rafmacalaba/data-use-mentions-extended huggingface dataset:
Figure A.4: Validation with SICONFI data across years - payment

# (a) Minas Gerais (MG)

<!-- Start of picture text --> 2014 2015<br>150 150<br>100 100<br>50 50<br>0 0<br><-25 -20 -15 -10 -5 0 5 10 15 20 25> <-25 -20 -15 -10 -5 0 5 10 15 20 25><br>2016 2017<br>200 200<br>150 150<br>100 100<br>50 50<br>0 0<br><-25 -20 -15 -10 -5 0 5 10 15 20 25> 5 0 5 10 15 20 25<br>2018 2019<br>150<br>100 100<br>50 50<br>0 0<br><-25 -20 -15 -10 -5 0 5 10 15 20 25> <-25 -20 -15 -10 -5 0 5 10 15 20 25><br>2020 2021<br>200 200<br>150 150<br>100 100<br>50 50<br>0 0<br><-25 -20 -15 -10 -5 0 5 10 15 20 25> <-25 -20 -15 -10 -5 0 5 10 15 20 25><br>% difference from SICONFI data - MG % difference from SICONFI data - MG<br>(b) Paraná (PR)<br>2013 2014<br>80<br>40<br>60<br>30<br>40<br>20<br>20 10<br>0 0<br><-25 -20 -15 -10 -5 0 5 10 15 20 25> <-25 -20 -15 -10 -5 0 5
1.38|16866|88.26|0.44|4.21|27.57|
|Sub-Saharan Africa|1.68|3151|65.28|2.26|0.67|11.65|

Source: Authors’ construction using World Development Indicators, World Bank 2014 The period from 1996 to 2001 saw two major patterns in the developing world. The first was positive increase in income growth and modest increases in both per capita income and trade shares with SSA countries experiencing a positive average increase of 0.77 percent in income growth, a mild 1.3 percent average increase in income per capita (from US$ 2335 during 1991–1995 to US$2365 during 1996–2001), and a 9.56 percent increase (from 53.29 percent to 62.85 percent) in trade-GDP shares. The second pattern was a significant decline in mineral rents (to 0.36 percent), a doubling of gas rents (to 0.31 percent), and a modest increase in oil rents (to 6.39 percent). As explained below, income, trade, and resource rents indicators improved considerably 5
to these characteristic (see the seminal papers Oaxaca 1973 and Blinder 1973; Fortin et al. 2011 for a recent survey of the literature; and Filmer et al. 2005 for an application to a 1997 crosssection of World Bank personnel files).

> 12The Technical Appendix and codebook provide further details.

> 13Non-monetary benefits (such as health insurance) are substantial at the WBG, but homogeneous within the sample we consider, particularly across genders (described below).

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Kiswahili in Grades 2 and 3. After the survey, only the Grade 2 and 3 teachers were invited to take the teacher assessment. Teacher assessments were subject-based and linked to the curriculum. For Kiswahili, teachers were expected to read a short text and answer 8 comprehension questions, while for Math they answered 10 questions about basic algebra operations and geometry.

Finally, in each school, one Grade 2 and one Grade 3 teacher were randomly selected for classroom observation using the _Teach_ Classroom Observation tool (Molina et. al. 2018). _Teach_ allows enumerators to rate teaching practices through two 15-minute observations during a lesson. The practices are organized into nine dimensions: Supportive Learning Environment, Positive Behavioral Expectations, Lesson Facilitation, Checks for Understanding, Feedback, Critical Thinking, Autonomy, Perseverance and SocioEmotional Skills. These dimensions are measured on a five-point scale and then averaged across the two 15-minute observations.

