rafmacalaba/datause-encoder-data huggingface dataset:
- 17 -

nominal freight rate of 5.6 per cent which is the lowest figure reported for any developing country group. Freight rates for the Central American Common market (Guatemala, El Salvador, Honduras and Costa Rica) were almost exactly double (11.3 per cent) the Caribbean rate while the average LAFTA rates were about one and one half points higher. As far as individual countries are concerned Guyana recorded the highest ad valorem freight rate in the Caribbean group (13.1 per cent), due largely to its high concentration of exports of nonferrous ores while the corresponding freight factors for Barbados, Haiti and the Leeward and Windward Islands are all under four per cent.

For several countries listed in Table 3 aggregate ad valorem freight rates exceeding 10 per cent are recorded with Guinea facing freight rates that are approximately one-quarter the f.a.s. value of its exports. In each of these cases the results are due almost exclusively to a concentration of bulky low value items in exports like crude agricutural materials or ores (i.e., over 90 per cent of Guinea's exports are metal ores; 65 per cent of Liberia's exports are iron ore; over 50 per cent of Chile's exports are copper, iron ore concentrates or nonferrous ores, etc.) rather than geographic location. 12/ Table 4 attempts to reduce the influence of these product-mix variations on the transport cost comparisons by analyzing differences in freight rates for tariff line level products (i.e., the most finely specified

- _ll/_ For land-locked countries like Nepal or Paraguay, United States import statistics reflect transport costs from the first port of exportation (which in these cases would likely be in a neighboring country) to the entry port in the United States. As such, the statistics do not reflect the costs of overland transport to the port of the exporting country. Similarly, for other countries listed in Table 3 the data do not reflect internal transport costs from the point of production to the point of export. For some countries studies have shown that these internal transport costs may be considerably higher than international freight costs involved in shipments from port-to-port (See Livingston 1986).
# PPR Working Paper Series

||Thle|Author|Date|Contact<br>or paper|
|---|---|---|---|---|
|WPS127|Linking Development, Trade, and<br>Debt Strategies in Highly Indebted<br>Countries|Ishac Diwan|November 1988|I. Diwan<br>33910|
|WPS128|Public Finances in Adjustment Programs|Ajay Chhibber<br>J. Khalilzadeh-Shirazi|December 1988|A. Bhalla<br>60359|
|WPS129|Women in Development: Defining the<br>Issues|Paul Collier|December 1988|J. Klous<br>33745|
|WPS130|Maternal Education and the Vicious<br>Circle of High Fertility and Mal-<br>nutrition: An Analytic Survey|Matthew Lockwood<br>Paul Collier|December 1988|J. Klous<br>33745|
|WPS131|Implementing Direct Consumption<br>Taxes in Developing Countries|George R. Zodrow<br>Charles E. McLure, Jr.|December 1988|A. Bhalla<br>60359|
|WPS132|Is the Discount on the Secondary Marke|t|||
||A Case for LDC Debt Relief?|Daniel Cohen|November 1988|M. Luna<br>33729|
|WPS133|Lewis Through a Looking Glass: Public<br>Sector Employment, Rent-Seeking and<br>Economic Growth|Alan Gelb<br>J.B. Knight<br>R.H. Sabot|November 1988|A. Hodges<br>61268|
|WPS134|International Trade in Financial<br>Services|Silvia B. Sagari|January 1989|W. Pitayatonakarn<br>60353|
|WPS135|PPR Working Papers Catalog<br>of Numbers 1 to 200|PPR Dissem. Center|August 1988|Bookstore<br>32941|
|WPS136|Pricing Commodity Bonds Using<br>Binomial Option Pricing|Raghuram Rajan|December 1988|J. Raulin<br>33715|
|WPS137|Trends in Nontariff Barriers of<br>Developed Countries: 1966 to 1986|Sam Laird<br>Alexander Yeats|December 1988|J. Epps<br>33710|
|WPS138|Fiscal Adjustment and Deficit<br>Financing During the Debt Crisis|William R. Easterly|January 1989|R. Luz<br>61760|
**Table 13: Impacts of falling oil prices**

