rafmacalaba/data-use-mentions-extended huggingface dataset:
Table 3: Roll-Out of Intervention

||Number of Villages|
|---|---|
|No training in year 1|136|
|Training for VH only|69|
|Training for VH + CL|65|

The civil society leaders invited to attend the sessions were required to be from the “non-traditional” sector, and included village health workers, representatives of farmers’ groups, church leaders, representatives of NGOs and school development committee members.<sup>13</sup> These same sets of leaders have often been represented on VIDCOs and tasked with implementing reforms via that institution (Munro, 1998, p. 308-314, 340-324). The expectation was that these leaders would provide a constituency for reform because they had less stake in the traditional system than the village head. Indeed, table 4 compares data from our surveys of village heads and our surveys of a representative sample of civil society leaders in these villages to show that – on average – civil society leaders are more pro-reform than village heads.<sup>14</sup> Specifically, the top panel of table 4 shows that civil society leaders are often from demographic groups who would benefit from the reform of village-level governance. For example, a majority of civil society leaders in these village are female. In addition, they are younger and less likely to be visible supporters of the ruling party than the village head (as measured by whether they had a sign displayed outside their home during our interviews, which were shortly after the 2013 elections). At the same time, the profile of the average civil society leader suggests low power differentials between them and the village head. They are significantly more educated than village heads, and they report higher levels of income and wealth. These findings suggest civil society leaders often have both an interest in and the ability to check the village head’s power. We also find that 57 percent of all civil society leaders have a family relationship to the village head.
North America would enjoy the benefit of the doubt under the decisions rule adopted here to decide the existence of a concentration problem. Latin America and Europe—both east and west—are once again the two regions in which the concentration levels are the highest. Eastern Europe and Asia are not that far behind.

While the concentration indicators are useful, once more, they do not tell the full story. First, it may be useful to point out that in 2003, Deutsche Telekom and SBC shared 40% of the market controlled by these 9 companies in the world. Second, actors relatively small at the global level can be very important are the regional level. This is the case of Telstra who is big in Asia but relatively small globally. Finally, however strong the presence of these firms may be in developing areas, for most of them the core business continues to be in developed countries, most importantly in Western Europe and North America.

**<u>Table 4: Regional HHI for Telecoms – Fixed</u>**

||<br>**GLOBAL**|<br>**Africa**|<br>**Asia &**<br>**Oceania**|<br>**Latin**<br>**America**|<br>**North**<br>**America**|**Eastern**<br>**Europe**|**Western**<br>**Europe**|
|---|---|---|---|---|---|---|---|
|**Market indicator**||**Nu**|**mber of w**|**orking lines**|**per country**|||
|**HH min**|**2009
may affect the gender gap. We distinguish between ‘status variables’ or ‘innate characteristics’, and those which are shaped by the behavior of the industrial firm such as managerial practices, investment in innovation or worker training and the adoption of advanced technology. ‘Innate characteristics’ cover traits such as being informal, catering to the domestic or export market, firm size or being in the private sector or located in an industrial zone.

We find that, contrary to evidence from other countries around the world, the COVID19 shock led ‘overall’ to a slight improvement in the gender employment gap in manufacturing. This gap however stems from a larger ‘reduction’ in male employment compared to that for females. Men have borne the brunt of the pandemic in Egyptian manufacturing. The relative weaker direct employment impact on women compared to men is primarily due to the very limited number of women in employment in manufacturing to start with. Female employment in manufacturing is just 18% of total employment in the sector (EIFBS data). More generally, with just 7% of total female participation in industry (UNDP 2021), Egypt occupies the bottom position compared to its oil importing counterparts such as Tunisia, Jordan or even agriculture dominated Morocco. Industry encompasses more than just manufacturing, it additionally includes sectors such as construction, mining and quarrying; electricity, gas and water supply, which are inherently even more male-dominated compared to manufacturing.