The study also included a student survey and student assessment. For each school, around 20 students (10 each from Grades 2 and Grade 3) were randomly selected from a list of all Grade 2 and 3 students (provided by the head-teacher). Students were tested on foundational concepts in Math and Kiswahili. These tests

> 5 For more details see: https://riseprogramme.org/countries/tanzania

> 6 <u>https://www.worldbank.org/en/topic/education/brief/teach-related-blogs</u>

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>15</sup>

> 12 Wald tests of equality of coefficients confirmed that the differences in trends between the numbers of domestic and international issuers in Table 4, Panel A are statistically significant at the 1 percent level. These unreported tests were computed within each of the subsamples of economies. 13 For robustness, we run regressions using total assets of listed firms (instead of our proxy based on issuance size) and find an even larger decline in the size of domestic bond issuers between 1990-98 and 2008-16 (Appendix Table 2). 14 The fact that the sum of different types of issuers is close to 100 percent in the first decile means that most of the smallest issuing firms raised funds in only one (domestic) market. The sum of these percentages does not need to be 100 percent because firms in each decile can issue in more than one market and thus belong to more than one group of issuers. 15 There is a high correlation between firm size (in terms of assets) and age. Using Worldscope data on listed East Asian firms, a 1 percent increase in age is associated with a 0.5 percent increase in size.

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<mark>Burkina Faso shoulder virtually all the care work in households, a recent survey</mark><sup>13</sup> <mark>provides quantitative precision: 96% of women reported that they do most or all the cooking in their households, while 80% reported that they do most or all the childcare. In addition, women’s agency in decisions on spending money is limited: only 66% of surveyed women report being able to fully decide how to spend their own income, and 60% indicate not fully participating in decisions on how to spend household money even on major household purchases.</mark> Women’s economic participation is also restricted by their limited ability to fully control their health and reproductive lives. For example, while Burkina Faso has succeeded in reducing maternal mortality more than some peer countries (Mali, Niger, Uganda) and the mortality ratio per 100,000 live births (320) is lower than the regional average (425), it remains well above the global mean (160), and mortality reduction in Burkina Faso has progressed at a slower pace than in aspirational peer countries (Ethiopia, Rwanda). Nationally representative data shows that in 75% of households, the husband is the main decisionmaker over the wife’s health, while female genital mutilation is highly pervasive across income groups—ranging from 77% of women having been mutilated in the first income quintile, to 69% in the fifth income quintile (DHS 2010). This is despite female genital mutilation having been legally banned since 1996, showing the importance of addressing customary norms beyond legal changes. The UN’s most recent data from 2015 shows that the situation has not improved, with 68% of women aged 15-29 having suffered genital mutilation (UN 2019).

Lastly, while the gender gap in both gross primary and secondary school enrollment has reversed in recent years, more than half of Burkinabè women aged 15-24 are illiterate, and girls have lower competency in
14 Figures 3a: NTMs coverage ratios by selected industry, collecting agencies’ classification <!-- Start of picture text --> Coverage ratio by industry and NTM<br>1<br>0.9<br>0.8<br>0.7<br>0.6<br>0.5<br>0.4<br>0.3<br>0.2<br>0.1<br>0<br>Total imports Agriculture Primary Intermediate Manufacturing<br>A ‐ SPS<br>B ‐ TBT<br>C ‐ Preshipment inspection and other formalities<br>E ‐ Non‐automatic licensing, quotas, prohibitions and quantity control measures other than for SPS or TBT reasons<br>F ‐ Price‐control measures<br><!-- End of picture text --> Source: Authors' calculation based on data from COMTRADE and UNCTAD NTMs database.
infringe competition. It is also charged with removing unnecessary regulatory barriers and simplifying administrative procedures through ex post assessment of norms.

The applicable regulations are laws and decrees issued between 2007 and 2017 that specifically target the ICT sector and either facilitate or complicate competition. Facilitating regulations improve the administrative efficiency of entering or operating in an ICT market, improving competition by facilitating both market entrance and resource allocation, and potentially contributing to productivity growth. Conversely, regulations that impose additional administrative requirements or make current ones more complex are likely to generate the opposite effect, hindering market entrance, limiting resource movement, and thus deterring productivity growth. However, it could also be argued that new regulations can also address market failures because an explicit purpose of some is to improve service quality. In this sense, they could raise quality or productivity standards for entering a market or for doing business and remaining in the market, which would translate into higher average market productivity. Possibly, each new regulation could boost or depress productivity—the complexity it adds makes it hard to determine whether it promotes or restricts competition.