|**Country**|**% of electricity**<br>**generated**<br>**domestically**<br>**from HFO and**<br>**diesel**<sup>**a**</sup>|**Fuel cost**<br>**saving as %**<br>**of current**<br>**GDP**|**QFD as % of**<br>**current**<br>**GDP**|**Expected QFD**<br>**as % of current**<br>**GDP at Brent**<br>**price of**<br>**$52/barrel**|**Expected QFD as % of**<br>**current GDP at**<br>**benchmark**<br>**performance at**<br>**$52/barrel**|
|---|---|---|---|---|---|
|São Tomé and||||||
|Príncipe|91%|2.04%|6.1%|4.0%|-1.3%|
|Seychelles|98%|2.00%|-0.3%|-2.3%|-2.8%|
|Gambia,The|100%|1.91%|5.8%|3.9%|-0.6%|
|Comoros|100%|1.64%|4.1%|2.5%|-0.8%|
|Senegal|100%|1.50%|2.2%|0.7%|-0.5%|
|Cape Verde|87%|1.37%|1.6%|0.3%|-1.7%|
|Mauritius|41%|0.71%|0.4%|-0.3%|-0.7%|
|Mauritania|100%|0.69%|1.5%|0.8%|-0.3%|
|Burkina Faso|90%|0.52%|1.0%|0.5%|0.0%|
|Madagascar|41%|0.33%|2.2%|1.9%|0.1%|
|Rwanda|60%|0.36%|1.0%|0.7%|0.1%|
|Togo|70%|0.33%|1.6%|1.3%|-0.7%|
|Mali|77%|0.33%|1.3%|1.0%|0.3%|
|Cameroon|24%|0.23%|0.7%|0.4%|-0.3%|
|Liberia|100%|0.29%|0.4%|0.1%|-0.3%|
|Guinea|26%|0.23%|2.1%|1.9%|0.7%|
|Sudan|19%|0.18%|1.4%|1.2%|1.1%|
|Tanzania|16%|0.20%|0.3%|0.1%|-0.3%|
|Burundi|28%|0.17%|1.0%|0.8%|0.3%|
|Sierra Leone|33%|0.16%|0.9%|0.7%|-0.1%|
|Niger|77%|0.15%|0.5%|0.3%|-0.2%|
|Gabon|8%|0.10%|0.4%|0.3%|-0.3%|
|Kenya|19%|0.10%|0.8%|0.7%|0.3%|
|South Africa|2%|0.07%|3.4%|3.4%|2.7%|
|Botswana|4%|0.06%|3.4%|3.3%|3.0%|
|Uganda|4%|0.03%|-0.1%|-0.1%|-0.4%|
|Central African<br>Republic|2%|0.01%|0.4%|0.4%|-0.1%|
|Zambia|0%|0.01%|1.2%|1.2%|0.8%|
|Benin|100%|0.01%|0.3%|0.3%|-0.3%|
|Ethiopia|0%|0.00%|1.7%|1.7%|1.1%|
|Lesotho|0%|0.00%|0.5%|0.5%|0.1%|
|Congo,Rep.|0%|0.00%|0.6%|0.6%|-0.1%|
|Mozambique|0%|0.00%|0.9%|0.9%|0.1%|

_Source_ : World Bank staff calculations.

a. Imports including purchases from regional SPVs are excluded, meaning there may not be a direct correlation between dependence on oil based generation and fuel cost savings.

The reduction in the cost of electricity service as a share of GDP in the reference year does not take into account the impact of oil price on GDP. The impact is likely to be positive in net importers and negative in net exporters heavily dependent on oil. However, two leading net exporters in SSA which would have seen a large negative effect of the low oil price on GDP—Angola and Nigeria—are not among the countries analyzed.

