rafmacalaba/data-use-mentions-extended huggingface dataset:
|Outcome|Table|Population|Primary?|Rounds|Description|
|---|---|---|---|---|---|
|Index of Women’s<br>Divorce Prospects<br>(Standardized)|-|Core<br>Respondent|No|4|Standardized index of ability of core<br>respondent to divorce her husband and<br>maintain household property.|
|Index of Fertility|||||Standardized index of differences in core|
|<br>Empowerment<br>(Standardized)|-|Core<br>Respondent|No|4|respondent and her husband ideal degree of<br>family planning.|
|Index of Self-|||||Standardized index of core respondents need|
|Determination in Marriage<br>(Standardized)|-|Core<br>Respondent|No|4|for permission from her husband to undertake<br>certain activities.|
|Index of Frequency of<br>Social Contact<br>(Standardized)|-|Core<br>Respondent|No|4|Standardized index of core respondents’<br>frequency of travelling outside the community<br>and sending and receiving phone calls and text<br>messages.<br>Standardized index of a series of questions|
|Index of Spousal Abuse<br>(Standardized)|-|Core<br>Respondent|No|4|both asking about when it is acceptable for the<br>husband to beat his wife, as well as whether<br>the husband is violent towards the core<br>respondent.|
|Age Difference Between<br>Wife and Husband|-|Core<br>Respondent|No|4|Age difference between core respondent and<br>her husband.<br>Standardized super index of married economic<br>control, measured for
not fall into this category, unless it has lasted for more than 5 days or is accompanied by other symptoms. It is likely that formal care is not the appropriate response to many of the diarrhea spells in the sample.<sup>13</sup> Indeed, mild diarrhea cases can be treated with ORT, which can be prepared at home. Alternatively, pre-mixed ORS packets can be purchased, and providers may also recommend ORT in addition to or in place of prescription medication. Column (3) of Table 3 shows that 12 Unconditional use of care is uninformative, because illness incidence varies between treatment groups, see below.

> 13The 2014 data reported here constitutes a small sample of spells and does not cover a long enough period to identify spells in which care was required per WHO guidelines in an unbiased manner.

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# Local-area level remoteness and socio-economic characteristics

The degree of a community’s remoteness within a country context is correlated with its socio-economic characteristics. For example, people living in more central parts of a country are more likely to be employed in paid work, or to have wages or salaries as a main source of income (Figure 4). In particular, the local areas with the highest proportion of people or households in paid work, or with wages or salaries as a main source of income, tend to be among the very least remote, according to our indicator.<sup>8</sup> However, there is variation around this general pattern across the case-study PICs, consistent with variation in the PICs’ respective geographies. The relationship is less clear in FSM, where the population is particularly widely dispersed, and where there are several key population hubs some distance apart.

The link between remoteness and a variety of socio-economic characteristics is explored comprehensively in a companion piece<sup>9</sup> to this work, though that piece focuses on related but alternative definitions of remoteness defined more explicitly according to areas’ distance from defined population hubs (e.g. the measures discussed in Appendix C).

> 8 These same local areas also tend to be the most populous. For most of the case-study countries, the negative relationship between local-area remoteness and the respective employment indicator is only statistically significant when the data are population-weighted.

> 9 World Bank, 2019. ‘Socio-economic analysis: A spatial analysis of population and housing census data’, a background paper prepared for _A Review of Spatial Development Issues in the Pacific Islands Countries_ (P166346).

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Another form of latent unemployment is involuntary temporary work: in 2002 about 5 percent of all employees (full-time and part-time) accepted fixed-term contracts because they were unable to find permanent jobs. While temporary employment gives employers more flexibility in their personnel practices, it has obvious negative consequences for the economic security of labor market participants.

