rafmacalaba/datause-encoder-data huggingface dataset:
principals and teachers involved in it. Setting aside the one-time-only expenditures in the design of the intervention, the cost of implementing the program amounts to USD 1.85 per student. Estimates of the monetary benefits of ENTRE suggest an internal rate of return of 28% and a benefit-cost ratio of almost 19 with a 5% discount rate over a 40-years span. Another interesting cost-effectiveness measure can be computed by multiplying the main ITT estimate of the program (0.013) by 100 and dividing it by the implementation cost per student (1.85). This measure of additional years of student participation per USD 100 spent allows us to compare ENTRE with other type of interventions. For example, in a recent review from J-PAL, the impact of all the scholarships, conditional cash transfers, and subsides analyzed range between 0.01 and 0.17 additional years of education per USD 100 spent (including the well-known PROGRESA in Mexico with an impact of 0.01 additional years).<sup>18</sup> ENTRE is much more cost-effective based on this metric, since it provides 0.70 additional years of student participation per USD 100 spent. Moreover, and perhaps most importantly for scale and sustainability, for Guatemala where perstudent government spending at the primary level was over USD 530 in 2018, the costs of a program like ENTRE are feasible to absorb into national public budgets.<sup>19</sup>

# 6. Final Remarks

This paper presents experimental evidence that a low-cost and scalable early warning system can significantly reduce school dropout rates in the transition from primary to lower secondary, in a middle-income country with high average dropout. Using a 4,000-school multi-arm randomized experiment, we show that the program reduced the probability of student dropout in treated schools by 1.3 percentage points, and we estimate that this effect grows to 3.1 percentage points when we look at the impact on compliers (roughly 3.6% and 8.5% of the baseline dropout rate). The low implementation cost of the program—about 2 USD per student—makes the intervention highly cost-effective. The (conservative) rate of return of the program is estimated to be almost 30%, with a cost-benefit ratio of approximately USD 19 per each 1 USD invested. The evaluation was embedded in a large-scale implementation including almost 17% of all primary schools in Guatemala, making the results more informative for understanding the impacts of the program in ongoing, “real world” conditions.

> 18 See Figure 4 in J-PAL Policy Bulletin (2017) for a cost-effectiveness comparison with these and other programs.

> 19 Data on public education spending from the World Development Indicators.

36
- Kouparitsas, Michael A. (2001). “Should Trade Barriers Be Phased-Out Slowly? A Case Study of North America”. _Journal of Policy Modeling_ 23(8) (November): 875–900

- Lloyd, Peter J. & Xiao-Guang Zhang (2006). “The Armington Model”. _Staff Working Paper_ 31921, Melbourne, Australia: Australian Productivity Commission

- Lucke, Bernd (2001). “Fiscal Impact of Trade Liberalization: The Case of Syria”. In _Proceedings of the 75th International Conference on Policy Modeling_ . Brussels, Belgium

- Mayer, Wolfgang (1984). “Endogenous Tariff Formation”. _American Economic Review_ 74(5) (December): 970–985

- Mitra, Pradeep (1992). “The Coordinated Reform of Tariffs and Indirect Taxes”. _World Bank Research Observer_ 7(2) (July): 195–218

- Romagnoli, Alessandro & Luisa Mengoni (2009). “The Challenge of Economic Integration in the MENA Region: From GAFTA and EU-MFTA to Small Scale Arab Unions”. _Economic Change and Restructuring_ 42(1–2) (May): 69–83

# **Technical Appendix**

The precise calculation of the price change resulting from a trade policy change depends on how a country applies its tariffs and other trade taxes and charges. In Syria, tariffs are collected as a percentage of the c.i.f. import value, the spending tax, and the revenue tax are levied on the tariff-inclusive c.i.f. import value, while other charges—such as the city local tax—are a complex combination of fixed amounts as well as percentage shares of more than a dozen different tax bases; for simplicity, however, we assume that all other charges are calculated as a percentage of the c.i.f. import value.