The results in Table 13 show that the cost savings from the drop in oil prices are expected to be greater than 1 percent of GDP in six countries (São Tomé and Príncipe, Seychelles, The Gambia, Comoros, Cape Verde, and Senegal). The price reductions would remove the QFD in Mauritius. The QFD is reduced to 58
24 labor-intensive.<sup>15</sup> In this way, the industrial structure of non-state enterprises aligned itself more closely with China's regional and even international comparative advantages. The entry of TVEs alleviated the structural imbalances that had been caused by a development strategy focussed on heavy industry.

**Table** 4: **Growth Rate of Output and Total Factor Productivity**

||1980-B8|1980-84|1984-88|
|---|---|---|---|
|State Sector||||
|Output|8-49|6.77|10.22|
|TFP|2.40|1.80|3.01|
|Collective<br>Sector||||
|OutDut|16.94|14.03|19.86|
|TFP;P|4-63|3.45|5.86|

Source: World Bank (1992), Reform and Role of the Plan in the 1990s, Washington, D.C-

# Macro-Policy Environmental Reform

In the traditional economic structure, the distorted macro-policy environment was linked most closely to the development strategy- It had on!y indirect effects on allocative and technical efficiency. Reform of macro-policies was the most sluggish element in the system. Later, we will argue that most economic problems that appeared during the reforms - for example, the boom-and-bust cycle and the rampant rent seeking - could be attributed to the inconsistency between the distorted policy environment and the liberalized allocation and 15 For example, in 1 986 the average industrial enterprise in China had 179.9 workers, and the fixed investment per worker was 7510 yuan (China Industrial Economy Statistical Material 1987, p. 3). Whereas the average TVE in the same year had 28.9 workers, and the fixed investment per worker was 1709 yuan (Statistical yearbook of China 1987. p. 205).
indicators), a stabilizing effect is still present in 9 of them (or 10%). Additionally, the analysis of the de-trended variables indicates no stabilizing effect in 11 of the 41 countries that have a counter-cyclical REM.

The stabilizing or destabilizing impact of the various capital inflows may depend not only on their stochastic behavior, but also on their share in GDP.<sup>9</sup> Examining the 37 countries with share of remittances in GDP higher than the mean value of 5.75 % (Table 1), we find REM and GDP to be positively correlated in 29 countries. Of these, REM is destabilizing in 19, has no impact in 6, and is stabilizing in 4. In other words, REM is not destabilizing in one third of the countries where REM is pro-cyclical. Based on the de-trended variables, the results indicate that among the 10 countries with counter-cyclical REM, for 5 there is stabilization, for 2 - no effect, and for 3 - a de-stabilizing impact. Thus, based on de-trended variables, REM is only stabilizing in 50% of the countries where it is counter-cyclical.

Our results about the stabilizing impact of remittances come at odds with the negative and significant coefficient of remittances found by IMF (2005) in the regression explaining output volatility. However, the volatility definition used in that study consists of the standard deviation of output growth, while we define it as the coefficient of variation over the period examined. Moreover, the IMF study measures remittances using the remittances/GDP ratio, hence the finding of a negative impact might be due to the fact that this ratio would be negatively correlated with GDP even in the case where remittances were constant and possibly even if remittances were pro-cyclical. On the other hand, we use for each individual country the actual level of remittances rather than its ratio to GDP.

# 5. Conclusions

That remittances are a stable and growing source of foreign exchange and are more stable than foreign direct investment (FDI) and official development aid (ODA) flows seems to have become the received wisdom. To check this and other findings in the previous literature, this study investigated the stability, cyclicality and stabilizing impact of remittances, FDI and ODA. Both at the country and aggregate levels, it was found that REM is less stable than ODA, but more stable than FDI. Second, while ODA is counter-cyclical in 54% of the countries (43% according to analysis based on de-trended indicators), remittances and FDI are pro-cyclical in between 80% 9 Acosta et al (2008) show that the inequality-reducing effects of remittances are comparatively larger in countries where remittances represent a higher share of income.

