rafmacalaba/data-use-mentions-extended huggingface dataset:
derived and modeled from CDRs at subnational and annual scales. As for social networks, Spyratos et al. (2019) used anonymized and publicly available data provided by Facebook’s advertising platform to estimate the number of Facebook Network (FN) “migrants” in 119 countries of residence and concluded that these estimates could be used for trend analysis and early-warning purposes. Specifically concerning climate change, some have highlighted that in combination with field-level data derived from household surveys and key-informant networks, big data could be used to detect how sudden-onset natural disasters and progressive environmental change impact migration patterns (Franklinos et al., 2020). Along these lines, for example, Lu et al. (2016) used anonymized CDR from a mobile network provider (Grameenphone) to retrieve the geographical position and movements of users, so as to be able to examine the human mobility effects of the 2013 Mahasen cyclone in Bangladesh. Finally, for an interesting comparison between mobile phone and census data, see Wesolowski et al. (2013) and Kirchberger (2022) for a 21
waters. In 2012, 14,765 large ships passed through the Suez canal.<sup>10</sup> A one percentage point increase in private maritime security hires (148 hires) leads to 32 fewer attacks (35.3 percent of the 91 attacks in 2012), which in turn implies that 148 _/_ 32 _≈_ 4 _._ 6 private teams can reduce the number of attacks by 1 through the mechanisms outlined in our model. On a side note, the cost of 4.6 security teams, as estimated by (Oceans Beyond Piracy 2015), is between $92,000 and $220,800.

Even though private maritime security reduces the number of pirate attacks, it also results in a significant displacement externality towards smaller ships. Figure 10 highlights this effect by showing the number of attacks and hijacks to ships below (red dashed) and above (black dash-dotted line) the median size. Around the baseline estimate, a onepercentage-point increase in protection lowers the number of attacks (hijacks) on large vessels by 42.9 (43.8) percent, and at the same time, increases the number of attacks (hi-

> 10We classify the following vessel types in the published traffic data as “large”: tankers, LNG ships, bulk carriers, combined carriers, container ships, and car carriers.

34
29 international organizations consisted of technical support and a modest degree of financial resources, relative to basic education. Civil society mobilization has continued to be low, in most countries, and political transitions have not elevated ECE as an issue.

For several factors, COVID-19 worsened conditions in a way which particularly disfavored ECE. In terms of both Ideas and Issue Characteristics, distance-learning methodologies were seen as particularly ill-suited to ECE-age children. These perceptions were based on both their shorter attention spans and limited ability to use the technology, and their developmental needs which favor more social and play-based learning environments. At the same time, the perception of young children’s lower capacity for compliance with masking and social distancing requirements reduced prioritization of ECE in the return to school. In all countries, ECE suffered from competition for government attention with the levels of education preparing for high-stakes examinations.

The sheer urgency of the crisis also weakened several factors which previously had helped prioritize ECE. The promotion of global norms around ECE took many years of painstaking research and dialogue, which simply was not possible on the timeline of pandemic response. Previous household surveys on access to technology and, in some cases, rapid phone surveys provided indicators on the severity of the issue, but these were quite limited compared to the availability and richness of data in normal times. The COVID pandemic crowded out potential focusing events around ECE, as events were cancelled or repurposed to focus on the crisis itself. The fragmentation of policy communities increased as many ECE donors and civil society organizations responded to the pandemic autonomously rather than as a cohesive force. There was also little time for policy entrepreneurs to emerge.

