rafmacalaba/data-use-mentions-extended huggingface dataset:
irritation: 55%), and respiratory (shortness of breath: 45%).<sup>5</sup> Most (88%) of the surveyed farmers reported multiple symptoms, with an average of 4 and a maximum of 9. Among farmers reporting symptoms, 82% attributed them to pesticide use.

**Figure 2: Self-reported health impairments after using pesticides** (%)

To assess the validity of self-reported symptoms, the study included a team of doctors<sup>6</sup> who screened and tested the farmers for pesticide exposure. The initial screening used several key indicators for potential pesticide exposure – prevalence of skin diseases, abnormal blood pressure, respiratory disease, and heart disease. The tests revealed a high prevalence of skin disease (41%) and abnormal blood pressure (18%), with 3% incidence for reported respiratory disease and 1% for heart disease.

Building upon the initial screening exam, the medical team administered blood tests to 190 farmers to check for cholinesterase enzyme inhibition from exposure to

> 5 Other studies in Vietnam report similar findings for self-reported ailments.  In a study of 369 tea farmers, Xuyen _et al_ . (1998) report incidence rates for headaches (44%), nausea (15%), skin irritation (58%) and dizziness (24%).  Du and Phoung (2003) report the incidence of headaches (60%) and dizziness (27%); and a survey of 1,982 farmers by Hon Tu _et al_ . (1999) reports the incidence of fatigue (26%), skin irritation (20%), headaches (20%), dizziness (20%) and eye irritation (4%).

> 6 Staff doctors from the Centre of Occupational and Environmental Health (COEH) of the Vietnam Association of Occupational Health (VINOH), Hanoi, Vietnam.

7
Nicolas Orgeira, Alpha Simpson, Joe Lelee Sloan, and Kairat Umargaliyev provided excellent field coordination and research assistance. This study was approved by the Harvard Institutional Review Board (IRB14-1833) and Health Media Lab IRB (556WBG18). It was registered in the AEA RCT registry (AEARCTR-0004272 and AEARCTR-0011158). The findings, interpretations, and conclusions expressed in this paper, including any errors, are entirely mine and do not necessarily represent the views of the World Bank Group, its Executive Directors, or the countries they represent.
surveys in the Demographic and Health Survey (DHS) family. More DHS surveys were added in 2007. The 2012 database (Bredenkamp et al. 2012b, c, d, e, a) also included data from UNICEF’s Multiple Indicator Cluster Survey (MICS) and the World Health Organization’s (WHO’s) World Health Survey (WHS). Data on service coverage and health outcomes in all three databases were presented for the population and for ‘wealth’ quintiles, the latter being formed by applying principal components analysis (PCA) to a variety of indicators capturing the ownership of assets (e.g. car and
the attempt to deal with this issue.

# **2.2. Households' near-term plans and intentions to improve their housing conditions 2.2.1 General assessment of the housing situation**

Sociological surveys indicate that households' assessments of their housing conditions have recently changed for the better (Fig. 2.1). The number of households who said they were satisfied with their housing has risen by 1.6% in Moscow, 6.4% in Vladimir and 3.6% in (3orodets. Nevertheless, 36.8, 47.6 and 48.2% respectively still considered housing to be a pressing problem.

Fig. 2.1. Satisfaction With Housing Conditions (% of households polled) <!-- Start of picture text --> 70- 61.3 62.9<br>60- 54 52.4 51.8 51.8<br>50 - 46 48.2 48.2<br>40 -<br>30-<br>20-<br>10<br>0<br>1993 1996 1994 1996 1994 1996<br>Moscow Vladimir Gorodets<br>I Esatisfied U dissatisfied<br>]1<br><!-- End of picture text -->

