will end up estimating the impact of these sectors jointly. In a later stage, should the opportunity arise, we encourage researchers to try to disentangle the effects of small-scale and large-scale mining. 3 Data To conduct this analysis, we combine different data sources using spatial analysis. The main mining data is a dataset from InterraRMG covering all large-scale mines in Ghana, explained in more detail in section 3. 1. This dataset is linked to survey data from the DHS and GLSS, using spatial information. Geographical coordinates of enumeration areas in GLSS are from Ghana Statistical Services (GSS). 2 Point coordinates (global positioning system [GPS]) for the surveyed DHS clusters3 allow us to match all individuals to one or several mineral mines. We do this in two ways. First, we calculate distance spans from an exact mine location given by its GPS coordinates, and match surveyed individuals to mines. These are concentric circles with radiuses of 10, 20, and 30 kilometers (km), and so on, up to 100 km and beyond. In the baseline analysis where 2 The data was shared by Aragón and Rud (2013) 3 Both the DHS and GLSS enumeration area coordinates have a 1-5 km offset. The DHS clusters have up to 10km displacement in 1 % of the cases.
The authors argue that Croats listened to Serbian radio for its consumption value but reacted negatively to national- istic messages intended for Serbian ears. Election results and street surveys are used to elicit preference for extremist nationalist parties among Croats who are able to listen to Serbian radio and those that do not. The authors ﬁnd that 3 to 4 percent of those 59See Yanagizawa-Drott (2014). 60See, for example, Enikolopov et al. (2011) and DellaVigna and Kaplan (2007) who ﬁnd large eﬀects on voting shares. 70
not better positioned to work in the formal private or public sector, their participation in trade and service relates to economic 47 This analysis uses the relaxed definition to measure the current employment status of the host community and refugees. 48 As the previous chapter highlighted, most of refugees engaged in agriculture activity are livestock holders (see Chapter 3). 44 37 42 55 LFPR Nearest to Zone Nearest to Woreda but not Zone Nearest to border but not Zone & Woreda Remote 40 40 49 LFPR High accessibility Medium accessibility Low accessibility Figure 6.2: Labor force participation rate by proximity to resource hub, market accessibility Source: World Bank Staff based on SESRE 2023. Note: High, medium, and low accessibility refers to the level of market access, with >0, [-0.5, 0], and <-0.5 standard deviations from the average, respectively. 60 40 56 44 68 32 46 54 Employment rate Unemployment rate Nearest to Zone Nearest to Woreda but not Zone Nearest to border but not Zone & Woreda Remote 64 36 60 40 50 50 Employment rate Unemployment rate High accessibility Medium accessibility Low accessibility Figure 6.3: Refugees’ labor market outcomes Source: World Bank Staff based on SESRE 2023. Note: High,
Since the poverty headcount only reflects the proportion of poor people, it is usually complemented by a measure of the depth of deprivation, the poverty gap, which estimates the average gap between poor individuals and the poverty line. All poverty measures constructed in such a way are based on an underlying welfare metric. In most cases, the metric is defined at the household level and needs to be transformed into an individual measure. The transformation either divides household welfare by household size, providing a per capita measure or, in a more sophisticated way, takes into account differences in household composition (usually age and gender), leading to a per-adult equivalent measure. To measure household welfare, different metrics have been proposed and can generally be classified either into monetary or non-monetary metrics. Monetary metrics equate levels of well-being to a monetary indicator of utility (Samuelson, 1974), usually income, consumption or expenditure. Non-monetary metrics define normatively dimensions of deprivations, e. g., access to education and clean water, and aggregate them either by using dimension-specific thresholds or an aggregated threshold. The most commonly used approach in this class is the Multidimensional Poverty Index by UNDP and Oxford University (MPI; OPHI, 2018). While it is not uncommon to find experts with a strong preference for one measure over the other, both classes of poverty measures are in most cases complementing each other. While the monetary metric has the advantage of its theory-grounded definition without normative choices, it is complex to measure
Addis Ababa Eritrean Somali South Sudanese Addis Ababa Eritrean Somali South Sudanese Addis Ababa Has hand washing place/item Water available Detergent available Hosts Refugees Percent Figure D.15: Hand washing facility Source: World Bank Staff based on SESRE 2023. Annexes 105 Table D.5: Labor force statistics by survey domains Eritrean Somali South Sudanese Hosts Refugees Hosts Refugees Hosts Refugees Participation (strict) 57% 38% 44% 35% 55% 28% Employment (strict) 89% 72% 94% 77% 96% 82% Unemployment (strict) 11% 28% 6% 23% 4% 18% Participation (relaxed) 62% 60% 51% 49% 57% 38% Employment (relaxed) 81% 45% 81% 55% 91% 60% Unemployment (relaxed) 19% 55% 19% 45% 9% 40% Source: World Bank Staff based on SESRE 2023. Table D.6: Determinants of refugee-host earnings gap (1) (2) (3) (4) Earnings Earnings Earnings Earnings Refugee (% difference from hosts) -69.8*** -63.7*** -62.1*** -40.7*** (0.077) (0.123) (0.122) (0.126) Control: Region Yes Yes Yes Yes Control: Demographics Yes Yes Yes Control: Occupation/Sector Yes Yes Sample: Working outside camp Yes Sample Size 743 742 742 572 Source: World Bank Staff based on SESRE 2023. Note: Monthly earnings are collected for employees only (including work for government, NGOs, and private households). Log earnings are winsorized at the 1st and
Each respondent was presented with three vignettes, where key aspects of the sce- narios were randomly varied across respondents. These three vignettes were designed to probe the impact of diﬀerent pull and push factors on the refugees ’ return deci- sion, allowing us to go beyond the data limitations of the above analysis. That is, the vignettes not only explore the impact of security on return decisions, but also of employment prospects in both the country of asylum and Syria, the status of property in the home community, and the availability of ﬁnancial assistance. In particular, the ﬁrst vignette probes three questions: ﬁrst, whether the ability to 11According to this classiﬁcation, Jebel Saman, Deir-ez-Zor, Homs, Al Ma ’ ra, and Duma are high- conﬂict districts. 16
used in the Skills Profile Survey (SPS) and SESRE, we find similar patterns in some of the indicators common in both surveys among in camp refugees such as demographic composition, primary and secondary net enrollments, housing condition, access to basic infrastructures, employment and attitude of hosts toward refugees. Moreover, both surveys find that in camp refugees in Ethiopia are much poorer than host community households and poverty rates are heterogenous across refugee groups: South Sudanese refugees have the highest incidence of poverty, while Eritrean refugees have the lowest poverty incidence amongst the refugees. However, different poverty estimation methodologies and different poverty lines are used. Likewise, both surveys indicate that refugees are more food insecure than the host community. Annex F, Table F.1 shows a summary of these findings. Source: Pape, U. J., Petrini, B., and Iqbal, S. A. (2018). Informing Durable Solutions by Micro-Data: A Skills Survey for Refugees in Ethiopia. Box 1.1: Comparison of SPS 2017 and SESRE 2023 Sociodemographic Profile 9 2. Sociodemographic Profile T his chapter presents results on sociodemographic outcomes of refugees and hosts. It provides the context for refugees and their hosts, covering demographic characteristics, human capital, living conditions, and displacement experience, which are crucial
### Financial Management Risk and Mitigation