To the extent that there were mitigating factors supporting prioritization of ECE, these were more country-specific. Liberia’s response to COVID-19 clearly benefited from its relatively recent
growing sorghum and groundnuts. Table 1a shows that for the entire sample (N = 2629 households), there are, on average, 6.6 members in each household, of whom 1.6 are children under 84 months and 1.9 are children of school going age (7 to 15). Mean annual household per capita expenditures (including own consumption) were 99,951 FCFA (approximately $220 USD using the January 2010 exchange rate of $1 USD = 455 FCFA). Of the children ages 7 to 15, 65.7 percent are reported by their parents to be enrolled in school, but when enrollment is measured using school administrative rosters, the enrollment rate is only 49.2 percent, suggesting survey respondents may overstate school participation as Baird and Özler (2012) document.<sup>11</sup> School attendance conditional on enrollment as measured from school rosters is high at 98.1 percent, suggesting that, once enrolled, children are very likely to attend classes. The attendance rates are consistent with other research in Africa using administrative school data (Miguel and Kremer, 2004 in Kenya; Benhassine et al., 2012 in Morocco; Kazianga, de Walque, and Alderman, 2012 in another region of Burkina Faso). Furthermore, at least for Burkina Faso where enrollment is low, they are suggestive of an environment where parents strategically choose which children they register and then make sure the children attend regularly. We also report attendance unconditional on enrollment, a broader measure of school participation that incorporates enrollment and attendance effects. On an average school day, 46.2 percent of children ages 7 to 15 are in class. Mean education expenses per child are $9.66 per year.

> 11 To obtain the school roster information about enrollment and attendance, survey enumerators took the list of children reported to be enrolled by their parents and searched for them in the school’s administrative rosters. After matching the child’s name, they then recorded the
fifth-graders in the affected schools did not achieve basic levels of learning in math and reading, respectively.<sup>19</sup> School shutdowns can increase learning gaps between low and top performers if their impacts are more detrimental for low performers.<sup>20</sup> To investigate whether the impacts of the school shutdowns are more pronounced at the lower tail of the learning distribution, we estimate quantile treatment effects using the Athey and Imbens (2006) changes-in-changes (CiC) estimator.<sup>21</sup> Figure 2 shows that the negative effects of the school’s shutdown were stronger in math, and potentially stronger in the lower tail of the test score distribution, as suggested by the inter-quantile difference between the lower and top deciles estimates in math.

Figure 2: Distributional impacts of the school shutdowns, fifth-grade (2007-2009) <!-- Start of picture text --> Extended winter break 95% CI Extended winter break 95% CI<br>2.0 2.0<br>0.0<br>0.0<br>-2.0<br>-2.0<br>-4.0<br>-4.0<br>-6.0<br>-6.0<br>-8.0<br>-10.0 -8.0<br>10 20 30 40 50 60 70 80 90 10 20 30 40 50 60 70 80 90<br>Percentiles of test score distribution Percentiles of test score distribution<br>(a) Math, TD (b) Reading, TD<br>, SAEB scale γ , SAEB scale γ<br><!-- End of picture text --> Note: The authors’ estimate is based on data from _Prova Brasil_ , Census of Education, and IBGE. 95% Confidence Interval. Math performance on a scale from 0 to 350 (SAEB scale). reading
# EDUCATION **AND** EARNINGS INEQUALITY IN MEXICO

## Ulrich Lachler*

* Principal Economist, Mexico Country Department, World Bank.

This paper was prepared with research assistance from Gladys Lopez Acevedo, who processed the ENIGH data discussed therein. Many helpful comments were received from Barry Bosworth, Nancy Gillespie, George Psacharopoulos, RosaMaria Rubalcava, Fernando Cortes, Enrique Hernandez Laos, and Eduardo Velez.
Policy Research Working Paper 7557

# **Abstract**

This paper uses a set of national household surveys to study the regional Sub-Saharan Africa distribution of consumption expenditure among individuals during 1993 to 2008. The analysis puts the disparities in living standards that exist among persons in Africa into context with the disparities that exist within and between African countries. Regional interpersonal inequality has increased (from a Gini index of 52 percent in 1993 to 56 percent in 2008), driven by increasing disparities in living standards across countries, while there has been no systematic increase in within-country inequality. For the African distribution as a whole, growth of consumption expenditure (from household surveys) has been low (around 1 percent per year). This growth has been uneven and as a result the richest 5 percent of Africans received around 40 percent of the total gains, while the bottom third stagnated.