**Figure 8.  Employment by Main Sectors in the EU Accession and Candidate Countries, 2002**

<!-- Start of picture text --> 80.0<br>70.0<br>60.0<br>50.0<br>40.0<br>30.0<br>20.0<br>10.0<br>0.0<br>CY EE HU LV BG SK CZ LT SI PL RO<br>agriculture industry and costruction services<br>employment share, percent<br><!-- End of picture text --> _Source_ : _Canstat_ 2003/2

**Figure 9.  Self-Employment Share in Total Employment in Central European Countries**

<!-- Start of picture text --> 30<br>25<br>20 2000<br>2001<br>15<br>2002<br>10 2003<br>5<br>0<br>RO PL LT CZ BG HU SI LV SK EE<br>percent<br><!-- End of picture text --> _Source_ : ILO (Laborsta database) and national statistical offices; 2<sup>nd</sup> quarter.

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**Figure 2: Deviation Exports/GDP, Latin American countries**

(actual versus predicted value) <!-- Start of picture text --> 27.6<br>Argentina<br>15.4<br>26.3<br>Uruguay<br>15.9<br>22.7<br>Colombia<br>23.0<br>20.2<br>Bolivia<br>-1.9<br>19.5<br>Peru<br>9.7<br>18.5<br>Venezuela, RB<br>19.6<br>7.6<br>Chile<br>-4.1<br>6.5 Difference 2000<br>Mexico<br>10.8 Difference 2008<br>6.5<br>Brazil<br>4.3<br>5.1<br>Ecuador<br>6.3<br>1.0<br>Paraguay<br>-11.0<br>-20 -10 0 10 20 30<br><!-- End of picture text -->

# **Export growth by categories**

Official statistics in Peru break exports down among traditional and non-traditional products.<sup>9</sup> Traditional products are essentially commodities which Peru has produced and exported historically, reflecting its comparative advantages associated to the relative abundance of resources. Examples include concentrates of and refined copper, lead, zinc, iron, tin, gold, silver, fishmeal and oil, among others.<sup>10</sup> 9 The distinction between traditional and non-traditional exports does not respond to a formal analytical criterion, but in practice it is used frequently because traditional exports are an approximation of the basic raw materials that were responsible for almost all exports since the end of the 1970s (especially minerals and agricultural commodities)
to see whether labor force participation rates return to previous levels, and whether individuals who left school return to formal education.

_A high participation rate and employment-to-population ratio_ As it has been noted before (e.g. Phan, 2009; ILO, 2010a), labor force participation is high in Vietnam; it is toward the high-end of the range of the participation rates of other lower-middle-income countries (Table 1). The participation rate of women is lower than for men in all countries, but the participation of women in the labor force in Vietnam has 5
# **3.  Data**

I rely on disbursement data for individual World Bank projects over the period 1985‐2009. Over this period I have information on actual quarterly disbursements by project over the life of each project, for the universe of all projects financed by the two main lending arms of the World Bank: non‐ concessional lending to middle‐income countries by the International Bank for Reconstruction and Development (IBRD), and concessional lending to low‐income countries through the International Development Association (IDA).<sup>5</sup> For each project, I sum the quarterly data within each calendar year to arrive at annual disbursement flows for each project. Then for each country and year, I sum across all active projects to obtain _total disbursements_ on World Bank loans. I then subtract disbursements on projects approved in the same year to arrive at my measure of _disbursements on previously‐approved projects_ on World Bank loans. Disbursements on previously‐approved projects by construction reflect project approval decisions made in previous years, and my basic identifying assumption is that they are unlikely to be correlated with contemporaneous macroeconomic events. As discussed above, I also construct an alternative measure of disbursements on previously‐approved projects that excludes disbursements on projects approved in the current _and_ previous year.

Figure 1 shows the fluctuations over time in total disbursements and disbursements on previously‐approved projects as a fraction of GDP for one country in my sample, Zambia. The height of the bars shows total disbursements on World Bank loans. These are large in Zambia, averaging 3.4 percent of GDP, and moreover are also very volatile, ranging from close to zero in the late 1980s and late 2000s, to well over five percent of GDP in many other years. The dark‐shaded lower portion of each bar isolates my measure of disbursements on previously‐approved projects, while the remainder of the bar shows disbursements on projects approved in the same year. In most years, the bulk of disbursements on World Bank loans
involving redistribution)? The large between group component of the Gini 12The IPCC's First Assessment Report noted that an immediate reduction of 60-80 percent of current carbon emissions would be necessary to stabilize atmospheric concentrations at their 1990 levels (IPCC 1990).

