rafmacalaba/datause-encoder-data huggingface dataset:
their mothers in Brazzaville, Congo, following the 1994 devaluation of the CFA franc _Bulletin_ (Vol. 78, pp. 108-118): World Health Organization.

Nguyen, B. T., Albrecht, J. W., Vroman, S. B., & Westbrook, M. D. (2007). A quantile

- regression decomposition of urban-rural inequality in Vietnam. _Journal of Development Economics, 83_ (2), 466-490. doi: DOI: 10.1016/j.jdeveco.2006.04.006

- Patrinos, H. A., & Sakellariou, C. (2006). Economic volatility and returns to education in Venezuela: 1992–2002. _Applied Economics, 38_ (17), 1991 - 2005.

- Ruel, M. T. (2003). Operationalizing Dietary Diversity: A Review of Measurement Issues and Research Priorities. _The Journal of Nutrition, 133_ (11), 3911S-3926S.

- Ruel, M. T., Garrett, J. L., Hawkes, C., & Cohen, M. J. (2010). The Food, Fuel, and Financial Crises Affect the Urban and Rural Poor Disproportionately: A Review of the Evidence. _The Journal of Nutrition, 140_ (1), 170S-176S. doi: 10.3945/jn.109.110791

- Stifel, D. C., & Averett, S. L. (2009). Childhood overweight in the United States: A quantile regression approach. _Economics & Human Biology, 7_ (3), 387-397. doi: DOI: 10.1016/j.ehb.2009.05.005

- UNICEF. (2009). Tracking Progress on Child and Maternal Nutrition: a survival and development priority

- Weismann, D., Basssett, L., Benson, T., & Hoddinott, J. (2009). Validation of the World Food Programme‘s Food Consumption Score and Alternative Indicators of Household Food Security _Discussion Paper_ IFPRI.

24
<!-- Start of picture text --> Figure 4: Impulse Responses<br>Entry Exit<br>8 8<br>7 7<br>6 6<br>5 5<br>4 Entry US 4 Exit US<br>Entry Brazil Exit Brazil<br>3 3<br>Entry Egypt Exit Egypt<br>2 2<br>1 1<br>0 0<br>1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22<br>-1 -1<br>Time (Years) Time (Years)<br>Capital Labor<br>4 2.5<br>3.5<br>2<br>3<br>1.5<br>2.5<br>2 Labor US<br>K US 1<br>Labor Brazil<br>K Brazil<br>1.5 Labor Egypt<br>K Egypt<br>0.5<br>1<br>0.5 0<br>1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22<br>0<br>1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 -0.5<br>Time (Years)<br>-0.5<br>Time (Years)<br>TFP GDP<br>9 10<br>8 9<br>8<br>7<br>7<br>6<br>6<br>5<br>TFP US 5 GDP US<br>4 TFP Brazil GDP Brazil<br>4<br>TFP Egypt GDP Egypt<br>3<br>3<br>2<br>2<br>1 1<br>0 0<br>1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22<br>Time (Years) Time (Years)<br>Percentage-point deviation w/r to initial ratio to GDP Percentage-point deviation w/r to initial ratio to GDP<br>Percentage-point w/r to initial ss growth<br>Percentage-point deviation w/r to initial ss growth<br>Percentage-point deviation w/r to initial ss growth Percentage-point deviation w/r to initial ss growth<br><!-- End of picture text --> 26
# ABSTRACT

Emerging trends in education<sup>show that the private sector is playing an increasingly important role in</sup> financing and providing educational<sup>services in many countries. Private sector development in</sup> education has not arisen primarily<sup>through public policy design though it has, of course, been affected</sup> by the designs and limitations of<sup>public policy. This paper traces trends in private sector development</sup> in World Bank education projects.<sup>In this paper, 11 out of a total of 70 World Bank education projects</sup> during the period 1995-97 have<sup>been studied to trace the trends. The 11 country examples reveal that</sup> the Bank's interest in private sector<sup>development is fundamentally in capacity-oriented privatization to</sup> address excess demand for education.<sup>World Bank lending for private sector development in education</sup> does not vary widely from the<sup>Bank's overall strategy for education lending: promoting access with</sup> equity, focusing on efficiency<sup>in resource allocation, promoting quality and supporting capacity</sup> building. The Bank's focus on<sup>private sector development in education emphasizes increasing private</sup> sector access to public funding and<sup>opportunities for capacity-building, especially teacher training for</sup> primary and secondary levels, and<sup>overall institutional capacity building at tertiary and vocational</sup> levels. The underlying principle being<sup>that strengthening the private sector's role over time at the non-</sup> compulsory levels of education will<sup>release public resources to be utilized at the compulsory, primary</sup> level. The 11 country examples help<sup>to demonstrate that the role of the private sector in education is</sup> emerging as a large force that governments,<sup>donors, and other technical assistance agencies cannot</sup> ignore.

