rafmacalaba/datause-encoder-data huggingface dataset:
microfinance lenders; the Arab Republic of Egypt, with a maximum interest rate of 7 percent for commercial transactions; and Bangladesh, with a cap of 27 percent for microcredit loans. The United Kingdom currently has an absolute interest rate ceiling of 2 percent per month for credit unions, and Greece limits the credit rate of nonbanks to 6.75 percent per year. As illustrated above, the application of absolute interest rate caps is limited to specific types of credit or specific types of institutions (iff/ZE 2010).

Indications of _relative interest rate ceilings_ were found in 32 countries, most of them in SSA, LAC, ECA, and Western Europe. The majority of them use an endogenous benchmark rate, and only six use exogenous reference rates (see table A4).

Of those 26 countries that use _endogenous_ benchmark rates, 17 use the _multiplication coefficient_ over the reference rate, 7 use _fixed margins,_ and 2 use a combination. Some examples of countries using the _multiplication coefficient_ applied to an endogenous rate are Armenia, which has a ceiling of twice the banking rate; Estonia _,_ with a ceiling of three times the market average; Chile, with a maximum interest rate of 1.5 times the average interest rate; and Portugal, with a maximum rate equal to 133 percent of the average APR by type of credit. Countries that apply a _fixed interest margin_ to an endogenous reference rate are the Kyrgyz Republic and those in CEMAC, while Germany uses both a multiplication factor and a fixed margin to establish the maximum APR. In that case, the fixed margin of 12 percentage points serves as a second restraint on the dispersion of the ceiling from the mean (iff/ZEW 2010).

On the other hand, countries such as Belgium, Brazil, Mauritania, the Netherlands, and Spain use an _exogenous benchmark rate_ . Multiplication coefficients are used in Brazil, which caps the interest rate on commercial loans at two times the SELIC (Sistema Especial de Liquidação e Custodia) rate, and in Poland, which uses a coefficient of four times Lombard rate, that is, the rate that determines the cost of liquidity obtainable at the National Bank of Poland (NBP). In the Netherlands, the base rate is set on the basis of the European Central Bank rate plus a fixed margin of 12 percent. Belgium uses a more complicated method for calculating the cap _,_ where the references are derived from fluctuations of either the three-month Euribor or the one- or the two-year government bond rates (iff/ZEW 2010).

**2.2.5. Unique or Different Ceilings.** According to this study, most of the countries with interest rate caps establish different ceilings either on the amount of credit to be extended, the credit type, the duration of the credit, or a combination. Examples are Chile, which has nine categories of ceilings based on size, currency, and term; France, which calculates 12 caps based on the amount and type of credit; and Uruguay, where the interest cap depends on the amount of the loan. In addition, authorities sometimes impose different ceilings based on the type of institution to which the loan is made. For instance, Zambia

11
# **The Dog that Didn’t Bark: The Missed Opportunity of Africa’s Resource Boom**

James Cust<sup>1</sup> , Alexis Rivera Ballesteros<sup>1</sup> and Albert Zeufack<sup>2</sup>

**Keywords** : Africa, natural resources, growth, resource curse, commodities, poverty, growth.

**JEL:** O4, O13, Q3

> 1 World Bank. Office of the Chief Economist Africa Region. jcust@worldbank.org and alexis.rivera.b@gmail.com

> 2 Chief Economist, World Bank Africa Regions. azeufack@worldbank.org
Policy Research Working Paper 10893

# **Abstract**

This paper characterizes economically optimal investments in Africa’s road network in partial and general equilibrium —based on a detailed topography of the network, road con-struction costs, frictions in cross-border trading, and economic geography. Drawing from data on 144 million trans-continental routes, it first assesses local and global network efficiency and market access. It then derives a large network connecting 447 cities and 52 ports along the fastest routes, devises an algorithm to propose new links, analyzes the quality of existing links, and estimates link-level construction/upgrading costs. Subsequently, it computes market-access-maximizing investments in partial equilibrium and conducts cost-benefit analysis for individual links and several investment packages. Using a spatial economic model and global optimization over the space of networks, it finally elicits welfare-maximizing investments in spatial equilibrium. Findings imply that cross-border frictions and trade elasticities signifi-cantly shape optimal road investments. Reducing frictions yields the greatest benefits, followed by road upgrades and new construction. Sequencing matters, as reduced frictions generally increase investment returns. Returns to upgrading key links are large, even under frictions.

