rafmacalaba/data-use-mentions-extended huggingface dataset:
<br>-2.0% 0.0% 2.0% 4.0%GHA 6.0%<br>-6.0% -10.0% CMR<br>-8.0%<br>-10.0% LBR -20.0%<br>LBR<br>-12.0%<br>Annualized change in GDP -30.0% Annualized change in GDP<br>informality<br>for LE-SE<br>Annualized change in total<br>Annualized change in informality<br>wage employees<br>Annualized change in<br>Annualized change in informal informalily for unpaid workers<br><!-- End of picture text --> Source: Own elaboration based on GMD data (y-axis) and WDI (x-axis).

In summary, the urban informal sector is large and persistent in Sub-Saharan Africa. The formal private sector employs approximately 18 percent of urban workers while the informal sector is the source of more than half of all jobs. It is dominated by low-educated self-employed workers, as well as informal sector employees. Short-term trends suggest that urban labor markets do not uniformly move toward formality in the short run, though there may be a shift toward more organized employment types as people move away from unpaid labor into other types of informal work. Economic growth does not seem to necessarily lead to a decline in informality in the short-run.

# **5. Profile of Urban Workers**

Given the persistence of urban informal employment, it is useful to characterize urban workers within employment type. We use unconditional statistical comparisons as well as estimate conditional correlations (Tables 2 and 3) as described in the methodology section above. We consider their demographic characteristics including gender, age, education level, and poverty levels. We also consider their characteristics as workers, namely the 19
poverty line (Ravallion, 2015).

> 2 The fertility adjustment was made on the basis of separate data from Demographic and Health Surveys. See Watkins and Quattri (2016), p.34.

> 3 Convention on the Rights of the Child, Part I, Article 1: “For the purposes of the present Convention, a child means every human being below the age of eighteen years unless under the law applicable to the child, majority is attained earlier.”

2
in these three countries, reaching historically low records, between 1.2 and 1.5 standard deviations below the world’s historical average. In Morocco, as well, school safety dropped dramatically between 2007 and 2011, although school safety tends to be a persistent issue in Morocco and the situation has since improved slightly.<sup>5</sup> School safety also declined significantly in Lebanon (-0.4), the Islamic Republic of Iran (-0.1) and Turkey (-0.4), between 2007 and 2011, which have to varying degrees been impacted by political instability and spillover effects from neighboring countries. School safety is quite degraded in the Gulf countries, Jordan and Morocco, but trends remain steady between 2011 and 2015.

Analyzing the determinants of school safety across countries confirms that, even after considering social background, population density and socioeconomic factors, MENA schools tend to be less safe compared to other regions. Furthermore, an Oaxaca-Blinder decomposition indicates that sociodemographic factors, including educational possessions, age, gender, and urbanization levels explain around one-third of the gap in school safety between MENA and other countries.<sup>6</sup> Thus, school safety is not determined by socioeconomic background of students. School safety is reduced as the share of children from affluent background decreases in a given school. On average, a school with 50 percent or more children from affluent backgrounds enjoy a safety index around 25 percent of a standard deviation higher. And while the connection between school safety and socioeconomic background is positive, it remains much weaker than the connection between students’ performance and socioeconomic background. On average, socioeconomic factors and demography explain only around 10 percent of the variance in school safety, but around 51 percent of the variance between student performance in mathematics and science.