iii
## Figure 3

# **CHILEAN** ENERGY SECTOR: THE INITIAL SITUATION

**ENERGY** CONSUMPTION

<!-- Start of picture text --> 2190<br>170<br>110<br>150<br>90<br>50 -<br>1988 1989 1990 1991 1992 1993 1994 1995 1996<br><!-- End of picture text --> SOURCE: NATIONAL ENERGY COMMISION 16
established, their distinct feature being their highly professional culture, aiming at a clearly unbiased conduct. Systems in other parts of the world were studied and sound methodologies were applied. The future of the trade liberalization process depended partly on how successful the government could be in convincing domestic producers of the fact that serious institutions would defend them against unfair international competitors. However, local manufacturers also had to understand that the newly created institutions were not meant to provide unjustified protection.

The strengthening of institutions as well as of the legal structure of the contingent protection system took place at the time the NAFTA was being negotiated. It is important to underscore that most procedures and methods adopted by Mexican institutions resulted from the public officials’ interest, as mentioned before, in creating sound and reliable structures for administering these protection policies. The pressure exerted by Mexico’s trade partners was not the key reason to account for the legal and institutional reforms introduced in that period.

**Table 11 – Number of Tariff Items Subject to Antidumping Duties in 2002**

|**Investigated countries**|**Number of tariff items**<br>**investigated**|**Percentage of total tariff**<br>**items**|
|---|---|---|
|China|1,317|96.27%|
|UnitedStates|19|1.39%|
|Russia|10|0.73%|
|Korea|9|0.66%|
|Brazil|7|0.51%|
|Ukraine|7|0.51%|
|Denmark|5|0.37%|
|Taiwan|5|0.37%|
|France|4|0.29%|
|10countries|3|2.19%|
|3countries|2|0.44%|
|4 countries|1|0.29%|
|Total tariff items subject to duties|1,368|Not applicable*|

Source: Based on data from the World Trade Atlas and the 2002 Antidumping Agreement.

The figures in Tables 11 and 12 serve to assess the actual impact of contingent protection mechanisms on current trade flows in Mexico. Most products affected by antidumping duties come from China; 96% of tariff items currently subject to antidumping duties are of Chinese origin (see Table 11 below). Nevertheless, when assessing the global impact of such duties on Mexican imports, it is worth noting that Mexican authorities have succeeded in not using these 42
# **Figure 11**

<!-- Start of picture text --> Average price of one pure gram of powder cocaine in the US<br> (in 2002 US dollars / gram)<br>700<br>600<br>500<br>400<br>300<br>200<br>100<br>0<br>< 2 grams 2 to 10 grams 10 to 50 grams > 50 grams<br>1981 1983 1985 1987 1989 1991 1993 1995 1997 1999 2001 2003*<br>US$<br><!-- End of picture text -->

- <mark>Based on information from only the first two quarter of this year.</mark> Source: OND <mark>CP</mark>

# **Figure 12**

<!-- Start of picture text --> Price of cocaine in US and Europe at street purity<br>(US$ / gram )<br>300<br>250<br>200<br>150<br>100<br>50<br>0<br>Europe retail Europe wholesale<br>US retail US wholesale<br>1990 1991 1992 1993 1994 1995 1996 1997 1998 19992000* 2001 2002 2003 2004 2005<br><!-- End of picture text --> <mark>Source: UNODC</mark> 57
interactions between the month of birth and the assessed birth weight (<sup>**_γ_**</sup> **_k_**<sup>’s) in (6) ,</sup> rejects the null hypothesis that the survival probabilities of weak and robust children, born in a certain month of the year are the same.

The probit estimations of (6) show that children of a higher birth order, born in poorer households or with younger mothers, and children born small (weak) are more likely to die in the first year after birth<sup>14</sup> . The sample for this estimation includes all children born in the family. Table 6 shows that while children born in certain months of the year, whose weight at birth was assessed as small, were less likely to live past the age of 12 months, the pattern of survival is inconsistent with the observed monthly variations in children’s health outcomes. For example, in the 1992 sample, boys that were weak at birth were less likely to survive if they were born in April, May, July, and October. According to the ‘selective survival’ hypothesis, this would result in observations of better health outcomes for children born during these months, which is not the case. The probability to survive for weak children appears to be unaffected by their month of birth for the sample of girls in 1992 and the boys sample from 1998.