To disentangle the layers of complexity, we look at how enforcement of any type of regulation affects productivity and markups: First, we study the behavior of firms that were affected by either an increase or a reduction in regulatory requirements. We then do the analysis separately by isolating observations that were affected only by one type of regulation.

We match changes in regulations and their enforcement over time to the firm-level panel. Regulatory cases are matched to firm data by looking at the market affected, defined by the 2-digit ISIC sector and by the year of implementation. We compare the behavior of these firms to that of firms in the same ICT branch that were not subjected to any new regulation, controlling for firm, sector, and year characteristics through fixed effects—if other sector-specific regulations had been introduced, their effect will not be confounded because it is controlled by the fixed effects. The regulatory variables are coded as dummies where 1s imply a change in
# **1. Introduction**

The COVID-19 pandemic has severely disrupted economic activities worldwide. In 2020, real GDP declined by 1.8 percent in Sub-Saharan Africa (SSA) and by 3.2 percent globally, compared to a projected growth of 3.5 percent in SSA and 3.3 percent globally (International Monetary Fund, 2021). In addition, most countries, and especially African countries have faced large exchange rate depreciations and rising energy and food prices in 2020 and 2021 (Anyanwu and Salami, 2021). Lakner et al. (2021) estimate that in 2020, the COVID-19 crisis increased the number of people below the poverty line by about 120 million in the world and 31 million in SSA. Projections by Mahler et al. (2021) show that while a global rebound was expected in 2021, poverty was expected to further increase in low-income countries, and at a much faster rate than was expected before the pandemic. For low-income countries, poverty was set to increase by 2.7 percent by 2021, compared to the pre-pandemic projection of a 0.2 percent increase (ibid.). These numbers for Sub-Saharan Africa were 2.5 percent compared to 1 percent (pre-pandemic projection).

Beyond these aggregate indicators, systematic evidence of the socio-economic impacts of COVID-19 on households and individuals in low- and middle-income countries (LMICs) is limited, especially for SSA. Egger et al. (2021) analyze phone survey data collected during April-June 2020 in nine LMICs,<sup>2</sup> including nationally representative samples for seven countries, for which they estimate that 25% to 87% of households lost income and 29% to 49% experienced a loss of employment. Josephson et al. (2021) analyze the early socio-economic impacts of the pandemic in Ethiopia, Malawi, Nigeria and Uganda, where they estimate that 77% of the population lost income during the pandemic, while 60% of the adult population experienced either moderate or severe food insecurity.
(2018) used the modified CW approach (Vu, 2009) in QUAIDS concluding that, despite the growing income and urbanization levels in Vietnam, the demand for rice is still expenditure and price inelastic with respect to other foods. Moreover, Hoang (2018) shows that a 10% decrease in income or a 30% increase in rice prices would induce Vietnamese households to revert a larger portion of expenditure on rice away from other foods. This suggests that despite the economic growth, in Vietnam rice remains a core staple for housheolds’ food security.

Despite the availability of methods to (partially) address quality effects, some studies still employed market prices without quality correction. Meyerhoefer et al. (2007) studied the relationship between the demand for health care and the consumption of food, non-food goods, and leisure using the VHLSS 1997 and market data at the commune level with LAIDS in Vietnam. Their results suggest that, overall, Vietnamese consumption patterns are not strongly influenced by changes in health care costs, unless the household is directly affected by illness and some of the members are under treatment. On the contrary, the demand for health care is responsive to changes in income and in the prices of rice and non-food goods. Le (2008) used market prices to analyze the demand for rice, other food, meat and fish, but with the advantage of using prices collected with the Community Price Survey conducted by the GSO in parallel to the VLSS 2004.

A more direct approch to separate the quality from the quantity effect of price changes is the unrestricted method (UM) proposed by McKelvey (2011). This direct approach is seldom adopted because it requires both price and unit value data. Apart from McKelvey (2011), published applications of this direct approach are Gibson and Kim (2013a), Gibson and Romeo (2017) and Gibson and Kim (2019). The UM uses the relationship between unit values and actual prices to directly estimate the magnitude of quality substitution. McKelvey (2011) demonstrates
reasoning test. But take-up is unrelated to household wealth, expressed willingness to pay for training, marital status, or willingness to take risks. As with existing enterprises, take-up is lowest in Colombo.