The overall FM risk is rated **Substantial** due to the multiplicity of implementing agencies and the limited capacity of district-level accountants. Key mitigation measures include: (i) appointment of a dedicated FM specialist at the central PIU; (ii) mandatory use of the SIGAF government accounting system for all transactions above USD 5,000; (iii) quarterly internal audits by the Ministry's internal audit department; and (iv) annual external audits by a firm acceptable to the Bank, with reports submitted within six months of fiscal year-end.
Formula (5) can be decomposed into two parts: eδs, which measures the average income level in district s, and eηszh ≡ eβs (Eh s − Es) + eχs (Hh s − Hs) which captures individual-speciﬁc variation in income. Migration models predict that, other things being equal, the choice of migration destination should depend on g E [yhs | zh]. This means that if we regress the choice of destination separately on eδs and eηszh, they should have the same coeﬃcient. The same methodology is used to construct other variables that may aﬀect the choice of 9The literature has often emphasized that migrations often serve an important role in household formation. For migrants, the prospect of forming a large, successful household is likely to be one of the purposes of migration. 10The 1995 / 96 NLSS survey adopted the following sampling strategy. Within each district a small number of wards were selected at random. Within each ward, 12 randomly selected households were interviewed. Because the wards diﬀer widely in terms of population, applying sampling weights is essential in order to obtain consistent estimates of δs. 16
UNHCR has adapted a policy of structured provision of health services for different
nationalities in order to maintain affordable access to secondary and tertiary referral
services. Essential secondary and tertiary referrals are available to eligible refugees of all
nationalities based on a pre-defined set of criteria at governmental hospitals and other
private affiliated hospitals (though UNHCR’s implementing partner Jordan Health Aid
Society; JHAS).

