rafmacalaba/datause-encoder-data huggingface dataset:
2004), and an even greater share, 98%, of Mexicans have a sense of well-being. However, half of Mexican youth and one-fifth of Chilean youth feel socially excluded.

There are few questions on macro factors, but the data do show that over half of the Mexican youth are from families whose parents have less than a primary education, while over one-third of Chilean youth have parents with less than a primary education. In addition, over half of Chilean youth have felt discriminated against at some time.

# **V. Results**

The clustering methodology identified four to seven sub-groups within each of the 10 age-sex-country cohorts, resulting in 53 (23 from Chile, 30 from Mexico) distinct groups of youth. To simplify the discussion, the commonalities across the clusters are presented in this section. The results are presented by risk category to allow us to characterize the heterogeneity in the youth population and to create a picture of youth in each category, based on the findings from the 53 clusters. Tables 3a and 3b present a summary of youth in the different risk categories in Mexico and Chile respectively while the full cluster results are presented in Tables 4a-4j. Annex B gives a brief description of each of the 53 clusters.

# **A. Who Are the Youth at Risk in Mexico and Chile?**

# **Type III Risk**

Thirty-three percent of Mexican youth can be classified as type III risk, meaning that they are coping with the outcomes, or consequences, of their risky behavior, while 16.8% of Chilean youth fall into this risk category (Tables 3a and 3b). Considering separately the agegender categories better characterizes type III risk youth in Mexico and Chile.

Fourteen percent of Mexican youth aged 12 to 14 are in this risk category. They have almost all dropped out of school, resulting in an average education level of primary school. Few are involved in organized activities and a large proportion is working (49% of boys and 27% of girls). We cannot report on the sexual activity of these youth since they were not asked these types of questions. All youth who are illiterate are in this category (Tables 4a and 4b, column 1).

Eight percent of Chileans age 15 to 17 and almost 40 percent of Mexicans in the same age range are classified as risk type III (Tables 3a and 3b). Almost all have dropped out of school prior to completing secondary education, many are inactive, most engage in risky sexual behavior and feel socially excluded. Among the women, a strong at-risk mother 13
# **Table 12: Illustration of Coding and Scoring Procedures**

|C: Central<br>I: Intermediate<br>L: Local|Corporate Income Tax|Income<br>Business Tax<br>Personal Income Tax|Payroll/Withholding|Pro<br>Property|**Scor**<br>perty<br>Transfers of Property|**ing**<br>Con<br>Sales/VAT/Turnover|sumption<br>Excise<br>Fuel|Industry and Trade|Ot<br>Vehicles|hers<br>Gambling|Stamps<br>Natural Resources|_Sco_<br>Decision Score|_res_<br>_Tax Assignment Index_|
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
|**Country Name**|||||||||||||**0.22**|
|_Instrument_|C|C<br>C|C|C|C|C|C<br>C|C, I|C|C|C<br>C|**_0.04_**||
|_Base_|C|C<br>C|C|C, I|C, L|C|C<br>C|C, I|C|C|C<br>C|**_0.11_**||
|_Rate_|C|C<br>C|C|I, L|I, L|C|C<br>C|C, I, L|C, I|I, L|C<br>C|**_0.29_**||
|_Administration_|C|L<br>C|C,I|I,L|L|C|C<br>C|C,I,L|I,L|L|C,L<br>C|**_0.46_**||

**_Notes:_** Author’s. Matrix design originally from the World Bank Qualitative Decentralisation Indicators. The Tax Assignment Index is used to proxy the level of decentralization in this paper

39
# **Figure 11 Fiscal expenditure and SWFs in Chile, Botswana, and Timor-Leste**

# **A. Chile**

<!-- Start of picture text --> Percent Fiscal expenditure $/mt<br>SWF<br>40 10,000<br>Copper price (RHS)<br>35<br>8,000<br>30<br>25 6,000<br>20<br>15 4,000<br>10<br>2,000<br>5<br>0 0<br>C. Timor-Leste<br>Index, 100 = 2008 Fiscal expenditure $/bbl<br>SWF<br>200 120<br>Oil price (RHS)<br>100<br>160<br>80<br>120<br>60<br>80<br>40<br>40<br>20<br>0 0<br>2007 2009 2011 2013 2015 2017 2019 2021<br>2008 2011 2013 2015 2017 2019 2021<br><!-- End of picture text -->

# **B. Botswana**

<!-- Start of picture text --> Percent Index<br>Fiscal expenditure<br>SWF<br>Commodity export price (RHS)<br>80 140<br>70 120<br>60<br>100<br>50<br>80<br>40<br>60<br>30<br>40<br>20<br>10 20<br>0 0<br>2006 2009 2012 2015 2018 2021<br><!-- End of picture text --> _Sources_ : Bank of Botswana; Fondo de Estabilización Económica y Social (website); International Monetary Fund; Timor-Leste Petroleum Fund (website);World Bank.