"<sup>3</sup> For example, Welsch (1993) appliedthe Gini index to examine the inequality effects of alternative emissions scenarios for a sample of countries.
market, shifting resources from the productive sector to the informal financial sector. Finally, a widening gap between official and parallel market rates added pressure to the legal economy by generating expectations of another devaluation, since it signaled the possibility that the government could not support the exchange rate with its stock of international reserves.

On December 16, 2015, the government announced its decision to remove the capital controls and currency restriction and let the peso float within certain limits. As a result, the currency immediately depreciated by 30 percent and the gap with parallel rates virtually closed. The removal of the _cepo_ boosted the debate on the exchange rate equilibrium levels. What is the exchange rate equilibrium level based on the fundamentals of the Argentine economy? What could be the equilibrium level going forward, in a context where economic fundamentals are expected to evolve?

To address these questions, this paper uses a model-based approach known as the behavioral equilibrium exchange rate (BEER), which allows the equilibrium exchange rate to vary over time according to fundamentals in the economy. A reducedform single-equation vector error correction model is estimated by employing Johansen’s (1995) approach using monthly data spanning from 1980 to 2015. The analysis identifies fundamental factors driving Argentina’s real exchange rate to be: the terms of trade, productivity differentials, trade openness, and reserves. While doing so, the analysis takes into account important features specific to Argentina in constructing adjusted measures of the REER and productivity differentials, such as: potentially underestimated inflation, potentially overestimated output, and a large share of agriculture in exports. Based on this approach, estimation results suggest that, as of October 2015, the peso was overvalued by 39%.

As a robustness check, the estimates of exchange rate misalignment are compared to alternative estimation-based methods, which signal that the peso was overvalued by approximately 34–46%, as of October 2015. Premia on parallel exchange markets are indicative of the magnitude of overvaluation, and had been widening since 2011 and reached about 34–36 percent
|**Table 2: Prevalence strata for **<br>|**validation listing**<br>|||||
|---|---|---|---|---|---|
|**Prevalence**|**Unions**|**Census**<br>**HH**|**Rohingya**<br>**HH out of**<br>**camps**|**Camps**|**Rohingya**<br>**HH in**<br>**camps**|
|Prevalence= 0|42|122305|0|0|0|
|Prevalence<.1|45|193626|7508|0|0|
|Prevalence>.1|18|59445|10251|0|0|
|With camps|5|38026|3571|27|281150|
|Total|110|413402|21330|27|281150|

Source **:** Union-level prevalence using the number of local households (based on the 2011 census) and the number of <u>out-of-camps Rohingya (based on the IPA population count). Note: HH = household.</u> This validation exercise implemented a full household listing. This involves going to each household in the chosen villages with a set of 12 questions that included: recontact details (household head name, phone numbers); demographic information on adolescents; and questions related to how long the household had been at that location, as well as details on where they had come from. If a village had a total population of fewer than 500 households, the full village was listed. This was the case for 27 out of the 33 villages. In the remaining six cases, the villages were divided into segments of 100-120 households each, and three segments were randomly chosen for the listing.
first step is an increase in parental involvement. We examine parental involvement in schools using four measures: whether parent associations organized school activities and events, whether parent associations met with teachers to discuss children’s academic progress, whether parent associations participated in school decision meetings, and the percent of parents attending parent association meetings.

In the next step, increase in parental involvement in schools should lead to changes in child inputs by parents and teachers. Parents have more information about their children’s behavior and performance in school, which allows them to adjust how they support their children at home. We measure two types of parental behavior at home: whether parents were aware of their children’s school assignments and whether parents helped with their children’s homework.