School safety and disciplinary climate however may vary with urbanization _._ School safety tends to be lower in urban and densely populated areas and higher in remote rural areas (Figure 3).
-<br>Government|1|
|4|TMA Solutions|Vietnam|US, Canada, EU,<br>Australia, Japan|1,70<br>0|$27|Cloud Computing, Big Data & Analytics,<br>Mobile|2|
|5|HiPT Group|Vietnam|Vietnam|262|$25|Systems Integration, Software<br>Development,IT Equipment|1|
|6|Harvey Nash|United<br>Kingdom|US, UK, EU,<br>Vietnam|945|$20|Software Development, BPO|3|
|7|Elcom Corp|Vietnam|Vietnam|335|$20|Software Development, R&D, Systems<br>Integration|1|
|8|Tinhvan<br>Technologies|Vietnam|Vietnam|363|$14|Software Development, Digital Content, IT<br>Consulting|1|
|9|Global Cybersoft<br>(HitachiConsulting)|United<br>States|US, Japan, EU,<br>Vietnam|850|$12|Enterprise Application Integration, Testing,<br>SoftwareDevelopment|3|
|10|KMSTechnology|Vietnam|US|459|$9|ProductDevelopment, SoftwareTesting|2|
|11|MK Smart|Vietnam|Vietnam, Japan,<br>Southern Africa,<br>Latin America|409|$8|Card Printing, Payment Card Security,<br>Automatic Payment|2|
|12|NTT Data|Japan|Japan, Vietnam|190|$8|Software Development, IT Consulting,<br>Manufacturing andLogistics|4|
|13|Technology and<br>Media Investment<br>Development|Vietnam|Vietnam|90|$6|BPO, Cloud Computing|1|
|14|SPi|Philippines|US,EU|800|$4|DigitizationServices, Content Solutions|4|
|15|Fuji Computer<br
), Industrial Raw Materials (SITC 27+28+68), Machinery, excluding auto (SITC 7-78), Automobiles & Parts (SITC 78), Textiles & Clothing (SITC 5+84), other Consumer Goods (SITC 5+6+8+9-65-68-84), Fuels (SITC 3) and All Goods (SITC 0 to 9).

Source: Based on UN COMTRADE Statistics.

Second, exports of capital and transportation equipment and automobile parts have dramatically expanded while their imports have kept up with the overall growth of total imports. Their aggregate share in total exports increased from 7 percent in 1990 to 11 percent in 1995, 21 percent in 2000 and 29 percent in 2004. Exports of machinery had a least square growth rate of 27 percent and of automobiles and parts of 45 percent in 2000-04. Turkey was a net exporter of automobiles and parts in 2001 and 2002 mainly due to the fall in import demand due to a strong depreciation of Turkish lira following the balance of payments crisis in 2001. The value of imports of automobiles and parts fell 54 percent in 2001 and was still 42 percent below its 2000
GDP in 2007 to 31.6 in 2011, soared the next year to 37.9, fell again to 30.8 in 2015 and then jumped again to 39.9 in 2016. This erratic behavior is not observed in the main monetary transfers in this study. On the one hand, social security benefits (i.e., contributory pensions and social insurance benefits) have seen a sustained increase from a little more than 5 percent of GDP in 2007-2008 to 7.4 percent in 2016. On the other hand, social assistance transfers (e.g., child program, maternity programs, merit programs) have oscillated around 2 percent of GDP during the past decade. As of 2016, these two components represent 18.6 and 5.1 percent of general government expenditures (see Table 1).

In terms of participation in the fiscal budget, contributory benefits, which include pensions, but also unemployment benefits and other social insurance benefits, represent 17 percent of public expenditures in 2016. Non-contributory benefits, which include child program, and other social assistance allowances, represent 5.1 percent of public expenditures the same year. These stand as 6.8 and 2.1, respectively of GDP (see Table 1).

The largest component among monetary transfers is pensions.<sup>5</sup> There are social welfare pensions, that support people not entitled to receive pensions from the social insurance system. These

> 3 Exemptions on gold sales are estimated to represent tax expenditures of MNT 41.3 billion. Financial, insurance and stock-market services 88.4 billion. Food staples 41.6 billion. These exemptions are estimated to represent 6.0, 12.8 and 6.0 percent, respectively, of total tax expenditures in year 2016 (or 0.7, 1.5 and 0.7 percent of total fiscal revenues in 2016). Data provided by the Mongolia Ministry of Finance in April 2017.

