rafmacalaba/data-use-mentions-extended huggingface dataset:
and Measurement of Key Variables**

We conducted surveys of village heads, a randomly selected civil society leader, and a random sample of eight households in each of the villages in the study three months following the completion of the training sessions, in late August and early September 2013. We contracted a local survey firm to conduct the survey after training from the research team. We were able to conduct household surveys in each of the 270 villages and to interview the village head in 91 percent of them. We also interviewed a randomly selected civil society leader in 96 percent of villages. Most questions on the questionnaires were closed-ended and retrospectively

> 15The differences in support for individual rights and beliefs about whether the dare should have more power are both statistically significant at the 95 percent confidence level.

17
.1|0.15<br>0.2<br>0.25|
|Neither<br>Both|Estimated|topic proportion|

Figure 3: Topic prevalence based on presence of returnees and IDPs, `Location Mentions` dataset.

The prevalence of violence- related discussion overall in the `Location Mentions` models, accounting for 7 of the 20 topics in Figure 4, outlines the persistent nature of violence in the daily lives of Syrians. Social media, especially public groups and channels, serve the population through announcements documenting daily violence and military movements which are ultimately useful for both those currently living in Syria and those choosing whether or not to return. Discussion in areas with only IDPs is often more similar to discussion in areas with both returnees and IDPs than to discussion in areas with neither. Though images are often used alongside, or in the place of, text to convey a message, explicitly violence related topics are less represented in the image analysis than in the text. This may be the result of filtering choices by the different platforms to remove violent or disturbing imagery.<sup>16</sup> For most violence related topics, discussion in areas with only IDPs is more similar to discussion in areas with both returnees and IDPs, whereas discussion in areas with just returnees is more similar to discussion in areas with neither returnees nor IDPs. Individuals fleeing violence often have little choice in their destination (Bank (2019)), but if fleeing violence are unlikely to remain in areas where it is prevalent. Returnees, on the other hand, are returning in part because of ties to their home town (Ghosn et al. (2021)) and thus may be willing to endure more uncertainty to be there. In fact, a UNHCR monitoring survey of voluntary returnees found that 54% returned to Syria to reunite with their families (Hoffman and Makovsky (2021)). The central role that violence plays also underscores the importance of using multiple platforms. As can
11 To obtain the school roster information about enrollment and attendance, survey enumerators took the list of children reported to be enrolled by their parents and searched for them in the school’s administrative rosters. After matching the child’s name, they then recorded the child’s enrollment status and the number of days the child was absent or present for each month during the academic year. Unfortunately, we were not able to collect school administrative data for every year for all children. There were 225 school rosters to be collected (3 rounds of data collection for 75 villages), but we could not collect 5 of them due to the school being closed and the teachers and principal having left for summer vacation. In addition, for some children, it was difficult to identify a match between the names on the school and household rosters because many children in a given class often have the same first and last name. For these difficult cases, we used child age, gender, and the mother and father’s names to confirm a match. In Section 5.5, we discuss the robustness checks we perform to confirm there was no differential selection across treatment groups in which children we were not able to collect administrative data for.

9
Since sparsity, rather than density, is the focus of the current body of work relating to the PICs, we focus on analyzing the inverse of this density measure: a dispersion-adjusted measure of population sparsity. It is defined as: The examples in Table 1 demonstrate ways in which the value of this indicator varies in different empirical settlings. Dispersion-adjusted density is higher in panel B than panel A, reflecting the greater concentration of the population in the most highly populated (dark blue) node. In contrast, a straightforward density estimate would not differentiate between these two settings (since their overall population, and overall area of terrain, is the same). Consider now Panel A and Panel E. The pattern of population distribution is the same across these two settings, and this is reflected in their common geographical scale of dispersion. However, dispersion-adjusted density is twice as high in panel E as in panel A, reflecting panel E’s larger population.