**Sources: Household Survey in Seven** Cities **Moscow, Decemnber** 1993; T'he Moscow Longitudinal **Household Survey, January 1996; Vladliniir and Gorodets Longitudinal Household Survey,** Oct-1994 **and** Dec.1996.
.010<br>(.008)|.010<br>(.008)|No need|once contr|ol for year|dummies|
|Dununy: the year before PC-adoption (i.e., Dt<br>1)<br>PCi,t_I|-.013<br>(.030)<br>.076**<br>(.038)|-.025<br>(.030)|-.025<br>(.029)|-.025<br>(.029)|-.004<br>(.029)<br>.017<br>(.039)|-.008<br>(.029)|-.007<br>(.029)|-.006<br>(.029)|
|PCi,t-2||.005<br>(.042)||||-.034<br>(.041)|||
|PCi,t-3|||.008<br>(.073)||||-.013<br>(.070)||
|PCit-4||||.038<br>(.103)||||.06<br>(.029)|
|Number of observations|6176|6176|6176|6176|5471|5471|5471|5471|
|R square|.455|.455|.455|.455|.489|.489|.489|.489|

Note. (a) Standard errors in parentheses. ", **, and *** represents significance levels of 10, 5, and I percent. (b) R<sup>2</sup> 's reported under FE models are R<sup>2</sup> within. (c) In all the contests between OLS
|
|Cases with missing age (%)|0|0|0|0|
|Age range (completed months)|0-60|0-60|0-60|0-60|
|Mean age (completed months)|32|32|32|32|
|Median age (completed months|33|33|33|33|
|Cases with missing height (%)|8.7|0|0|0|
|Height range (cm)|24.5-144.55|24.5-144.55|41.9-131.45|41.9-131.45|
|Mean height (cm)|85.2|85.2|85.3|85.3|
|Median height (cm)|86.9|86.9|87|87.1|

Given that different modules of the NNS focus on specific segments of the population, there is a tradeoff between the scope of nutrition drivers included and the size and age-composition of the sample considered in the analysis (Figure 1). For example, a total of 16,873 children have valid HAZ scores in the NNS and while all of these children are represented in each of the household-level modules of the NNS (Form 1.2, Form 1.5 and Form 1.6), only 10,188 (around 60 percent) are represented in Form 3.1, which captures variables on maternal health care, and only 5,945 (around 35 percent) are captured in Form 4.3, which captured data on infant and young child feeding practices for children under the age of 2. If data from the FIES are matched to the NNS sample, a total of 4,049 children with valid z- scores (all under the age of 2 years due to the inclusion criteria of Form 3.1) have information from all of the available NNS and FIES modules. There is no evidence that factors that influence stunting other than age are being affected
to be embodied in electric capital vintages. A technology that is especially relevant in our framework is the heating system, used pervasively in manufacturing to shape components or transform materials. For instance, old generations of boilers are powered by coal or gasoline, while new generations of the same technology are electric (Malek, 2005). Similarly, the arc furnace, an electric heating system, came to replace the older blast furnace powered by fuel. Thus, an increase in fuel prices may induce plants to scrap old fuel-powered machinery and purchase new electric equipment. Case studies evidence suggest that electric heating technologies are not only more energy-efficient, but also able to generate non-energy productivity gains, such as better product quality, process flexibility, speed and reliability (EPRI, 2007). Since electric machinery is more productive and energy-efficient, the negative effect of the fuel price increases is compensated by the positive effect on technological upgrading, with a potentially positive net effect on performance. It follows that electricity price hikes do not trigger substitution, because electric technologies are less likely to be outdated. Hence, the negative impact on performance.

# **5.1 Energy Prices and Technology Upgrading**

We turn to testing this mechanism. Our working hypothesis is that fuel price hikes trigger technology upgrading towards electric machinery, and that electricitypowered machinery is more productive than fuel-powered machinery. In line with this hypothesis, we should observe that upon an increase in fuel prices, plants invest in electric machinery and increase their technical efficiency.

Although our data provide information on sales and purchases of capital by type of asset, we cannot observe whether transactions on equipment refer to machinery powered by fuel or electricity. However, using energy consumption data we can infer changes in capital composition by looking at the energy content of plants’ capital stock. Columns 1 and 2 of Table 3 show that an increase in fuel prices boosts machinery turnover, as measured by the absolute value of the sum of purchase and sale of machinery.<sup>37</sup>
little overall movement throughout the crisis. Notwithstanding this gradual evolution of regulatory frameworks, there have been some notable changes in some areas of regulation and supervision.

Table 3 shows the subset of questions for which we observe statistical significant changes between the 2007 and 2011-12 surveys. The table presents responses from the 2007 and 2011-12 surveys for all countries combined and also distinguishes between crisis and non-crisis countries. Furthermore, for each question, the table shows the p-value from a test of differences in responses across the two surveys.

