rafmacalaba/datause-encoder-data huggingface dataset:
First two children boys <!-- Start of picture text --> (g) 1972-1984 (N=789) (h) 1985–1994 (N=1,665) (i) 1995–2006 (N=1,086)<br>Prob. boy (%) Prob. boy (%) Prob. boy (%)<br>0 5 10 15 20 0 5 10 15 20 25 0 5 10 15 20<br>Quarter Quarter Quarter<br>Prob. no birth yet Prob. no birth yet Prob. no birth yet<br>0 5 10 15 20 0 5 10 15 20 25 0 5 10 15 20<br>Quarter Quarter Quarter<br>85 85 85<br>80 80 80<br>75 75 75<br>70 70 70<br>65 65 65<br>60 60 60<br>55 55 55<br>50 50 50<br>45 45 45<br>40 40 40<br>35 35 35<br>30 30 30<br>1 1 1<br>.8 .8 .8<br>.6 .6 .6<br>.4 .4 .4<br>.2 .2 .2<br>0 0 0<br><!-- End of picture text --> Figure 9: (Continued) Predicted probability of having a boy and probability of no birth yet from nine months after second birth for urban women with 8 or more years of education by quarter. Predictions based on age 24 at second birth. Left column shows results prior to sex selection available, middle column before sex selection illegal and right column after sex selection illegal. N indicates the number of women in the relevant group in the underlying samples.

sex determination those who do are more likely to do so by choice.<sup>29</sup> Even then, the percentage boys born is between 60 and 65 percent. This pattern of sex selection for women with two girls is mirrored by rural women. As expected, given that most educated women do not want more than two children, there is no evidence for declining use of sex selection toward the end of the spell.

Women with either two boys or one boy and one girl as their first two children do not appear to use sex selection. Relatively few of these women go on to have a third child and the proportion that does declines substantially over time. This is best illustrated by the urban women in the 1995– 2006 period (Figures 9c, f, i). Close to sixty percent of the women with two girls will have a third child, while only around thirty percent of those with at least one boy will have a third child. For comparison, during the 1972-1984 period eighty percent of the urban women with two girls had a third child and almost sixty percent of those with at least one boy had a third child. The numbers are higher for rural women, but the pattern is the same.

> 29 For urban women, 25 percent of the sample in the first period had two girls, while only 22.7 percent of the third period sample had two girls.

35
For the growth in labor and fixed capital, we use known matches from the first step to establish confidence intervals for subsequent period values as a function of the number of years elapsed between observations. We break each variable into 500-unit increments, and require potential matches in non-adjacent years to fall within a 5th degree polynomial fit of the 10th and 90th percentiles of observed growth or decline in that variable. Based on our analysis of the pre-formed panel, we allow for variation of up to two years in the stated year of initial production. Conflicting matches are resolved by taking the match with the largest number of successfully matched variables.<sup>9</sup> Because we observe each firm’s year of initial production, we are confident that we can correctly identify survivors and entrants in our panel. However, given the substantial fraction of firms that are not surveyed every year, we are more reserved about our ability to identify exiting firms. The rates of exit that we observe in our panel are significantly higher than the rates that we extrapolate from the change over time of the distribution of years of initial production. Therefore in estimating productivity we avoid methods that rely on accurately identifying firm exit, and instead employ an index number method that is robust to potentially spurious exit. However, in Section 4.3, we explore how different assumptions about exiting firms could affect our productivity decomposition results, and in Section 4.5, we exploit the fact that we can confidently identify surviving firms to examine the impacts of the reforms on within-firm learning.

Summary statistics for the panel (to which we do not apply sampling multipliers) are presented in the final column of Table 3. Larger firms (those that are in the “census” sector and are surveyed every year) make up more than 60% of the firm-year observations in the panel, 45% of firm-year observations in the full sample of firms, and only 20% of firm-year observations in the estimated population. The panel should not be seen as representative of the population, but rather as a selection of relatively large firms. Nonetheless, the bottom rows in Table 3 show that 71% of firm-year observations that appear in the sample, representing 93% of total deflated output over 9The pre-formed 1998-2004 panel dataset does not contain similar permanent serial numbers or district identifiers, but we also have an older, cross-sectional dataset, which does have permanent serial numbers and district codes, covering the same years. We merge permanent serial numbers and district identifiers into the pre-formed panel dataset using a sample of common variables.