This paper is a product of the Office of the Chief Economist, Africa Region and the Kiel Institute. 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 author may be contacted at skrantz@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
36 TABLE 4

# ALTERNATIVE FORMS OF INTERGOVERNMENTAL GRANT PROGRAMS

<!-- Start of picture text --> Method of Determining the Total Divisible Pool<br>Method of Allocating Specified Share Reimbursement<br>the Divisible Pool of a Granting Ad Hoc of Approved<br>among Eligible Units Government Tax Decision Expenditure<br>Origin of Tax Collection A -- --<br>(general-purpose)<br>Formula B F --<br>(??) (??)<br>Cost Reimbursement C G K<br>(categorical) (ca*egorical) (categorical)<br>Ad Hoc Decision D H --<br>(??) (??)<br><!-- End of picture text --> SOURCE: Adapted from Roy Bahl and Johannes Linn, Urban Public Finance and Admin4stration in Less Developed Countries (Washington, DC: The World Bank, forthcoming).
-27-

The fact that the IMC is higher for coarse grains than for maize is consistent with the structure of the market discussed above and, to a degree, validates the model. Moreover, it is also noteworthy that only one of seven gari markets and two of nine yam markets in Nigeria studied by Heytens had an IMC lower than inter-commodity grain markets studied here. Furthermore, the intercommodity values for the IMC are also lower than 5 of the nine Indonesian maize market values in Timmer's (1987) study even though Asian markets are widely presumed to function more efficiently than those in Africa. That is, the price linkage in the markets studied is comparatively strong relative to other developing countries.

# RESULTS OF TESTS OF INTEGRATION AND COINTEGRATION

An alternative way of looking at the issue of information flows is to investigate co-integration within a single market. Table 2 reports tests of the integration of various price series as well of co-integration. The critical value reported in Engle and Granger is 3.37 at 5 percent level of significance and 4.07 at 1 percent. Schwert offers slightly different levels--levels which, moreover, vary if a trend variable is included. For our purposes, it is sufficient to note that one rejects the hypothesis that the series are I(l) unless one has a rather high critical value. The subsequent test of cointegration, then, must have at least the same critical values. The test of cointegration rejects the null hypothesis that the combination of the price series is I(l) at any plausible level of significance. The alternative hypothesis is
How do households in our sample compare with other households in Ecuador? Because of the criteria for selection into the BDH evaluation, households in the study sample tend to be poorer. Table 2 reports the means and standard deviations for selected characteristics of households in the study sample at baseline, for all households in the country, and for all households in the parishes included in this study. The samples for these calculations are limited to households with children ages 6-17. National averages are based on the 1999 _Encuesta de Condiciones de Vida_ , and averages for the parishes in the study sample are based on the 2001 Population Census. Table 2 shows that households in the sample have more members and fewer rooms than other households, are less likely to have access to piped water or a toilet, and are more likely to have a dirt floor in their home. Mean years of schooling of household heads in the study sample are more than two-and-a-half years lower than those of other households. These patterns are apparent both in comparison with other households in these same parishes, as well as in comparison with national averages.

# C. <u>Data</u>

The main sources of data used in this paper are the baseline and follow-up surveys designed for the BDH evaluation. Both surveys were carried out by an independent firm that had no association with the BDH program, the _Pontificia Universidad Católica del Ecuador._ The baseline survey was collected between June and August 2003, and the follow-up survey was collected between January and March 2005. The analysis in this paper is limited to households living in rural areas.

The survey instrument included a roster of household members and, _inter alia_ , information on the level of schooling attained, marital status, and languages spoken by all adults; school enrollment, grade progression, and work of all children ages 6-17; an extensive module on household expenditures, which closely followed the structure of the 1999 _Encuesta de Condiciones de Vida_ ; and a module on dwelling conditions, ownership of durable goods, and access to public services. We aggregated expenditures into a total consumption aggregate, and food expenditures into a food consumption aggregate. Food consumption includes both actual expenditures (including food consumed outside the home), as well as home production in the two weeks prior to the survey. Other expenditures include modules on schooling, health, entertainment, items for personal hygiene, clothing, shoes, transportation, services, and expenditures on durables. The items asked in the expenditure module, and the recall periods for each item, are exactly the same in the two surveys. We deflated prices across provinces using data on the prices of a basket of food items collected at the time of the baseline survey, and used the Consumer Price Index (CPI) to make the prices comparable between the two surveys.