Overall, we find changes in the area of bank capitalization, governance, activities, diversification, auditing, and deposit insurance. Furthermore, in some instances we find differences between crisis and non-crisis countries. First, we find that non-crisis countries exhibited an increase in their risk based and tier 1 capital ratios, while changes among crisis countries were not statistically significant. Second, among non-crisis countries we observe an increase in the share of countries that set regulatory limits on related party exposures. On the other hand, the percentage of crisis countries that set regulatory limits on related party exposures declined between the 2007 and 2011-12 surveys. Third, among non-crisis countries there was an increase in the percentage of countries that impose regulatory rules or supervisory guidelines regarding asset diversification. Fourth, most countries (and especially) non-crisis countries exhibited a relaxation of restrictions on bank activities between 2007 and 2011-12. Fifth, the share of countries requiring audits and risk management procedures to be disclosed increased significantly across all countries. Sixth, the share of countries with explicit deposit insurance increased among non-crisis countries and the coverage of deposit insurance increased across all countries.

11
Above, ∆Capitali are either changes in total regulatory capital ( _ΔRegulatory Capital/RWA_ ) measured as a percentage of risk-weighted assets, changes in Tier 1 capital ( _ΔTier1/RWA_ ) measured as a percentage of risk-weighted assets, or changes in a simple leverage ratio ( _ΔEquity/TA_ ) measured as a percentage of total assets for the banking systems in each country. These changes are calculated for each country _i_ by subtracting the level in 2010 from its value in 2016.<sup>19</sup> ∆Tier1Stringency is the change from 2010 to 2016 of an index that captures the stringency of the Tier 1 capital definition. The index ranges between 0 and 8, and is based on the number of components that supervisors do not allow as part of Tier 1 regulatory capital plus the number of components that are deducted from Tier 1 capital.<sup>20</sup> Thus, higher values of the index indicate greater stringency. BankingCrisisi is a dummy variable that takes on a value of 1 if a country experienced a systemic banking crisis between 2007 and 2009. This variable is constructed using data on banking crises episodes from Laeven and Valencia (2018). In the regressions, we control for the initial levels of each dependent variable to capture potential mean reversion in capital ratios or capital stringency (Capitali,2010, Tier1Stringencyi,2010). Macroi,2010p are four country-level variables that are commonly used as controls in cross-country analyses. These controls are the natural logarithm of the GDP per capita ( _ln(GDP per capita) 2010_ ), inflation computed using the consumer price index ( _Inflation 2010_ ), natural

> 19 We use as reference dates for BRSS 5 and BRSS 4 the years 2016 and 2010, respectively. This is because quantitative information is recorded up to year 2010 in BRSS 4 and up to year 2016 in BRSS 5.

20 The capital instruments that might be allowed into the definition of Tier 1 capital are: a) hybrid debt capital instruments, b) asset revaluation gains,
</sup> Ref.<sup>1</sup> reports annual area burned in the United States from 1985 to 2020. Extrapolating the linear trend from that data results in a 235% increase by mid-century relative to the average from 1985 to 2020.

Increases in burned area may be constrained in the future by the availability of fuel as more consistent, and larger fires, result in landscapes that carry lower fuel loads.<sup>15</sup> However, this does not appear to meaningfully reduce burned area estimates until after mid-century.<sup>36,29</sup> In order to use projections of burned area in our specification, we need to determine the relationship between burned area and smoke exposure. We also need to determine whether low- and high-density smoke days increase uniformly or if changes in biomass burned or fire intensity will lead to changes in the relative number of low- and high-density smoke days. For the first conversion, we can rely on ref.,<sup>1</sup> who document the increase in burned area as well as the increase in smoke days. They observe that, from 2006 to 2020, burned area increased by 32% while smoke days increased by 127%, implying smoke days may increase 4 _×_ faster than burned area. Unfortunately, they do not separately measure the change in low- and high-density smoke days.

Combining the central estimate of increases in burned area from ref.<sup>14</sup> of 160% with this 4 _×_ relationship implies that smoke days will increase by 460% by mid-century. This is substantially higher than the increase suggested by our linear extrapolation.

