rafmacalaba/datause-encoder-data huggingface dataset:
reflect some notion of market prices.<sup>23</sup> For certain types of analysis the issue can be avoided. For example, if we are concerned with the estimation of costs, multiple outputs can be included as independent variables. Similarly, for the estimation of a production function, Wouters (1993) suggests as an estimation strategy that output(s) be included as dependent variable(s). For example, the number of outpatients can be regressed on the number of inpatient days and other explanatory variables. In this framework, the number of outpatient visits is estimated _given_ the level of inpatient admissions at a facility. Although convenient, the approach imposes strong assumptions about the production technology.

In practice, most facility surveys have opted to measure output by the units of services actually rendered-i.e., outpatient visits, immunizations. While this may be unsatisfactory in some respects, it is often the only practical option. Moreover, many of the problems concerning the measurement and conceptualization of health facility outputs can, as noted, be overcome if the service data is sufficiently disaggregated. The level of disaggregation will however be largely determined by the way in which patients are registered at facility level and is therefore context specific. There is, however, some choice in the source of output data. Information on service outputs can be collected from either the patient register at facility level, or from administrative records at district or provincial level. In principle, these sources should be consistent. However, due to poor record keeping or incentive effects, there may be considerable discrepancies in practice. For example, results from a recent service delivery survey in Uganda indicate that districts have a tendency to over-report the number of patients seen in the facilities in the district (see Fig. 4).

lFigure 4 - Compaarnson of faciRlty and dAstirAct irecords in Uganda%

> 23 Composite output indices can, of course, be constructed on the basis of _ad hoc_ weights. If the limitations of the resulting output measure are squarely recognized, such output measures can provide a useful means of summarizing information.

> 24 Differences may arise due to low administrative capacity, or because district or facility staff know that the number will not be used or verified. Alternatively, if resources are allocated on the basis of reported patient numbers, or **if** these records are used to define user fee revenue targets against which the facility is held accountable, there may be incentives to over- or under-report patient numbers.

12
# **B Supplementary Materials**

The supplementary materials contain a number of additional analyses that are useful context for the analysis in the main text.

## **B.1 Daesh vs. non-Daesh RH Measures**

Figure B.12 provides three simple ways of viewing trends in oil production in Daesh held territory using remote sensing data. We assign all flares for this figure as Daesh or Non-Daesh according to the extent of Daesh territorial control in July 2014. Column 1 shows the number of sites flaring on any given day. Column 2 shows the average intensity of flaring activity over all sites, which is a rough proxy for total production. Column 3 shows the average RH measured at active sites, which captures in a rough way the intensity of production among working sites. The top row shows raw values, while the bottom row normalizes by activity levels measured before the war escalated (March-June 2012) as a way to highlight changes over time. As illustrated, Daesh’s productive base was small to start with and dropped rapidly long before the group took over (column 1). Moreover, its total productivity has generally fallen since January 2014 (column 2), and the productivity per well after its takeover, as measured by flaring activity, is quite poor compared to that in non-Daesh areas of Iraq and Syria.

46
39 Table 11: Increase in **EFTA** Imports from New Free Trade Partners (percent over five years, 1992/1988 constant prices)

|Exports from:|EE6|Israel|Turkey|World|
|---|---|---|---|---|
|Imports by:|||||
|Finland|_5_|-7|48|-1|
|Norway|-9|-11|161|12|
|Sweden|25|20|10|9|
|Austria|87|37|59|48|
|Switzerland|0|43|18|16|
|For reference:|||||
|EU|95|22|55|39|

Source: COMTRADE Table 12: Baltic Exports to the EU in "Europe" Categories **in** 1992 and Level of Protection in the EU (1990)

|||||Level of|Protection|by product|categorv|
|---|---|---|---|---|---|---|---|
||Share in|exports t|o EU (%)|Dutie|s (%)|NT|Bs*|
|"Europe" Product<br>Categories|Estonia|Latvia|Lithuania|GSP<br>(Poland)|Non-<br>GISP<br>(Czech)|GSP<br>(Poland)|Non-<br> <br>GSP<br>(Czech)|
|Al industrial<br>goods|92|95|93|0.1|7|24|24|
|Share in ind.-||||||||
|goods:|16|0|3|6.2|4.4|15|40|
||12|2|1|3.3|3.1|13|100|
|One-year delayed|26|7|14|0|8.7|22|21|
|Two-year delayed|1|2|1|0.1|5.6|57|64|
|Quota/five year|7|4|4|0|10.7|89|88|
|ECSC|38|85|77|0.1|5.6|57|64|
|MFA|9|67|49|||||
|Immediate free<br>trade<br>- of which oil||||||||

Source: Comtrade database. Duties and NTBs based on 1990 data, Baltic export data is from EU import data.