While the aggregate results show that there had been a slight overall improvement in the employment gap post-COVID, there are nuances based on individual characteristics of the surveyed firms. The heterogeneity analysis shows that exporting firms and firms in industrial zones have on average ‘increased’ both types of employment post-COVID. Egypt’s traditional sectors have been particularly hit by the pandemic (El-Haddad and Zaki 2022, El-Haddad and Zaki 2023a, El-Haddad and Zaki 2023b) which is reflected in their shock exposure. These feminized sectors have contributed to a deterioration of the gender gap.

Whilst providing ‘helping hand employment’ for men
agree more strongly that mathematics is important in life relative to their female peers (47.6 percent of boys agreeing a lot compared to 36.3 percent of girls). Among immigrant students, grade 8 boys were much more likely to attend a private school (11.1 percent) than grade 8 girls (2.7 percent) (table A1.2). Nonetheless, as at grade 4, most boys (87.7 percent) and girls (96.3 percent) attended government schools.

Again, similar to grade 4, NALO data for grade 8 show the differences in perceptions among teachers, school principals, and parents in boys’ and girls’ schools. A substantially lower proportion of teachers of grade 8 boys agree that parents have a good understanding of their child’s current academic level (associated with the second-largest effect size observed: _φ_ = .236; table A1.3). Similar to grade 4, this suggests greater misalignment between student performance and parental understanding among parents in boys’ schools. A lower level of respect for students who achieve at a high academic level is reported in boys’ schools, although teachers in boys’ schools are slightly more likely to view their grade 8 students as always being keen to excel academically. School principals report weaker parental support for learning for grade 8 boys than for grade 8 girls (table A1.4), and that boys’ parents’ expectations are being met to a lesser extent. There is little difference in grade 8 boys’ and girls’ access to a school library from which they can borrow books.

15
documents), in 832 cases the firm had closed and neighbors had said this was a permanent closure, in 871 cases the owner was unable to be contacted on three visits at different times and days, 699 cases the owner said they were too busy and/or refused outright to be interviewed, there were errors in records for 209 firms (such as them being listed twice), and 1,353 firms were interviewed. Thus the interview rate was 25 percent of all listed firms, and 48 percent of non-formal, non-closed firms without listing data errors.

Firms which appear in the baseline survey are almost evenly split between commerce and services, with less than 5 percent in manufacturing. The most common types of firms were hairdressers/salons (20%), bars (14%), automobile mechanics (8%), clothing (4%), and grocery stores (4%), with a wide range of other types of firms such as restaurants, bookstores, photocopying, flower shops, laundromats, and dance and language schools. The average owner is 44 years old and has run the business for 8 years, with 37 percent of the owners being female, and 42 percent having completed high school education or higher. The mean firm has 1.3 employees (not including the owner), reports annual revenues of R$52,000 (US$26,000) and monthly profits of R$2,000 (US$1,000).

# **4.4. Randomization to Treatment Status at the Individual Level**

Given that only one-quarter of the listed firms answered the baseline survey, it was decided to focus the communication treatments just on this subgroup, since there was little point in trying to provide information on the process of formalization to firms which were already formal, closed, or where the owner could not be found to talk to. We therefore randomly chose half of the firms which had responded to the baseline survey in each communication block to
The occupational mobility rates experienced by youths are presented in table 6, calculated based on the mobility tables, and they complement the description of intergenerational changes. The reviewing the rates enables us to affirm that, although around half of the youths experienced upward mobility, nearly 40% inherited their provider’s occupation and the rest move downward on the stratum. When observing the behavior of the analyzed subgroups, the difference between sexes stands out, with higher rates of upward mobility for women, in contrast to a greater immobility by men. But the subgroups with the largest gaps between them are the migrant and non-migrant subgroups; the former of which experience upward mobility in 7 of each 10 cases, while non-migrants experience this in only 4 of each 10 cases, and have high rates of immobility. The comparisons by ethnic backgrounds and treatment intensity show very limited differences.<sup>52</sup>