In both qualitative interviews and direct survey questions, those who attended appeared satisfied with the course. Among current enterprise owners surveyed in round two who had taken the course, 78 percent said they would strongly recommend, and 17 percent said they would somewhat recommend, the course to a friend currently running a business; 86 percent said that the course was more helpful than they had expected. Similarly, 81 (17) percent of potential owners said they would strongly (somewhat) recommend the training to someone starting a business, and 85 percent said it had been more helpful than they had expected.

# **3.3 Follow-up surveys**

Four rounds of follow-up surveys were conducted in September 2009, January 2010, September 2010, and June 2011 - corresponding to 3-4 months, 7-8 months, 15-16, and 24-25 months after the training. We refer to these as rounds 2, 3, 4 and 5 surveys, respectively. The follow-up surveys asked detailed information about business outcomes, including the key performance measures of business profits in the last month, sales in the last month, and capital stock (including raw materials and inventories). Business profits were asked directly, following the recommendations of de Mel et al. (2009b). Nominal values were converted into real values using the Colombo consumer price index. Appendix 3 addresses the possibility that training affected how profits were reported; we find that this is not driving any of our results.

Overall attrition was low – of the 624 (628) current owners (potential owners) selected for the experiment, 584 (588) were interviewed in the second round, 591 (587) in the third round, 580 (560) in the fourth round, and 575 (556) in the fifth round surveys. We cannot reject equality of attrition rates across
Outside of Sub-Saharan Africa, mortality rates are already lower and existing infrastructure coverage is higher, which results in a higher expected cost of around US$ 3000 per life-year saved. However, given the higher average income levels in these developing countries, the ratio of the cost per life-year saved relative to income per capita is similar, and ranges between 0.65 and 0.82 across regions. Given that the WHO guidelines classify any intervention costing less than the annual GDP per capita per life-year saved as “highly cost effective”<sup>6</sup> , further investment in water and sanitation appears highly desirable from a policy perspective.

The estimates presented in this paper also underline the magnitude of the potential humanitarian impact of further investments in water and sanitation. Our estimates imply that in our sample alone – which accounts for approximately 60% of the 102.5 million children born per year in the developing world<sup>7</sup> (World Population Prospects, United Nations Population Division) - providing full access to water and sanitation infrastructure to all children has the potential to save about 1.3 million child lives per year. Assuming comparable health improvements in the rest of the developing world, this means that approximately 2.2 million lives could be saved across all developing countries each year if access to the firstbest water and sanitation infrastructure could be provided to all households in the developing world.

The rest of this paper is structured as follows: in Section 2 and 3, we discuss the data and methodology used, providing a detailed description of the construction of the main variables of interest. We present the estimation results in Section 4, and compare the predicted reductions in child mortality rates with the current gap between child mortality and the MDG objective for each country. We also show estimates of total investment needed per life-year saved. We conclude with a discussion of our estimates in relation to the existing literature and a short summary in Section 5.

> 6 www.who.int/choice
results. The coefficient on whether the firm has bank credit remains negative and statistically significant—although the point estimate is larger in absolute value (see column 2).

As an additional robustness check, and to partly control for firm heterogeneity, we add some additional control variables to see whether this appears to affect our results. The additional variables are similar to those that Brown et al (2011) used to explain access to credit in the some of the same countries. They are: (i) a dummy variable indicating that the owner is female; (ii) a dummy variable representing whether the firm has audited accounts; (iii) a variable representing the business environment that the firm faces (the average of the firm‘s answers to perception questions on tax rates, tax administration, business licensing, and corruption) and (iv) a variable representing the number of competitors that the firm has in local product markets.<sup>28</sup> Including the first three variables reduces sample size from 1779 to 1726 observations. The point estimate for the credit variable becomes smaller (in absolute value)—although it remains larger than before we included the performance variables. Moreover, it remains statistically significant at conventional significance levels. The estimate suggests that firms with bank credit are about 4 percentage points less likely to die than firms without bank credit.