Based on this evidence, our results do not support the ‘selective survival’ hypothesis.

# _The ‘unplanned pregnancy’ hypothesis_

Assume that parents _believe_ that certain months are ‘bad’ for their children to be born in. Then, in order to improve their children’s health outcomes, parents would plan their pregnancies to give birth during the ‘good’ months. Under this assumption, children born during ‘bad’ months would more likely be a result of unplanned pregnancies and thus have disadvantaged health status (Kost _et al.,_ 1998)<sup>15</sup> . If this hypothesis is true, the observed variation in children’s anthropometrics across the months of the year could be explained by the higher proportion of unplanned births during the monsoon season. The

> **14** To make the categories of the weight-at-birth question consistent across waves of the NFHS surveys, we collapsed into one category the two lowest categories in the 1998 sample, and the two highest and two lowest categories in the 2005 sample.

> **15** A paper by Do and Phung (2008) shows that the difference in outcomes between children born in the ‘good’ and ‘bad’ years according to the Chinese horoscope can be explained by the fact that children born in ‘bad’ years are more likely to be unwanted, that is, to be the result of unplanned pregnancies.

16
<!-- Start of picture text --> c(tt—s) = Po + BilnUndex,,-5) + Baln(rtfpna)et—-5 + Oc + 6 + Ect<br>c,(t,t—5)<br>c,t-5<br>cts: TFP level (2011 = 1)<br>Cc<br>t<br>ct<br><!-- End of picture text -->
# **Table 1: Factor Endowment, Income Shares, Factor Intensity, and Trade Dependence in APEC Model Regions**

|USA|Japan|China|ASEAN4|Asian NIEs|<br>EU|
|---|---|---|---|---|---|
|_GDP and Trade Flows (billion US$):_||||||
|Exports<br>576.4|407.3|141.8|137.4|255.7|731.8|
|Imports<br>618.9|318.4|1S7.3|127.0|236.6|770.4|
|GDP<br>5899.1|3756.2|520.9|361.7|560.6|6691.4|
|_Trade Dependence (percenrt):_||||||
|Export/GDP<br>9.8|10.8|27.2|38.0|45.6|10.9|
|Import/GDP<br>10.5|8.5|30.2|35.1|42.2|11.5|
|_Share in World Factor Endownent (p_|_ercent):_|||||
|Land<br>13.0|0.3|6.7|3.9|0.2|5.7|
|Total labor<br>5.1|2.6|28.8|5.6|1.2|6.4|
|Capital<br>23.6|17.8|2.0|1.2|1.8|30.1|
|Agri. labor<br>0.2|0.3|41.4|6.1|0.5|0.8|
|_Factor Share in APEC Region Value_|_Added (perc_|_ent):_||||
|Land<br>0.3|0.9|8.3|5.3|3.7|0.4|
|Labor<br>64.7|58.8|53.1|29.3|53.0|65.6|
|Capital<br>35.0|40.3|38.5|65.4|43.3|34.0|
|_Labor Cost (thousand $):_||||||
|Average wage<br>27.8|31.2|0.3|0.5|3.8|27.0|
|Average agri. wage<br>14.7|17.8|0.2|0.2|3.8|19.5|
|Average non-agri. wage<br>28.1|32.0|0.6|0.7|3.8|27.4|
|_Capital Return (percent):_||||||
|Average capital rental<br>11.8|11.2|11.4|24.9|17.3|10.6|
|_Factor Proportions:_||||||
|Agri.labor/totallabor (percent)<br>2.1|5.8|66.6|39.1|8.2|5.5|
|Capital/labor ratio ($000/worker) 127.7|190.6|2.0|4.7|18.1|132.0|
|Rental/wage ratio (percent/$000)<br>0.4|0.4|36.4|47.7|4.5|0.4|

Source: APEC model database ASEAN4 and China, as low-income developing countries, are poorly endowed with capital relative to labor. They have the lowest capital-labor ratios, the largest share of agriculture labor in the total labor force (half of their labor force is in agriculture), and the highest rental-wage ratio. The reverse is true for Japan, the European Union, and the United States. The Asian NIEs fall somewhere between the advanced industrial countries and the poorer Asian developing countries. Their agricultural labor share is larger than that of the industrial economies, but is much smaller than that in China and ASEAN4.

6 _Lewis, Robinson, and Wang_
had a small contribution to the decline in inequality.