_Note_ : bbl = billion barrels; mt = metric ton; SWF = sovereign wealth fund.

A.B. Fiscal expenditure and assets under management of SWFs are expressed as percentages of GDP. C. An index for fiscal expenditure and SWF assets under management was constructed starting in 2008.

41
# Table I

# United States Imports, 1990: Percentage on Which the United States Imposes Nontariff Baniers

||Voluntary export<br>restraints_jI_|Restrictions on<br>textile imports b/|Antidumping and<br>countervailing duty actions g/|
|---|---|---|---|
|_All mrchandise_||||
|Imports from all countrles|7|5|6|
|Imports from Korea|9|15|5|
|_Manufactured goods_||||
|Import from all countries|6|7|9|
|Imports from Korea|7|16|5|

Source: World Bank staff estimates based on the UNCTAD Trade Control Measures System and the harmonized system for commodity classificaton system.

Notes: a. Includes voluntary price minimums and voluntary quantity maximums.

b. Includes those under the Multi Fibre Arrangement and those not under MFA.

c. Includes antidumping and countervailing duty orders in place, agreed undertakings in place and cs-ses initiated in calendar year 1990.
translated CII diploma and certificate level material into Arabic under a partnership arrangement), IFID having a similar role on the Maghreb and Cairo University producing approximately 30 actuarial graduates each year under a partnership arrangement with Kent University in the UK. Approximately 10% of these go on to do the UK professional exams<sup>12</sup> and as a practical expedient Associates of the leading international actuarial bodies with some years of experience are now being certified to do actuarial work.

# **5. Main Regulatory and Supervisory Issues**

## _5.1 Regulation_

## _Entry Requirements_

**Minimum capital requirements in MENA are in most cases high by international standards, but this has not prevented entry in a capital rich region.** Minimum capital requirements are a traditional supervisory tool to screen the number and quality of applicants in insurance and other sectors, but as noted above, in MENA it has not prevented a situation of excessive number of insurers in some markets, some of which are playing only a marginal role.

**Licensing requirements in most MENA countries generally follow international norms, including a business plan and fit and proper information on the senior management.** However, fit and proper information on Board directors and owners is less frequently required. It is also unclear why these fit and proper rules have not been able to screen applicants more effectively and prevent the entry of insurers which may not be able to play a meaningful role in the marketplace.  Also, most MENA countries allow composites to operate but enforced separation of assets and accounts is not always required.

**Licensing requirements include several restrictions on cross-shareholdings, branches, and foreign investments** .  Some MENA countries apply limits to cross shareholdings (e.g. banks in Algeria may not hold more than 15% of an insurer) and to the amount that can be held by any one entity (e.g. 40% in Syria).  In addition a number of MENA countries do not allow branches to be established (Egypt, Libya, Morocco, Qatar, KSA, Syria, Tunisia) and/or still restrict the percentage of a local insurer that can be held by non nationals (Table 7). Some of these restrictions may be justified for prudential reasons, while others seem questionable.

**Table 7:  Limits on foreign shareholdings in insurers**

|Algeria|Egypt|KSA|Libya|Qatar|Tunisia|UAE|Kuwait|Oman|
|---|---|---|---|---|---|---|---|---|
|70%. Existing<br>insurers are<br>grandfathered|10% but<br>exemptions<br>are usually<br>granted|<br>49%|40%|None for<br>national,<br>but<br>foreigners<br>can invest<br>in listed<br>companies|Subject to<br>approval|25%|Subject to<br>approval and<br>initial<br>performance|70%|

Sources: AXCO and WB on site research

> 12 American University also has an actuarial course but it provides no exemptions from US actuarial examinations.