# 2. Evaluation for the PICs

In evaluating our indicators of local-area level remoteness, the geographical scale of dispersion, and dispersion-adjusted density for the PICs, we rely upon data from population and housing censuses, collected by country National Statistics Offices and made available through the Pacific Community (SPC) PopGIS platform (see Appendix A for detail). We access data for Fiji (2007,<sup>6</sup> by Tikina), Solomon Islands (2009, by Constituency), Vanuatu (2009, by Area Council), Kiribati (2010, by island/atoll grouping), FSM (2010, by Municipality), Tonga (2016, by District), RMI (2011, by atoll grouping) and Tuvalu (2012, by village). Note that some of these census data are quite dated, so the results (which reflect the distribution of the population at a particular point in time) presented in this paper should be interpreted accordingly.

The distribution of local-area remoteness measures, and the country-level geographical scale of dispersion are illustrated for each
to benefit politicians and advance their careers. The types of firms that can be privatized also depends on investor demand. Highly non-profitable firms do not attract buyers and are difficult to privatize. Most existing studies on the effects of privatization rely on the firm fixed effect model, and do not otherwise deal with selectivity of privatization. Second, the causal effects of privatizations should differ across countries and periods. A convincing conclusion from the survey of privatization literature is that the effects of privatization differ by the institutional context of privatizations (Djankov and Murrell 2002; Estrin et al. 2009): more positive effects or associations, for instance, have been consistently ``` 2 ```
plement it with robustness checks using municipal election results as outcomes.

**Mayoral elections.** We web-scrape data for the 2004–2021 municipal elections, covering five election years in 335 municipalities and producing a total of 1,675 independent election observations. The original data come from the Consejo Nacional Electoral. We examine effects on the same two outcomes: electoral turnout and opposition support. To construct the share of opposition votes, we classify each candidate based on party affiliation and policy program. Appendix B provides details on each candidate’s classification process.

# **3.4 Additional Data**

**ENCOVI, 2014–2021.** These surveys are analogous to labor force surveys that are typically available in other countries in the region. They are cross-sectional surveys of independent households, representative at the national and state levels, and available for the main urban centers. As previously noted, they include a migration module that characterizes the relatives living abroad of Venezuelans between 2017 and 2021.

**Organized crime.** We also construct an annual municipal panel spanning 1993–2024 that combines information on violent events and the presence of organized crime and nonstate armed actors. These data come from the Armed Conflict Location and Event Data (ACLED) and the Global Terrorism Data Base (GTD).

**Other variables.** We also employ other data from multiple sources to examine the validity of the main results. These include municipal measures on the intensity of the 2019 energy blackouts, coverage of social welfare programs for 2016–2017, and measures of political repression under the Ch ́avez regime in 2004.<sup>17</sup> We also use annual municipal data on private firm expropriations by the government and annual data on inflation and global sanctions for

> 17These data come from Hsieh et al. (2011).

20
. van der Weide (2012), Two-Sample Cross-Tabulation, mimeo, The World Bank Fujii, T. and R. van der Weide (2013), Cost-effective estimation of the population mean using prediction estimators, mimeo, The World Bank HCP (2000-2010) National Accounts, Haut Commissariat au Plan, Maroc Grosse, Melanie, Klasen, Stephan and Spatz, Julius, (2009), Matching Household Surveys with DHS Data to Create Nationally Representative Time Series of Poverty: An Application to Bolivia, No 21, Courant Research Centre: Poverty, Equity and Growth - Discussion Papers, Courant Research Centre PEG.

Kijima, Y., Lanjouw, P. (2003): Poverty in India during the 1990s: a regional perspective. Policy Research Department Working Paper 3141. World Bank, Washington DC 25
|Dietary risk factor<br>(Author,Year)|Geographic<br>context, year|Nutrition/health<br>outcomes|Mortality cost|DALYs cost|Health care and other<br>economic costs|
|---|---|---|---|---|---|
|‡Dairy foods intake|Islamic|Reduction in CVD|n/a|n/a|Per capita savings in health care|
|(Javanbakht et al.|Republic of|andT2DMincidence|||costs: $0.43 in 1 year|
|2018)|Iran, 2016|due to optimal dairy|||$190.25 in 20 years|
|||food consumption|||Total cost$33.8 millionin 1year|

