rafmacalaba/datause-encoder-data huggingface dataset:
- Billing, including identifying consumers, keeping track of consumption/metering, and delivering billing statements

- Collection of debts due, including the physical process of collecting bills, the credit risk of consumers, and the design and implementation of penalty mechanisms for those who fail or refuse to pay.

The demand profile is often very difficult to assess. For example, demand for transportation infrastructure is influenced by competing modes of transportation, demographic shifts, economic conditions, the cost of the facilities to end-users, convenience, individual preference, speed and a number of other, often interrelated factors that make accurate demand forecasting difficult at best. The inherent vulnerability of traffic forecasts to optimism bias was demonstrated in a Standard & Poors study from 2002 of traffic forecasts in user-fee based toll road schemes, in particular out of 32 different projects, actual traffic was on average only 70% of that forecast, with a large majority of projects not reaching even 90% or the forecast traffic. Lenders achieved the greatest accuracy in their forecasts, but still only achieved an 82% performance ratio, while sponsors and investors were down at 66%.

# **Tariff levels and payments**

The level at which tariffs are set for services can be an extremely political issue. Historically, utility tariffs may have been used to subsidize certain elements of society, specific industries or public sector entities. More often, public utilities are subsidized and tariffs are not charged, charged at very low rates or not collected. PPP may necessitate formal arrangements with the project company for government subsidies or financing, particularly where the government is not willing to put tariffs up to profitable levels or where substantial investment in capital works is needed or desired. Though challenging, this can be a healthy transition for the utility, formalizing the subsidy for the sector and rendering transparent the burden on the public purse represented by artificially low tariffs.

# **Regulation**

Regulation is of particular interest for the operating function, as the regulator is likely to need to work closely with the project company to establish a baseline of data to be used for tariff setting, arguing for additional tariff increases, coordinating tariff with capital investment plans and responding to changes in law 47
**... while pursuing a stable and competitive real effective exchange rate**<sup>**43**</sup> **.** Despite the current incentives of the Central Bank (favorable to an appreciating exchange rate because of the large dollar-denominated external debt and its effects on income statements), a volatile and appreciated currency is not conducive to the expansion of new exportables, and negatively affects the production of tradables (Williamson, 2003; Prasad, Rajan, and Subramanian, 2007). Hence, to foster the diversification of the industrial base, to induce investment and entrepreneurship in tradables, and to promote the production and export of non-traditional manufacturing and services, it is necessary to pursue a stable and competitive real effective exchange rate (Dooley, Folkerts-Landau, and Garber 2003; Rodrik, 2006 and 2007a).<sup>44</sup>

# **Box 2. Getting the exchange rate right**

**A competitive exchange rate helps achieving rapid and sustained growth.** In the past decades, fastgrowing developing countries have simultaneously exhibited not-overvalued real exchange rates, high domestic savings, and current account surpluses. China is the present-day example, but in recent years this was the case also in high-performing Asian economies such as Korea, Malaysia, and Thailand, as well as in Chile. The opposite (an appreciated real exchange rate, low domestic saving, current account deficits - and low growth) is also recognized in the international experience (e.g., Mexico in 1993, Russia and Brazil in 1998, and Argentina and Turkey in 2000).

**The boost in aggregate demand accelerates investment and employment.** Assuming no supply constraints (i.e., local growth is not constrained by a lack of supply capacity, but by a shortage of demand), a competitive exchange rate increases demand for exports and import substitutes, and motivates entrepreneurs to produce non-traditional export commodities, expanding investment, employment, and economic grow. Conversely, when capital inflows appreciate the real exchange rate, growth gets hurt by reduced investment incentives.

_Source:_ Balassa 1984; Williamson, 2003; Prasad, Rajan, and Subramanian, 2007; Rodrik, 2006 and 2007a.

**How to do it?** To help identifying “ _what the country is good at producing_ ” (Hausmann and Rodrik, 2003) and, consequently, foster investments and determine the pattern of specialization, PEZA should make convincing commitments to improving the performance of the economic zones. In particular, it should: (i) provide non-fiscal incentives to the construction _in loco_ of first-rate infrastructure - e.g., via public-private-partnerships (PPP – see page 40); (ii) guarantee simplified business procedures; (iii) enhance in situ competition,

> 43 See footnote 3 page 7.

> 44 China and India have made a “stable and competitive real exchange rate” an explicit policy objective (Rodrik, 2006).

38
COST RECOVERY, EQUITY, AND EFFICIENCY IN WATER TARIFFS IN AFRICA household tariffs, suggesting cross-subsidization of residential consumers by high-volume industrial and commercial consumers.