18
Policy Research Working Paper 7463

# **Abstract**

This paper evaluates a youth internship program in the Republic of Yemen that provided firms with a 50 percent subsidy to hire recent graduates of universities and vocational schools. The first round of the program took place in 2014 and required both firms and youth to apply for the program. The paper examines the demand for such a program, and finds that in the context of an economy facing substantial political and economic uncertainty, it appears there is an oversupply of graduates in science, technology, engineering, and mathematics, and a relative undersupply of graduates in marketing and business. Conditional on the types of graduates firms were looking to hire as interns, applicants were then randomly chosen for the program. Receiving an internship resulted in an almost doubling of work experience in 2014, and a 73 percent increase in income during this period compared with the control group. A short-term follow-up survey conducted just as civil conflict was breaking out shows that internship recipients had better employment outcomes than the control group in the first five months after the program ended.

This paper is a product of the Finance and Private Sector Development Team, Development Research Group. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://econ.worldbank.org. The authors may be contacted at dmckenzie@worldbank.org.

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
# **Figure S1: Random Forest Estimates**

The following importance plots measure the mean decrease in the Gini coefficient of the top fifteen features, which corresponds to the marginal impact of including the variable in the model.

**(a) Standard Random Forest** Importance Plot: Top 15 Features

<!-- Start of picture text --> Ratio of magnitude of strongest repeating tempor al<br>pattern in duration outgoing daily to sum ofmagnitudes of all other patter ns, after first ●<br>activity<br>Ratio of magnitude of strongest repeating tempor al<br>magnitudes of all other patter ns, between firstpattern in duration outgoing daily to sum of ●<br>and last activity<br>Ratio of magnitude of strongest repeating tempor al<br>pattern in duration outgoing daily to sum of ●<br>magnitudes of all other patter ns<br>Ratio of magnitude of weekly repeating temporal<br>pattern in calls outgoing daily to sum of ●<br>magnitudes of all other patter ns<br>Ratio of magnitude of strongest repeating<br>temporal pattern in SMS outgoing weekly to sumof magnitudes of all other patter ns, after first ●<br>activity<br>Ratio of magnitude of weekly repeating temporal<br>magnitudes of all other patter ns, after firstpattern in calls outgoing daily to sum of ●<br>activity<br>Ratio of magnitude of weekly repeating temporal<br>magnitudes of all other patter ns, between firstpattern in calls outgoing daily to sum of ●<br>and last activity<br>Ratio of magnitude of weekly repeating temporal<br>pattern in daily max distance between towers used ●<br>daily to sum of magnitudes of all other patter ns<br>Ratio of magnitude of strongest repeating tempor al<br>pattern in SMS outgoing daily to sum of magnitudes ●<br>of all other patterns, after first activity<br>Ratio of magnitude of weekly repeating temporal<br>pattern in duration outgoing daily to sum of ●<br>magnitudes of all other patter ns<br>Ratio of magnitude of strongest repeating<br>temporal pattern in SMS outgoing weekly to sum of ●<br>magnitudes of all other patter ns<br>Ratio of magnitude of strongest repeating tempor al<br>pattern in duration outgoing weekly to sum ofmagnitudes of all other patter ns, after first ●<br>activity<br>Ratio of magnitude of weekly repeating temporal<br>magnitudes of all other patter ns, between firstpattern in duration outgoing daily to sum of ●<br>and last activity<br>Ratio of magnitude of strongest repeating tempor al<br>pattern in SMS outgoing daily to sum of magnitudes ●<br>of all other patterns<br>Ratio of magnitude of strongest repeating<br>temporal pattern in SMS outgoing weekly to sum ofmagnitudes of all other patter ns, between first ●<br>and last activity<br>2.0 2.5 3.0 3.5<br>Mean Decrease in Gini<br>Indicator<br><!-- End of picture text --> Ensemble of 500 trees. Mean nodes per tree: 424. Source: authors’ analysis from telecom data.

1
_Figure 12. Incidence, progressivity and marginal contributions in-kind transfers a. Concentration shares for in-kind transfers b. Progressivity of in-kind transfers (Kakwani Index)_ <!-- Start of picture text -->
1.0<br>All net in-kind transfers 0.17<br>0.8<br>Net health transfers 0.38<br>0.6 Hospital healthcare 0.26<br>Primary healthcare 0.55<br>0.4<br>0.2 Net education transfers 0.16<br>Technical educ. -0.07<br>0.0 Tertiary educ.<br>-0.53<br>Secondary educ. 0.13<br>Primary educ. 0.54<br>Pre-school educ. 0.36<br>-0.6 -0.3 0.0 0.3 0.6 0.9<br>Kakwani Index<br>1 2 3 4 5 6 7 8 9 10<br><!-- End of picture text -->