* study based on GBD model data

† dietary risks comprise the sum of adverse effects of diets in which 15 food types were either underconsumed (fruits, vegetables, legumes, whole grains, nuts and seeds, milk, fiber, calcium, omega-3 fatty acids from seafood, and polyunsaturated fatty acids) or overconsumed (red meat, processed meat, sugar-sweetened beverages, trans-fatty acids, and sodium) ‡ study modeling the cost savings associated with improved diet quality Abbreviations: ASDR age-standardized death rate; ASR age-standardized rate; BMI body mass index; BP blood pressure; CHD coronary heart disease; CVD cardiovascular disease; DALY disability adjusted life year; IHD ischemic heart disease; n/a not available (not reported); NCD non-communicable diseases; SSB sugar-sweetened beverages; T2DM type 2 diabetes mellitus; USD US Dollar; YLL years of life lost due to premature mortality 26
||Total|1806<br>82.8%|354<br>16.2%|22<br>1.0%|2182<br>100%|100%|
|---|---|---|---|---|---|---|
|Extracted minerals’ valu|e<br>||||||
||Status|No mine|High value|Low value|Total||
|Mineral deposits|No|1806|0|0|1806|82.8%|
||Yes|0|83|293|376|17.2%|
||Total|1806<br>82.8%|83<br>3.8%|293<br>13.4%|2182<br>100%|100%|
|Types of mining activiti|es<br>||||||
||Status|No mine|Extraction|Transformation|Total||
|Mineral deposits|No|1806|0|0|1806|82.8%|
||Yes|0|271|105|376|17.2%|
||Total|1806|271|105|2182|100%|
|||82.8%|12.4%|4.8%|100%||

Source: authors’ calculation (based on USGS data).

Table 4: Summary statistics

||Obs.|Mean|Std dev.|Min.|Max.|
|---|---|---|---|---|---|
|Gini index|21433|0.256|0.200|0.0|0.940|
|Mean logarithmic deviation|21433|0.271|0.334|0.0|4.
cards for LPG in the Dominican Republic. In this regard, recent developments in biometric databases of personal information merit attention; presumably it would be more difficult to escape detection loaning cards with biometric information than loaning cards without. The government of India is proceeding with what it calls end-to-end computerization of the targeted public distribution system, which distributes subsidized food and kerosene. Some states are now piloting distribution of subsidized food and fuel using smart cards containing biometric information about beneficiary families (India 2013). Egypt is planning to introduce a nation-wide smart card system for rationing subsidized gasoline starting in July 2013, and eventually subsidized diesel except for agriculture and food industries (Reuters 2013). While it is always possible to sell the fuel purchased in this way and obtain cash, the transaction cost of doing so would presumably discourage resale on a large-scale.

# **Unintended consequences of keeping domestic prices low**

Rising claims on the budget or growing tax expenditures, the public being shielded from sharp price rises, and weak price signals reducing incentives for fuel conservation are among the predictable consequences of policy of keeping domestic prices artificially low. Less expected are growing fuel shortages, protection of inefficient fuel suppliers, and rising demand with rising prices once subsidies are reduced or removed.

Fuel shortages are common in a number of markets with low prices. In Egypt, LPG shortages in recent years have been so serious that several consumers have been killed in scuffles over LPG cylinders and the army and the police have provided armed guards for LPG transport. Shortages occur because of commercial malpractice, implicit rationing, and adverse effects of subsidies on the operational and financial performance of oil companies. Subsidized fuels are diverted to black markets or smuggled out of the country, reducing fuel availability in the formal sector. Even when there is no commercial malpractice, as in the United States in the 1970s, price
**Figure 16: A Multipronged approach was used during the capital surge in mid 2000s which included an increase in CRR and policy rate but also resulted in some increase in money supply**

