rafmacalaba/data-use-mentions-extended huggingface dataset:
# **2.2 Construction of** **_Expected Dowry_**

Unlike other data sets, such as the India Human Development Survey (IHDS), that record total marriage expenditure in the year of survey by families _similar_ to the respondent’s family, the 2006 REDS collected data on _actual_ payments by brides and grooms in the surveyed households.<sup>11</sup> Specifically, it recorded the value of gifts received or given at the time of marriage in addition to the year of marriage and demographic information of spouses (e.g., caste and years of schooling) for 17,401 marriages that occurred during 1986-2007.<sup>12</sup> We compute net dowry as the difference between “gross payments by the bride’s family to the groom or his family” and “gross payments by the groom’s family to the bride’s family,” and deflate the nominal amounts using the 2005 national Consumer Price Index.

We plot the distribution of net and gross marriage payments in Figure 1.<sup>13</sup> The proportion of marriages with a negative net dowry, i.e., where the groom’s family paid more to the bride’s family than the other way around, is non-zero, but quite small. The vast majority of the marriages involved positive net dowry payments to the groom’s family. We do not observe any marriages where the value of gifts was reported to be zero.<sup>14</sup> Figure A.1 describes the variation in the dowry variable by year of marriage; the top panel shows the raw data on the real net dowry paid by the bride’s family and the bottom panel displays, separately, the real value of gifts from the bride’s family and from the groom’s family.<sup>15</sup> Ideally, to examine how dowry expectations impact household behavior, we would like selfreported data on
Policy Research Working Paper 10702

# **Abstract**

Job quality can impact workers’ productivity and contribute to societal well-being. To analyze the evolution of job quality in Bolivia, this paper employs Bolivian household survey data spanning 2007 to 2021 to construct a synthetic job quality index. The index incorporates a broad definition of a good job, encompassing six dimensions: adherence to - regulations, working conditions, establishment of an appro priate wage-job linkage, productive usage and adaptability of skills, availability of career opportunities, and employment resilience. The findings indicate that job quality in Bolivia has mostly remained incessant, exhibiting limited change even during periods of high growth in economic output. However, this result masks heterogeneities, with significant variation in job quality associated with workers’ demographic and job-specific characteristics and across regions.

This paper is a product of the Poverty and Equity Global Practice. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://www.worldbank.org/prwp. The authors may be contacted at gcanavire@worldbank.org, mdavalos@worldbank.org, and rcuevac1@illinois.edu. A verified reproducibility package for this paper is available at http://reproducibility.worldbank.org, click **here** for direct access.

<!-- Start of picture text --> TRANSPARENT<br>ANALYSIS<br>G<br>R E<br>N<br>S<br>I P<br>Y E<br>K A<br>C A<br>R P<br>LI R<br>O E<br>O C<br>W R<br>H<br>S<br>P<br><!-- End of picture text --> _The Policy Research Working Paper Series disseminates the
|Study and Location|Definition of<br>Empowerment|Measurement<br>Concept|Data Sources|Focus|Conclusions|Implication|Scope|
|---|---|---|---|---|---|---|---|
|_implementation in_<br>_13 countries (South_<br>_Africa, Mexico,_<br>_Uruguay, Indonesia,_<br>_Pakistan, Belarus,_<br>_Croatia, Estonia,_<br>_Romania, Ukraine,_<br>_Canada, New_<br>_Zealand, and Wales)_|<br>(whom) to do<br>(what)|based on the<br>average of five<br>indicators scored<br>from 0 to 3: activity<br>and effectiveness of<br>civil society in<br>informing and<br>educating, building<br>capacity for<br>collective action,<br>empowering poor<br>people, empowering<br>women, and<br>building social<br>capital|community<br>surveys,<br>secondary data<br>and fact finding|the world|Society Index<br>with a larger<br>scoring matrix<br>and 69 indicators<br>encompassing<br>four dimensions<br>(structure,<br>external<br>environment,<br>values, and<br>impact of<br>activities)|forces, map of<br>civil society;<br>power relations in<br>society and<br>relations within<br>organizations)|relation to the impact of<br>activities of civil<br>society (opportunity<br>structure); indicators<br>related to aspects of<br>inclusion/participation<br>(under structure)
its ability to function without political interference, ensure continuity in government policy, and effectively implement reforms.