- _c. Redistributive effects of in-kind transfers_

<!-- Start of picture text -->
1.5 1.24<br>1.05<br>0.95<br>1.0<br>0.5<br>0.04 0.13 0.05 0.03 0.09<br>0.0<br>-0.5<br>-0.55<br>-1.0<br>Pre-school educ. Primary educ. Secondary educ. Tertiary educ. Technical educ. Net education transfers Primary healthcare Hospital healthcare Net health transfers All net in-kind transfers<br><!-- End of picture text -->

_Source: Authors’ calculation based on UNHS 2016/17._ _Note for c: A positive redistributive effect means inequality declines, while a negative redistributive effect means inequality increases (in Gini points)._ 33
capturing (iv) the percentage of the population over 60 covered by pension schemes, (v) the cost of pension spending as a percentage of the country's GDP, (vi) the logarithm of the age of eligibility, (vii) the percentage contribution rate and (viii) the ratio of employer/employee contribution from the World Bank Pensions database (2014).<sup>18</sup>

# **4.2 Results and analysis**

Table 1 presents descriptive statistics for the main variables in the analysis of saving for old age around the world. Column 1 present weighted averages for the pooled sample of all countries (147,692 individuals), while Column 2 and Column 3 present averages for individuals who save for old age (24.8% of the weighted sample from 30,395 individuals) and those who do not (75.2% of the weighted sample, from 117, 297 individuals), respectively.<sup>19</sup> Column 4 also presents the mean difference and asterisks for the level of significance from a test of difference in the means of the variables between the two samples.

The comparison of the figures between individuals who save for old age around the world and those who do not in Columns 2-4 suggests that individuals who save for old age are more likely to be males, residing in an urban region, more likely to have tertiary or secondary education, less likely to have primary education or less, more likely to be in the older age groups and less likely to be in the age range 18-25, less likely to be single or never married, and less likely to have children aged under 15. They are more likely to be in the top three income centiles by country, and less likely to be in the bottom two or the missing income centile. Those who save for old age are more likely to be employed, and less likely to be self-employed, unemployed or inactive.

Savers for old age are more likely to be financially included, and to have an outstanding mortgage. They are more likely to reside in countries with higher generic-savings rates and in countries with higher GDP per capita. They reside in countries with lower GDP per

> 18 The data and description are described by Pallares-Miralles et al. (2012) and are available at: http://www.worldbank.org/en/topic/socialprotectionlabor/brief/pensions-data.

> 19 For completeness, Table A1 in the Appendix presents descriptive statistics for the main variables in the analysis by country group, for each of the eight country groups in our classification. Then, Table A2 in the Appendix presents the weighted pairwise correlation matrix for the main variables in our analysis.

13
**Table 1.1.  Main macroeconomic indicators, 2006-09**

||**2006**|**2007**|**2008**|**2009**|
|---|---|---|---|---|
|GDPgrowth,%|7.7|8.1|5.6|-7.9|
|Industrialproductiongrowth, y-o-y,%|6.3|6.3|2.1|-10.8|
|Fixed capital investmentgrowth,%, y-o-y|16.7|21.1|9.8|-17.0|
|Federalgovernment balance,% GDP|7.4|5.5|4.0|-6.4|
|Inflation(CPI),% change,e-o-p|9.0|11.9|13.3|8.8|
|Current account,billion USD|95.6|76.6|98.9|46.0|
|Unemployment, % (ILO definition) (period<br>average)|7.2|6.1|6.3|8.4|
|Memo: Oilprices,Urals(USD a barrel)|61.2|69.5|95.1|61.4|
|Reserves(including gold)billion USD,e-o-p|303.7|478.8|427.1|425.0|

_Source:_ Rosstat, CBR, Ministry of Finance, Bloomberg.

* Preliminary estimate by Ministry of Economic Development.

**  Preliminary World  Bank staff estimate.

**_Robust growth, higher oil prices and structural fiscal reforms that eliminated nonpayments and arrears, transformed the (primary) fiscal deficit into a primary fiscal surplus_** (See Fig. 8a). As a consequence, the public debt-to-GDP ratio declined rapidly and foreign exchange reserves reached nearly 40 percent of GDP in 2007 (See fig. 8b).