16
# **Appendix 8: Comparison of GEM and non-GEM Business Service Providers**

In order to compare the characteristics of the business service providers offering services in the GEM program to other providers in the market, we conducted a survey of 333 service providers (62 GEM service providers and 271 non-GEM service providers). This covered all four types of service providers in the program: accounting firms, marketing firms, HR providers, and general business consultants. The sample of non-GEM service providers was obtained through industry association lists, online searches, word of mouth, and business directories. Kantar TNS RMS surveyed these providers between November 2017 and June 2018.

Overall, we see the service providers selected for the GEM project tend to be larger than the nonGEM providers. There is an average of 46 workers for GEM providers compared to 28 for nonproviders; 57 percent have multiple branches compared to 35 percent of non-GEM providers; and 66 percent are registered as companies versus 35 percent of non-GEM providers. They have slightly more skilled staff, with 78 percent of staff having university degrees compared to 71 percent of non-GEM firms, and an average of 12 workers who belong to professional associations, compared to 9 in non-GEM firms. However, they serve similar customer bases, with a similar mix of firms by employee size category. Their usual contracts are also similar in price and duration across the two groups, with an average duration of 65 to 67 days per year, and mean cost of one day per week of services of 94,000-104,000 Naira. This median cost is much lower, at 40,000 per month for GEM firms and 37,500 per month for non-GEM firms, with the amount firms in the GEM program reported paying of 50,000 per month lying between the median and mean of typical payments.

We asked providers what they recommend as the minimum size in terms of employment and revenue for a small business client seeking their services. The GEM firms report a mean (median) of 4.7 (3.5) employees, compared to 8.0(5.0) employees for non-GEM firms, with this difference not statistically significant. GEM firms recommend a mean (median) monthly revenue of US$2590 (US$1370), which compares to mean monthly sales in our baseline of $3,265. Non-GEM firms report higher minimum revenue levels needed, but not significantly so, with large heterogeneity (mean of $6200, median of $685).

GEM providers do not differ significantly from non-GEM providers in their willingness to offer some form of quality guarantee. This is typically a promise to redo work if unsatisfactory, with fewer than 3 percent of firms offering guarantees offering money-back.

When we consider the different types of providers, we see that the GEM accountants tend to be more likely to be sole proprietors with excess capacity than the non-GEM accounting firms interviewed, while the marketers and HR providers tend to be larger companies.

81
examinations had significant and positive effects on reading scores. In India, going from having no physical facilities to having all 17 listed facilities (including toilets, computers and musical instruments) would increase math scores by 0.7 standard deviations and reading scores by 1.0 standard deviations.

Until recently, little test data was comparable between Latin American countries. Casassus and others (2000) present results from the 13 countries across Latin America and the Caribbean, not including Guatemala, which participated in UNESCO’s Laboratorio exam. Overall, they found that achievement in math was worse and more varied across students than achievement in Spanish. Compared to boys, girls showed better achievement in language but worse achievement in math. They found that school-level factors explained about two-thirds of test score variation between students. Student background was also critical in explaining student outcomes (for a survey of related literature, see Todd and Wolpin 2003). Although a child’s achievement is inherently individual in nature, a large body of evidence points to the existence of persistence effects in educational achievement across generations (Fertig 2003; Fertig and Schmidt 2002; Currie and Thomas, 1999). Consequently, one must control for individual pupil characteristics as well as family background. Finally, one needs to control for characteristics on school environment as well as institutional arrangements.