> 4 Exemptions on hybrid cars are
the household-level. We use repeated cross-sectional data compiled from our five FSMS in lean season that provide household-level information on food consumption along with key socio-economic characteristics. We thus propose the following general reduced form that relates the FCS to an RSQ index: _yi,d,r,t_ is the FCS in lean season of year _t_ for household _i_ , living in department _d_ and region _r_ . _rsqd,t_ is an RSQ index measuring the quality of the previous rainy season in department _d_ .<sup>19</sup> **_Xi,d,r,t_** is a vector of controls and **_Vi,d,r,t_** is a broadly defined vector of vulnerability factors such that the marginal effect of the RSQ on individual _i_ ’s food consumption is given by _β_ 1 + **_β_ 2**<sup>**_′_**</sup><sup>_._</sup><sup>**_Vi,d,r,t_**.Ofcourse,theproposedmodelassumesalinear</sup> relationship between food consumption and the RSQ and the vulnerability function for household _i_ is therefore given by _vi_ ( _rsq_ ) = ( _β_ 1 + **_β_ 2**<sup>**_′_**</sup><sup>_._</sup><sup>**_Vi,d,r,t_**)</sup><sup>_× rsq_,althoughourresults</sup> also include estimations with more complex polynomial functional forms.

Regional fixed-effects _γr_ absorb time-invariant unobserved spatial characteristics at the regional level that are not captured in **_Xi,d,r,t_** . Those include, for instance, access to food markets, to urban markets for trade or non-agricultural work, climatic and geographic factors, institutions and cultural characteristics. Year fixed-effects capture yearly variations at the country level such as those due to exogenous price shocks
The condition for a household to be in the study was that at least one of the members should be in the target age range of our intervention, i.e., 18-25 years old.

Second, the research team randomly selected one person age 18-25 in each household to be invited to the screening of a Nigerian movie, different from MTV Shuga. We denote this initial screening as Screening 0. The selection was stratified by gender, half males and half females. Out of 17 _,_ 224 people invited to Screening 0, 6 _,_ 613 attended, with a turnout rate of 38 _._ 4 percent. Appendix Table A1 compares those who chose to attend Screening 0 and those who did not, on a number of characteristics that we collected when we first visited the households, as well as the normalized pair-wise differences and the p-values for the test that the difference in means is zero.<sup>1</sup> The two samples are well balanced, with few variables showing significant differences, but of extremely small magnitude: _in all_ cases the normalized difference is _below the threshold of_ 0 _._ 25 _suggested by Imbens and Rubin (2015)_ . We thus conclude that those who attended Screening 0 were a representative subset of the households invited.

The third step was the selection of our baseline sample. In each location enumerators paid home visits to 64 individuals among those who attended Screening 0, randomly selected.<sup>2</sup> All were invited to participate in the study and administered the baseline survey if they agreed. _Appendix Table A2 shows balance in observable characteristics between the people who attended Screening 0 and were selected into the baseline sample and those that were not._ We also compared our sample to the 2008 Nigeria DHS, restricted to the South-Western region, and found that the two were quite similar in terms of religion (a third Muslim and two thirds Christian), years of education (around 11 years) and television-ownership rates (around
greater than 95 percent are excluded. Second, to render household demographics more homogeneous, we exclude households in which the household head is younger than 21 years of age or older than 75 years of age. These restrictions are similar to those used by Costa (2001), Gibson, Stillman, and Le (2008) and Hamilton (2001). Finally, rural households in all the countries in this study, except Mauritius, Nigeria, and Rwanda, are dropped because the CPIs in these countries reflect prices faced by urban populations only.<sup>12</sup> Because of this, our estimates of CPI

> 12 While the national CPIs for Mauritius reflects urban prices only, the Household Budget Survey for Mauritius does not identify households’ location – either urban or rural areas. Therefore, all households must be included for the estimates of CPI bias in the case of Mauritius.

13
13 Table 4 shows the amount of legally entitled severance pay and actual payments by a set of employee and job characteristics using data from the Sakernas (2008) survey. Here, the amount actually received by women as a proportion of their legal entitlement is higher than that for men: 0.3559 and 0.2697, respectively. Generally, both legally entitled severance pay amounts and actual severance pay received increase across the age distribution up to 35-49 years: from 0.0681 at ages 15-18 years to 0.3985 at ages 35-49 years. Contrary to _a priori_ expectations, the proportions for the oldest two age groups drastically decline. These proportions compare to the all-age average of 0.2961. Except for those employees with less than primary education, the legally entitled amount increases with education. The ratio of the amount actually received, however, only increases at the highest education levels (that is, senior secondary and tertiary).