There is little evidence that indicates how the increase in smoke days will be apportioned 21
**_Example 6. The tourism GVC_**

<!-- Start of picture text --> Foreign<br>Retail Travel Foreign Tour Air Ticket Arrival Transfers Hotel Stay Food & Beverage Services Activities, Tours &<br>Agent Operator Shopping<br>10-14% 30-35% 5% 35-40% Outside the<br>Hotel<br>10-15%<br><!-- End of picture text --> Source: World Bank, 2011b Notes: percentages are indicative of the repartition of value in a well-functioning tourism GVC; the Tourism Satellite Accounts edited by the World Tourism and Travel Council present a more detailed analysis of the tourism direct and indirect benefits in recipient countries.

# **_Example 7. The offshore services GVC_**

<!-- Start of picture text --> Industry Specific<br>General Business Activities Activities a-b<br>HIGH<br>ITO KPO Banking, Financial Services and<br>Information Technology Outsourcing Knowledge Process Outsourcing Insurance (BFSI)<br>Ex. Investment research,<br>private equity research, and<br>Software R&D Business Consulting risk management analysis<br>Business Analytics Legal Services<br>Market Intelligence Manufacturing<br>Ex. Industrial Engineering<br>and sourcing and vendor<br>IT Consulting management<br>BPO<br>Business Process Outsourcing Telecommunications<br>Software Interoperability testing and Ex. IP transformation,<br>ERM DSP and multimedia<br>ERP (Enterprise Resource Planning): HRM CRM<br>manufacturing/operations, supply chain management, financials & project management (Enterprise Resource (Human Resource Management) Relationship (Customer Ex. Energy Trading and Risk Energy<br>Applications Development Management) Management) Management , and Digital oil field solutions<br>Finance & Training Marketing & Travel &<br>Applications Integration Accounting Sales Transportation<br>Desktop management Procurement, Talent systems, customer loyalty Revenue management<br>Logistics and
The number of IDPs increased rapidly in 2014 and has remained at more or less the same level to the present day. **Figure A1b** displays reported dates of (first) displacement in our survey data, which is representative for the displaced population in North-east Nigeria in 2018.

Most IDPs in North-east Nigeria are displaced within their state of origin, 74% of IDPs are located in Borno state and 83% of all IDPs are from that state. An estimated 57% of IDPs reside in one of the 2,085 documented host communities, while the remaining 43% live in one of the documented 307 camps or camp-like settings. Of the IDPs in host communities, 90% live in private buildings.

**Gender inequality and gender-based violence.** Gender inequality and gender-based violence are highly prevalent in the region, as the conflict and other factors create and perpetuate gender-based disparities, discrimination, barriers to empowerment, and risks of intimate partner violence (e.g., Ekhator-Mobayode et al., 2020). <mark>Specifically, the strong social and gender norms have been shown to shape nutrition and welfare outcomes across and within families (UN OCHA, 2018, Nwoke et al., 2022) a</mark> s well as conflict outcomes, such as recruitment into Boko Haram (Rexer, 2018).

Social norms in the region continue to create strong, gender-specific challenges and disadvantages for women in many dimensions (Agbonifo, 2020; CARE, 2022). Women are often primarily expected to fulfill their responsibilities as caregivers and subsistence farmers and face genderbased barriers to access to credit, land properties, employment, education, and medical care, among other things (Allanana, 2013; Onwuka et al., 2015). In addition, it has been shown that several factors, including climate stress and food crises, increase rates of marriages at an early age

> 4 <mark>There were more than 11,500 reported fatalities by the group in 2015, the deadliest
and one member each from the scheduled castes and scheduled tribes<sup>3 4</sup> . An advisory committee is also to be formed at the range-level to ensure the smooth implementation of the programme, and should include the local MLA.

At the outset, government consolidation officers hold meetings with landowners to explain the potential benefits of land consolidation, the main provisions of the OCH & PFL Act, and the manner in which their interests shall be represented. Villagers are then called upon to nomini-e the names of people for the committee. In practice, there tends to be extensive public involvement in the plains and coastal areas in which a high proportion of the operated area is irrigated, but much less involvement or commitment in the hilly tracts of western Orissa.