# 6 A scorecard of tariff performance

A scorecard compiled on the basis of cost recovery, efficiency, and equity criteria suggests that many utilities are able to balance these goals, a majority of the utilities meet one of the conditions, and a few score low on all the conditions (table 9 and annex J). ELECTRA in Cape Verde has the most effective tariff structure and scores high on equity, efficiency, and cost recovery. The other outstanding performers are Oshakati, Windhoek, STEE, SONEB, and Katsina WB. These utilities impose the most efficient pricing mechanism, complemented by cost recovery and equity. STEE in Chad and AWSA in Ethiopia are implementing the most equitable tariff structure. ELECTRA, Oshakati, Windhoek, STEE, SONEB, and Katsina WB score the highest in efficiency. The cost-recovery conditions are met by four utilities— ELECTRA, Oshakati, Windhoek, and eThekwani—located in the MICs of Cape Verde, Namibia, and South Africa.

**Table 9. Final scorecard for meeting tariff objectives: cost recovery, efficiency, equity**

|Criterion|Maximum<br>score|Average (%)|Utilities scoring above average|
|---|---|---|---|
|Equity|4|51|ELECTRA, AWSA, NWASCO, SEEN, Katsina WB, FCT, Kaduna WB,<br>Electrogaz, NWC South Darfur, SDE, STEE, DAEASCO, NWSC,<br>Drakenstein, NWSC|
|Efficiency|3|45|SONEB, ONEA, ELECTRA, Dire Dawa, GWCL, KIWASCO, WASA,<br>CRWB, Oshakati, Windhoek, Walvis Bay, Katsina WB, FCT,<br>Electrogaz, Upper Nile, STEE, Johannesburg, Tygerberg|
|Cost recovery|2|22|SONEB, ONEA, SODESI, NWASCO, WASA, JIRAMA, BWB,<br>Oshakati, Windhoek, SEEN, NWC Upper Nile, NWC Khartoum, SDE,<br>DAEASCO, NWSCO, eThekwani, SWSC|
|One point is awar<br>[1] Cost recovery<br>[2] Cost recovery<br>[3] Efficiency: No<br>[4] Efficiency: Me<br>[5] Efficiency: Th<br>[6] Equity: Small<br>[7] Equity: Standp<br>[8] Equity: Conne<br>[9] Equity: Reside|ded for each of<br>: O&M cost reco<br>: Capital cost re<br>fixed charge or<br>tering ratio is hig<br>e price of the las<br>piped consumer<br>ost consumers<br>ction cost as sh<br>ntial consumers|the following criteria:<br>very<br>covery<br>minimum consumption<br>her than sample avera<br>t block meets the capit<br>s (at 4 m<br>3) pay less tha<br>pay less than small pip<br>are of GNI per capita is<br>pay less than nonresid|charge<br>ge (77%)<br>al cost<br>n average piped consumers (at 10 m<br>3)<br>ed consumers (at 4 m<br>3)<br>lower than sample average (27%)<br>ential consumers at 100 m<br>3of consumption|
|_Source:_AICD W|SS SurveyData|base,2007.||

# 7 Conclusion

Cost recovery is a mandate for water and sanitation utilities in Africa, and African utilities perform well in recouping at least the cost of operations and maintenance (O&M) from their tariff structure. But only 36 percent of the utilities surveyed in this paper are meeting their full O&M cost (assuming an 24
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_A-_ measures has been successful in raising GDP growth rates. domestic savings ratios, and export ratios, though these gains are more moderate for low income couAAti ies than for others. However, the reviews have also found that in many countries, external viability has not been achieved.

# _2. Empiical Evidence_

The volume of foreign assistance increased sharply in Sub-Saharan Africa during the 10-year period 1981-90. Figure 1 represents data on the average annual inflow of net official development assistance (ODA) I adjustment in SSA: Ghana, Kenya, Malawi, Tanz2nia, and Uganda. For purposes of comparison, tlde period is divided into two halves: the years 1981-85 define the prereform period and the years 1986-90 define the period of reform.' The substantial increase in aid in all five countries during the period of reform i striking. Figure 1 also shows that Tanzania has remained the largest recipient of foreign assistance, both in the rre-reform period and during the period of reform.

- 2 The source for all daa on ODA are the World Bank's World Development Repoit, nd the African Development Indicators (UNDP/World Bank, 1992), which obtain this data from the OECD. The OECD databae is based on reporting from donors. In this databae, ODA is defrued to include outrigkt debt cancellations by donors but not the debt reschedulings grnted under the auspices of the Paii Club.