* NTBs are percentage of imports covered by them. See footnote 18 for definitions of **the** categories.
**Table 2. US social cost of carbon estimates, 2007 $ / t CO2**

||5%<br>discount<br>rate|3%<br>discount<br>rate|2.5%<br>discount<br>rate|95<sup>th</sup>percentile<br>of 3%<br>discount rate<br>distribution|
|---|---|---|---|---|
|2010|4.7|21.4|35.1|64.9|
|2015|5.7|23.8|38.4|72.8|
|2020|6.8|26.3|41.7|80.7|
|2030|9.7|32.8|50.0|100.0|
|2040|12.7|39.2|58.4|119.3|
|2050|15.7|44.9|65.0|136.2|

Source: Interagency Working Group on the Social Cost of Carbon (2010) The figures for the 3% discount rate in Table 2 should be fairly consistent with the figures for a pure rate of time preference of 1% in Table 1. These figures can, in turn, be compared with the carbon market prices shown in Figure 1. Starting with carbon market prices, we see EUA and CER prices lying in the range of Euro 10-15 per ton CO2 over most of Phase II of the ETS. This corresponds, roughly, to $14-21 per ton CO2. In 2010, therefore, the US recommended social cost of carbon for a 3% discount rate is just at the upper limit of the predominant EUA price. In contrast, the figures for the social cost of carbon from the fitted distribution with 1% PRTP in Table 1 have a mean of $45/t CO2 and a median of $34/t CO2, distinctly above both the US recommended cost and the predominant EUA and CER prices.

These figures point at the dilemma facing policy makers choosing between high and low carbon emitting alternative projects: Carbon market prices are closely linked to the business cycle and existing carbon markets are not necessarily designed to maximize global welfare, which implies that they are not generally going to equal the social cost of carbon. Therefore the policy maker would have to establish criteria for choosing a social cost of carbon if they wanted to ensure that project choice contributed to maximizing global welfare (which may not be a concern of nonAnnex I countries under the Kyoto Protocol, since they do not have emission caps). At a minimum these criteria would need to include assumptions about discount rates and the degree of precaution (as reflected in the choice of the percentile of the distribution of the social cost of carbon) to exercise. We return to these questions in the concluding section.

7
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Policy Research Working Paper 9049

# **Abstract**

This paper uses data obtained from three Moroccan household surveys that took place between 2000 to 2013, to address issues related to the so-called “Arab puzzle.” Welfare inequalities are low and declining in Arab countries and exist against the backdrop of a growing sense of dissatisfaction and frustration. The paper hypothesizes that welfare inequality plays a role, if seen through the lens of absolute measures and notably absolute polarization. The paper argues that the relatively worse perception of poor, vulnerable, and lower middle-class Moroccan households mirrors the ongoing hollowing out of the welfare distribution process and its concentration in the tails. The results of a multi-logit regression indicate that polarization is significantly correlated to perception and, importantly, that this correlation is asymmetric. The poorer are the households, the more polarization is perceived to link negatively to the well-being of households; and the richer are the households, the more polarization will positively correlate with their perceived well-being. The results are robust to the use of classes or quintiles for ranking social groups from the poorest to the richest.

This paper is a product of the Poverty and Equity Global Practice. 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://www.worldbank.org/prwp. The authors may be contacted at vmolini@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
**Table 5. Wage Premia by Subgroup**

||_Sector of em_|_ployment_|
|---|---|---|
|_Item_|Maquila|_Non-_maquila|
|Men|2<br>δ|Control|
|Women|3<br>2<br>1<br>δ<br>δ<br>δ<br>+<br>+|1<br>δ|
|Wage gap<br>(men/women)|)<br>(<br>3<br>1<br>δ<br>δ +<br>−|1<br>δ<br>−|

_Source_ : Based on equation 5 The excluded category in equation (5) is men outside the _maquila_ sector; the three parameters capturing the gender, _maquila,_ and interaction effects are interpreted as shifts in wages with respect to this control group. To clarify these effects, we show the wage premia assigned by equation (5) to the different population subgroups. A woman working in the _maquila_ sector, for example, will receive a market premium equal to δ 1 + δ 2 + δ 3 (with respect to men outside the _maquila_ sector) controlling for the market remuneration to her personal characteristics ∑β _j_<sup>_x_</sup> _i_ , _j_ . _j_ The wage premium of women working in the _maquila_ sector with respect to women in the other sectors will be equal to (δ 1 + δ 2 + δ 3 ) − δ 1 = δ 2 + δ 3 .