7
Frustration and desperation because of poverty may lead to aggressive behaviors such as crime and violence. Moreover, effects impact other risk factors such as school dropout and push out. As described above, targeting at-risk youth needs to be based not only on income poverty indicators, but also on a number of risk and protective factors which will be addressed in the following sections.

# **4. Education and the Labor Market**

## **Education and Drop out and Push out**

Illiteracy is widespread in Haiti but has been rapidly decreasing since the 1970s. In 1970, 78 percent of the population was illiterate, while in 2000 less than 40 percent was (UNDP 2002). This marked drop is explained by increasing years of education, stemming from a great concern by Haitians about education. The general level of trust in schools and in teachers’ skills is great. This trust motivates most parents to send their children to school although public provision is scarce and quality is unregulated<sup>13</sup> (Salmi 2000). As a result, school attendance rates for children and youth are relatively high. Most schools are private and 80 percent of students attend these.<sup>14</sup> More than three out of four aged 6–14 attend school; however, at age 15–24 a transition naturally occurs from school into the labor market, which decreases school enrollment rates. Nevertheless, the decrease in school attendance is too rapid to provide secondary or tertiary education to a sufficient proportion of the youth. Table 4.1 reveals that nearly two out of three youth aged 15–22 abandon school altogether.

Table 4.1: Proportion undertaking Education 2001

|Age|Percent|Age|Percent|
|---|---|---|---|
|15–16|76.6|15–19|67.7|
|17–18|65.3|20–24|28.8|
|19–20|44.8|15–24|50.7|
|21–22|29.0|25–34|4.2|
|23–24|22.6|35–44|0.1|

_Source:_ Own calculations based on ECVH 2001.

In terms of educational attainment youth are doing better than older generations. The maximum level of education attained is higher for youth than their older peers even though more than 50 percent of youth are still enrolled. According to Table 4.2, 46.6 percent of youth had completed primary education in 2001. This is 54 and 64 percent more than the cohorts aged 25–34 and 35–44, respectively. A slightly larger proportion of youth than of the age group 25–34 has completed secondary education, while these

> 13 In a representative test of 1200 public and private schools in 1996, one-third of teachers at the primary level did not know how to rank words alphabetically (Salmi 2000).

> 14 While 80 percent of the limited public expenditures go to Port-au-Prince, spending on education represents only two percent of GDP, less than half of that of other developing countries (World Bank 2005b).

10
4 4 such as the frontier production function. We focus here on the latter.

Suppose for simplicity that the production function is Cobb-Douglas: (3) lny, = 00 + Ejpjlnxu + ui where y is output, the **xj** are inputs, the P's are output elasticities and u is an error term. Feldstein (1967) suggested that the residuals of eq (3) might be used as estimates of technical inefficiency, so that a hospital with a zero residual is said to be of average technical inefficiency, while a hospital with a positive (negative) residual is said to be of above-average (below-average) technical efficiency.5 A disadvantage of this approach is that it provides no information on the level of efficiency. Clearly, it is important to know whether inefficient hospitals are very inefficient or only marginally so. This defect can be overcome using the deterministic frontier model (DFM) of Aigner and Chu (1968), which differs from eq (3) in that it constrains the error term to be non-positive. Hospitals can thus operate on or below the production frontier but not above it, and the extent of technical inefficiency is indicated by the estimated residuals, u1. The DFM can be estimated using a variety of methods, the simplest of which is Corrected Ordinary Least Squares: this involves shifting up the OLS estimate of the intercept until one residual is zero and all the rest are negative.<sup>6</sup> There is, however, a second problem with Feldstein's approach, which is not overcome by the DFM, namely that it implicitly assumes that all cross-sample variation in the error term of the estimating equation is due to variation in efficiency. In reality the residuals are also likely to reflect random influences outaide the hospital's control, as well as statistical 'noise'. A better tool is the stochastic frontier model (SFM) [cf eg Aigner et al. (1977)]: (4) lny; = 00+ EjAjlnx1<sup>j+vj+ ui</sup> uiS0, so that the error term vj+u1<sup>is composed of two parts, v; being two-sided</sup> and capturing random shocks and statistical noise, and ui being one-sided and reflecting inefficiency, which is constrained to be 4. For surveys of parametric and non-parametric approaches to efficiency measurement see Schmidt (1986) and Barrow and Wagstaff (1989).