Because only manufacturing firms were asked about competition, sample size falls considerably when the competition index is included—from 1726 observations to 666. Despite this, the coefficient remains statistically significant and is slightly larger than before. The estimate suggests that firms with bank credit are about 8 percentage points less likely to die than firms without credit.

> 28 Brown et al (2011) include two additional variables in their analysis that were not included in the 2008 BEEPS data set.  The two variables are: (i) percent of firm earnings received through a bank account and (ii) the percent of working capital financed with retained earnings.  We omit these
firms can help workers upgrade to higher-quality jobs in higher-performing firms; however, we find that, a year after the rises in the minimum wage, only a minority of workers from firms that exited had found in other, formal employment. Using complementary data from surveys, we find that the decline in formal employment was accompanied by a rise in inactivity and unemployment, as opposed to a rise in informal employment. This suggests that workers from these exiting firms mostly failed to find employment one year after the minimum wage hike.

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22 J.C. Duque, N. Lozano-Gracia, J.E. Patino, P. Restrepo / LCR Flagship Report on Cities and Productivity Cheng, Y., Zhao, L., Wan, W., Li, L., Yu, T., & Gu, X. (2016). Extracting urban areas in China using DMSP/OLS nighttime light data integrated with biophysical composition information. Journal of Geographical Sciences, 26(3), 325-338.

- Cheshire, P. C., & Gordon, I. R. (1996). Territorial competition and the predictability of collective (in) action. International Journal of Urban and Regional Research, 20(3), 383-399.

- Combes, P. P., Duranton, G., & Gobillon, L. (2010). The identification of agglomeration economies. Journal of Economic Geography, 11(2), 253-266.

Duque, J. C., Lozano-Gracia, Patino, J. E., and Restrepo, P. 2017. Urban form and productivity: in what shape are Latin American cities? LCR Flagship Report on Cities and Productivity. World Bank (forthcoming).

De Esteban, A. (2009). Área metropolitana. Diccionario Crítico de Ciencias Sociales.

- Dobbs, R., Smit, S., Remes, J., Manyika, J., Roxburgh, C., & Restrepo, A. (2011). Urban world: Mapping the economic power of cities. McKinsey Global Institute.

Feiock, R. C. (2009). Metropolitan governance and institutional collective action. Urban Affairs Review, 44(3), 356-377.

- Feria, J. M. & Susino, J. (2005). Movilidad por razón de trabajo en Andalucía. Dimensiones básicas y organización espacial. Instituto de Estadística de Andalucía.

- Fischer, M. M. (1980). Regional taxonomy: A comparison of some hierarchic and non-hierarchic strategies. Regional Science
br>0.50 deferred income<br>0.45<br>0.385<br>0.40<br>0.361<br>0.351<br>0.385<br>0.35<br>0.30<br>0.25<br>Market Income Disposable Income Consumable Final Income<br>Income<br><!-- End of picture text --> Source: Own estimations using HBS and SILC data Note: The poverty and inequality estimates differ slightly from official estimates based on the SILC because imputed rent is included in the income aggregate, and the direction of the results is robust to whether imputed rent is included.

The reduction of inequality in Serbia due to fiscal intervention is smaller than that in several countries in Central and Eastern Europe, some neighboring countries, and Latin American countries of similar income level where the CEQ analyses have been conducted. When 14
replaced lost villages by comparable villages in the same counties.  Households lost through attrition were replaced (at least in principle) on the basis of random sampling. For a detailed discussion of the RCRE panel data set, including discussions of survey protocol, sampling, attrition, and comparisons with other data sources from rural China, see Benjamin, Brandt and Giles (2005). Other work exploiting the panel nature of this dataset includes: Benjamin, Brandt and Giles (2011), which examines the relationship between village inequality and income mobility; Giles (2006) and Giles and Yoo (2007), which analyze the risk-management and risk-coping behavior of households; and de Brauw and Giles (2008a, 2008b), which look at the effects of village-level migration on educational investment and household welfare, respectively. 13 The complete RCRE survey covers over 22,000 households in 300 villages in 31 provinces and administrative regions.  We have obtained access to data from 10 provinces, or roughly one third of the RCRE survey.

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