**Corruption** Country-level corruption is measured using an index from the ICRG that captures perceptions of corruption within the political system. This includes the misuse of public office for private gain through practices such as bribery, patronage, and nepotism. **Peace/conflict status** Countries are grouped based on their peace or conflict status at the beginning and throughout the entire period of analysis. A country is classified as _initially at peace_ if, at the time of the first survey in that country, there are no major episodes of political violence (such as civil conflicts, ethnic violence, riots, popular protests, or repression of dissidents). Countries not meeting this criterion are classified as _initially in conflict_ . We also categorize countries based on their conflict status throughout the entire analysis period. A country is classified as _always in conflict_ if major episodes of political violence begin before the first survey wave and persist throughout all subsequent waves. See Table C1 for details.

8
669|0.334|
|Observations|3,853|3,845|3,828|3,866|3,853|3,888|

_Source_ : Authors’ analysis from student surveys.

_Note_ : Dependent variable is an index of related questions. All components of the indices are standardized to mean 0 and standard deviation 1, based on the sample frame at baseline. Standard errors clustered at the school level in parentheses. *** _p <_ 0.01, ** _p <_ 0.05, * _p <_ 0.1. _Knowledge of symptoms and causes of STI subindex_ : Respondent knows STI symptoms include (a) abnormal discharges from the penis/vagina; (b) lesions/sores in genitals; and (c) painful urination; respondent knows: (d) vomiting and headache are not STI symptoms; (e) HIV can be transmitted by having sexual intercourse without a condom; (f) HIV can be transmitted by a contaminated blood transfusion; (g) HIV transmission does not depend on hygiene; (h) HIV cannot be transmitted via food sharing; (i) clothes sharing; or (j) being in a pool with an HIV-positive person. Respondent knows that (k) HIV is not transmitted if a condom is used while having sexual intercourse with an HIV-positive individual. _Sexual violence knowledge subindex_ : Respondent identifies (a) nonconsensual touching of genitalia, buttocks, breasts, inner thigh as abusive sexual contact; (b) forcible sex by husband on his wife as a form of sexual abuse; (c) having sex with a person who is impaired due to alcohol as a form of rape; (d) if an individual changes his/her mind about sex even at the last minute, sex is nonconsensual and hence a form of sexual abuse; (e) the use of threats to obtain sex is a form of sexual abuse; respondent knows: (f) sexual abuse is more often than not
These three cases show that the inferences made about the relationship between the informality share based on employment and emissions per unit of value added cannot always provide information about the relationship of emissions and informality based on value added. For example, if a negative relationship between the informality share based on employment and the emissions per unit of value added is found, this can constitute either case 1 or case 2 and, hence, one cannot infer anything about the relationship between emissions per unit of value added and the informality share based on value added. However, if the relationship for informal employment is positive, one can infer that the relationship for informal value added is also positive (case 3). Conversely, a negative relationship between the emissions per unit of value added and the informal value added share also implies a negative relationship for informal employment (case 1). The above equation can be estimated in a regression and the data allow to test this across countries and industries.

# **3. Empirical Approach**

The objective of this study is to estimate the impact of the informal economy, which is a prevalent feature of developing countries, on CO2 and non-CO2 emissions. It regresses the emissions per value added on the share of informal workers in total employment using cross-country and industry data where the industries include agriculture, manufacturing, trade, mining, construction, finance, other services, transportation and communication, and utilities. The choice of these broad sectors is determined by the availability of data on the industry value added and informal employment. This econometric approach estimates the impact of the share of informal employment on emissions per unit of value added using fixed-effects regressions as shown in Equation (8): 8
calorie intake. But if the two are aggregated this trade-off is not observed. Second, quantities and expenditures are likely to be measured with errors, therefore also unit values derived from the ratio between the two are likely to be measured with errors.

Deaton (1988) proposed a procedure to correct this bias. In order to estimate price elasticities, Deaton’s method is based on two assumptions. The first is the weak separability assumption that assumes that the household utility is weakly separable in the commodity groups. This allows to use unit values as a proxy for price. The second assumption is that surveyed households are geographically clustered in groups that share the same market prices. Price elasticities are then estimated on the basis of intercluster variation correcting quantities and unit values, reducing the bias due to quality effects and measurement errors.