A given _ceteris paribus_ tariff change for good _i_ from exporter _j_ leads to a percentage price change given by where _τij_ , _speij_ , _revij_ and _remij_ are the tariff, the spending tax, the revenue tax and an aggregate of all other charges applied on good _i_ from country _j_ , respectively, and a prime indicates the post-reform value of a variable. For what follows, we utilize the tariff 29
COST RECOVERY, EQUITY, AND EFFICIENCY IN WATER TARIFFS IN AFRICA

# Annex E Structure and levels of nonresidential tariffs

||||**I**|**ndustrial**<br>||**C**|**ommercia**<br>|**l**<br>|**Gove**<br>**i**|**rnment/p**<br>**nstitution**<br>|**ublic**<br>**s**<br>|
|---|---|---|---|---|---|---|---|---|---|---|---|
|Country|Utility|Connection<br>charge|Fixed<br>charge|Number<br>of<br>blocks|Price<br>of 1st<br>block|Fixed<br>charge|Number<br>of<br>blocks|Price<br>of 1st<br>block|Fixed<br>charge|Number<br>of<br>blocks|Price<br>of 1st<br>block|
|BEN|SONEB||n|1|0.85|n|1|0.85|n|1|0.85|
|BFA|ONEA||y|1|2.13|y|1|2.13|y|1|2.13|
|CIV|SODESI||y|4|0.48||4|0.48|n|1|1.07|
|CPV|ELECTRA||n|1|0.78|n|1|0.78|n|1||
|DRC2|REGIDESO||n|1||n|3|0.01|n|1|0.00|
|ETH1|AWSA||n|1|0.42|n|1|0.42|n|1|0.42|
|ETH2|ADAMA||—|—|—|—|—|—|—|—|—|
|ETH3|Dire Dawa||—|—|—|—|—|—|—|—|—|
|GHA1b|GWCL||n|—|—|—|—|2.20|y|—|—|
|KEN1|NWASCO|||—|—|—|4|0.18|—|—|—|
|KEN2|KIWASCO|y|—|—|—|—|5|0.60|—|—|—|
|LSO|WASA|y|y|1|0.69|y|1|0.69|y|1|0.69|
|MDG|JIRAMA||||||||n|2|0.23|
|MOZ1|ADeM Beira||n|2|15.69|n|2|15.69|n|2|15.69|
|MOZ2|Adem Maputo||n|2|16.75|n|2|16.75|n|2|16.75|
|MOZ3|AdeM Nampula||n|2|13.88|n|2|13.88|n|2|13.88|
|MOZ4|AdeM Pemba||n|2|15.02|n|2|15.02|n|2|15.02|
|MOZ5|AdeM Quilimane||n|2|15.22|n|2|15.22|n|2|15.22|
|MWI1|LWB||y|2|0.49|y|2|0.49|y|2|0.45|
|MWI2|BWB||—|—|—|—|—|—|—|—|—|
|MWI3|CRWB||—|—|—|—|—|—|—|—|—|
|NAM1|Walvis Bay||n|4|1.99|n|4|1.99|n|4|1.99|
|NAM2|Windhoek|y|n|1|1.63|n|1|1.63|n|1|1.63|
|NA M3|Oshakati|y|y|3|17.70|y|3|17.70|y|3|17.70|
|NER|SEEN||n|3|0.85|n|1|0.87|n|1|0.87|
|NGA1b|FCT WB||n|1|7.84|n|1|0.78|n|2|0.47|
|NGA3|Kaduna WB||n|3|0.55|n|2|0.55|n|2|0.19|
|NGA5|Katsina WB||n|1|1.57|n|1|1.57|n|2|0.20|
|RWA|Electrogaz||n|3|0.44|n|3|0.44|n|3|0.44|
|SDN1a|NWC Khartoum||n|1|0.73|n|1|0.73|n|1|0.73|
|SDN2|NWC South Darfur||n|1|1.41|n|1|1.41|n|1|1.41|
|SDN3|NWC Upper Nile||n|1|1.35|n|1|1.35|n|1|1.35|
|SEN2|SDE||—|—|—|—|—|1.62|n|—|1.62|
|TCD|STEE||n|2|0.22|n|2|0.22|n|2|0.22|
|TZA1|DAWASCO||n|3|0.57|n|3|0.57|n|3|0.57|
|TZA2|DUWASA||n|1|13.04|n|1|13.04|n|1|13.04|

34
results suggest the opposite if anything. We may thus be dealing with a more complex pattern of endogeneity in self-reported shocks.