- 3 The time period under review is held constant in this paper, despite slight differnce in the period when refornm were introduced in different countries, in order that extenal tems of trade **shocks** could be eliminated as a sourme of difference between the econoiic perforr=ncs of these countries.
# **II. Determinants of poverty reduction and intra-generational mobility**

20. **This section shifts from stylized facts about poverty, inequality and shared prosperity to the analysis of determinants of observed changes in wellbeing and intra-generational mobility.** Income poverty decompositions are used to quantify the contribution of different factors to changes in welfare and inequality across classes, areas and gender. Having identified the labor market’s contribution as the most important driver of poverty reduction in Turkey, we explore the mechanisms behind this impact.

## _2.1 Drivers of changes in poverty, inequality and intra-generational mobility_

21. **The labor market was the most important factor driving poverty reduction in Turkey in the 2000s.** As income and consumption poverty trends are very similar in Turkey, an income poverty decomposition was used to quantify the contribution of different factors to poverty reduction (see figure A.4 in annex). As shown in figure 3.1, overall income poverty declined by 30 percentage points between 2002-2011 years. Labor market (earnings and added worker effect<sup>7</sup> ) was responsible for 18 percentage points of this reduction, making it the largest single contributing factor. The role of pensions was important as well, accounting for 7 percentage points, with demographics (share of adults) and social assistance each accounting for 3 percentage points of poverty reduction.

22. **The relative contribution of different factors to poverty reduction is not the same across urban and rural areas.** Social assistance, pensions and added worker effect played a more important role in rural areas in relative terms. For example, pensions were responsible for more than one third of poverty reduction in rural areas compared to 20 percent in urban areas. In contrast, labor earnings played a more important role in urban areas. Thus, labor earnings were responsible for 42 percent of poverty reduction in urban areas compared to 28 percent in rural areas (figure 3.3).

**Figure 3.1: Income poverty decomposition, Figure 3.2: Income Gini decomposition, 20022002-2011 2011**

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> 7 The added worker effect (share of employed) measures the impact of having household members with non-zero labor income.

15
country differences in the quality of governance, our focus here is limited to measuring the perceptions of interested parties -- residents of a country, entrepreneurs, foreign investors, and civil society at large -- regarding the quality of govemance in a country. Although this kind of data is inherently subjective, there are several reasons why it is useful in measuring governance. First, for many issues such as the prevalence of corruption, objective data is almost by definition rather difficult to obtain. There are few alternatives to subjective indicators if one wishes to measure these aspects of govemance. Second, perceptions of the quality of governance may often be as important as objective differences in institutions across countries. While a country may nominally enjoy a set of sound institutions according to certain standards, the confidence of residents of a country in these institutions is also required if they are to contribute to good govemance. Third, we have found in other work that subjective perceptions can have significant explanatory power for future economic outcomes.<sup>4</sup> We use our definition of govemance to organize a subset of the govemance indicators into six clusters. We summarize two key aspects of the process by which those in authority are selected and replaced with clusters labelled "Voice and Accountability", and "Political Instability and Violence". We capture the capacity of the state to implement sound policies with two clusters we refer to as "Government Effectiveness" and 'Regulatory Burden". Finally, two clusters labelled "Rule of Law" and "Graft" capture the respect of citizens and the state for the rules which govem their interactions. For each of these six clusters, we use the procedure laid out in Kaufmann, Kraay and Zoido-Lobat6n (1999) to construct aggregate governance indicators. The advantage of these aggregate indicators is that they span a much larger set of countries than most individual indicators, permitting cross-country comparisons of between 155 and 173 countries, depending on the aggregate. More important, the aggregation method we use provides quantitative measures of the precision of both the aggregate governance indicators and their components, allowing formal statistical testing of hypotheses regarding cross-country differences in govemance along these dimensions.

(Stanford University), in an effort coordinated by the Center for Intemational Development at Harvard University.

In the context of the East Asian financial crisis, Kaufmann, Mehrez and Schmukler (1999) find that investor perceptions of future financial instability had significant explanatory power for future actual volatility, over and above available macroeconomic data.

2
- OECD (2007 ), _PISA 2006: Science Competencies for Tomorrow's World: Volume 1: Analysis_ , PISA, OECD Publishing, Paris, http://dx.doi.org/10.1787/9789264040014-en.

- OECD (2004), _Learning for Tomorrow's World: First Results from PISA 2003_ , PISA, OECD Publishing, Paris, http://dx.doi.org/10.1787/9789264006416-en.