5. The rationale behind this is that the output of a hospital with a residual equal to zero is exactly the output that wouLd be expected of It given its input utilization and the average estimated productivity of the inputs. By contrast, a hospitaL with a positive (negative) residual produces more (Less) than it would have been expected to produce on the basis of its input usage and the estimated parameters of the production function.

- . Cf. Forsund, Lovelt and Schmidt (1980) and Schmidt (1986).
12

# Table S

# Market Price Distortion Indices

|Country||P|rice Distort|ion Index|
|---|---|---|---|---|
|||Total|<br>Labor|<br>CaRital|
|**Outward-focuse**|||||
|Malaysia||1.57|2|2|
|South Korea||1.57|1|2|
|Thailand||1.43|1|1|
|**Inrd4fcused**|||||
|Egypt<br>Nigeria|2.71|2.14|3<br>3|3<br>3|
|Tunisia|1.57||1|2|

Source: Agarwala, 1983.

Egypt and Nigeria, for example, with strongly inward-focused trade regimes exhibit the highest levels of market price distortions. Outward-focused trade regimes in Malaysia, South Korea, and Thailand, on the other hand, are associated with low levels of market price distortion. The only exception to this pattern seems to be Tunisia, which is described above as moderately inwardfocused, but whose price distortion index matches that of countries like South Korea. Here, in the case of labor market price distortions, Agarwala's Judgement conflicts with a later U.S. Agency for Intemational Development study (Rucker, 1990) which found strong evidence of policy distortions In Tunisian labor markets.

Agarwala referred to the difficulty of comparing labor market price distortions since very few developing countries have systematic data on wages and productivity. His basic Indicator was whether real wages In manufacturing rose significantly faster than per capita real income adjusted for changes In extemal terms of trade. He also included In his subjective ranking any signfficant evidence of govemment and trade union interventions In labor markets. In Egypt and Nigeria, he
|||-0.67|-0.79|-1.04||0.18|0.14|-0.23||-1.57|-1.52|-1.47|
|---|---|---|---|---|---|---|---|---|---|---|---|---|
|Average Wage<br>2009||-0.001**|-0.001**|-0.001***||-0.001*|-0.001**|-0.001**||0|0|0|
|||-2.08|-2.36|-2.63||-1.87|-1.97|-2.15||-0.5|-0.55|-0.47|
|Population||0.009***|0.006***|0.006***||0.006**|0.005**|0.005**||0.126***|0.119***|0.123***|
|||3.56|2.76|2.66||2.25|2.1|1.98||6.78|6.3|6.35|
|Share Ukrainian||6.568***|6.579***|6.518***||4.626***|4.722***|4.614***||7.418***|7.448***|7.465***|
|||12.88|12.88|12.85||6.83|6.97|6.9||9.49|9.51|9.52|
|Participation<br>Ratio||||0.046***||||0.180***||||-0.012|
|||||6.25||||12.71||||-1.39|
|_cons|148.970***|150.224***|154.541***|151.036***|148.271***|150.637***|156.805***|142.434***|141.009***|141.960***|142.554***|143.334***|
||183.11|139.74|113.34|101.81|131.2|98.1|65.05|53.01|63.84|59.46|52.72|51.8|
|R Adj sq.|0.195|0.211|0.214|0.218|0.321|0.333|0.337|0.376|0.038|0.056|0.056|0.057|
|N|10503|10485|10485|10485|4876|4873|4873|4873|5627|5612|5612|5612|

The regression also includes oblast dummies, dummies for different types of schools and evening schools. The full table can be found in excel tables which can be made available upon request. *** means significant at the 1% level, ** at the 5 % level and * at the 10 percent level. T statistics are based on robust standard errors for the OLS specifications.