Disagreement persists over whether spending additional resources on schools has greater impact in developing than in industrialized countries. An earlier analysis of the Second International Mathematics and Science Test Study (Heyneman and Loxley 1983) also found that added resources for schools had more impact on learning in developing than in industrialized 6
Table 1113: Public **Recuent** E nditures per Student in Primary and Higlher Education

|Country|Year|Primary<br>US$|Higher<br>US$|Ratio o<br>Primary|f Higher to:<br>GNP per capita|
|---|---|---|---|---|---|
|Botswana|(84)<br>|97<br>|4,887<br>|50<br>|4.7<br>|
|Burkina Faso|(85)|43|1,989<br>|46<br>|10.5<br>|
|Costa Rica|(86)<br>|134<br>|1,435<br>|11<br>|.9<br>|
|Cote d'Ivoire|(85)|142<br>|3,703<br>|28<br>|_5.0_<br>|
|Ghana|(85)|38|3,095<br>|81<br>|7.9<br>|
|Lesotho|(86)|23<br>|3,527<br>|153<br>|9.5<br>|
|Mali|(88)|65|1,161|18<br>|_5.5_<br>|
|Niger|(86)|104|2,412|23<br>|9.3<br>|
|Nigeria|(85)|73|4,834|66<br>|13.1<br>|
|Pakistan|(84)|24|184<br>|8<br>|.5<br>|
|Philippines|(86)|44|258<br>|6<br>|.4<br>|
|Rwanda|(86)|52<br>|4,458<br>|86<br>|14.9<br>|
|Tanzania|(86)|18|3,740<br>|208<br>|20.8<br>|
|Turkey|(84)|49|609<br>|12<br>|_.5_<br>|
|Zambia|(86)<br>|14<br>|2,162<br>|154<br>|8.6<br>|
|Zimbabwe|(85)|93|2,391|26|4.1|

Note: In principle, the numbers in this table represent recurrent<sup>govermnent</sup> expenditures per student in public institutions (see footnote 2).

3.29 In some cases, reports also base their judgment<sup>on recent trends in the</sup> distributional pattern of government education expenditures.<sup>Thus, an increase in the share</sup> of higher education in the sector budget at the expense<sup>of primary education is taken as</sup> further evidence of a misallocation of public resources.<sup>However, just as a decline in civil</sup> service wages relative to the price of nonpersonnel<sup>expenditures may lead to a</sup> nondiscriminatory reduction in the share of education in<sup>total expenditures (see box III.1),</sup> the same tendency also holds with respect to intrasectoral<sup>resource distribution. A decline</sup> in wages will therefore tend to raise the share allocated<sup>to higher education, a material-</sup> intensive and capital-intensive subsector, and to lower the<sup>share to primary education, the</sup> most labor-intensive subsector.

3.30 Evidently, no single indicator suffices in providing a valid assessment<sup>of the</sup> "appropriateness" of the intrasectoral distribution of government<sup>education expenditures.</sup> Unless sector output goals are clearly defined, and process<sup>efficiency analyzed, judgments</sup> remain at best tentative.

30
# The Role of Groups and Credit Cooperatives in Rural Lending

by Monika Huppi and Gershon Feder

# Table of Contents

|I.|Introduction|1|
|---|---|---|
|II.|The Place of Lending Groups and Credit Cooperatives<br>in Rural Lending|3|
|III.|Essential Characteristics<br>of Group Lending|4|
|IV.|Characteristics<br>of Credit Cooperatives|8|
|V.|Experience with Group Lending|17|
|VI.|Experience with Credit Cooperatives in LDCs|28|
|VII.|Conclusions|43|
|Refer|ences|52|
stunted, and about one third were wasted. Table 3 provides similar measures taken from the 2003 Demographic and Health Survey (Institut National de la Statistique et de la Démographie and ORC Macro, 2004) which is the most recent available national survey at the time of our study. It can be seen that child malnutrition is widespread, and the northern region (which includes our study area) is worse off than most other regions. Together, these figures indicate that these households are facing severe constraints on nutrition and one could expect significant gains from the program.