Niimi (2005) tested the robusteness of Deaton’s method comparing expenditure and price elasticities (see tables 1 and 2) and the welfare impact of price changes in Vietnam, estimatimating different food demand systems using market price data, unit values and Deaton’s procedure. The author concludes that Deaton’s procedure tends to overestimate the expenditure elasticities and that it is possible that it does not identify and correct appropriately the quality effects. Subsequently, several other studies found significant differences in price elasticities estimated with Deaton’s method with respect to actual market prices, among these McKelvey (2011) and Gibson and Kim (2013a; 2019). The disadvantage of Deaton’s method is that the variation used to correct price elasticities is not only due to price variation but also it can be affected by other unexplained factors. Moreover, Deaton’s approach is quite complex and therfore difficult to implement.

Deaton’s method was used recently by Bairagi et al. (2020) to estimate a demand system with 15 major food items in Vietnam (see tables 1 and 2 for detailed items). Their main contribution consisted of using three waves of the VHLSS (2012, 2014 and 2016)
MINIMUM WAGES IN CAMBODIA 5 <!-- Start of picture text --> 1997 2000 2003 2006 2009 2012 2015<br>Year<br>Nominal Real<br>300<br>250<br>200<br>150<br>100<br>Minimum wage index, Jan 1997=100<br>50<br><!-- End of picture text --> Figure 1. Nominal and real minimum wage index in Cambodia _Source_ : Nominal minimum wage data from Ministry of Labor and Vocational Training. _Note_ : Vertical lines represent times of minimum wage hikes. This paper studies the change represented by brown vertical lines.

men and women hovered around 80 percent over the study period. Wage employment as a share of total employment increased from 25 percent in 2007 to 49 percent by 2015 (Figure 2). Particularly for females, garment sector also grew in prominence. Garment sector wage jobs were 30 percent of female wage employment in 2007, which increased to 42 percent by 2015. In contrast, garment jobs are less than 10 percent of male wage employment.

Increased employment in the garment sector has translated to higher wage earnings for the workers. Average monthly earnings in the garment sector are higher compared to other private sectors (Figure 2). The sectoral earnings gap is particularly pronounced for females, which is suggestive of lack of better opportunities for women outside garments. For instance, for male workers with other options, the sectoral gap in earnings is non-existent.

However, higher monthly earnings in the garment sector does not necessarily translate into higher productivity (measured by hourly wages). As the dashed lines in Figure 2 show, hourly wages for workers in the private sector is higher than that of the garment sector. For women wage workers, hourly wage in the garment sector are statistically indistinguishable from other private sectors. The discrepancy in hourly and monthly wage earnings arises due
**Figure C.2. Probabilities of Female-Headed Households Falling in Poverty in Second Year Conditional on Being Non-poor in First Year (percentage)**

<!-- Start of picture text --> Egypt 2017-2020 Iraq 2007-2012<br>Self-reported Potential Self-reported Potential<br>Females>0.5 Educated fem. Females>0.5 Educated fem.<br>Jordan 2010-2013 Mauritania 2014-2019<br>Self-reported Potential Self-reported Potential<br>Females>0.5 Educated fem. Females>0.5 Educated fem.<br>Palestine 2011-2017 Tunisia 2015-2021<br>Self-reported Potential Self-reported Potential<br>Females>0.5 Educated fem. Females>0.5 Educated fem.<br>FHH wo/children FHH w/children Non-FHH<br>20 20<br>18 18<br>16 16<br>14 14<br>Percentage (%) 12 12 Percentage (%)<br>10 10<br>14 18<br>12 16<br>10 14<br>8 12<br>Percentage (%) Percentage (%)<br>6 10<br>45 16<br>40 14<br>35 12<br>30<br>10<br>Percentage (%) Percentage (%)<br>25 8<br><!-- End of picture text --> Note: Estimates are obtained with synthetic panel data and weighted with population weights where the second survey round is used as the base year. The figure shows the percentage of the population that enters poverty in the second year. FHH characteristics are measured in second period. Dashed red lines represent the national average for each period. Household heads' ages are restricted to 25-55 for the first survey round and adjusted accordingly for the second survey round. Standard errors are estimated with 1,000 bootstraps. ’s are estimated using Equation (C6). ρρ 93
Page 16 Laat et al. 2008). However, in Uttar Pradesh in India, neither informing communities about the quality of local schools, what they should expect from schools, local funding for schools, and the responsibilities of Village Education Committees (VECs), nor training communities and VECs in techniques for monitoring schools and assessing their children‟s progress, had any impact on school performance (Banerjee et al. 2009).