**Table 6. Intergenerational occupational mobility rates. Youths from 18-35 years of age of ENCEL 2017. Total, by sex, ethnic background, migratory status and treatment intensity.**

|||By|sex|By ethnic b|ackground|By migrat|ory status|<br>By tre<br>inte|atment<br>nsity|
|---|---|---|---|---|---|---|---|---|---|
|Type of<br>Mobility|Total<br>(n=3,084)|Females<br>(n=1170)|Males<br>(n=1914)|Indigenous<br>(n=830)|Non-<br>indigenous<br>(n=2254)|Migrant<br>(n=702)|Non-<br>migrant<br>(n=2124)|Low<br>intensity<br>(n=
direct experience with the PSNP. After dropping households with missing observations, an unbalanced panel data set remains, consisting of 11,989 observations from 3,649 households.<sup>9</sup> In addition, surveys were conducted at the kebele level using structured focus group discussions with kebele leaders and other people who are knowledgeable about the locality. The information collected in these discussions includes: kebele characteristics such as infrastructure and population size, and aspects of PSNP implementation. As a part of this survey, retrospective price data were collected on monthly prices on grains consumed by households in that locality. The informants were also asked to estimate the distance to the nearest food market and bank; distributions of these are reported in Figures S1.2 and S1.3 in the appendix.

This population poor and food insecure. Mean monthly per capita consumption in 2006 was 133 birr per capita or, approximately $0.49 US per person per day. Food accounted for 82 percent of consumption. The Government of Ethiopia measures food security using a construct called the “food gap”. This was measured by asking survey participants to report the number of months, out of the preceding 12 months, that they had “problems satisfying the food needs of the household” with a month where the household had “problems satisfying food needs” being defined as one where the household experienced hunger for five or more days. Table 1 shows that only 37 percent of households in the sample report being fully food secure (i.e. food gap is zero) at any point across the five survey rounds. The mean food gap is 2.4 months. More than three quarters of household heads (77.9 percent) have never attended school and just over a

> 9 These households are found in four regions (Amhara, Oromia, SNNP and Tigray), 78 woredas and 191 EAs.

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br>and diesel prices for the month of January.|www.stat.kz.|
|Kenya|91 RON gasoline. For Jan 2012, regulated maximum<br>prices for gasoline, diesel, and kerosene in Nairobi and<br>reported LPG prices in Mombasa.|www.erc.go.ke for gasoline, diesel,<br>and kerosene, and news articles for<br>LPG.|
|Lao PDR|<br>91 RON gasoline, prices in Vientiane.|laostatefuel.com/ for gasoline and<br>diesel, Vientiane Times for LPG.|
|Liberia|Maximum prices set by government.|Announcements by the Ministry of<br>Commerce and Industry.|
|Madagascar|Gasoline with 95 RON (regular gasoline with 91 RON<br>was phased out in 2011), LPG in 12.5-kg cylinders.<br>Maximum prices for gasoline, diesel, and kerosene, and<br>average LPGprices in Antananarivo.|www.omh.mg.|
attainment, is motivated by the fact that previous studies have argued that adolescent aspirations for the future are important predictors of adult attainment. For example, it has been shown that young people with high employment aspirations are more likely to enter a professional career in adulthood (Clausen, 1993; Mello, 2008; Schoon, Martin, & Ross, 2007; Schoon & Parsons, 2002). Similarly, a number of studies in Australia and the United Kingdom have identified a ‘lack of aspiration’ as being one of the key barriers to participation in further education for poorer students (Bradley et al. 2008; James et al. 2008; Goodman and Gregg, 2010). Hence, despite their subjective nature, focusing on aspirations may be argued to constitute the first step in analyzing the overall impact of social-emotional capital on adult attainments.

The primary dimension of social-emotional capital we focus on in this paper is selfefficacy. In behavioral psychology, self-efficacy refers to an individual’s self-belief that they can accomplish a given task and cope with life’s challenges (Bandura 1977). Selfefficacy has been recognized as an important constituent of psychological empowerment (Ibrahim & Alkire, 2007; Zimmerman, 2000). It can be manifested through various elements of personal behavior, such as how well a person perseveres in the face of adversity, whether they have an optimistic or pessimistic attitude about their future, etc. In addition, we also look at self-reported measures of depression and hope as alternative expressions of social-emotional capital.