Increases in parental involvement at school also mean greater oversight over teachers in how they manage their classrooms. Teachers may be induced to exert greater effort given that parents are regularly participating in school activities and events. We measure two types of teaching behavior: recorded days of teacher absences in the past month and an index of student-centered instruction. The index of student-centered instruction is the first principal components from principal component analyses of four survey items: (i) teacher explains concepts clearly, (ii) teacher reviews homework assignments, (iii) teacher does not ask students to copy from textbooks/blackboard without any explanation, and (iv) teacher gives students exercises that apply concepts learned in class.<sup>7</sup> The last step in the theory of action is improvements in educational outcomes. Using administrative records from the school census data, we measure school-level failure, repetition, and dropout rates. We use the national standardized exam data for student-level test scores in Spanish and Math. Finally, we measure disciplinary action in schools by whether a student had been suspended, expelled, or involved in any other type of disciplinary action (i.e., referred to the principal) in the past academic year.

# **5 Empirical Strategy*
million unique subscribers. The methodology fused CDR data with data from public transport validations (the SUBTE smart card in Buenos Aires) and publicly available household mobility survey data from 2010/2018 - _Encuestas de Movilidad Domiciliaria_ (ENMODO). In addition, the analysis incorporates data from a largescale interception survey and a stated-preference survey with private motorized transport users across AMBA implemented by the study team, respectively, in November-December 2021 and February- March 2022.

**The mobility indicators are calculated for personal mobility travel, filtering out from the origindestination (OD) matrices the trips associated with professional mobility (e.g., taxi drivers)** . The methodology for identifying professional mobility and overall methodology for calculating OD matrices generally follows other studies that have leveraged CDR data for mobility analysis (see, e.g. Bachir _et al_ ., 2019; Bayir _et al_ ., 2010). The analysis is based on a total of 2,010 travel zones across the metropolitan area, of which 534 are in central Buenos Aires (Autonomous City of Buenos Aires, or CABA) and 1,476 in the Province of Buenos Aires (PBA). The CDR data sourced from the mobile phone operator was processed into OD matrices by following a verification process and developing algorithms that disaggregate the matrices into different modes (i.e., non-motorized, public transport, and private motorized), segment them into trip purposes (i.e., home-based trips to work, home-based trips to other activities, and nonhome based trips), and by gender and age (using anonymized client data available from the mobile operator, with gender-specific expansion factors applied based on the available household travel survey data for AMBA).

**The assessment of the mobility patterns distinguishes by socioeconomic (income) group.** This is done based on the spatial association of the identified travelers’ home locations and the socioeconomic
United States, Jacobson’s work (Jacobson 1989 and Jacobson 1991) shows that payment incentives do lead to declines in absenteeism. However, the welfare impacts are less certain.

Jacobson (1989) documents how a payment incentive scheme led to a decline in teacher absenteeism. Nevertheless, one year later a fact- fi nding mission concludes that: “While the District’s attendance statistics for the past several school years may lead some to conclude that attendance improved (...) the fact fi nder does not believe the record before him established that improved attendance rate (...) raised the quality of teachers or teaching in the District. In fact, the District and Association expressed their agreement that they knew of no way to measure the effectiveness of a sick teacher who came to work to assure receiving a higher share of EIT money vs. that of a sick teacher who stayed home to recuperate while a substitute taught his/her classes (...) I conclude that an attendance based criterion for the 1987/88 EIT distribution simply would not serve to promote the "excellence in teaching" envisioned by the State Legislature and the Governor (PERB 1988: 9-10).” The situation in low-income countries may be very different. Certainly, studies in India (Chaudhury and others 2005) suggest that teacher absenteeism is largely due to shirking rather than illness. Jacobson’s work however, cautions us in extrapolating views from one continent to another. If teachers in Zambia and other Sub-Saharan countries are absent because they shirk and incentive schemes and greater accountability lead both to greater attendance and better performance, then such schemes can lead to better learning outcomes. However, if teachers’ utility functions are altruistic so that most absenteeism is “genuine”, incentive schemes might hurt teacher motivation. This con fl ict between treating teachers as “professionals” who respond to monetary incentives and thinking of them as “dedicated to students’ needs” remains at the center of a contentious debate in the United States.
|19.8|38.5|-9.0|

Note: Data is based on two-year averages of 1991-92, 2001-02, and 2007-08.