This paper is a product of the Office of the Chief Economist, Africa Region and the Poverty and Equity Global Practice Group. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http:// econ.worldbank.org. The authors may be contacted at ljirasavetakul@imf.org and clakner@worldbank.org.

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
Where does this additional water for irrigation come from? The majority of irrigated land prior to the implementation of MNREGA was irrigated with water from wells. Our hypothesis indicates that farmers should have further increased their irrigated area by using water from these groundwater wells but not necessarily from other sources of irrigation. This is because, if MNREGA improved access to groundwater by facilitating recharge, it should have lowered access costs for these wells and consequently increased the area irrigated by these wells. If, by contrast, the increase in irrigated area was due to MNREGA’s improvements in other irrigation infrastructure, we should observe increases in area irrigated by non-well sources.

We can test this implication of our hypothesis directly using data from ICRISAT on the area irrigated. In Table 4 we show that farmers increase the area irrigated with water from wells by roughly 17% after the implementation of MNREGA. Like with our other outcomes, the event study (Figure 5) shows no meaningful pre-trends prior to MNREGA implementation. When we examine the change in area irrigated by canals, tanks, or “other sources” we see no significant (economic or statistical) change in area irrigated from any of these sources.<sup>20</sup> The event study for area irrigated by canals, estimated using the method in Borusyak et al. (2024), may suggest some increase in area irrigated by water from canals (Figure 5B). However, our difference-in-difference estimates (Table 4, column 2) indicate no significant change in area irrigated by canals. The point estimate suggests a small, 3% increase with wide (-9% to 16%) confidence intervals. This is confirmed by the event studies estimated using the method in Callaway and Sant’Anna (2021) which do not suggest a meaningful increase in area irrigated by canals in the post period (Figure A6).

Collectively, our results on soil moisture, irrigated crop area, and area irrigated by source all suggest that after the implementation of MNREGA farmers increase their
An increasingly sophisticated empirical literature attempts to directly estimate the knowledge production function using patents as a proxy for new knowledge. Jaffe and Trajtenberg (2002) and Griliches (1990) offer as stylized facts that in cross section patents are probably roughly proportional to R&D implying an elasticity of unity, while the “within” panel dimension suggests strongly decreasing returns to scale.<sup>5</sup> The few studies in the second category (Hausman, Hall and Griliches 1984,1986; Blundell, Griffith and Windmeijer 2002), along with Blundell, Griffith and Van Reenen (1995) that looks at the impact of market structure on innovation, have contributed important advances in the theory of count data estimators in a panel context. The latter two focus particularly on modeling dynamics and controlling for the unobserved heterogeneity that renders cross sectional estimates suspect. In this sense, they parallel closely the recent literature on dynamic panel modeling with continuous dependent variables (Arellano and Bond 1991, Blundell and Bond 1998). Both issues are found to be of central importance in modeling the innovation process and generating consistent parameter estimates.

All the panel studies confirm the stylized fact of decreasing returns to scale. Hausman, Hall and Griliches’s (1984) non-dynamic estimates of the elasticity of patents with respect to R&D are in the range of 0.3-0.6, depending on the technique employed. Hall, Griliches and Hausman’s (1986) estimates hover around .35 and are similar to those estimated in a dynamic context by Blundell, Griffith and Windmeijer (2002) of around 0.5. Using industry level panel data Kortum and Lerner (2000) find an elasticity of .48.52. There thus seems to be support in the micro level within estimates for the more pessimistic view of increasing difficulty and congestion.