Generally, there is wide variation in both legally entitled and actual severance pay received across industries. The industry patterns differ greatly across the two surveys. The relationship between both legally entitled and actual severance pay is positive and systematic for tenure. Legally entitled severance pay amounts increase from 1.135 million IDRs for those with less than one year of tenure to 22.942 million IDRs for employees with 10+ years. Generally, the ratio of actual to legally entitled severance pay also increases with tenure, rising from 0.1897 for less than one year to 0.3055 for employees with 10+ years of tenure.

For firms of different sizes, there is a positive and systematic relationship between both legal entitlement to and actual severance pay received. In firms with fewer than 20 employees, the ratio of actual severance pay received to the legally entitled amount is below the overall average of 0.2916; on the other hand, in the largest two firm-size categories, both ratios exceed this average.

Wage-and-salary workers employed by government agencies are the least likely to receive the severance payment to
also augmented by mobile phones), power (the electricity generating capacity of the economy in MW per 1,000 workers), and transport (the length of the road network in km per sq km of land area, also augmented by the railroad length), based on panel data of over 100 countries spanning 19602000.</mark>

- **<mark>Electricity</mark>** <mark>. Aterido, Hallward-Driemeier and Pages (2011) examine the incidence of power outages on firm outcomes, finding that poor infrastructure has a detrimental effect on the growth of all firms but the micro ones. Fernandes and Pakes (2008) find that firms which suffer more production losses due to electricity outages have lower TFP and underutilize both labor and capital.</mark>

It is important to note that this study deals entirely with constraints to productivity and innovation faced by existing establishments. We identify which aspects of the business environment are most important and potentially impactful in improving productivity and innovation within incumbent firms. We unfortunately cannot examine the constraints to increasing the prevalence of high-productivity entrants, which may have an even greater overall disruptive transformational growth potential than existing incumbent firms – as we do not observe those firms that could have entered but were prevented from doing so by prevailing constraints in the business environment. Thus, our analysis does not, and cannot, account for the productivity effects of increased industrial dynamism though entry and exit _per se_ .

12
whether a rural road passes by within the community’s boundary regardless of the road length.<sup>11</sup> How to define households and areas affected by the rural road development is methodologically important. Given the nature of rural roads, this study considers that households in the communities in which rural roads were developed have been affected.<sup>12</sup> Among the 204 communities analyzed for this study, 72 communities had URRAP or other types of rural roads developed between 2010 and 2014. The total length of the segment of the roads within the analyzed communities has reached 400 km.

The main welfare outcome to be considered in this study is household consumption. The consumption aggregate in the ESS includes expenditures on and own-consumption of food (with a recall period of 7 days) and also includes spending on a selection of important nonfood items, including education. Health spending is not included in the aggregate to avoid that large expenses incurred following adverse health shocks would signal an increase in household welfare. This study adjusts the consumption aggregate in the three waves of the ESS in 2016 prices. In addition, spatial adjustments are also made to account for differences in living cost across regions. To convert the nominal consumption into a spatially adjusted real consumption, the consumer price index (CPI) is used to perform temporal adjustment (that is, convert all consumption values into 2016 prices) and the Fisher spatial price index is used for spatial adjustment. For the analysis of poverty, the poverty

> 11 Development of non-rural roads, such as regional corridors, is not considered as the treatment. Iimi et al. (2018) is an example that analyzes the impacts of road access by distinguishing rural roads and regional corridors in Ethiopia.

> 12 No spatial spillover is a key assumption for the identification of the impacts of rural roads (stable unit treatment value assumption, or SUTVA).