Source: Based on UN COMTRADE Statistics (trade data) and UNIDO database (production data).

Table 7 shows the disaggregated imports of our developing country sample from all developing countries by three digit industries. Again in many of the sectors the share of imports from developing countries is very low. For industrial countries the significant market shares are concentrated in two distinct sets of industries, traditional and new labor intensive activities. But unlike the imports of industrial countries, the shares of imports in total demand are quite low in 18
to receive the offer starting in April 2018 (control group). We stratified the randomization by cotton zone, whether the cotton societies’ administrative data indicated that they already owned any oxen, whether they requested one or two oxen, and whether they owned a cart. We measure impacts using detailed household surveys conducted in July and August 2018.<sup>8</sup> As cotton cultivation is a key outcome of interest in this experiment, Figure 1 presents the timing of the distribution of the oxen under the experiment together with the key activities of the 2017 and 2018 cotton

> 6The cotton component of the project operated in Bere, Poro, Tchologo and Worodougou, and partnered with Intercoton—the cotton value-chain interprofessional organization in Cˆote d’Ivoire—and its five constituent cotton societies (CIDT, COIC, IVOIRE COTON, SECO and URECOSCI) to implement the matching grant intervention under the broader goal of increasing agricultural productivity in the country.

> 7The market value of two traction oxen at the time of delivery was FCFA 480,000, implying a matching grant value of FCFA 240,000 (US $408). In practice, there are small variations in treatment across farmers. While 96% of farmers requested two oxen, 4% instead requested one ox: households assigned to the treatment group were provided with the opportunity to purchase their requested number of oxen. Moreover, 7% of farmers in the treatment group requested and received a multicultivator, 6.4% a seed drill, 5.1% a plow, and less than 3.5% a received tillers or carts. Appendix Table B1 provides a full list, and shows that households own an average of 2 pieces of equipment, irrespective of their treatment status. The most commonly owned tools are multicultivators (52% households), followed by carts (46%) and plows (43%).

> 8We only collected information on agricultural inputs use from a random half of the sample, due to budgetary reasons. The data
|(0.367)|
|2009|49 (0.167)|51 (0.175)<br>100|(0.342)|
|2010|47 (0.153)|53 (0.170)<br>100|(0.323)|
|2011|47 (0.145)|53 (0.165)<br>100|(0.310)|
|2012|46 (0.144)|54 (0.169)<br>100|(0.313)|
|Change 2006-2012|99 (-0.121)|1 (-0.001)<br>100|(-0.122)|

_Sources:_ Authors’ calculations based on data from Social Security Records: Rela ̧c ̃ao Anual de Informa ̧c ̃oes Sociais (RAIS) in Brazil, Caja Costarricense de Seguro Social (CCSS) in Costa Rica, and Instituto Ecuatoriano de Seguridad Social (IESS) in Ecuador. _Note_ : The table reports the results of the variance decomposition. Cells contain the share of the total variance explained by each decomposition element. The total variance explained by each decomposition element is shown in parentheses.

65
**

When assessing the urban extent there is value in relying on what one “sees,” especially in countries where urbanization is messy in nature. Subjective assessments can capture the multifaceted nature of cities—relatively large spaces with a higher density of construction, better access to transportation networks, and greater availability of residential amenities. In this paper, we develop what we believe is a credible methodology for the subjective assessment of urban status across very diverse places.

Human judgment could be dismissed as a tool on the grounds that much rests on the eyes of the beholder. However, our methodology convincingly addresses this potential shortcoming. It shows indeed that the classification of places only changes at the margin when involving assessors with different backgrounds or following different protocols.

The increased availability of satellite imageries, of crowdsourcing tools and of computing capability also makes human judgment a scalable methodology. Physically visiting thousands of places to assess their status would be costly and time-consuming. But Google images make a remote assessment possible in a growing number of countries. Crowdsourcing makes it efficient to collect judgments for a representative sample of places. And the availability of remote sensing data, especially of built-up cover and nighttime lights, makes it viable to predict the urban status of thousands of other places.

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