# **II.b. Accountability in the School “Production Function”**

52. Students‟ performance, and consequently school performance, can be measured on the basis of many different outcomes, e.g. students‟ average test scores, repetition rates, drop-out rates etc. Thus, the _education production function_ can take the form 53. where _qij_ is the performance of school _i_ in terms of output _j_ , and _xi_ represents the level of educational resources, _i.e._ school and teachers‟ characteristics, available in school _i_ . The set of accountability efforts made in school _i_ can be divided into two components: _a1i_ captures the **_topdown_** accountability efforts exercised by educational office inspectors and school director as well as transparency in school administration; and _a2i_ refers to the **_parental and local community participation_** in holding school director and teachers to account, as well as parents‟ general involvement in their children education; _zij_ comprises attributes of the students‟ parents and community. Finally, the term _ηij_ is a random error, which may includes school, community and household unobservable characteristics.

54. However, a note of caution is needed. This investigation into school performance in Albania also employs retrospective data and is therefore not exempt from possible biases due to omitted variables and endogeneity. Nevertheless, the richness of the new data from the Albania School Stakeholder Survey is unique, and allows researchers to investigate the relationship between school outcomes and: (1) school physical and human resources; (2) top-down accountability and transparency; (3)
<!-- Start of picture text --> am, ¥ == 4 OlBeat<br>Md SC-. Ra4 &<br>SUD aMi 2ae* + od<br>ae indian Ocean<br>RWANDA LA ~ oe oy Acute Food Insecurity Phase<br>Kigs pia} ~ 3 FEWS NET Presence Countries<br>Cz “a F GR +: None orMinimal<br>BURUNDI = 2 Stressed<br>)) TANZANIA ME 3 Crisis<br>{ i HB 4: Emergency<br>Y qj MMB 5 CatastropheFamine<br>iN i Non-Presence Countries<br>Fe y (Bt: None or Minimal<br>. al 3 Crisis or higher<br>1,000 >| AY (GQ) 2 Stressed<br><!-- End of picture text -->

<!-- Start of picture text --> Wi. Tigray Tigray i*ice S* y Ethiopia<br>By emai poe Rural Population/Sq Mi Year 2005<br>N conden iaD prey eenAfarae Wereda Level Population Density<br>ee Zoned - HE Above 600<br>Oy Sco HH 400 to 600<br>aa BahinDarg * s 7 TM 200 to 400<br>/<br>in) veces “BTM. jwicoiampnge fantg | , Below100 to 21 00<br>Beneshangul Gunz Fi € = : he ie<br>fom14 adeee © Some F aede gon1% shine » sommes Zone Boundary<br>@ Kamashi —_ GRE IGeD og = Dire. Dawa’ ——_ Region Boundary<br>Tangorsiw’ g rer 4 N. ‘Shewa (4) Pere<br>Wi. es Shows ey co<br>welegs pe Sy Addismbaba J aN<br>a ee Ng oe iar’. Harerg iene<br>Zone 3 é Zone 1 : ae in Cn v a ed ‘ sip f }<br>feebleZone2 ylGodard"Sheka2 mae
**Table 1: Descriptive Statistics Based on Administrative data**

||**Total**|**1981–99**|**2000-–09**|**2010–14**|**2015–19**|
|---|---|---|---|---|---|
|No. of leases issued|58,582|6,641|4,845|39,189|7,907|
|per year|1,502|350|485|7,838|1,581|
|_of which_owned solely by males<sup>a</sup>|0.263|0.766|0.632|0.149|0.208|
|Sporadic registrations per year|619|350|485|1,222|1,313|
|Systematic registrations per year|883|||6,616|269|
|Share of residential property|0.892|0.853|0.924|0.889|0.921|
|No. of transfers per year|210|51|93|390|871|
|No. of mortgages per year<br>|168|117|87|289|400|
|Share of area built<sup>b</sup>|0.475|N/A|0.460|0.484|0.498|
|Share of registered area built<sup>b</sup>|0.128|N/A|0.066|0.155|0.223|

_Source:_ LAA land administration database from 2011 and digitization of paper records, 1981–2011. a Gender relates to the 94.4 percent of properties registered in the name of natural persons rather than legal entities. b Share of built-up area is at the block level,
differentiate from cases where parents might have done so following the initiative of the teacher, termed as DUTYMOM.