We use a recent World Bank survey of 3,942 adolescent girls and young women in the 2
focus on more and more formalized activity, e.g. licensed businesses from micro to medium sized, all the way to firms in the census of industrial production, the degree of concentration increases. This suggests that the spatial concentration observed in the VAT data represents a feature of the formal sector more broadly.

Unlike formal sector trade, we find that other observable types of domestic flows, like migration flows also do not exhibit a similar spatial concentration (see Table 2).<sup>16</sup> For instance, while Nairobi is the destination for 29% of all long-term inter-county migration, it accounts for 69% of total outlinks and 65% of total inlinks in the formal sector firm network.

A potential concern is that the observed spatial concentration in urban centres is mainly driven by firm headquarter locations being more likely to be based in Nairobi or Mombasa. While this concern is mitigated by the fact that we observe a similar spatial concentration in other measures of formal economic activity, we also use micro-data from the 2010 Census of Industrial Production to address the question about the role of multi-establishment firms more explicitly. In Appendix A.6, we compare the spatial concentration of sales and firm locations with and

> 16We compute long-term migration flows using data on birthplace and current residence from the 2019 population census.

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, Gual and Trillas (2004) first estimate two policy indexes (one for openness and one for the existence of an IRA) and then analyze their impact on performance. They find that pro-entry policies and the creation of an independence agency have positive effects on network penetration and negative effects on productivity. However, after accounting for endogeneity, results are not very robust statistically.

Interestingly, even though there is “political” or conceptual consensus about the importance of institutions and governance for sector performance, a very limited number of studies have included such variables in the analysis. As mentioned before, Wallsten (1999) includes the expropriation risk as a governance control. More recently, Gutiérrez (2003) explicitly recognizes the importance of governance when assessing sector performance. He uses a governance index as an explanatory variable to analyze the effects of telecom reforms on performance in 22 Latin American countries during the period 1980-1997. However, the components of his governance index refer more to particular characteristics of reform policies in the sector than to governance structures per se. After taking into account the endogeneization of policy variables, he finds that regulatory procedures influence network expansion and efficiency.
to facilitate the evaluation of the Danida-supported Agricultural and Rural Development Sector Program Support (ARD-SPS). In subsequent rounds, a part of the sample was replaced in each round to correct for aging of the original sample. In total, approximately 3,000 households were sampled in each round from 2008 onwards. We restricted our sample to households covered in all four rounds between 2008 to 2014, the latest round of VARHS to which we were able to gain access. Matching this with the administrative data left us with 509 households in each round of the VARHS spread across 73 communes in the RTP3 sample; a total of 2,036 observations in four consecutive rounds, spanning an eight-year period.

# _Administrative data_

We used administrative data on road improvements at the level of each road. This data included: type of activities carried out under RTP3 (classified into rehabilitation, periodic maintenance, and routine maintenance), the dates when these activities were carried out, and the location of the road. We retrieved these data from project management units located within the DoTs in each province with significant assistance from the central project management unit located in the Department of Roads Vietnam (DRVN) in Hanoi.