Nevertheless, the firm level estimates, and to a lesser degree those at the industry level, may miss the spillover effects that one firm’s R&D may contribute to another
||Table 5 – continued||
|---|---|---|
|country<br>Coefcient<br>Rank<br>|Correlation|Rank|
|Other countries data from Hertz et al. (2007).|||
|Estimates for Sub-Saharan African countries are|World Bank calculations.||

# **5.4 Cohort analysis by gender**

In this section, we analyze the trends in intergenerational educational persistence across five-year birth cohorts by gender.<sup>12</sup> Table 6 reports estimates of intergenerational elasticity and the correlation coefficient among daughters and sons separately in each country. As we observed above, there is an increase in intergenerational mobility across birth cohorts. Although the general trend in intergenerational mobility is similar across cohorts, the pace of change varies along gender. In all countries, the pattern of intergenerational educational mobility is different among sons and daughters in the same birth cohorts. Both measures of intergenerational persistence are higher among daughters than sons except in the Comoros and Madagascar. This is especially true among children born after the 1960s. The results suggest that daughters education is more dependent on parental education relative to sons. The higher intergenerational educational persistence among daughters compared with sons is consistent with previous findings in both developing and developed economies. For instance, Ranasinghe (2015) and Emran and Shilpi (2015) report higher educational persistence among women compared with men in Australia and India, respectively. Emran and Shilpi (2015) also document lower occupational mobility from agriculture to nonfarm activities among women in Vietnam and Nepal.

> 12Our analysis across gender is based on intergenerational elasticity that is estimated separately AMONG daughter and son subsample, showing the cohort trend within each gender.

20
contexts in which labor market transitions occur, the literature examining the actual transitions is considerably sparser and tends to focus on specific groups or specific stages of the life cycle (an exception is the earlier contribution of Gatti et al, 2012). Yassine (2015) takes an aggregate view of labor market transitions in Egypt, computing flow rates that characterize the level of dynamism in the labor market, primarily with the 2012 round of the ELMPS. The paper also provides an excellent vantage point to view the extent of rigidity in Egypt’s labor market relying on descriptive survival analyses over how long individuals would stay in one job. Meanwhile, Amer (2015) studies labor market insertion, focusing in particular on youth entering the labor market, and the time needed for insertion. Therefore, by construction Amer (2015) only studies transitions to the first job. The paper affirms Yassine’s (2015) finding on rigidity and adds further insights from a gender perspective, highlighting that women who obtain a formal job upon entry into the labor market end up staying longer in the labor market as opposed to women who obtain other types of employment.

Building on the existing rich compendium of notable work examining the employment profile in Egypt and labor market transitions for specific groups, our paper contributes to the literature in at least two ways. First, our paper provides a detailed discussion of Egypt’s labor market transition dynamics post-Arab Spring, focusing on the two most recent rounds of the Egypt Labor Market Panel Survey. Thanks to the panel structure of the data, we examine labor market transitions in Egypt between 2012 and 2018, tracking individual employment status and job trajectories between the two waves. While important work has been done to characterize the 2
EAST AFRICA’S INFRASTRUCTURE: A REGIONAL PERSPECTIVE

**Figure 2.8. Ratio of current demand to reported capacity**

<!-- Start of picture text --> a. General cargo b. Container traffic<br>150% 150%<br>125% 125%<br>100% 100%<br>75% 75%<br>50% 50%<br>25% 25%<br>0% 0%<br>Source: AICD ports database, 2008.<br>Ratio of current demand to reported capacity Ratio of current demand to reported capacity<br>Cotonou Cape Town Luanda Port Sudan Douala Dar es Salaam Mombasa Cape Town Douala Cotonou Mombasa Luanda Tema Dar es Salaam Durban<br><!-- End of picture text --> East African ports do not compare favorably with those of southern Africa, and even less so with global best practice, in terms of performance and charges (table 2.6). Compared with global best practice, Africa’s ports are expensive to use and subject to extensive delays, though those of southern Africa tend to perform somewhat better than those in other African regions across a range of parameters. The services provided by East African ports cost nearly twice as much as those in other global ports. Crane productivity in East African ports, in terms of containers or weight, is about half the international benchmark. Global best practice for truck cycle time is 1 hour, but trucks spend between 4 and 24 hours in East African ports. The international standard for port dwell time is seven days or less, but in East Africa, containers routinely spend more than a week in the terminal. The result is terminal congestion and port inefficiency. Incentives for speedier pickups might include a daily storage charge after a given number of free days and specific rules to prevent the dumping of empty containers at the terminal. Unlike in East Africa, most terminals in southern Africa offer a given number
**The control group** did not receive any intervention under this study, including information and pharmacy vouchers. However, the ongoing mass media campaign funded through the MOH provided information on the prevalence of diabetes and hypertension and encouraged adults to screen for free for hypertension and diabetes in the local primary health care clinic. These campaigns involved broadcasts on public and private television stations, billboards on major roads, posters in health facilities and post offices, and text messages from the MOH.