> 6[Hsin and Xie, 2014] investigate in great detail data from a set of longitudinal surveys that cover thousands of children over a long period of time starting from their early childhood through high school. As part of the explanation of the superior performance of Asian immigrant children, the authors report that “Asian students report greater parental expectations of academic success.”

12
17 43 and 45 percent respectively. Among the “anocracies”, group membership and attendance in meetings is particularly high for Tanzania.<sup>12</sup> The Afrobarometer data suggest that local-level organization of civil society into groups does not exclude the poor. For six countries—Benin, Botswana, Ghana, Senegal, South Africa, and Zimbabwe—an indicator of poverty in the Afrobarometer (when a respondent mentions that the household has gone without adequate food many times in the recent past) is significantly associated with greater attendance of group meetings (after controlling for respondent age, gender, education, media access, household size, and neighborhood availability of infrastructure). However, the extent to which these groups indeed represent the interests of the poor, or have impact on improved accountability for development outcomes are questions on which the evidence is patchy. This will be discussed in the following section. However, what can also be seen in the Afrobarometer data for seven countries-Benin, Lesotho, Mozambique, South Africa, Tanzania, Uganda, Zimbabwe—is that respondents that report going without food many times (an indicator of poverty) are significantly more likely to report fear of punishment or reprisals should they complain about poor quality of government services or misuse of government funds.

In five countries—Benin, Ghana, Senegal, Zambia, and Zimbabwe—respondents that report frequent attendance in group meetings are also more likely to be those with ethnic grievances. In these countries, ethnic grievance is also correlated with respondents reporting any instances of joining with others to raise an issue. Whether their participation in group and organized activities is geared towards broad collective action or narrower redress of ethnic grievances is an important concern for the efficacy of civil society action in addressing broad accountability failures.

These insights from research and evidence into local-level groups, and how their membership and leadership changes in response to the availability of external funding is pertinent for other donor initiatives to promote transparency and accountability through national groups and associations. We are not able to uncover
Notes: Adjusted for inflation using the World Bank World Development Indicators Consumer Price Index with 2010 as the base year. Data on tax revenue is from the Lagos State Government Digest of Statistics 2006, 2010, 2013. The period between the red vertical lines indicates when the federal government withheld transfers from Lagos local governments.

In Lagos, the specific actions taken by the tax administration focused on deploying technology by introducing electronic payments and tax withholding, by creating an autonomous tax agency separate from the civil service, and by hiring and incentivizing skilled professionals. There was political support for enforcing tax laws, like imposing fines and sealing delinquent businesses. In addition, there was significant taxpayer education and outreach, and publicity campaigns to foster tax morale by linking the visible public infrastructure investments to the expansion in tax payments. Overall, this case suggests that success in increasing tax collection requires a combination of factors, including a well-motivated government and an ability to deploy diverse tools, particularly those relating to technology and personnel.

Another key factor that may influence a government’s decision of how much to enforce taxes is the availability of technology tools that reduce the political and economic costs of taxation by making tax collection more automated and less salient. For example, using employers to withhold personal income taxes removes the need to require citizens to remit payments, and consumption taxes like the value-added tax may be less salient to citizens. Such tools or instruments may lead to less political resistance—but they only work well if the government has access to appropriate technology tools for implementing them. As an example from the United States context, Cabral and Hoxby (2012) show that property taxes are less salient to property owners who use the technology-aided practice of bundling their taxes with their monthly mortgage payment through a tax escrow account, compared to other homeowners with mortgages who make one or two large direct tax payments a year to the government. Areas with higher rates of escrow use also have higher property tax rates, suggesting that the lower salience and automation of collection allows