12
The United States has also promoted efforts to crack down on refining facilities in producer countries. This may have limited potential because refineries have little fixed capital and can be cheaply and rapidly replaced.

# **Trafficking and Smuggling Controls**

Another set of control programs aims at the smuggling of drugs into the wealthy nations. Most large seizures are made through interdiction, i.e. as cocaine or heroin is being moved across or toward borders. Indeed, interdiction seizures may account for as much as 40 percent of total cocaine production; large seizures are made by the exporting Andean countries, some of the transshipment nations (particularly Mexico), and by U.S. Coast Guard and Customs. Heroin seizures appear to be a much smaller share of total production, perhaps only 18 percent, as indicated in Table 5.<sup>36</sup> Most of the heroin seizures are made in Asia, close both to the production centers (Afghanistan and Myanmar) and to the largest consumer populations (India, China, Iran, Pakistan).

The effect of interdiction on the availability of cocaine has been examined in only a small number of studies (e.g. Reuter, Crawford and Cave, 1988; Crane, Rivolo and Comfort, 1997). Interdiction is like a stochastic tax; shipments and agents (crew members, pilots, unloaders) are subject to a probability of interception and the smuggler incurs costs to replace the shipment and to provide compensation to agents for the risk of being incarcerated. This will be reflected in the margin that smugglers charge, i.e. the difference between the price at which they purchase (export from source/transshipment country) and the price they charge in the destination country.

In Table 7 (abbreviated from Reuter and Greenfield, 2001), the difference between export and import values for world agricultural trade amounted to about 6 percent of the export value; absent data for a particular product or market, the Food and Agricultural Organization typically applies a standard “add factor” of 12 percent. In glaring contrast, the cross-border mark-up on, for example, Tajikistan-Russia heroin shipments is thought to be vastly larger, perhaps a ten fold increase, even though what is crossed is just a pair of land borders.<sup>37</sup> Another indication of the high effectiveness of interdiction is the high price per kilo of shipping drugs across international borders. It costs less than $100 to send a kilogram of coffee by express mail from Bogota to London; it costs $10,000 to send a kilo of cocaine between the same two cities.

> 36 This is the percentage of estimated total world production reported as seizures in UNODC (2003). It may be an overestimate because seizures are not purity adjusted and often are very much less than 100 percent pure. 37 Tajikistan is separated from Russia by Kazakhstan.  Citizens of both Kazakhstan and Tajikistan have the right to enter Russia without visas; the Russian border is moreover very long and lightly guarded.

22
Tatyana Bogomolova, Gregorio Impavido, Montserrat Pallares-Miralles joining the system after the reform. Only one variant is modeled with respect to benefit indexation and rate of return: wage indexation in the remaining old scheme and 5% real interest rate on investments.

Compared to the immediate switching for all, allowing only new entrants to join the new scheme will have the same impact on expenditure as discussed in the pure defined contribution reform scenario. The impact on government expenditure is presented in Figure 34 and Figure 35.

**Figure 34: Hybrid reforms lowers Government expenditure for civil servants but expenditures patterns are identical to the pure DC reform***

<!-- Start of picture text --> 2.5%<br>2.0%<br>1.5%<br>1.0%<br>0.5%<br>0.0%<br>2007 2012 2017 2022 2027 2032 2037 2042 2047 2052 2057 2062 2067 2072<br>Year<br>ref II.1A ref II.2 base<br>Expenditure (% GDP)<br><!-- End of picture text -->