However, the IV estimates of model (2) with interaction terms did not appear credible on two counts. First, some of the marginal effects turned out to be too large. For instance, the marginal effect of commercial development on the impact of the labor market shock was a negative 61%. Larger marginal effects are of course consistent with measurement error, but the IV effects appeared too large to be credible. Secondly, the IV estimates also generated a large number of cases with a positive impact of the crisis on living standards, accounting for as much as _25%_ of all crisis-affected households, which again appeared highly implausible. (We interpret a large number of positive impacts ultimately as a sign of model misspecification.) For these reasons, we decided not to use the IV estimates at the risk of some potential bias due to measurement error. If the IV estimates of model (I) are any guide, there may be some upward bias in our estimated impact.

We thus use counterfactual consumption based on ordinary least squares estimates of the (restricted) interaction model (2) to assess the impact on poverty and inequality. We use the FGT class of poverty measures and a number of inequality measures including Theil's T index and the generalized entropy measures (see Foster, Greer and Thorbecke, 1984, and Cowell, 1995). For the poverty measures, we use the provincial poverty lines developed by Balisacan (1999). 19 Table 4 sumnmarizes the key results.

The results indicate a modest impact of the crisis. There is a negative effect on mean consumption of about 5%. This may be compared with the 2% decline in real per capita GNP,

> 19 In effect, we use the Manila poverty line of **Pl** 1,677 per person per year corresponding to a nutritional norm of 2000 calories per person per day and allowing for basic nonfood expenditure (see Balisacan 1999 for further details). The provincial poverty lines have in fact already been used above to express nominal consumption of all households into 1998 Manila prices.

18
I INTRODUCTION

# Appendix (continued)

|Country,|Last publi|shed census|||
|---|---|---|---|---|
|ecoronow or<br>territory|Date|Population<br>(1000)<br>*|<br>Total population. mid-1985|Total fertility.<br>1985-90|
|Tuvalu|May 79|7 F|Based<br>on UNWPVSR<br>7/89 (official<br>est.|) -|
|Uganda|Aug 69|9549 F|U.N. 1989 (prelim.<br>version)|U.N. 1989 (prelim.<br>version)|
|United<br>Arab<br>Emirates|Dec 80|1043 F|UNPWSR<br>4/87 (official<br>est.)|U.N. 1989 (prelim.<br>version)|
|United Kingdom|Apr 81|55678 F|UNPVSR 7/86 (official<br>est.)|U.N. 1989 (prelim.<br>version)|
|United States<br>of America|Apr 80|226546 F|UNPVSR 7/86 (official<br>est.)|U.N. 1989 (prelim.<br>version)|
|Uruguay|Oct 85|2955 F|Official<br>est. from 1985 census|U.N. 1989.<br>(prelim.<br>version)|
|U.S.S.R.|Jan 89|286717 F|U.N. 1989(prelim.<br>version)|Based<br>onRonnier1S88|
|Vanuatu|Jan 79|111 F|Based<br>on official<br>1987<br>est.|USBOC<br>1987|
|Venezuela|Oct 81|14517<br>F|UNPVSR<br>1/87 (official<br>est.)|U.N. 1989 (prelim.<br>version)|
|Viet Nam|Apr 89|64411<br>F|Bank projection<br>from 1977<br>census|Bank est.|
|Virgin Islands|Apr 80|97 J|USBOC 1985|Based on USBOC 1987|
|(U.S.)|||||
|Wake Island|Apr 70|2 F|Based<br>on UNPVSR<br>7/89 (official<br>est.|)|
|Wallis<br>and|Mar 76||Based<br>on UNPVSR<br>7/89 (official<br>est.|)|
|Futuna|||||
|West Bank|||Bank est.|Bank est.|
|Western Sahara|Oec70|76425 F|UNPVSR<br>1/87||
|Western Samoa|Nov 81|156 F|U.N. 1989 (prelim. version)|Bank est.|
|Yemen Arab Rep.|Feb 86|9274J|<br>Bank assessment|Bank est.|
|<br>Yemen. People's<br>Dem. Rep. of|<br> <br>Mar 88|2345 F|U.N. 1989 (prelim. version)|U.N. 1989 (prelim. version)|
|<br>Yugoslavia|Mar 81|22425 J|UNPVSR<br>4/87 (official<br>est.)|UNPVSR<br>10/88<br>(official<br>est.)|
|<br>Zaire|Jul 84|29441 F|<br> <br>U.N. 1989 (prelim. version)|U.N. 1989 (prelim. version)|
|Zambia<br>|Aug 80|5662 F|Bank projection from census|Based on Bank sector report|
|Ziirbabwe|Aug 82|7546 F|Bank projection from census|OHS 1988|