# **Figure 8a. Primary Fiscal Balance 8b. Foreign Exchange Reserves**

<!-- Start of picture text --> 15 80 FX Reserves, % of GDP<br>10 50<br>60<br>5 40<br>0 40<br>30<br>-5<br>20 20<br>-10<br>10<br>-15 0<br>0<br>Primary GG fiscal balance, % of GDP<br>-10<br>Russian Oil price in US$ per bbl (right scale)<br>-20<br>19971998199920002001200220032004200520062007<br>19971998199920002001200220032004200520062007<br><!-- End of picture text --> Source: World Bank.

**_C. High oil prices boosted recovery, but prudent fiscal policy and fiscal reforms were key to strong economic and policy performance_**

**_Russia has certainly benefited from a favorable external environment as oil and metals prices recovered and capital inflows resumed._** Russia’s oil price increased by more than four-fold since 2000 until 2007 (see Fig. 6a). Nevertheless, Russia maintained a very conservative fiscal stance: although the non-oil primary fiscal balance ( _nopd_ )<sup>2</sup> turned into a deficit again in 2000, but this deficit stayed at modest levels of 2 to 4 percent of GDP–– until 2007. By comparison, oil fiscal revenues were above 10 percent of GDP from 2005 onwards (fig. 8a), indicating substantial net savings out of oil revenues. In 2007, the _nopd_ is estimated to have expanded further to slightly below 5 percent of GDP, although this is still less than a half of total fiscal oil revenues for the same year.

> 2 Non-oil primary fiscal balance is defined as non-oil fiscal revenues minus non-interest expenditures.

10
active management, trading capabilities, and principal investing. Several vice presidents have been appointed and new groups have been created to manage active strategies in the three investment departments that had been established in earlier years. Staff expansion is likely to continue in fiscal 2008 and beyond.

# **3.6 Investment Performance**

The share of CPP assets managed by the CPPIB increased steadily over the years (Table 3.2). All CPP assets were effectively transferred to the CPPIB by the end of March 2007.

|Tabl|e 3.2:Asse|t Compo|sition, C|PPIBand|FDF,20|00-2007|||
|---|---|---|---|---|---|---|---|---|
|End March|2000|2001|2002|2003|2004|2005|2006|2007|
|percent of total|||||||||
|CCPIB Assets|5.4|14.8|26.7|31.5|46.5|72.1|90.4|99.4|
|FDF Assets|94.6|85.2|73.3|68.5|53.5|27.9|9.6|0.6|

Source: CPPIB Annual Reports Asset allocation reflected the legacy of a large volume of non-tradable government bonds on the books of CPP and the decision to invest all new cash flow in equities. Fixedincome instruments declined from 95 percent of the total in 2000 to 25 percent in 2007. Public equities in Canada and overseas reached 58 percent in 2007, while alternative assets, including private equity, real estate and infrastructure projects reached nearly 14 percent in 2007 (Table 3.3). This is likely to increase further in the future both because of past commitments that are gradually reaching the realization stage and because of increased emphasis on such investments. Inflation-linked bonds made up 3 percent of total assets.

|Table <br>|3.3:Ass<br>|etAlloc<br>|ationof<br>|CPP Ass<br>|ets,200<br>|0-2007<br>|||
|---|---|---|---|---|---|---|---|---|
|End March<br>percent of total|2000|2001|2002|2003|2004|2005|2006|2007|
|Public Equities|5.4|14.7|25.9|28.1|42.7|56.2|58.5|57.9|
|Private Equities|0.0|0.0|0.7|2.7|2.6|3.6|4.5|6.9|
|Real Estate|0.0|0.0|0.0|0.5|1.0|1.0|4.3|4.9|
|Inflation-Linked Bonds|0.0|0.0|0.0|0.0|0.0|0.0|4.1|3.3|
|Infrastructure|0.0|0.0|0.0|0.0|0.0|0.2|0.3|1.9|
|Bonds|80.4|72.7|60.8|55.8|42.8|35.2|27.8|25.0|
|Cash & Money Market|14.2|12.7|12.5|12.9|10.9|3.8|0.6|0.1|
|Total|100.0|100.0|100.0|100.0|100.0|100.0|100.0|100.0|

Source: CPPIB Annual Reports Investment returns for all CPP assets, including the non-marketable bonds that originally resided with the FDF and the assets managed by CPPIB, averaged 8.2 percent over the period 2000-2007. The returns exhibited significant fluctuation from year to year, reflecting the high volatility of returns of global equity markets (Table 3.4).

42