6
# <mark>3. DATA AND DESCRIPTIVE STATISTICS</mark>

# _(a) Data_

Studies on the agricultural productivity gender gap typically use one of two indicators to identify farm outcomes by gender: (i) the gender of the household head or (ii) the gender of the plot (or farm) manager. Several papers point out that the latter is likely better at capturing the gender gap, since the former does not take into account the distribution of inputs and the specific decision-making process among household members <mark>(de la O Campos, Covarrubias and Patron 2016</mark><sup>5</sup> <mark>; Peterman et al. 2011).</mark> Another problem with using the gender of the household head to compare agricultural productivity across households is that there are potential omitted variables, given that many female heads of household tend to be widowed, have a migrant husband, or are otherwise systematically different from male-headed households <mark>(Kleinjans 2013).</mark> The advantage of our household data set is that the survey captures who is the primary responsible person for each crop production. We use detailed data on individual farmers and their agricultural activities from the Household Income and Expenditure Survey 2016. The survey was conducted by the Department of Census and Statistics of Sri Lanka and the data are representative at the national and district levels. The survey includes questionnaires on demographic and socioeconomic characteristics of individuals and households, as well as relatively detailed income modules. Data on agricultural self-employment activities include information on crops cultivated, crop area, value of output, agricultural inputs, ownconsumption, and use of subsidies. While not all crops are individually listed, information is collected on paddy, other seasonal crops (chilies, onions, vegetables, cereals, yams, tobacco), cash crops (tea, rubber, coconuts, coffee/pepper/betel, banana/fruits) and livestock (meat, eggs, milk), fish, horticulture,
. The analysis uses a sample of 6,345 firms from the World Bank’s Enterprises Surveys in Colombia, Greece, Italy, Jordan, Kazakhstan, Kenya, Morocco, Peru, Portugal, the Russian Federation, Turkey, and Ukraine. All surveys were conducted within the last three years and have wide scope, covering a representative sample of at least 600 firms in each country.<sup>2</sup> The share of firms responding to the financial questions, however, varies.

> 2 We use this sample from an overall sample of 75 economies with recent data, as it is broadly representative of Southern Europe and upper middle-income emerging markets. We intentionally shy away from lower middle-income

2
Figure 2 presents the results of the distribution of transfers for pensions throughout the income distribution and also presents the results of progressivity in relative terms of these transfers.

<!-- Start of picture text --> Figure 2. Absolute and relative progressivity of government transfers for pensions<br>Panel A. Progressivity in Absolute Terms Panel B. Progressivity in Relative Terms<br>70 9<br>8<br>60<br>7<br>50<br>6<br>40 5<br>30 4<br>3<br>20<br>2<br>10 1<br>0 0<br>1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10<br>Decile Decile<br>pensions<br>% of pension transfer received by each decile % of market income +<br><!-- End of picture text --> Source: World Bank Group staff estimates based on the 2017 ENPH Note: The deciles were put together using market income + per-capita pensions As stipulated in Colombian legislation and as ratified by the Constitutional Court, “a person who has reached the age and met the number of weeks required by law to access the old-age pension, has configured in his favor the right to enjoy said benefit and therefore is in the face of an entitlement, which cannot be taken away.” The fact that pensions in Colombia are considered an entitlement suggests that all income in respect to pensions should 17
The use of an annuity instead of individual values for depreciation and return on capital serves two purposes. First, it simplifies the calculations. Second, the use of a constant annuity implies adopting an increasing pattern of depreciation. Given that we evaluate capital over a 35-year period, an increasing depreciation rate provides the correct allocative signal, since the system is bound to have excess capacity at the beginning of the period.

# **3.5 Estimating operation and maintenance costs**

In general, during tariff revision processes, and in particular when estimating long-run marginal costs, a generalized percentage of total assets is used to estimate annual operation and maintenance (O&M) costs when no detailed information is available. The reference values generally fall between 2.5 percent and 3 percent of invested assets. For the purposes of this study, the upper limit of 3 percent is assumed as a reference value.<sup>20</sup> When this methodology is applied to all utilities represented in the IBNET database, O&M costs represent an average 24.7 percent of total efficient costs, which is similar to the average 28 percent figure from our sample of Chilean model firms.

# **3.6 Estimating efficient tariffs for utilities listed in IBNET**

Having estimated the operating costs, depreciation, taxes, and capital remuneration for utilities listed in IBNET, we can now compute an efficient revenue requirement for water and sanitation services separately for each utility using Equation 1. We then estimate an efficient average tariff by dividing the efficient

# **3.7 Estimating full tariffs for utilities listed in IBNET**

The tariffs computed in the previous section are intended to recuperate the capital and O&M costs of an efficient model firm. But this assumption of efficiency is unrealistic: most utilities present larger inefficiencies mostly having to do with excessive operations and maintenance costs due to overstaffing and water production losses. However, capital expenditures can also be inflated since extra assets are required to increase production to make up