# **_Experimental Methods_**

# A. **_<u>Study sample and randomization</u>_**

The experimental sample drew on the administrative records of the PHC clinics in the public sector Armenia. Health clinic administrative records in Armenia are relatively complete and of high quality, as the e-health system is nationwide in scope and is updated following the patients’ visits. The health sector is dominated by public health facilities, particularly outside Yerevan. In addition, 100 percent of the rural population and 85 percent of the urban population is registered for care at the PHC level. Hence, the e-health database is likely to have information on most of the diabetes and hypertension screenings conducted in Armenia, particularly at the PHC level.

After selecting public health facilities in 4 provinces (Ararat, Armavir, Kotayk and Lori) chosen on the basis of their infrastructure and NCD prevalence and local culture affecting behavior and screening rates and which were sufficient to reach the desired sample size of 2,000 individuals, the experimental sample was randomly drawn from the patient records, proportionally to the size of the catchment population of the health facilities. A total of 6,934 individuals were selected from the registered population of the selected PHC facilities. The inclusion criteria of subjects selected from the e-health database were individuals between the age of 35 and 68 years old, and who had not been screened for diabetes or hypertension in the last 12 months. From this sampling list, individuals were randomly assigned to the 5 study arms of the study
POLICY RESEARCH WORKING PAPER 1711

# Summary findings

C6te d'Ivoire is one of the few cotntries in Sub-Saharan Africa that conducted household surveys between I _985_ and 1995. These surveys make it possible to trace changes in urban and rural poverty and changes in poverty arnong different socioeconomic groups.

During the decade surveyed, the country experienced a major recession. Economic recovery began only with the devaluation of the CFA franc in January 1994. Poverty increased substantially during the recession and did not diminish in the year after devaluation, in part because rnuch of the increase in export crop prices, especially for cocoa, was taxed away.

Moreover, the effects of the recession and devaluation were not uniform. Between 1988 and 1993, urban poverty increased faster than rural poverty did, though mean expenditures in urban areas remained substantially ,ibove mean expenditures in rural areas. And food crop farmers apparently suffered more than export crop farmers. These trends persisted after devaluation.

But exploring poverty trends across regions and socioeconomic groups raises questions about the patterns of change and the reliability of the data and the methods used to derive poverty estimates. Secondary data cast some doubt on certain survey findings, suggesting that they may be more an artifact of the survey data than a reflection of real economic trends.

These problems are not unique to C6te d'Ivoire. Results from surveys in Uganda and to a lesser extent Ghana have also raised issues of comparability.

The ability to draw reliable conclusions from time series data is crucial for our understanding of how policy reform affects poverty. Far more attention must be paid to comparison issues in designing surveys and analyzing data. Attention must also be paid to developing better regional and temporal price indices, if reliable time series data are to be generated for Sub-Saharan Africa.

- - This paper a product of the Macroeconomics and Growth Division, Policy Research Department is part of a larger effort in the department to understand the link between economic policy change and poverty. Copies of the paper are available free from the World Bank, 1818 H Street NW