rafmacalaba/data-use-mentions-extended huggingface dataset:
we explore sensitivity to this choice. We also examine how results are affected by the equivalence scale used to weigh individuals within households.

The paper is organized as follows. In Section 2, we present the data collected, and examine the likely implications of observing consumption at the level of small groups within the household on estimated inequalities and poverty levels. In section 3, we describe intrahousehold inequality and its contribution to overall inter-individual inequality. Section 4 is dedicated to the revision of poverty assessments brought about by the prevalence of intrahousehold inequalities, and Section 5 presents some robustness checks. Section 6 concludes.

# **2. The “Poverty and Family Structure” survey**

# 2.1. The Survey

The PSF Survey was conducted in Senegal in 2006-2007. It results from the cooperation between the National Statistical Office of Senegal and a team of French researchers.<sup>3</sup> It is a nationally representative survey covering 1,800 households spread over 150 clusters drawn randomly from the census districts so as to insure a nationally representative sample. About 1,780 records can be exploited. Nevertheless, for the purpose of this paper, we exclude households with missing consumption information or incoherent records.<sup>4</sup> We are left with a sample of 1762 households. Among them more than half live in rural areas, while 28% are in Dakar.

The survey collects the usual information on individual characteristics, as well as a detailed description of household structure, consumption, and budgetary arrangements.

6
Achievements**

Botswana has made enormous strides in providing access to information and communication technologies (ICTs), especially mobile communications. In just over a decade, the number of mobile subscriptions went from zero to exceeding the country’s population by the end of 2010. While the real level of access is lower than these numbers suggest, accounting for duplicate and inactive subscriptions and the trend towards dual-SIM card phones,<sup>6</sup> Botswana’s mobile penetration of 118 per 100 people in 2010 was the highest in Sub-Saharan Africa (table 12).

Botswana’s high mobile penetration is partly due to the early introduction of competition in 1998, when two operators were licensed, Mascom and Orange. This duopoly continued for a decade before a third mobile operator, a subsidiary of the incumbent fixed-line operator Botswana Telecommunications

> 6 According to one survey carried out between 2007 and 2008, 59.5 percent of Botswana’s population 16 years and older had a mobile phone. This corresponds to some 46 percent of total mobile subscriptions in 2008, giving some idea of the high number of duplicate and inactive subscriptions. Applying the same ratio to the 2009 mobile subscriptions results in an estimate of 87 percent of those aged 16 and older with a mobile phone. The survey data are published in Gillwald and Stork (2008).

27
facilitation.<sup>4</sup> What sectorally-disaggregated work there is tends to focus on broad categories rather than particular sectors that might be thought to be particularly sensitive to improvements in trade facilitation. Zaki (2010), for example, uses data disaggregated into 25 sectors to assess the effects of administrative burdens on bilateral trade. For the case of ASEAN, Shepherd and Wilson (2009) disaggregate trade flows into seven sectors using the one digit level of the Broad Economic Categories (BEC). In their analysis of transparency as one type of trade facilitation measure, Helble et al. (2009) split the data into trade in agriculture versus manufactures, and differentiated versus homogeneous goods. Other examples of exploiting these kinds of broad splits in the data include Persson (2010; homogeneous versus differentiated, and agriculture), and Portugal-Perez and Wilson (2010; fuels, ores and metals, manufactures, and textiles).

The two papers closest to ours in terms of sectoral disaggregation are Nordas et al. (2006) and Djankov et al. (2010). Both papers use Doing Business data on the time taken for export and import transactions as a measure of trade facilitation performance. Nordas et al. (2006) explicitly consider trade in intermediates, while Djankov et al. (2010) split the data between time-sensitive and time-insensitive products. The value added of our paper in relation to these two previous contributions comes from focusing on the distinction between final products and parts and components, which has not previously been examined in the literature. As we show in the next section, there are good theoretical reasons to believe that trade facilitation should have a particularly strong impact on parts and components trade. Our approach therefore expands on the level of sectoral analysis currently available in the trade facilitation literature.