So far the analysis has not incorporated any time dimension. As noted earlier, from a theoretical point of view, trade reforms can be seen as a shock redistributing resources across the different sectors of the economy. This redistribution process is concomitant to price changes or changes in market returns to personal characteristics. We are interested in the welfare effects brought about by change in _maquila_ employment, the change in the premia given to workers in the _maquila_ sector, changes in the overall gender gap, and in particular the interactive effect capturing the gender wage gap differential between the export-oriented sector and other sectors. The change in the wage premia can be easily measured by introducing a time dimension to equation (5). Define _t_ as time dummies, and redefine _Dw_ = _D_ 1 , _Dm_ = _D_ 2 , and _Dw Dm_ = _D_ 3 as follows: The first term on the right-hand side of equation (6) captures the returns to personal characteristics; the second term captures the effects shown in table 5; the third term shows time controls; the fourth term allows for time-varying gender, _maquila,_ and interactive effects; and the last term is a normally distributed random component. Parameters λ _tk_ (called difference-indifference estimators) reveal how the premia shown in table 5 vary over time.<sup>9</sup> If the trade 9. In strict sense, these are triple difference estimators, because they capture differences between men and women, between workers inside and outside of the _maquila_ sector, and over time.

10
Can Environmental Cash Transfers Reduce Deforestation and Improve Social Outcomes? A Regression Discontinuity Analysis of Mexico’s National Program (2011-2014) Jennifer M. Alix-Garcia* Oregon State University Katharine R.E. Sims* Amherst College Victor Hugo Orozco-Olvera* Development Research Group - The World Bank Laura Costica Development Research Group - The World Bank Jorge David Fernandez Medina National Forestry Commission of Mexico Sofía Romo-Monroy National Forestry Commission of Mexico Stefano Pagiola Environment and Natural Resources Global Practice – The World Bank Keywords: payments for ecosystem services, land conservation, social capital, regression discontinuity, REDD

*Corresponding coauthors’ emails: <u>jennifer.alix-garcia@oregonstate.edu; ksims@amherst.edu;</u> and <u>vorozco@worldbank.org.  Jennifer Alix-Garcia and Katharine Sims are Principal Investigators and Victor Orozco Co-Principal</u> Investigator. We thank Mexico’s Comisión Nacional Forestal (CONAFOR)’s departments of Production and Productivity, and Monitoring, Reporting and Verification for their technical and logistical support to this study; and the University of Chapingo for comments on study design and organization of survey data collection. We thank the following for financial support, including time: CONAFOR, Mexico’s National Evaluation Agency (CONEVAL), the World Bank’s i2i and PROFOR programs, the World Bank Environment and Natural Resources Global Practice, the University of Wisconsin-Madison, the University of Oregon, Amherst College, and the Carnegie Corporation of New York. We thank Srini Vasudevan, Jens Engelmann, and Carolina Vergara for valuable research assistance. The authors benefited from comments provided by seminar participants at the World Bank Development Impact Evaluation Unit, the University of Toulouse, University of Oxford, London School of Economics, Forests and Livelihoods: Assessment, Research, Engagement meeting, the Association of Environmental and Natural Resource Econ Conference, the Northeast Agricultural and Economics Workshop, the 2018 World Bank Land and Poverty Conference and the World Congress of Environmental Economists.  The current paper integrates results pertaining to environmental, socioeconomic and social capital outcomes of the program. Sections of this working paper include text and results published in Alix-Garcia et al. 2018 (PNAS). Results on willingness to accept are expanded in a manuscript by AlixGarcia, Phaneuf and Sims (2018). The number for the study’s institutional review board is 2016/04/17.
Policy Research Working Paper 7147

# **Abstract**

The potentially-adverse impact of salinity on paved roads is well-established in the engineering literature. The problem seems destined to grow, as climate-related changes in sea level and riverine flows drive future increases in groundwater salinity. However, data scarcity has prevented systematic analysis for poor countries. This paper assesses the impact of groundwater salinity on road maintenance expenditures in the coastal region of Bangladesh. The assessment draws on new panel measures of salinity from 41 stations in coastal Bangladesh, and road maintenance expenditures, income, road network length, and road surfaces from 20 coastal municipalities. In a model relating maintenance expenditure for paved roads to groundwater salinity, municipal income, and road network length, large and significant effects are found for salinity. The regression model is used to predict the effect of within-sample salinity variation on road maintenance expenditure share, holding municipal income and road length constant at sample mean values. Increasing salinity from its sample minimum to its sample maximum increases the predicted road maintenance expenditure share by 252 percent. The implied welfare impact may also be substantial, particularly for poor households, if diversion of expenditures to road maintenance reduces support for community sanitation, health, and other infrastructure related programs.