# 4 Empirical Strategy

The study uses an experimental, prospective randomized design in which villages are randomly assigned to treatment and control groups and data are collected before the interventions are rolled out and after the interventions have been implemented (Burges, 1995; Duflo, Glennerster and Kremer, 2008). Our identification strategy relies entirely on the random assignment of the villages to treatment and control groups. Because of this random assignment the estimated program impact has a causal interpretation. Our main assumption is that the outcomes of interest would have remained identical across these groups if the program has not been implemented. Therefore differences observed across the groups in the follow up survey can be attributed to the program.

Because the program was offered at the village level, we estimate the average intent to treat (AIT) effect, that is, the impact of the program, on average, for all children in a given age range within a village whether or not all children in the village were receiving the treatment. This estimate measures the average program impact on eligible individuals (i.e. the impact of the intervention instead of the impact of the treatment), and is relevant for two reasons. First, since in practice policy makers have no influence on program participation, AIT is relevant for policy analysis. Second, AIT provides a lower bound for average treatment on the treated (ATT) under the assumption that the program impact on non participants in treatment groups is lower than its effect on compliers.

To estimate the AIT we use children in the control villages as the counterfactual group, with the assumption that control villages are not impacted by the program. We measure the 10
overwhelming majority of refugees are hosted in the developing world, something to which we will return.

Table 1: Top 10 destination and top 10 source countries, 2017

|Destination|No. persons|Source|No. persons|
|---|---|---|---|
|Turkey|3,789,119|Syrian Arab Rep.|6,455,328|
|Germany|1,399,554|Afghanistan|2,958,208|
|Pakistan|1,396,619|South Sudan|2,446,277|
|Uganda|1,395,115|Myanmar|1,197,794|
|Lebanon|1,014,165|Somalia|1,044,646|
|Iran (Islamic Rep. of)|979,519|Dem. Rep. of the Congo|756,899|
|Bangladesh|932,319|Sudan|746,663|
|United States of America|929,762|Iraq|635,101|
|Sudan|924,789|Eritrea|564,447|
|Ethiopia|891,990|Central African Rep.|558,487|

**Notes:** This table reports the top 10 source and top 10 destination countries, measured by stocks of refugees recorded in 2017.

# **3 The Globalization of Refugee Movements**

How is the responsibility for hosting refugees shared? To get a better sense of the spatial distribution of refugees across countries, we first construct a measure of refugee dispersion. Namely, we compute a host country Herfindahl index, which measures how concentrated or dispersed refugees are across all destination countries worldwide. Concretely, the (weighted) destination Herfindahl index is defined as where _Rdt_ is the total number of refugees at destination _d_ at time _t_ , so the denominator is simply the global stock of refugees. Refugee numbers _Rdt_ are weighted by _ωdt_ . When _ωdt_ = 1, the result is the textbook Herfindahl index, which takes a value of 1 if one country ends up hosting all the refugees in the world and converges to 0 if every country hosts the same number of refugees. Alternatively, a GDP-weighted version of the destination Herfindahl index is calculated by setting _ωdt_ = 1 _− GDPGDPworldtdt_<sup>andaccounts</sup> 7
Policy ReseaRch WoRking PaPeR 4313

# **Abstract**

The World Bank Group Entrepreneurship Survey measures entrepreneurial activity around the world. The database includes cross-country, time-series data on the number of total and newly registered businesses for 84 countries. This paper finds significant relationships between entrepreneurial activity and indicators of economic and financial development and growth, the quality of the legal and regulatory environment, and governance. The analysis shows the importance of electronic registration procedures to encourage greater business registration. These results can guide effective policymaking and deliver new capabilities for identifying the impact of reforms.

This paper—a product of the Finance and Private Sector Team, Development Research Group—is part of a larger effort in the department to study entrepreneurship and small and medium sized enterprises (SMEs). Policy Research Working Papers are also posted on the Web at http://econ.worldbank.org. The author may be contacted at lklapper@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