**_Survey and correction of existing_** _RORs:_ Consolidation is carried out within the circle of a particular police station. Eventually all villages within the circle are covered. The first step is to conduct a plot-to-plot survey of the village area (similar to the process followed in a survey and settlement operation), beginning in the northwest corner of each village and ending in the south-east corner. The existing RORs are then updated. Following the initial survey, if it is determined that there is too little cultivable land to make land consolidation worthwhile, the operation does not proceed further (i.e. these villages are placed under section 13(4) of the Act).

**_Consolidation of holdings:_** There are two alternative processes of consolidation, depending on the type of terrain: (i) _rectangulation,_ where the entire area to be consolidated is flat and irrigated (as in parts of Ganjam district); and (ii) _amalgamation,_ where there is undulating terrain (as in Khurda and Sambalpur districts).

Under the amalgamation process, the model pioneered in Uttar Pradesh is adopted, in which relative scores are awarded to plots on land of differing quality, subject to agreement among members of the local
** . Other authors ( <mark>Guio et al., 2018)</mark> have constructed and proposed a specific suitable and additive deprivation measured focused on the specific situation of children using the EU-SILC data, which could be implemented in future analysis.

**The analysis on Roma in Bulgaria could potentially be extended to other countries, if ethnicity is regularly collected as part of the official household surveys to monitor income and living conditions.** This is important to build consensus about who belongs under the “vulnerable population” rubric and could offer a more comprehensive overview of the risks and vulnerabilities that the Roma community faces.

39
he is forced to keep borrowing, thereby mortgaging the produce of his land for many subsequent years. Rights to the produce of the land eventually accrue to the moneylender for such a long period that tribal land owner is reduced to the status of little more than a bonded labourer producing crops for the moneylender, on land that legally remains his own. One study of four districts (Dhenkanal, Ganjam, Koraput and Phulbani) estimated that about 56 percent of the total tribal land was lost to non-tribals over a 25-30 year period through these means (Viegas, 1987). Of this total, 40 percent was lost through indebtedness and land mortgage, 23 percent through encroachment, 17 percent as a result of displacement by development projects, 15 percent through personal sale, and the balance due to floods and other natural calamities.

A less well-understood pattern is the administrative erosion of tribals' communal land rights through survey and settlement operations themselves. In recent decades, cadastral survey by the chain survey method has gradually given way to the plane-table method to reduce operational costs. But land with a gradient greater than 10 percent cannot accurately be surveyed by the plane table method, and in Orissa these unsurveyed lands have customarily been lumped together as 'uncultivable wasteland' in the record-of-rights in land (Roy Burman, 1987). The outcome is catastrophic for tribal groups. In a 1961 land survey and settlement operation in Niyamgiri hills of south-western Orissa, for example, only 15 acres out of a total village area surveyed of 2647 acres were declared to be 'cultivable land' (Roy Burman, 1987). Only on this land was rent assessed and demanded of the 16 owners in the village. One acre was recorded as grazing land, 7 acres under housing, and only half an acre classified as common land for the village graveyard. The remaining 2624 acres, being of a gradient greater than 10 percent, were recorded as (state-owned) 'uncultivable wasteland'. In reality, much of this area was owned by tribal households, and
the negative impact of practices related to incentives/monitoring is ameliorated if there is a greater proportion of recent projects on which officials report observing others engaging in corrupt practices. This suggests that the negative consequences of corrupt practices can be partially o↵set by the provision of incentives/monitoring of bureaucrats.

> 20In 2015 Ghana scored at the 53rd percentile worldwide on the World Governance Indicators’s Control of Corruption measure; Nigeria scored at the 13th percentile [World Bank 2018].

> 21The first measure is based on asking what proportion of unofficial payments are shared with the superior in the hypothetical scenario that, ‘Imagine that a corrupt bureaucrat extracts unofficial payments. Typically in your organization, what proportion of the unofficial payments does s/he share with the following types or groups of people.’ An organization-level average from across all interviews is constructed and for our whole sample, the organization-average was 11%, but wide a relatively wide dispersion reflected in a standard deviation of 8%. The second measure used a similar question structure, but asked officials the proportion of projects on which they ‘observed others breaking service rules for their own benefit’. Officials are more likely to report the corrupt behavior of others, and 16% of officials have observed such acts by others in their organization.

21