This paper is a product of the Environment and Energy Team, Development Research 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 Sdasgupta@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
**Figure 3 - Adult Enrollment across Age Groups**

<!-- Start of picture text --> 35%<br>30%<br>25%<br>20%<br>15%<br>10%<br>5%<br>0%<br>20-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59 60-64<br>Primary Secondary Tertiary<br>Net Enrolment Rate<br>(of qualified individuals)<br><!-- End of picture text --> Source: Encuesta de Hogares, 2000 Note: The high tertiary enrollment at age 20-24 includes the fulltime student population that continues directly from secondary to tertiary education.

The figure shows that there is marginal adult enrollment in primary and secondary education above the age of 25, while there is some enrollment in tertiary education up to the age of 50.<sup>3</sup> Many factors could explain the low enrolment. Cultural and national factors, such as poverty, lack of security, economic instability, educational culture and local labor market conditions, surely affect adult enrolment. Further, the education system could be insufficiently geared towards adult education, Holm-Nielsen, Thorn, Brunner and Balan (forthcoming). However, a pre-condition for the success of lifelong learning policies that better accommodates adult learners into the education system is that there are economic gains for the adult population in re-entering the education system. This next section describes the methodology to estimate those gains.

3 In an international perspective, a small share of Colombians takes advantage of the high pecuniary gains from tertiary education. Only 0.4 percent of adults aged above 30 are enrolled. This compares to 2.1 percent in Sweden, 1.8 percent in the UK, and 1.5 percent in the US. In a regional context, Colombia also appears to be below average. Argentina (1.3 percent), Brazil (0.6 percent) and Uruguay (0.8 percent) have higher enrollment rates while Peru (0.1 percent) has lower enrolment, OECD (2001).

6
ences remains debated (Haaland and Roth 2020, Williamson 2020). Recent behavioral studies also suggest that perspective-taking interventions may influence native attitudes toward migrants. Simonovits et al. (2018) show that online interventions can reduce ethnic prejudice, while Adida et al. (2018), Williamson et al. (2021), and Chatruc and Rozo (2024) find that empathy-based interventions can increase support for migrants, albeit with short-term effects. Our study contributes to this literature by evaluating how information provision interventions affect native voting behavior, social capital, and attitudes toward migrants in the context of a large-scale regularization program.

# **II CONTEXT: THE PEP PROGRAM**

By mid-2022, more than 5.6 million Venezuelans had fled the humanitarian crisis in their country. Approximately 2.5 million of them had settled in Colombia, currently the primary recipient of Venezuelan migrants (UNHCR 2023). This number represents a shock equivalent to about five percent of Colombia’s total population.<sup>10</sup> Despite the size of the migration flows, the Colombian government granted these migrants free mobility and opportunities to regularize their status. One of the largest initiatives was the PEP program in 2018.

_The RAMV census:_ between April and June of 2018, the Colombian government undertook a countrywide survey to count the number of irregular (undocumented) migrants living in its territory. It was called the RAMV, _Registro Administrativo de Migrantes Venezolanos_ . Colombian authorities administered the survey at 1,109 different stations in 441 of the 1,122 municipalities. The registration points were located in border municipalities, in municipalities with a large population of Venezuelan migrants, and in municipalities where local authorities requested them. In order to register, migrants had to go to the registration point with proof of Venezuelan citizenship through official identification documentation. Registration was voluntary and was only advertised as a statistic exercise.

10Compared to the Colombian population, Venezuelan migrants are younger, more educated, and have lower employment rates (see Table A.1).

11
# Financial Development, Exchange Rate Regimes, and Growth

# Dynamics<sup>∗</sup>

Woubet Kassa<sup>†</sup> Emmanuel K.K. Lartey<sup>‡</sup> JEL Classification: E44 F33 F43 O40 O42 Keywords: Exchange Rate Regimes, Economic Growth, Productivity, Financial Development, Trade Openness

> ∗We are grateful to Souleymane Coulibaly, Fulbert Tchana Tchana and Albert Zeufack for very helpful comments. We also thank conference participants at the Center for the Study of African Economies (CSAE), University of Oxford, for invaluable comments. We are responsible for all errors.

> †The World Bank, 1818 H St. NW, Washington, DC 20433. Email: wkassa1@worldbank.org

> ‡The World Bank, 1818 H St. NW, Washington, DC 20433. Email: elartey@worldbank.org