**Source** : * Comparison of Government expenditure for civil servants – Reform II.1A, II.2 with baseline (as % of GDP).

**Source** : WB calculations based on PROST.

- 68 -
# FIGURE 14: SHARE OF TOTAL SERVICES IN EMPLOYMENT: SOVIET REPUBLICS AND WORLD ECONOMIES

<!-- Start of picture text --> 100%-<br>80%4<br>60%- -<br>40%- I I<br>;6 6<br>* 0 0 ~MO<br>ZO% S<br>LO OF PE CAPTA lCM<br>0%-<br>i<br>5 6 ~~~~~~7 8 9 10<br>LOG OF PER CAPITA INCOME<br><!-- End of picture text -->
|P148853|2015|2016|6/6/2016|2 Active|Eastern Africa|
|---|---|---|---|---|---|
|P148853|2015|2017|1/25/2017|3 Active|Eastern Africa|
|P148853|2015|2017|5/9/2017|4 Active|Eastern Africa|
|P148853|2015|2018|11/30/2017|5 Active|Eastern Africa|
|P148853|2015|2019|8/29/2018|6 Active|Eastern Africa|
|P148853|2015|2019|3/8/2019|7 Active|Eastern Africa|
|P148853|2015|2020|8/10/2019|8 Active|Eastern Africa|
|P148853|2015|2020|2/9/2020|9 Active|Eastern Africa|
|P148853|2015|2021|7/23/2020|10 Active|Eastern Africa|
|P148861|2015|2015|2/6/2015|1 Active|Seychelles|
|P148861|2015|2015|6/3/2015|2 Active|Seychelles|
|P148861|2015|2016|4/26/2016|3 Active|Seychelles|
|P148861|2015|2017|3/3/2017|4 Active|Seychelles|
|P148861|2015|2018|12/20/2017|5 Active|Seychelles|
|P148861|2015|2018|6/15/2018|6 Active|Seychelles|
|P148861|2015|2019|12/14/2018|7 Active|Seychelles|
|P148861|2015|2019|6/28/2019|8 Active|Seychelles|
|P148861|2015|2020|6/30/2020|9 Active|Seychelles|
|P148864|2014|2016|4/21/2016|1 Closed|Vietnam|
|P148864|2014|2017|1/17/2017|2 Closed|Vietnam|
|P148864|2014|2018|10/3/2017|3 Closed|Vietnam|
|P148868|2014|2014|6/25/2014|1 Closed|India|
|P148868|2014|2015|1/16/2015|2 Closed|India|
|P148868|2014|2016|9/25/2015|3 Closed|India|
|P148868|2014|2016|6/24/2016|4 Closed|India|
|P148868|2014|2017|11/14/2016|5 Closed|India|
|P148868|2014|2017|6/13/2017|6 Closed|India|
|P148868|2014|2018|6/27/2018|7 Closed|India|
|P148868|2014|2019|1/7/2019|8 Closed|India|
|P148868|2014|2020|8/23/2019|9 Closed|India|
|P148868|2014|2020|6/30/2020|10 Closed|India|
|P148886|2015|2015|4/8/2015|1 Closed|Guinea-Bissau|
|P148886|2015|2016|9/22/2015|2 Closed|Guinea-Bissau|
|P148886|2015|2020|6/15/2020|3 Closed|Guinea-Bissau|
|P148893|2014|2020|4/2/2020|1 Closed|Ukraine|
|P148896|2016|2016|2/24/2016|1 Active|West Bank and Gaza|
|P148896|2016|2017|8/12/2016|2 Active|West Bank and Gaza|
|P148896|2016|2017|2/17/2017|3 Active|West Bank and Gaza|
|P148896|2016|2018|8/31/2017|4 Active|West Bank and Gaza|
|P148896|2016|2018|3/26/2018|5 Active|West Bank and Gaza|
|P148896|2016|2019|11/8/2018|6 Active|West Bank and Gaza|
|P148896|2016|2019|6/7/2019|7 Active|West Bank and Gaza|
|P148896|2016|2020|12/10/2019|8 Active|West Bank and Gaza|
|P148896|2016|2020|5/28/2020|9 Active|West Bank and Gaza|
|P148927|2015|2015|5/1/2015|1 Closed|Rwanda|
|P148927|2015|2016|11/4/2015|2 Closed|Rwanda|
|P148927|2015|2016|11/14/2015|3 Closed|Rwanda|
A Behavioral Approach to Water Conservation: Evidence from Costa Rica<sup>**1**</sup> Saugato Datta (ideas42) Juan José Miranda (The World Bank) Laura Zoratto (The World Bank) Oscar Calvo-González (The World Bank) Matthew Darling (ideas42) Karina Lorenzana (ideas42) _JEL classifications: C93, D03, H41, L95, Q25_ _Keywords: water conservation, behavioral science, impact evaluation, randomized control trials_ 1 We are thankful to staff of the Municipality of Belén, in Costa Rica, and in special to its mayor Horacio Alvarado, Manual Alvarado, Denis Mena, Lorena Núñez and Sileny Rivera for their motivation and support throughout the pilot’s implementation.
# **1 Introduction**

The #MeToo movement highlighted the pervasiveness of violence against women worldwide. In a survey of women in 22 countries, over 50% reported being physically harassed in public and over 70% reported being followed (Livingston, 2015). A recent literature shows that harassment and violence against women in the public space might altogether discourage women from participating in market activities (Jayachandran, 2020; Vel ́asquez, 2019; Field and Vyborny, 2022).