Notes: When a source for an estimate is directly cited (e.g., UNPVSR 7/86), the estimate is taken as is from that publication. An ettimate "based on" a source is not reported in that publication but derived from data contained in it. When a source is given for a fertility or mortality estimate prior to 1985-90, the corresponding 1985-90 estimate is a projection from the earlier estimate. Citations for the main documents referred to here (usually by abbreviations) are in the list of references.

- Nature of population estimate: F **=** de facto, J a de jure.

- Not applicable. No census has been taken, or no estimates were used because no projections were made for these small ccGJntries.

- a Census was for entire peninsula.

- b 55 people.
# **1. Introduction**

The aim of this paper is that of assessing the risk sharing opportunities enjoyed by Latin American and Caribbean (LAC) countries, as reflected in co-movements of rates of growth of (aggregate) domestic consumption with rates of growth of national income and rates of growth of aggregate consumption (averaged across a macro-area of interest).

The underlying theoretical idea is that when a country has full access to risk sharing opportunities within a given macro area, consumption growth rates should not co-vary with aggregate income growth rates of the same country, but rather with aggregate consumption growth in the reference area (equivalently, consumption growth rates should be perfectly correlated across individual countries). Therefore, only aggregate risk should matter, whereas individual (idiosyncratic) risk should be diversified away.

If the possibility of insuring against idiosyncratic risks is something desirable in all economies, this is particularly true in developing countries, where lack of insurance may lead to more inequality and to lower levels of investments, income, consumption, and savings (Townsend (1994), Greenwood and Jovanovic (1990), Banerjee and Newman (1993)). Increasing inequality, in turn, may constitute a relevant obstacle to the development of growth processes in such countries (Townsend (1994)).

Of course, there are many reasons why idiosyncratic (at an individual country level) risk may not be wiped off, including incomplete financial or real markets, limited participation in real or financial markets, absence of intra or inter generational transfers, limited saving opportunities, etc.

In particular, in the last few years growing attention has been paid, in this stream of literature, to the effects of financial integration on the risk sharing opportunities enjoyed by individual economies, both in the case of developed and developing countries. Imbs (2006) shows that financial integration increases both correlations in GDP fluctuations and in consumption fluctuations, but that the effect is larger on the former. This helps explain the so called “quantity puzzle”, i.e. what appears to be a persistent gap between the two groups of correlations (whereas theory would rather predict an inverse gap, with consumption correlations being larger than output correlations). Kose et al. (2006), on the other hand, show that emerging market economies have not benefited, in terms of improved insurance opportunities, from what seems to be a substantial increase in international financial flows in the last two decades, suggesting a sort of “threshold” effect for the gains from financial integration.

Over the last fifteen years or so, economists have resorted to various tests of consumption insurance, run both at a microeconomic level, and at a macroeconomic level, to evaluate the degree of risk sharing within a country or within a broader area.

2
# _5.2 National Discretion_

The approaches proposed in the various projects have yet to detail implementation issues closely. The Basel Committee, in contrast, has made it clear that there are a number of elements of the banking three-pillar approach that are subject to national discretion.