The results in table 2, panel b, suggest that the changes in the skill and gender composition in the sector-occupation-formality status cells did not play a large role in the observed changes in inequality between 2002 and 2015. This is somewhat puzzling, because in a period of rapid formalization, those who exit informality and enter the formal sector are likely to be very different from those who do not change formal/informal status (McCaig and Pavcnik 2015). To provide a better understanding of who became formal, this paper analyzes this issue in more detail for Argentina, Brazil, and Mexico, whose labor force surveys contain a rotating panel that tracks individuals over a period of up to 12 months. Using these rotating panels, this paper builds annual transitions from informality and self-employment to the formal sector during the 2000s (see supplementary online appendix S1.2 for details on the construction of the data and years covered) and examined differences in workers’ observable characteristics. As documented by McCaig and Pavcnik (2015) for Vietnam, workers who switch to the formal sector from informal employment or self-employment are more likely to be male, younger, and more educated than stayers (supplementary online appendix S4, table S4.1). In other words, they tend to have observable characteristics that are more similar to those observed among workers who are already formal.

What are the implications of workers’ transitions for inequality? To shed some light on this question, this paper builds on the work of Maurizio (2015) and compute the average yearly transitions to the formal sector from informal wage employment and self-employment, by wage quartile of the origin and destination sectors (table 4). The first interesting fact this paper notes is that the majority of workers who formalized during the 2000s were previously informal employees, rather than out of labor force, unemployed or self-employed. Among those who became formal, 77 percent were previously informal employees in Argentina, 66 percent in Brazil, and 58 percent in Mexico. Considering the distribution of wages at the origin, the informal employees who became formal are concentrated in the highest quartiles of their original wage distribution in the three countries, possibly contributing to the fall in wage inequality among informal employees. However, the observed transitions to formality among lower-wage informal employees are nonnegligible (around 40 percent of all those who moved were below the median informal employee wage). Considering the distribution of wages in the destination sector, the majority of informal employees who formalized in Argentina and Brazil ended up below the median wage of the formal sector, with a high concentration in the first quartile, possibly contributing to a widening of the wage distribution of formal employees. Only 8 (11) percent of those who transitioned to the formal sector from informal employment ended up in the top quartile of the formal wage distribution in Argentina (Brazil). By con21
# **8. Conclusion**

This paper analyzes the reopening process of the countries in Europe and Central Asia after the first wave of the pandemic and provides evidence on the effects of different reopening trajectories, the speed, and sequencing of reopening, on economic recovery. We use high-frequency data on electricity consumption during the reopening period as a proxy indicator for the levels of economic activity.

Our analysis indicates that countries that adopted a gradual and staged reopening experienced stronger economic recovery compared to the countries that rushed into lifting the restrictive measures. The transition from the full to partial to no lockdown appears to be a more effective strategy of lifting the restrictions than a quick lifting of the restrictions from full to no lockdown. Similarly, economic activity seems to react positively to partial school reopening, compared to the full school reopening.

The timing of reopening, i.e., the wait time expressed in the number of days after the first peak of deaths before the reopening process starts, also matters. Opening before the peak of the pandemic reduces electricity consumption relative to predicted, while delaying the opening past the peak leads to faster recovery. However, when this decision is modeled to be based strictly on epidemiological considerations it has no effect on the path of economic recovery. Lastly, countries that reopen slowly by gradually lifting the stringency measures rather than lifting them faster also experience a more robust economic recovery.

We demonstrate that governance, particularly trust in government institutions, is an essential determinant of economic recovery. Our results show that a higher level of trust in government is associated with a faster recovery among countries that carried out a gradual reopening process. Incorporating trust into the analysis even increases the success of a fast reopening process, although there the relationship is more complex. The analysis also shows that fear and anxiety about the spread of the pandemic may hinder the recovery of economic activity as countries reopen. Providing the population with objective information and data about the progress of the pandemic could be an effective policy instrument in promoting faster recovery, though causality is difficult to establish.

23
Tripp, A.M, (2010). Museveni’s Uganda: Paradoxes of power in a hybrid regime. Rienner.

West, B.T. and Olson, K. (2010). How much of interviewer variance is really nonresponse error variance. Public Opinions Quarterly, 74, 1004-1026 West, B.T., and Blom, A.G. (2017). Explaining interviewer effects: A research synthesis. Journal of Survey Statistics and Methodology, vol.5, 175–211 Williams, A.J. (1964). Interviewer-respondent interaction: A study of Bias in the information interview. Sociometry. 27(3): 338-352 Zwane, A. P., Zinman, J., Van Dusene, E., Pariente, W., Nul, C., Miguel, E., Kremer, M., et al. (2011). Being surveyed can change later behavior and related parameter estimates. Proceedings of the National Academy of Sciences, 108 (5): 1821–26 24
bphltest are available for download at https://webspace.utexas.edu/rcc485/www/code.html Suppose we have a dataset with binary outcome Y, binary treatment T, instrument Z, and covariates X1, X2.