Commuting to opportunity presents a specific risk for women and girls. For instance, the risk of violence on the way to school may reduce or distort women’s and girls’ human capital investments (Borker, 2021; Muralidharan and Prakash, 2017). Yet, the recurring nature of this harassment and the costs faced by women who _do_ commute daily have not been formally documented. Moreover, there is a lack of evidence on policies capable of combating sexual harassment on public transit.

In this paper, we use high-frequency data on women commuters to study a reserved space policy on public transit in Rio de Janeiro, Brazil. In response to the increased public awareness of the high prevalence of sexual harassment in the public space, the creation of women-reserved “safe spaces” has surged.<sup>1</sup> This policy response is highly controversial.<sup>2</sup> On the one hand, advocates argue that providing women-reserved spaces allows women to avoid harassment. On the other hand, detractors make the case that, by playing into latent prejudice, these reservation policies may reinforce norms restricting women’s movement in the public, non-reserved space, ( _e.g., “women should not overstep their boundaries”; “to be safe, a woman should stick to her reserved space”_ ); if this legitimizes and increases harassment in the public space, it may be deleterious to women’s safety overall. Both sides of the argument are still wanting for rigorous evidence (Aguilar et al., 2021).

> 1At the time of publication, women-reserved spaces in public transit have been adopted by cities in the Arab Republic of Egypt, Bangladesh, Belarus, Brazil, India, Indonesia, the Islamic Republic of Iran, Israel, Japan, Malaysia, Mexico, Pakistan, the Philippines, the United Arab Emirates, and the Republic of Korea, among others.

> 2See for example Guardian (2015).

2
heightened caution within communities affected responses among those surveyed. This is consistent with the fact that Rumbek has the highest self‐reported and external conflict exposure measure and also the lowest consent rate from the other three counties. While the external indicator is used to mitigate these biases, it may be an underestimated indicator of conflict exposure as it only includes deadly events that were reported. The self‐reported conflict variable is relatively more precise as it is comprised of a wide range of micro‐level conflict exposure variables and captures specific types of damage which are not reflected in the ACLED data. For these reasons, we use both external and self‐ reported indicators to inform our analysis.

The impacts of the ongoing conflict are overwhelming, and action must be taken immediately to prevent them from escalating. One important policy implication from this study is that adolescent girls and young women are an important resource for economic engagement and empowerment and that economic and business development initiatives should include criteria for targeting and incentivizing participation of this particular demographic in economic activities. Adolescent girls exposed to conflict reported higher empowerment and entrepreneurial index scores, indicating willingness to work and start businesses in the future. Creating such opportunities for girls would, in turn, have the potential to contribute to economic growth and poverty reduction, as well as address pervasive conditions of income inequality among the poor and among the overall population (Acharya 2008). Targeted programming to support and incentivize girls’ economic engagement further improves household food security and economic welfare. Depending on the types of activities in which girls choose to engage, an integrated approach that enables a school‐to‐work transition through both livelihoods and skills development, as well as with cognitive and non‐cognitive skills training interventions would prove especially useful.

That said, increasing economic opportunities alone are not enough to improve the well‐being of girls. The findings in this paper also help improve our understanding of the longer‐term psychosocial consequences of conflict. For example, lowered aspirations and high anxiety during early years have been linked to worsening economic outcomes in adulthood (Powell and Butterfield 2003; Reigle‐ Crumb, Moore, and Ramose 2011). Additionally, the issue of early and likely forced marriage is a prevalent feature of South Sudan, as are other dimensions of gender‐based violence (IRC and GWI, 2017). These challenges highlight the need for interventions that focus on increasing access to education services in part to enable improved employment opportunities, building capacity for provision of psychosocial and mental health services, and wider prevention programming addressing pervasive and challenging social norms that perpetuate among other issues violence or harmful 23
conflict‐affected populations. The conflict exposure module included key questions related to looting, household damage, and physical harm (including death) to members of the household (Table 1). A subset of these questions has already been used in the High Frequency Pilot conducted by South Sudan’s National Bureau of Statistics after comprehensive discussions of the impact of these questions on the emotions of the respondent. Understandably, several respondents chose not to answer these questions.