_A “national discretion” element may prove to be a useful tool for the insurance sector as it develops the various proposals. In this way, countries can provide an incentive to companies to progress their development of the necessary risk management and technical infrastructure before agreeing to implement the more advanced approaches._ A system that requires preconditions to be in place, infrastructure to be developed and justification to be made to enable the national authorities to provide acceptance can act as an incentive for change. Once the preconditions are identified and elaborated, then the industry leaders will have an incentive to develop the necessary infrastructure, improve the technical capacities, and to do so collaboratively if necessary.

# _5.3 Strengthening the First Pillar_

For many countries, the fundamental insurance solvency regimes will require change as a result of the proposed accounting standards.

First, and most obvious, will be the reclassification of some premiums to deposit type treatments. Where the insurance solvency margin requirement is constructed to include a factor based multiple of premiums then this may undermine the solvency intention.

The move to market-based “fair values” for assets may require some additional supervisory oversight at first in jurisdictions where asset values are not as robust due to limited markets, low turnover, or limited experience in the valuation of non marketable assets.

The IASB initiatives will require increased technical capacity and increased access to market data in many cases. Such approaches require the collection and examination of basic data about the frequency and severity of claims events. The usual experience is that such data will not exist at first or will not be in a form suitable for robust analysis. There may be limited expertise to analyze the data and to apply it to build and then maintain the necessary financial models. These limitations may be expressed both in the number of people and the skills of those available. The IASB and IAA proposals will, in particular, encourage or even mandate improvements to company risk management systems.

36
# **Urban Transport Infrastructure and Household Welfare: Evidence from Colombia**<sup>**1**</sup>

Tobias Pfutze Florida International University Carlos Rodríguez-Castelán Daniel Valderrama-González The World Bank Georgetown University JEL Classification: O15, O18, R23, R40 Keywords: BRTs, Welfare Effects, Transport policy evaluation, Urban displacement, Colombia 1 The authors would like to thank Erich Battistin, Samantha Lach, Nancy Lozano, Ambar Narayan, Sergio Olivieri, Lourdes Rodriguez-Chamussy, Paul Rodriguez-Lesmes, Tara Vishwanath, Robert Zimmerman, and participants of the 2015 Learning Days of the Poverty Global Practice at the World Bank, the 2016 Summer University of the Poverty and Equity Global Practice at the World Bank, and the FAD Seminar at the International Monetary Fund for their thoughtful and useful comments. The authors would also like to acknowledge Sarah Knob and Luz Karine Ardila Vargas for their outstanding research assistance. The findings, interpretations and conclusions in this paper are entirely those of the authors. They do not necessarily represent the view of the World Bank Group, its Executive Directors, or the countries they represent.
**Table 3: Conflicts and their characteristics (Total number of plots: 861)**

|||||**Landlord-**||**C**|**onflict start**|**ed**|
|---|---|---|---|---|---|---|---|---|
||**Total**|**Family**|**Neighbors**|**Tenant**|**Government**|**Before**<br>**1996**|**1996-98**|**‘99-2001**|
|Plots ever affected by conflict|48.08%|28.74%|48.31%|18.36%|4.59%|30.92%|25.85%|43.24%|
|Distribution of conflict|414|119|200|76|19|128|107|179|
|**Conflict characteristics**|||||||||
|Share resolved|51.93%|57.98%|56.00%|36.84%|31.58%|50.78%|60.75%|47.49%|
|Through formal means|75.98%|63.03%|83.33%|79.45%|66.67%|66.15%|80.00%|65.89%|
|**Reason for conflict**|||||||||
|Inheritance|10.87%|35.29%|1.50%|0.00%|0.00%|9.38%|14.02%|10.06%|
|Exceeding boundaries|49.28%|25.21%|73.00%|30.26%|26.32%|50.00%|52.34%|46.93%|
|Tenancy|35.51%|35.29%|24.50%|61.84%|47.37%|32.81%|33.64%|38.55%|
|Public land|4.35%|4.20%|1.00%|7.90%|26.32%|7.81%|0.00%|4.47%|
|Length(includingunresolved ones)|3.49|2.44|3.55|4.54|4.89|8.05|2.47|0.86|

Source: Own analysis based on the 2001 EPRC/World Bank survey.