|**Narrow and broad money supply increased**<br>**and CRR and Repo Rate increased as well**<br>**during the surge **|
|---|
|2<br>4<br>6<br>8<br>10<br>12<br>Percent<br>CRR<br>Repo Rate<br>Reverse Repo<br>2<br>7<br>12<br>17<br>22<br>27<br>0<br>20,000<br>40,000<br>60,000<br>80,000<br>100,000<br>120,000<br>y-o-y % change<br>mln, $ Total Capital Flows<br>% change in RM with public<br>(RHS)<br>% change in M3 (RHS)|
|Source: RBI Handbook of Statistics on the Indian Economy<br>The increase in money supply is also evident in quarterly data. In Table 2, using data from<br>2000-2007, we regress measures of money supply for a dummy for surge years, alternatively<br>takes value 1 for years 2005-2007, or 2006 and 2007. Results show an acceleration in money<br>supply, which picked up in the later years of the surge. It was most pronounced in reserve<br>money supply but less so in the reserve money in circulation and in broad money supply,<br>due to the increase in the CRR. The acceleration is evident even after controlling for GDP<br>growth in the regressions in Table 2.<br>**Table 2: Money Supply during Capital Flow Surge
zero. By contrast, employment growth in these small firms is as high as 13 percent while employment growth averages zero percent in firms with 50 or more employees. In Ethiopia, the picture is somewhat better although labor productivity growth is not as high as it is in Tanzania. Average sectoral employment growth in Ethiopia’s large firms is around 6.5 percent per year while it is around 7.5 percent per year for firms with between 10 and 49 employees. (Although the employment growth rates may seem high in Ethiopia, it is important to remember that the country is starting from an extremely low base.) Labor productivity growth is around 5 percent per year for both small and large firms. To complete the analysis of Ethiopia, the authors examine a group of mechanized firms with fewer than 10 employees using the Small-Scale Industries survey. Average annual employment growth among these firms is around 17 percent, while labor productivity growth is an average of zero, with considerable heterogeneity. The combined evidence for Ethiopia and Tanzania suggests that the 9
is interesting for a number of reasons. First, the country has been enduring a protracted conflict for over five years that has resulted in a large increase in the share of children not attending school (e.g., OCHA 2020). Second, in addition to the violence from the conflict, there are a number of other conflict-related shocks that have affected the ability of children to attain an adequate education, such as the suspension of salary payments to teachers, the inability to acquire teaching materials, and the substantial increase in the share of households that are financially struggling (e.g., OCHA 2020). And lastly, there are a number of education interventions currently being implemented in Yemen that need up-to-date information on how and where to best support schools and parents (e.g., OCHA 2019a).

This analysis utilizes a monthly mobile phone survey conducted by the World Food Programme (WFP) that tracks school attendance, food security, and access to health care for a panel of households beginning in March 2019.2 The survey initially reached households through random digit dialing in the first month, and then each subsequent month contacted a mix of both previous and new respondents to reach a monthly sample size of approximately 2,400 households that is distributed across the entire country according to population. Prior to the beginning of the COVID-19 crisis in March 2020, the survey reached approximately 13,500 households an average of two times each. The survey is one of the most complete data sources describing the evolution of school attendance during active conflict and offers a unique 1For a survey of the literature, see Blattman and Miguel (2010), Justino (2012), and Verwimp et al. (2019).

2The monthly survey tracking only food security began in August 2015, but an expanded module tracking access to basic services was inserted in March 2019.

2
Greco, G., Skordis-Worrall, J., Mkandawire, B. and Mills, A., 2015. What is a good life? Selecting capabilities to assess women's quality of life in rural Malawi. _Social Science & Medicine_ , 130, pp.69-78.

Greco, G., Skordis-Worrall, J., and Mills, A., 2018. Development, Validity, and Reliability of the Women’s Capabilities Index, _Journal of Human Development and Capabilities,_ 19 (3), 271-288 Harper, M., 2002. Self-help groups and Grameen Bank groups: What are the differences. Beyond micro-credit: Putting development back into micro-finance. New Delhi: Vistaar.

Hasan, A., 2017. Functioning of self-help groups in India: Members’ perceptions of key issues. _Asian Social Work and Policy Review_ , 11 (2), 124-131 Holden, E., Linnerud, K. and Banister, D., 2017. The imperatives of sustainable development. _Sustainable Development_ , 25 (3), pp.213-226.