1. To compute ∆<sup>ˆIV</sup> along with bootstrapped confidence intervals, type:

- ivregress 2sls Y X1 X2 (T=Z), vce(bootstrap, reps(199))

- estat bootstrap, percentile

2. To compute ∆<sup>ˆBP</sup> ATE<sup>andˆ∆BP</sup> ATT<sup>alongwithbootstrappedconfidenceintervals,type:</sup>

- bootstrap _b ate=r(ate) att=r(att), reps(199): biprobittreat (Y = T X1 X2) (T = Z X1 X2)

- estat bootstrap, percentile

3. To run the Murphy score and Hosmer-Lemeshow goodness-of-fit tests, type:

- biprobit (Y = T X1 X2) (T = Z X1 X2)

- scoregof

- bphltest

# A.2 Derivation of ∆LATE/∆ATE approximation (12)

Using (8) and (11), we compute a first-order Taylor approximation of<sup>∆</sup> ∆<sup><u>LAT E</u></sup> AT E<sup>about ρ, γ, α = 0.</sup> Although the ratio is undefined for γ = 0 or α = 0, the limit limα,γ,ρ→0 ∆∆LAT EAT E<sup>existsand</sup> is equal to 1, so we can still compute the Taylor expansion around this point. The terms involving the derivatives with respect to γ and α are zero because<sup>∆</sup> ∆<sup><u>LAT E</u></sup> AT E<sup>=1whenρ=0,</sup> regardless of γ and α. This leaves us with 21
women’s economic, political and social status are increasingly using edutainment. Through vicarious learning, people may acquire new information about social norms as well as ways of responding to social situations based on behaviors modeled by program characters (Bandura, 2004).

Field experiments of edutainment demonstrate that dramatized narratives are effective in promoting attitudinal and behavioral change across development sectors, including improving financial decision-making (Berg and Zia, 2017), increasing willingness to report corruption (Blair et al., 2019), reducing deference to authority (Paluck and Green, 2009), improving educational outcomes (Kearney and Levine, 2019), and promoting safer sexual behaviors (Banerjee et al. 2019 _b_ ; Orozco-Olvera et al. 2019; W. Vaughan 2000; Wang and Singhal 2016).

The evidence base of edutainment in development economics has recently expanded to gender norms and VAW. In Nigeria, Banerjee et al. (2019 _a_ ) showed that a short storyline on domestic violence embedded in the television drama MTV Shuga was effective in changing attitudes and behaviors related to domestic violence. In Uganda, Green et al. (2020) found that short advertisement clips during a film festival were effective in increasing audiences’ willingness to report violence to police or community leaders and in decreasing reported incidence. In Mexico, Arias (2019) finds that a radio drama increased rejection of VAW and increased support for gender equality.<sup>5</sup> The Uganda and Mexico studies provide experimental evidence that effects were driven by the social channel, facilitated by the communal delivery of public information.<sup>6</sup> The potential of social media platforms in delivering SBCC is greatly untapped in development. For instance, in India, where our study takes place, over 70 percent of individuals between 18 and 34 years used Facebook in 2018. Most of them spent between two and four hours on social media every day (Statista 2020). Despite their potential to reach many at low costs, social media are still overlooked by development programs. A potential reason is the general lack of empirical evidence on their effectiveness at achieving development objectives.

or desirable in their community (Burchell et al., 2013; McKenzie-Mohr, 2000).

> 5These findings confirm quasi-experimental evidence that suggested that by exposing viewers to outside views and lifestyles in a dramatized format, communities’ access to cable or to the “soap opera” channel were effective in improving gender outcomes in Brazil (La Ferrara et al., 2012) and decreasing acceptability of VAW in India (Jensen and Oster, 2009).

> 6This is in line with Bursztyn et al. (2020), who show that pluralistic ignorance – i.e., when most group members privately reject a group norm but publicly follow it as they believe that most members accept it (Miller and McFarland, 1987) – might be affecting men’s willingness to allow women’s participation in the labor force in Saudi Arabia.

5