21
# **1. Introduction**

Having achieved remarkable economic growth over the last four decades (1960-2000), the citystate of Singapore entered the 21<sup>st</sup> century with a relatively high level of income/capita, but growing recognition of the need to sustain future growth through innovation. As highlighted in Wong (2004, 2003), for much of its history of rapid economic growth, Singapore had relied on a strategy of attracting direct foreign investment (DFI) from global multinational corporations (MNCs) and leveraging this to exploit technologies and know-how developed elsewhere. However, as the city-state’s costs increasingly approach those of leading cities in the advanced economies, and as global competition for DFI continues to intensify particularly with the opening up of major economies in Asia like China and India with large domestic markets and abundant supply of skills, Singapore’s only recourse to stay competitive is to become more innovative, i.e. not just by being efficient in “using” technologies and knowledge produced elsewhere, but by “creating” (commercializing) its own intellectual capital as well.

This paper examines the challenges and concerns that Singapore faces in becoming more innovative through the lenses of the industry players currently involved in the three leading business sectors where innovation is thought to be critical for competitive survival: high-tech manufacturing industries, knowledge-intensive business services (KIBS), and creative content industries. In particular, the paper highlights the key findings from an explorative, semi-structured survey with the senior management of 40 representative firms from these three innovative sectors.

# **2. Brief Profile of the Leading Innovative Sectors in Singapore**

As widely discussed in the literature (see e.g. Yusuf and Evenett 2002, Yusuf et. al. 2003, OECD 2003, Muller and Zenker 2001, Florida 2002 and Howkins 2003), the New Economy has been identified with the following three key business sectors deemed to have a high innovative propensity: high-tech manufacturing, particularly information and communications technologies (ICT) and life sciences, knowledge-intensive business services (KIBS) and creative content industries. A brief overview of these three sectors in Singapore is provided below.

# **2.1 The high-tech manufacturing sector in Singapore**

It is by now well-documented that the main source of Singapore’s rapid economic growth was the leveraging of direct foreign investment by global multinational corporations (MNCs) to achieve continuous industrial re-structuring and upgrading, particularly in the high-tech manufacturing sector 1
is a demanding set of requirements, requiring more time than is available for many policy decisions. When time is of the essence, as it frequently is,<sup>7</sup> I would say that it would be better to base policies on a less rigorous model with approximately the right features than on an explicit model with demonstrably wrong features.

Finally, **empirical evidence** was reviewed, producing the following highlights: Useful insights have been obtained from analysis of six kinds of data: aggregate cross-sectional quantitative data, micro cross-sectional quantitative data, panel data, cross country time series data, experimental data, and qualitative data.

Among the questions that have been asked and partially answered are: Are labor markets segmented? Why do people work informally? Why is the unemployment rate so low in most developing countries but so high in a few?

One area in which good empirical policy analysis has been conducted is an assessment of India’s employment protection laws. Recent work is marked by careful attention to welfare economic concerns and sophisticated econometric modeling.

On the other hand, an area in which many policy conclusions have been drawn, in my view unconvincingly, has been policies with respect to investments in education. In education as in many other areas, the existing studies do not provide the information that is needed for public policy: knowledge of how market conditions would change if a particular action were to be undertaken along with knowledge of how the marginal social benefits compare with the marginal social costs.

For labor market policy modeling to be persuasive, it must have an explicit and carefully-formulated objective or set of objectives, theoretical foundations that capture the essential stylized facts in the economy under consideration, and statistical/econometric evidence drawn from careful empirical studies. To the extent that any given study falls short of these criteria, our confidence in the policy conclusions reached falls short accordingly.

Many so-called policy implications do not stand up to the most basic scrutiny. When it comes to the question of what should be done from a policy point of view, few studies have reached convincing policy implications of the type, “Do A, not B, with the

> 7 And it especially is for World Bank operations officials.

56