The paper proceeds as follows. The next section reviews the theoretical and empirical literature on production networks, focusing on the role of trade costs and facilitation. Section 3 presents our dataset,

> 4 A number of papers use
2012). Current State of Statistical Capacity in the OIC Member Countries. February.

- Partnership in Statistics for Development in the 21<sup>st</sup> Century (PARIS21) (2002). _Statistical Capacity Building Indicators Final Report_ . <u>https://www.paris21.org/sites/default/files/scbifinal-en.pdf.</u>

- Sanga, D., Dosso, B., and Gui-Diby, S. (2011). “Tracking Progress towards Statistical Capacity Building Efforts: The African Statistical Development Index”. _International Statistical Review_ , 79(3): 303-329.

- Tapsoba, Sampawende J‐A., Codjo Neree Noumon, and Robert C. York. (2017). "Can Statistical Capacity Building Help Reduce Procyclical Fiscal Policy?" _Journal of International Development,_ 29(4): 407-430.

UNICEF. (2018). _Progress for Every Child in the SDG Era_ . New York: UNICEF.

- United Nations (2016). _Evaluation of the Contribution of the United Nations Development System to Strengthening National Capacities for Statistical Analysis and Data Collection to Support the Achievement of the Millennium Development Goals (MDGs) and other Internationallyagreed Development Goals._ Technical report.

22
28 consideration are plans in Malawi, Mongolia, Rwanda, and Zambia to increase storage capacity (MERA 2010; Dow Jones 2012a; All Africa 2012b; All Africa 2011a).

Minimum stockholding requirements are often not enforced for cost reasons. In theory, a small fee can be levied on each fuel to finance construction of additional storage capacity and its management, but governments are reluctant to increase costs of supply and add to world oil price increases. The government of Togo acknowledges that the country has little storage capacity but does not have the financial means to expand it (Togosite 2011). Uganda’s only reserve storage facilities for gasoline and diesel in Jinja, in need of rehabilitation, have been empty since 2006 (Dow Jones 2011c).

At the opposite end of the spectrum are policies outside the petroleum sector that can amplify price increases. For example, in late 2010 in China, severe diesel shortages forced thousands of filling stations to shut down and others to ration, as firms turned to diesel power generation when power was rationed to meet the energy intensity target in the 11th Five-Year Plan (2006–10). Power tariff subsidies, which lead to financial difficulties for utilities resulting in insufficient operating capacity for generation, transmission, and distribution, have led to similar scenarios.

# **_Promoting price competition_**

Where prices are not controlled or only price ceilings are set, the government can promote price competition by making information available. The price information needs to be broken down by company, and preferably by filling station. In addition, it is important to promulgate and enforce a rule that requires prices to be posted on display boards at readable heights that are clearly visible to drivers.

Some governments post detailed information about fuel prices to help consumers. Some list current prices only, others post recent but not current prices, and a handful lists both current and historical prices. Among the most detailed and timely is the online price database in Chile— mandated by a resolution issued in January 2012—which is
.820|0.858|-0.052|0.744|

Notes: The table reports clusters’ characteristics measured at baseline, by experimental condition. Population numbers come from census data. The normalized difference is the difference between the two means divided by the square root of the sum of the variances of the two variables.

distance from the nearest medical center and caste (Column 3 of Annex Table D2) and provides a convenient mapping into administrative data on malaria incidence, which are disaggregated across urban and rural locations. In India, non-solid and semi-solid dwellings make up approximately 15% in urban areas and around 50% in rural areas (India DHS).<sup>21</sup> To overcome the challenge that Facebook does not offer the option to target ads by dwelling type, we created Lookalike Audiences in Facebook and dynamically increased budget to them in districts where non-solid dwellers were underrepresented.<sup>22</sup> The Lookalike Audience tool allows advertisers to connect with fresh users who mirror their current customers or desired target audience. Drawing from our formative research surveys, we provided Facebook with the “seed audience” of individuals that lived in non-solid dwellings. Leveraging its rich data and algorithms, Facebook then assembles a Lookalike Audience by extrapolating patterns identified within the seed audience.