- OECD (2001), _Knowledge and Skills for Life: First Results from PISA 2000_ , PISA, OECD Publishing, Paris, http://dx.doi.org/10.1787/9789264195905-en.

Reporters Without Borders (2014), _World Press Freedom Index 2014,_ Reporters Without Borders, Paris, France.

SACMEQ (www.sacmeq.org) UNESCO (2015), _Education for All 2000-2015: Achievements and Challenges_ , UNESCO, Paris. Report (http://en.unesco.org/gem-report/report/2015/education-all-2000-2015- <u>achievements-and-challenges#sthash.QTUk60tu.dpbs</u> UNESCO Regional Office for Education in Latin America and the Caribbean (10 April 2014) “The Latin-American Laboratory for the Assessment of the Quality of Education (LLECE): Associated Factors. Presentation in Washington, DC.

UNESCO Regional Office for Education in Latin America and the Caribbean (n.d.) Mapa de Evaluaciones Educativas (www.unesco.org/santiago) Wagemaker, H. (2014), "International Large-Scale Assessments: From Research to Policy", in L. Rutkowski, M. v. Davier, & D. Rutkowski. (eds.), _Handbook of International Large-Scale Assessment: Background, Technical Issues and Methods of Data Analysis_ , Taylor and Francis, New York.

Walker, M. (2011), _PISA 2009 Plus Results: Performance of 15-year-olds in Reading, Mathematics and Science for 10 Additional Participants._ ACER Press, Victoria.

Woessmann, L. (2002), "Cross-country Evidence on Human Capital and the Level of Economic Development: The Role of Measurement Issues in Education", _Historical Social Research,_ Vol. 27, No. 4, pp. 47-76. GESIS.

World Bank (2015 April) World Bank EdStats.

World Bank (2015), _Worldwide Governance Indicators,_ World Bank, Washington DC.

World Bank (2015) historical country classification (https://datahelpdesk.worldbank.org/knowledgebase/articles/378834-how-does-the-world-bank- <u>classify-countries)</u> World Bank (2014). _Doing Business 2015: Going Beyond Efficiency_ , The World Bank, Washington DC.

20
Hence, child labor is not a serious problem in rural Argentina and, furthermore, the majority of children may be both working and studying.

# **6. Factors Explaining Rural Labor Income**

After a short and simple presentation of wages and incomes, this section addresses determinants of wages in dispersed rural areas in Argentina. It looks at factors determining rural wages and investigates the characteristics that differentiate low and high paid workers.

<mark>Workers located at different points in the wage distribution are compared to analyze this issue, using a quantile regression methodology based on the RHS from 2003. Wages are compared across workers grouped by gender, education, experience, labor status, and location. Findings indicate that wages are by no means determined in the same way for high and low paid workers. For example, female workers are paid much less than males working in the high end of the wage distribution relative to their peers in the low end of the distribution, and returns to lower levels of education are far smaller in the upper income quantiles than in the lower ones.</mark> The quantile regression methodology characterizes the distribution of labor income in more detail than traditional ordinary least squares (OLS) and two stage least squares (2SLS) regressions, as it makes it possible to break down the wage determination process across the entire wage distribution. Specifically, this section addresses the determinants of rural labor incomes of employees and self-employed, including investigations of differences between low and high paid workers (the next section addresses agricultural producer incomes). Comparisons of workers age—14 and older—located at different locations in the labor income distribution shed light on these questions. Labor incomes are compared across workers organized by gender, education, skills, labor status, sector, and location.

Labor incomes are modeled by using log annual labor incomes as the dependent variable. The general model contains explanatory variables in levels and allows for nonlinearities in the data. For example, the log labor income equation is found to be nonlinear in education. In addition, the model contains dummy variables that take the value of one if, for example, a worker holds a job in the formal sector, and zero otherwise. Such a dummy variable may reveal whether there is an income premium related to formal sector employment. The 25<sup>th</sup> , 50<sup>th</sup> , 75<sup>th</sup> , and 90<sup>th</sup> quantiles are used in the analysis. Findings indicate that labor incomes are by no means determined in the same way for high and low paid workers. Findings for dispersed rural areas in Argentina are presented in Table 6.1.

All of the included variables are significantly different from zero for all quantiles. Each explanatory variable will now be discussed in turn: education, experience, labor market association and status, sector, gender, and geographical location.

Having completed primary education contributes to better wages, and the premium increases rapidly with the level of education attainment. Better-educated individuals in 20