In order to facilitate referrals, UNHCR has established two levels of authority with the
implementing partner in order to facilitate and control the referral process. If the estimated
treatment cost is less than JODs 750 per person per year then the UNHCR partner will
manage the referral directly, while if the referral cost is more than JODs 750 per person per
year, the case has to be approved by the UNHCR health unit (for emergency cases) and/or
Exceptional Care Committee (ECC) for non-emergency cases before the referral takes place.

**Data Collection and Analysis**

Referral care is considered an essential part of access to comprehensive health services, thus
UNHCR since 2014 has maintained a medical referral database in order to monitor trends in
urban and camp settings in Jordan.
The Afrobarometer data reveal that technical capacity and not corruption or lack of accountability may be the reason local governments are not successful in transforming revenues into better public goods and services for better welfare outcomes.

Employment estimates in the artisanal gold-mining sector vary considerably-from 6,000
according to a Sustainable Development Observatory (ODHD) survey (2011) to 1 million in the
three active mining regions, according to the Chamber of mines (2013), and 200,000 according to
a survey by Central Bank of West African States (BCEAO 2013). The latest population census
estimates the number of people involved in artisanal gold mining at 25,000. The national labor
survey (the Permanent Household Survey, EPAM) of 2010 estimates that 28,000 people are
involved primarily in extractives. In addition, 14,000 people work in extractives as a secondary
activity, with farming being the primary activity of 76 percent of these people. The difficulty in
estimating the number of people employed in artisanal gold mining arises from the fact that the
activity is sometimes practiced in a "rush" manner, which may not coincide with a census or survey
-- PAGE 12 --> For the decomposition analysis of emissions intensity, we obtain annual country-level total passenger and freight transport traveled by road and rail from the World Road Statistics and the International Transport Forum databases.

The level of urbanization, and the value added from agriculture, manufacturing, and service sectors are all obtained from the World Bank World Development Indicators database.

Data on country-level BRT systems are obtained from global BRT database.

Diesel and gasoline prices are compiled from fuel price documentation from the Deutsche Gesellschaft für Internationale Zusammenarbeit GmbH (GIZ).

Farm data were collected by conducting a face-to-face survey among a
Our research complements and extends the findings of Demirci, Foster and Kirdar (2022), who investigated health and nutrition disparities between native children and Syrian refugee children aged 0 to 5 years in T ¨ urkiye, using data from the Demographic and Health Survey. The authors document find no significant differences in infant or child mortality rates between refugee children born in T ¨ urkiye and their native counterparts, it did reveal that refugee infants have lower birth weights and age-adjusted weights and heights compared to native infants. Our work broadens the scope of analysis beyond anthropometric indicators to encompass a holistic assessment of child development. By incorporating measures of physical, cognitive, socio-emotional, and mental health devel- opment, along with factors such as food security, time use, risky behaviors, and social integration, we offer a more comprehensive understanding of the developmental chal- lenges faced by displaced minors. Additionally, our study includes a wider age range, 5Chiovelli et al. (2021) examine the effects of forced displacement on separated sibling in the long-term. 8