We used this procedure to ensure that in each district we recruited a sufficient sample size for measuring the effects of the campaign on those most at risk of the disease. The benefits of this stratification can be seen in Annex Figure C3, which shows an improvement in the share of non-solid dwellers per district and a reduction in its variance across districts as a result of the optimization. Table 1 shows that, eventually, the stratified recruitment and cluster-randomization resulted in a sample with two important features: (1) baseline cluster characteristics are balanced across treatment and control districts, a condition for internal validity; (2) the average share of cluster population living in solid houses is around 50%, which allows the
years of repeated cross-sectional Integrated Living Conditions Survey of individuals from 2007 to 2016, where respondents answered a set of questions about local infrastructure quality. The second method uses the Demographic and Health Survey from 2015-2016. Since DHS allows for approximate household location identification, I match the locations with a unique road quality dataset and use topographic control variables. In order to address the problem of endogeneity and reverse causation, the study uses an instrumental variable strategy based on historical military and postal routes in Armenia from a 1903 map, when Armenia was part of the Russian Empire.

The analysis with both datasets and methods shows that road quality is positively associated with non-agricultural employment in rural areas. Households living further from good quality roads are more likely to be employed in agriculture and less likely to be employed in seasonal employment. The DHS analysis shows negative association between distance to good quality roads and employment outcomes. People are 5.7 percentage points less likely to work in the non-agricultural sector and 5.1 percentage points less likely to be engaged in skilled manual employment with 1 log increase in distance (or approximately 2.7 fold increase in distance). Women are particularly affected in the type of pay they receive for work. The results show that 1 log increase in distance decreases the probability of getting cash earnings for work by 9.3 percentage points. These results are particularly interesting in the prism of women’s empowerment, where financial independence is one of the key factors.

The result on seasonal employment is particularly interesting for its unexpected opposite sign. The analysis from both datasets shows a positive association of seasonal employment with better quality roads. The analysis on ILCS shows that people reporting poor road quality leading to towns and markets are 5.2 percentage points less likely to engage in seasonal work. The analysis on DHS shows 5.5 percentage points less likelihood of seasonal employment with one unit increase in log distance from a good quality road (approximately 2.7 fold increase). These results could be explained by the outcome
<!-- Start of picture text --> 100% 100%<br>90% 90%<br>80% 80%<br>70% 70%<br>60% 60%<br>50% 50%<br>40% 40%<br>30% 30%<br>20% 20%<br>10% 10%<br>0% 0%<br>Asia Latin America Sub-Saharan Average Asia Latin America Sub-Saharan Average<br>Africa Africa<br>Rural Urban Male Female Poor Non-poor Educated Non-educated<br><!-- End of picture text --> _Note:_ Individuals who have completed at least primary education are grouped as “educated”; individuals who are in the bottom 40 percent of the national income distribution are classified as “poor.” Individual weights are applied in the calculation.

The demographic profiles of mobile internet users and nonusers are notably different (figure 2). Across the countries covered in the sample, 54 percent of the nonusers are female, and 68 percent of them are living in rural areas, while the majority of mobile internet users are male and urban residents. The average age of mobile internet users is 29.6 while that of the nonusers is 37.1, indicating that the elderly lag behind in adopting new technologies. Mobile internet users tend to be more educated and wealthier than nonusers. The average number of years of formal education (12.0 years) of mobile internet users is almost twice that of the nonusers (6.1 years). Furthermore, 92 percent of mobile internet users have at least completed primary school, while more than half of the nonusers have either no formal education or have not completed their primary education. The monthly income of mobile internet users is $303.4, more than double that of nonusers at $123.6.