**Table 1: Variables in the endline questionnaire measuring conflict exposure.**

|**Variable**|**Description**|
|---|---|
|Household looted|Was your household looted during the conflict?|
|Other household looted|Was any household in your neighborhood looted in the conflict?|
|Household damaged|Was your household damaged in the conflict?|
|Household member harmed|Was any member of your household harmed in the conflict?|
|Number of Household members|How many members of your household were harmed in the|
|harmed|conflict?|
|Household member died|Did any member of your household die due to the conflict?|
|Number of Household members died|How many members of your household die due to the conflict?|
|Member left|Did any member of your household leave due to the conflict?|

Out of 3,137 respondents, 804 respondents (around 25 percent) chose not to respond to the questions in the conflict module (Figure 2). While it seems that respondents from Juba and Yei mostly consented, there is significant variation in the rates of consent across clusters in Rumbek and Torit (Figure 3). Besides area, we find no bias in terms of age, household size, religion, and years of residence when exploring the characteristics of the non‐consenting individuals (Table 2).

10
pattern in a mountain watershed in Nepal. _Agriculture, Ecosystems and Environment_ 99 (1–3): 83.

- Glaeser, E. D. Laibson and B. Sacerdote. 2002. “An Economic Approach to Social Capital,” _The Economic Journal_ , 112 (483):F437-F458.

- Guthman, J. 1997. Representing Crisis: The Theory of Himalayan Environmental Degradation and the Project of Development in Post-Rana Nepal. _Development and Change_ , 28:45-69.

- Gächter, S., 2007. Conditional cooperation: Behavioral regularities from the lab and the field and their policy implications. In Frey, B. and A. Stutzer (eds): Economics and Psychology. A Promising New Cross-Disciplinary Field. The MIT Press 2007, pp.19-50.

- Gächter, S. and E. Renner, E., 2010. The effects of (incentivized) belief elicitation in public good experiments. _Experimental Economics_ 13, 364-377.

- Henrich, J., R. Boyd, S. Bowles, C. Camerer, E. Fehr, H Gintis, and R. McElreath, 2001, In Search of Homo Economicus: Behavioral Experiments in 15 Small-Scale Societies, American Economic Review, 91(2), 73-78.

- Herrmann, B. and C. Thöni, 2009. Measuring conditional cooperation: A replication study in Russia. _Experimental Economics_ 12, 87-92.

- HMG/DoF. 2005. Forest Cover Change Analysis of the Terai districts, 1990/91 – 2000/01. Kathmandu: Department of Forest, Ministry of Forest and Soil Conservation.

- Hobley, M. 1996. Participatory forestry: The process of change in India and Nepal. _Rural Development Forestry Network_ , Overseas Development Institute, London.

- Hobley, M. and C. Jha. 2012. “Community Forestry Program Impact Study Persistence and Change: Review of 30 Years of Community Forestry in Nepal,” for Nepal Ministry of Forests and Soil Conservation.

- Kanel KR and Niraula DR. 2004. Can Rural Livelihood be Improved in Nepal through Community Forestry? _Banko Jankari_ 14(1): 19-26.

- Knack, S. and P. Keefer. 1997. “Does Social Capital have an Economic Payoff? A Cross-Country Investigation,” _The Quarterly Journal of Economics_ , Vol. 112 (4): 1251-1288.

- Kocher, M., T. Cherry, S. Kroll, R. Netzer, and M. Sutter, 2008. Conditional cooperation on three continents. _Economic Letters_ 101, 175-178.

- Ledyard, J., 1995. Public goods: A survey of experimental research in Kagel, J. and A. Toth (eds.), _Handbook of Experimental Economics_ , Princeton University Press, Princeton.

- Martinsson, P., N. Pham-Khanh, C. Villegas-Palacio, 2013, Conditional cooperation and disclosure in developing countries, _Journal of Economic Psychology_ 34, 148-155.

- Mekonnen, A. and R. Bluffstone (2008) “Does Common Property Forest Management Change On-Farm Behavior?  Evidence on Tree Planting in Highland Ethiopia,” EfD and Resources for the Future Discussion Paper Efd DP 08- _29_ .

- MOFSC. 2013. Persistence and Change: Review of 30 Years of Community Forestry in Nepal. Ministry of Forest and Soil Conservation.

- Nyangena, W. 2011. “The Role of Social Capital in Sustainable Development: An Analysis of Soil Conservation in Rural Kenya,” in _Agricultural Productivity in East Africa: Investment, Sustainability and Poverty Reduction_ . R. Bluffstone and G. Köhlin eds. Resources for the Future Press, forthcoming 2011.

27
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