43
23

# **VII.   TABLES**

# **Table 1**

|Dependent variable:|Panel A<br>Exports of<br>1996‐2012|: Growth o<br>Goods an<br> 1996‐2003|f Total<br>d Services<br> 2004‐2012|Panel<br>Exp<br>1996‐2012|B: Growth<br>orts of Go<br> 1996‐2003|of Total<br>ods<br> 2004‐2012|Pan<br>Manu<br>1996‐2012|el C: Grow<br>facturing E<br>1996‐2003|th of<br>xports<br> 2004‐2012|
|---|---|---|---|---|---|---|---|---|---|
|Real Exchange Rate Change|**‐1.202 *****<br>0.184|**‐1.417 *****<br>0.215|**‐0.702 *** **<br>0.051|**‐1.173 *** **<br>0.223|**‐1.383 *****<br>0.261|**‐0.626 *** **<br>0.094|**‐1.099 *****<br>0.246|**‐1.294 *****<br>0.300|**‐0.615 *****<br>0.120|
|Lag real GDP|**‐2.782**<br>3.038|**‐0.058**<br>13.277|**‐17.015 *** **<br>3.458|**‐1.808**<br>3.213|**‐8.155**<br>19.558|**‐19.562 *** **<br>3.460|**‐4.387**<br>3.901|**‐15.084**<br>21.896|**‐18.643 ****<br>7.579|
|Foreign real GDP|**0.743**|**1.003**|**0.510**|**1.523**|**1.310**|**1.541 ****|**1.374 ***|**1.710**|**1.230 *****|
||0.829|1.610|0.459|0.969|1.820|0.630|0.797|1.696|0.408|
|Time Fixed Effects|Y|Y|Y|Y|Y|Y|Y|Y|Y|
|Country Fixed Effects|Y|Y|Y|Y|Y|Y|Y|Y|Y|

Source: Exports of Goods and Services are from OECD‐WTO TiVA processed by Duval _et al._ (2014), exports of goods and manufacturing exports from UN Comtrade.

Note: *** indicates statistically significant 1%, ** indicates statistically significant at 5%, and * indicates statistically significant at 10%. Point estimates in bold letters and robust standard errors below.

Countries as in the Appendix.
in a period of time without imposing an average delay that exceeds a pre-established or reasonable level, for instance delays to departing flights average four minutes at peak hours. On the other hand, saturation capacity refers to the maximum number of aircraft that can be served in a given period of time under continuous demand conditions.

Airports are productive units whose capacities can only be increased through the incorporation of large and indivisible units. If runway capacity at a given airport is equivalent to a maximum number of "n" airplanes per period, and the airport operates below that level, the cost of operating an additional plane would be equal or close to zero. However, if such an airport operates at full capacity, to increase traffic would require the construction of a new runway. Therefore, if traffic volume at peak periods increases sharply, obliging the construction of another runway, this would imply capacity underutilization at off-peak hours. Fluctuations in demand for airport services and investment indivisibilities, leads inevitably to excess capacity, with important repercussions on the cost structure of the airport industry. Peak period pricing, however, may help to lessen that problem and allow for more efficient capacity allocation.

The shape of the cost curve for runways exhibits a positive slope for traffic volumes below available capacity. Instead, once capacity is surpassed, the cost grows asymptotically. This cost is known as capacity cost and its behavior is shown at Figure 1.2. **Figure 1.2. Runways Costs Functions** <!-- Start of picture text --> Total<br>Costs<br>K 2<br>K1<br>C C 2 Passengers<br>K ,: Sm all runway capital cost<br>K2: Large runway capital cost<br>C,: Small runway capacity<br>C2: Large runway capacity<br><!-- End of picture text --> Source: Walters (1978).

Terminal building capacity is becoming more important as non-aeronautical airport services are given a greater weight as a result of the emerging role of the private sector. Commercial and other activities carried out in the terminal building require large spaces. This capacity can be evaluated by considering two important variables: _level of service_ and _volume of service._ Level of service is closely linked to quality. Space, waiting time, comfort experienced by users or treatment provided by airport staff, are all determinants of quality.

_7_