# **Figure 2. Demographic profiles of mobile internet users and nonusers**
tax payments made by smaller taxpayers. Collectively, these findings illustrate that there are binding trade-offs that policy makers must directly confront when designing and administering these regimes.

This study raises the question of whether it is worth it for governments in SubSaharan Africa to direct substantial resources towards the taxation of small businesses. There has been an extensive normative discussion in the literature about whether governments should focus on small business taxation, especially given many, if not most, of these taxpayers likely live below the national poverty line (e.g., see Moore (2023)). This study demonstrates that even if governments were determined to tax small businesses, they would most likely not be able to do it in a way that adequately meets their objectives. This is particularly clear when examining the trade-off between having a simple tax regime that is easy to comply with (e.g., a set fee) compared to a more vertically equitable but complex approach (e.g., requiring a percentage of business turnover be paid). Furthermore, improving taxpayer knowledge about the characteristics of STRs is likely to ensure that they are implemented more in line with the country’s tax legislation, but this may not always be in the interest of the revenue authority.

Several areas for future research emerge from this study. Firstly, an analysis of tax administrative data in other Sub-Saharan African countries could be done to examine the _de facto_ implementation of STRs. Secondly, further experimental work could be conducted to thoroughly examine trade-offs along the simplicity–equity margin to help inform optimal tax policy design. Thirdly, stocktakes of countries’ tax legislation could be conducted covering other types of taxes and/or other regions of the world to help shed light on variations in _de jure_ attributes of tax systems.

27
.0|4508.1|11202.3|1|1.5|2.7|6.7|
|1996|1647.7|2464.2|4442.9|11328.5|1|_1.5_|2.7|6.9|
|1997|1811.9|2709.7|4882.1|12692.2|1|1.5|2.7|7.0|

Source: Presidencia de la Republica, Primer Informe de Gobiemo, 1989, and Tercer Informe de Gobiemo, 1997.

The great disparity in per-student spending at different education levels in Mexico is also reflected in Table 4, which only refers to federal expenditures. This Table also shows, however, that the evolution of public spending on education in Mexico has become more egalitarian across different schooling categories over time. In the early 1980s, the amount of federal spending per university student averaged 10 times the amount spent per primary student. This ratio fell to around 7 times in the early 1 990s. Federal spending on the other levels relative to the primary level indicate a similar decline, even though the absolute amounts increased at all levels. In other words, even though the recent pattern of spending on education in Mexico exhibited a highly uneven bias in favor of tertiary education relative to other categories, the pattern of spending in earlier periods exhibited and even greater bias.

# D. **The Rates of Return on Investments** in **Education**

One way to assess the economic merits of the preceding spending patterns, considered as investments in education, is by comparing their relative rates of return. This section compares the rates of return to education as derived from several human capital earnings functions. These were estimated with data from two income-expenditure surveys (ENIGH) carried out by the National Statistical Institute (INEGI) in the third quarters of 1984 and 1994. These two survey years provide an excellent setting for comparisons: first, both years can
**_7_**

cash holdings (a stock), either relative to the money supply (Ml) or relative to GDP. Thele ratios, with the largest values underlined, are shown below for Europe, Japan, and the U.S. for 1993.

**Indicators of cash use, 1993**

||**_Cash/Mi_**|**_Cash/GDP_**|
|---|---|---|
|Europe|.14|.04|
|Japan|**.27**|**.08**|
|U.S.|.11|.02|

Cash holdings in Japan are effectively twice those in Europe or the U.S., suggesting a much greater use of cash for payments. But Europe is far from homogeneous. Within Europe, Switzerland, the Netherlands, and Belgium all have a higher currency/Mi ratio than Japan while Sweden, Norway, Denmark, the U.K., and Finland have a lower ratio than the U.S. This result is evident from Table 1 which 0hows the cash/Mi and cash/GDP ratios for 14 countries during 1993 as well as a decade earlier.