Ibrahim, S. and Tiwari, M. eds., 2014. _The capability approach: From theory to practice_ . Springer.

John, J., 2009. A study on Kudumbashree project: A poverty eradication programme in Kerala. Performance, impact, and lessons for other states. Planning Commission of India, Kerala Development Society (KDS).

28
childcare, but these authors were unable to examine effects on uptake. Whether on-site childcare increases the chances of uptake of public works has not yet been studied.<sup>4</sup> Participants in the public works component were paid by direct deposit into bank accounts that they opened in their names. In some contexts where women have low bargaining power, lack of control over their earnings is one potential reason why they have chosen not to enter the labor market (Field et al., 2021). Therefore, by having participants open bank accounts in their own name, the public works program aimed to ensure that the women were free to exercise control over their own earnings.

The public works program entailed 50 days of work for four hours per day over the course of 2.5 months. At midline, women report working 4.8 hours per day, on average, which includes breaks. The program participants earned a daily wage of 1,000 FDJ (Djiboutian francs), which corresponds to approximately 80 percent of the official minimum wage, or 5.6 USD, or 9.9 USD 2021 PPP. Compared to the EDAM 2017 data, this wage is below the 25<sup>th</sup> percentile of the hourly wage rate for all workers in Djibouti. As noted previously, the public sector employs primarily skilled laborers and constitutes a high share of all wage work in Djibouti. Compared to private sector wages specifically, the public works program pays closer to the 30<sup>th</sup> percentile of the wage distribution in 2017. For workers with a primary education at most, the program pays at the 25<sup>th</sup> percentile, and for women without any education, wages are closer to the 40<sup>th</sup> percentile in 2017.<sup>5</sup> The potential income gains from the public works program are substantial in the context of low employment, even if the
/cyclone/hurricane|0.086|0.282|0.121|0.331|
||Rainfall|0.086|0.282|0.061|0.242|
||Flood|0.229|0.423|0.182|0.392|
||Drought|0.200|0.403|0.152|0.364|
||Earthquake|0.057|0.234|0.061|0.242|
||Landslide|0.057|0.234|0.030|0.174|
|Level of analysis|Country|0.377|0.488|0.313|0.471|
||Subnational|0.269|0.448|0.226|0.425|
||Household|0.346|0.480|0.355|0.486|
||Individual|0.212|0.412|0.129|0.341|

_Note_ : CCDR = _Country Climate and Development Report_ . Sample has 70 studies. When the CCDRs are excluded, the sample has 33 studies. Each row represents the share of studies in our sample with the specific characteristic. Country or region indicators, type of shock indicators, and level of analysis indicators are not mutually exclusive.

15
---|---|---|---|
||Pa<br>|nel A: Regres<br>|sion results<br>|
|Land share of cofee * LogPrice|0.822***<br>(0.205)|0.834***<br>(0.207)|0.580*<br>(0.300)|
||Panel B: Im<br>between 2|plied efects o<br>011 and 2013|f 50% price decrease<br> for average farmer|
|all sample|-2.06%|-2.09%|-1.45%|
|_≥_5% land share of cofee|-13.49%|-14.18%|-9.84%|
|_≥_10% land share of cofee|-16.85%|-17.1%|-11.89%|
|_≥_25% land share of cofee|-23.02%|-23.35%|-16.24%|
|_≥_33% land share of cofee|-25.89%|-26.27%|-18.27%|
|_≥_50% land share of cofee|-30.83%|-31.28%|-21.75%|
|_N_|9525|9525|9525|
|_R_<sup>2</sup>|0.650|0.608|0.710|

Notes: This table is based on three rounds (2011, 2013, and 2015) of ESS survey. Standard errors are clustered at zone level. All regressions include household and zone-year fixed effects, and log rainfall. EAC stands for adultequivalent consumption. All dependent variables are in log units of monetary value adjusted for variation in living expense across regions. _Land