rafmacalaba/datause-encoder-data huggingface dataset:
12 The move towards more debtor-friendly contractual structures probably reflects three interrelated factors: Russia’s aim to build a “financial fortress” to limit its dependence on foreign capital, the view that geopolitics demand it, and the lessons learned from its recent debt crises.<sup>39</sup> The geopolitical aspect is reflected in the “risk factors” sections for all bonds issued since 2014, stating that “[d]ifferences of views between the Russian Federation and certain other countries (including the United States and Member States of the EU) regarding events in Ukraine have resulted in ... [the mutual imposition] of economic sanctions.”<sup>40</sup> They also address sanctions regimes and the risk of their expansion in more detail, in particular with respect to sovereign debt.<sup>41</sup> The debt stock’s contractual features seem to be designed to slow down progress towards recovery. The main aggregate characteristics working in favor of the debtor sovereign are:

- (1) short prescription clauses (13 of 15 bonds), which establish the time creditors have before the claim is voided;

- (2) the lack of appointment of an agent to receive service (all bonds), which complicates serving Russia with suit;

- (3) the explicit rejection to waive sovereign immunity (all bonds), which preserves defenses in establishing jurisdiction to the maximum extent allowed by applicable law;

- (4) alternative payment currency clauses (9 of 15 bonds), which, under the assumed default scenario, potentially introduce controversy over whether there is a default for a number of bonds;

> 39 _See Fortress Russia: Russia’s economy is isolated from the global rout_ <u>, The Economist (March 25,</u> 2020); _<u>Isolating Russia: How new sanctions could cripple Russia’s economy</u>_ The Economist (February 27, 2022); Signyanina-Woodruff, note 6 _supra_ , 531 (pointing out that leaders as different as Peter the Great and Stalin “had similar attitudes” on this matter).

> 40 _See, e.g._ , Prospectus for the EUR 500,000,000 1.125 percent bonds due 2027 and the EUR 1,000,000,000 2.65 percent bonds due 2036 at 11.

> 41 _See, e.g._ , Prospectus for the EUR 500,000,000 1.125 percent bonds due 2027 and the EUR 1,000,000,000 2.65 percent bonds due 2036 at 13. Additionally, the disclosures under the header “The Russian Federation, the Former Soviet Union and the CIS” describe the litany of problems between Russia and Ukraine since at least 2014. _Id_ at 98-101.
For the decomposition analysis of emissions intensity, we obtain annual country-level total passenger and freight transport traveled by road and rail from the World Road Statistics and the International Transport Forum databases. Total passenger transport, measured in million passenger-kilometers, refers to the total movement of passengers using inland transportation. It represents the transport of one passenger for one kilometer. Total freight transport, measured in million tons-kilometer, refers to the total movement of goods using inland transport. It represents the transport of one ton over one kilometer. The total kilometer variable is available for 65 countries during the period from 2000 to 2018. These countries are listed in Table A2 in the appendix.

The level of urbanization, and the value added from agriculture, manufacturing, and service sectors are all obtained from the World Bank World Development Indicators database. Data on country-level BRT systems are obtained from global BRT database. Diesel and gasoline prices are compiled from fuel price documentation from the <mark>Deutsche Gesellschaft für Internationale Zusammenarbeit GmbH (GIZ).</mark> The summary statistics of variables are presented in Table 3.

# **5. Results**

In this section, we describe the results of the decoupling analyses, the general pattern of transport-related CO2 emissions, and the results of the regression analyses. The descriptive statistics reveal that CO2 emissions of the transport sector account for 24 percent of global CO2 emissions, making the transport sector the second-largest contributor to global CO2 emissions after the energy sector, which accounts for 42 percent of such emissions. Within the transport sector, road transportation is the predominant driver, accounting for 74 percent of all CO2 emissions; international sea transport accounts for 9 percent, and international aviation accounts for 7 percent (Figure 1). The composition of global transport CO2 emissions by mode has been fairly stable over time; the shares in 1990 were about the same as those in 2018 (Figure A1). There is interesting variation between income groups and regions; the CO2 emissions from road transportation are slightly below the global average in high-income countries, and above average in lower-middle and low-income countries (Figure A3).

Figures 2a and 2b present the distribution of global transport CO2 emissions in terms of GDP and population by income group and major emitting countries in 2018. The area of each rectangle represents the contributions of a country/income group to total global transport emissions. The rectangle's width represents the share of global GDP (population), and the height represents transport emissions per unit of GDP (population). Figure 2a suggests that the countries with the most carbon-intensive transport 10
**TABLE 2: Basic Demographic and Economic Data**