The decentralized implementation structure both impeded easy access to administrative data and lowered the quality of data we were eventually able to retrieve. Although some project data were maintained centrally, including by the World Bank, they were not at the level of detail sufficient to carry out an impact evaluation. Data on locations of each road, activities, and timelines were only maintained in the provincial DoTs responsible for the implementation of the project. Collecting the data took several months and was an iterative process based on conversations with staff of the DRVN and provincial DoTs. We learnt in the process that data on non-RTP3 activities and GIS data on roads were prohibitively difficult to retrieve, if not nonexistent. The data on the pre-intervention quality of the road were not available either. In the end, we were able to collect data covering project activity, start and end
> The analysis addresses the effects of alternative government spending patterns. In MAMS, these effects are covered via two mechanisms: (1) total factor productivity in selected production sectors is a function of the level of government service-specific capital stocks (cf. the disaggregation of government service sectors in Table 1), which are driven by government investments and depreciation rates; and (2) spending on health and water-sanitation has a direct impact on the MDGs for under-five mortality, water access, and sanitation.<sup>21</sup> The 19 A SAM is a square matrix that provides a comprehensive, consistent economy-wide summary of the payments in an economy during one year. It links institutions, factors, and production sectors. The latter are split into activities (which carry out production) and commodities (representing activity outputs or imports without domestic production). Given the consistency requirement, each account must be balanced – its receipts must equal its outlays. The accounts of the Liberia SAM closely match the disaggregation of MAMS (cf. Table 1). The elasticities used in MAMS draw on the international literature; given the consistency features of an economy-wide model like MAMS, as long as they stay within ranges that are widely accepted, most elasticities play a very minor role. In the analysis of the simulation results, we highlight the features of the model and the database (including elasticities) that have a significant bearing on our qualitative conclusions.

20 The higher the GDP (and GNI), the lower the average growth rate required to reach middle-income status by 2030. However, it is also worth noticing that economic activities that register the largest increases compared to earlier statistics (the informal sector and subsistence farming in particular) are less likely to grow rapidly.

21 In other MAMS applications, the impact of education has typically been captured by linking a detailed treatment of this sector to a labor market that is disaggregated by educational attainment, with higher wages (and marginal value products) for workers with more education. By permitting
**Table 1: Share of Gross Industrial Output Value by Ownership (100 million, calculated at Current price)**

||State sector|Non-state Sector|
|---|---|---|
||SOEs|Collective owned<br>Other oner7shiph|
|1962|87.8%|12.2%<br>0.0%|
|1980|76.0%|23.5%<br>0.5%|
|1985|64.9%|32.1%<br>3.1%|
|1990|54.6%|35.6%<br>9.8%|
|1995|34.0%|36.6%<br>29.4%|
|1996|28.5%|39.4%<br>32.1%|
|1997|25.5%|38.1%<br>36.4%|

Data source: China Statistical Yearbook "b" other ownership include joint ventures, solely foreign-owned firms, shareholding firms and private companies.

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BOTSWANA’S INFRASTRUCTURE: A CONTINENTAL PERSPECTIVE In fact, the lack of competition is argued to be one of the potential causes of Air Botswana domestic reputation for poor service with a very high index of delays and cancellations. This lack of reliability is commonly cited as a major obstacle to better performance in the tourism sector.

**Figure 9. Evolution of seats and city pairs in Botswana**

<!-- Start of picture text --> a. Seats b. City pairs<br>900,000 16<br>800,000 14<br>700,000<br>12<br>600,000<br>10<br>500,000<br>8<br>400,000<br>6<br>300,000<br>200,000 4<br>100,000 2<br>- 0<br>2,001 2,004 2,007 2009 (Est)<br>2,001 2,004 2,007 2009 (Est)<br>Total<br>International Total International<br>Intercontinental excluding flights between NA and SSA<br>Intercontinental Domestic<br>Domestic<br>City pairs<br>Number of seats<br><!-- End of picture text --> _Source:_ Bofinger 2009. Derived from AICD national database (www.infrastructureafrica.org/aicd/tools/data). _Note:_ As reported to international reservation systems.

# Water resources

Botswana has scarce water resources compared to countries occupying similar climatic zones. The renewable water resource per capita is estimated at about 6,819 cubic meters (m<sup>3</sup> ) per year (including cross-border flows), below the Sub-Saharan African average of 7,000 m<sup>3</sup> per year. Rainfall levels vary considerably across regions and during the course of the year, averaging a low 416 millimeters
0.24<br>nd. The trai|0.34<br>ning data is|0.46<br>split into t|0.45<br>wo subsets:|0.47<br>50% used f|0.44<br>or training (|0.49<br>training sub-|

Note: The values are scaled proportional to the largest value in the set. The model is trained using Tanzania 2020/21 round. The training data is split into two subsets: 50% used for training (training subsample) and 50% used for validation (testing sub-sample).

67