**_Changes in the use of cash over time._** Comparing the level of these ratios between 1983 and 1993, the ratio of cash to Ml fell-sometimes dramatically so-for all but one European country (Italy), rose slightly in Japan, and was constant in the U.S. Similar results were obtained for the ratio of cash to GDP over the same period: this ratio fell for all but one European country (Germany) while both Japan and the U.S. experienced a slight rise. The clear implication from changes in these two ratios is that cash use is falling in Europe.

An alternative way to illustrate the reduction in cash use is to compare the value of cash holdings per person (in constant U.S.
# **5 Concluding Remarks**

In this paper, we study the impact of labor provisions in trade agreements aimed at eliminating the use of child labor. Such provisions have become more common over time as trade agreements have become more expansive in scope and increasingly cover non-trade areas. Using a large set of survey data from across 101 developing countries, we employ a variety of DiD and triple DiD regressions to identify the effect of RTAs without a child-labor provisions on child labor outcomes, as well as the differential effect of an agreement that does have such a provision.

We find evidence that a trade agreement with no child-labor provision reduces the fraction of 14-17-year-olds in the labor force by a statistically and economically significant amount with corresponding increases in secondary school enrollment. We find similar effects for children under the age of 14 but these estimates are imprecise and not statistically significant. The pattern is consistent with an interpretation that a developing economy joining a trade agreement opens up possibilities for low-skill export employment and is consistent with the empirical findings of Edmonds and Pavcnik (2005) and Edmonds and Pavcnik (2006) that opening trade can reduce child labor in developing economies.

On the other hand, we find that the inclusion of child labor prohibitions in RTAs perversely _increases_ child labor—the opposite of their intended effect. We find statistically and economically significant increases in the employment of 14-17 year old children and statistically imprecise but economically significant increases in under-14 labor as well. We find corresponding drops in both primary and secondary school enrollment rates following entry into force of RTAs with child labor prohibitions.

Our results are strikingly similar to those predicted in Basu (2005) and found empirically in Bharadwaj _et al._ (2020)—a case study of the 1986 ban in India. As in these works and in our theoretical model, if the ban is enforced through a fine imposed on employers, it will tend to depress child wages, inducing the household to increase total labor supply in order to make up the lost income—including the household child
, Sulaiman, M., 2020. Women’s empowerment in action: Evidence from a randomized control trial in Africa. _American Economic Journal: Applied Economics_ , _12_ (1), 210–259.

- Banerjee, A.V.B., Bhattacharjee, S., Chattopadhyay, R., Ganimian, A.J., Duflo, E., Spelke, E.S., 2022. Street smart or school smart? The arithmetic skills of working children in two Indian cities.

- Barrera-Osorio, F., de Barros, A., Filmer, D.P., 2018. Long-term impacts of alternative approaches to increase schooling: Experimental evidence from a scholarship program in Cambodia (Working Paper No. WPS8566), _Policy Research Working Paper. The World Bank, Washington, D.C._

- Bau, N., Das, J., Yi Chang, A., 2021. New evidence on learning trajectories in a low-income setting. _International Journal of Educational Development_ , _84_ , 102430.

- Beegle, K., De Weerdt, J., Dercon, S., 2011. Migration and economic mobility in Tanzania: Evidence from a tracking survey. _Review of Economics and Statistics_ , _93_ (3), 1010-1033.

- Boon-Falleur, M., Bouguen, A., Charpentier, A., Algan, Y., Huillery, É., Chevallier, C., 2022. Simple questionnaires outperform behavioral tasks to measure socioemotional skills in students. _Scientific reports_ , _12_ (1), 1-11.

- Bowles, S., Gintis, H., 1976. Schooling in capitalist America: Educational reform and the contradictions of economic life. _Basic Books, New York_ .

- Brunello, G., Schlotter, M., 2011. Non cognitive skills and personality traits: Labour market relevance and their development in education and training systems (Working paper No. 5743), _IZA Discussion Paper. Institute of Labor Economics (IZA), Bonn