|**SummaryData**|**Arg**|**entina**|**Ch**|**ile**|**Me**|**xico**|
|---|---|---|---|---|---|---|
||**men**|**women**|**men**|**women**|**men**|**women**|
|**1.Amongworkingage**<br>**population(16-65):**<br>|||||||
|**%**currentlyemployed<br>|70.8%|40.0%|75.2%|38.0%|83.7%|44.1%|
|%ever employed|n.a.|n.a.|89.8%|70.5%|92.6%|78.5%|
|%affiliatedtoSSS<br>|75.5%||66.6%|41.6%|31.6%|14.6%|
|**2.Amongolderpopul.**(60+):<br>|||||||
|%who receive ownpension|49.7%|48.3%|67.6%|35.4%|30.5%|5.4%|
|%who receive otherpensions<br>|||4.4%|25.6%|.03%|9.4%|
|%who live inextendedfamilies|22.3%|36.6%|42.8%|52.5%|35.9%|44.6%|
|%whogetmonetarytransfers<br>fromextendedfamily<br>|7.7%|6.2%|NA|NA|_15.0%_|17.5%|
|**3.Lifeexpectancy:**<br>|||||||
|Atage60(genderspecific)<br>|17.8|22.5|19.1|22.8|19.2|22.3|
|Atage65(genderspecific)<br>|14.5|18.4|_15.5_|18.9|15.8|18.5|
|Unisexatretirement age|16.5|20.2|17.2|21.0|17.0|17.0|
|4.**Wagesandpensions:**<br>|||||||
|Averagemonthlywage(US$s)<br>|$661|$445|$335|$245|$299|$214|
|MinimumW.(as%ofaverage)|30.3%|44.9%|37.6%|51.4%|33.1%|46.3%|
|MPGorflat(as%ofav.wage)<br>|30.3%|44.9%|27%|37.2%|33.1%|46.3%|
|SocialAssistancePension<br>|NA|NA|12.8%|17.6%|NA|NA|
|Povertyline(as%ofav.Wage)|23.6%|35.1%|21.8%|29.9%|NA|NA|

# **Data sources and notes:**

For section 1, numbers are for urban population in household surveys described in Appendix B. Data are from 1994 (Chile), 1996-97 (Argentina), and 1997 (Mexico). Affiliation to the social security system in Argentina is from SAFJP: "Proyecto Indicadores de Control Previsional Etapa 2 - Informe Final." (1999).

For section 2, Chile and Argentina, numbers are from surveys described in Appendix B. For Argentina breakdown between own and other pensions is not available. For Mexico, data refer to country as a whole, from Parker and Wong (2001), using household survey data. Own pensions refer to old age, disability and severance; other pensions refer to widows and survivor benefits.

> For section 3 data are for population as a whole; for Chile and Argentina from CELADE

> (1998), "American Latina: Proyecciones de Poblacion 1970-2050," Demographic Bulletin 61; for Mexico from Partida, Virgilio, 1998 (CONAPO, Mexico).

For section 4, data refer to our sample and sample dates, as described in Appendix B (minimum wage, MPG and flat decline through time as % of average wage due to price indexation). In Argentina and Mexico there is no social welfare program targeted towards the elderly. The Mexican program (Progresa) is targeted towards families with children.

Argentinean currency is converted to US$s at 1997 exchange rates, 1 for 1. In 2002, peso fell to 25-30% of US$, so wage and pension values would be 25-30% of stated values. Exchange rate for Chile was Ch$413.45=US$1 and in Mexico 8 pesos=US$1.

44
effects of cuts to the number of tax payments on tax corruption are similar in China and Brazil. The response of tax corruption to cuts in TAXTIME is strongest in India, where a 10 percent decline in TAXTIME lowers tax corruption by 4.90 percent. In China the same experiment produces a 4.4 percent cut in tax corruption, while it is 4.7 percent in Russia.

It should be noted that since only business taxes are included in this study, the magnitude of the impacts of tax simplification on tax corruption, as calculated above, can be considered partial. In a study where personal income taxes are taken into account as well, the overall impact of tax simplification on tax corruption is expected to be stronger.

# **_3.3 Importance of Regional Differences in Determining Tax Corruption_**

As presented in section 2 of the paper, significant differences in the tax corruption measure are observed across regions. For example, while Latin American and South Asia countries tend to report lower measures of tax corruption, countries from Eastern Europe and Central Asia present much higher tax corruption ratios. These results are not entirely in line with observed instances of tax corruption. For example, it is generally expected that tax corruption is higher in South Asia than ECA. Our surmise is that two factors may be responsible for the slightly unexpected results: first, the cultural factors which may have an influence on the responses to the Enterprise Survey questions on tax corruption, and, second, the fact that tax corruption data are not collected from all countries. Nevertheless, there is value in exploring regional dimensions to gain some understanding of the dynamics of tax simplification and corruption in a region.

In order to understand the impact of regional differences on the link between tax simplification and tax corruption, the benchmark regression specification is run separately for each region. The regions included in the study are: Europe and Central Asia (ECA), Sub-Saharan Africa (SSA), Latin America and Caribbean (LAC), South Asia (SASIA), East Asia and Pacific (EAP), and the Middle Eastern and North Africa region (MENA). Due to data limitations, some regions are combined. Countries from SASIA and EAP are pooled together. Similarly, MENA and ECA countries form one group.

31
Attention could be also focused on removing policy constraints that impact both the movement of goods within countries and on trade across borders, such as lack of competition in the provision of transport and logistics services. In many African countries, transport cartels are still dominant and the cost of transportation is very high compared to other regions. We found that countries with poorer logistics performance, as measured with the LPI, also tend to have thicker borders. Measures that improve the availability of information on prices both within and across countries could also have an important impact on reducing differences in the relative price of food in different markets.

Finally, the approach adopted here could be useful in identifying the impact of these specific measures to reduce policy constraints to trade. For example, if procedures at the border are improved we should expect to see a decline in relative prices between markets on either side of the border.

24
outcome equation (2) to estimate the effect of microenterprise on household welfare.<sup>7</sup> To operationalize, we use instrumental variable techniques in a fixed-effects model.<sup>8</sup> The results are shown in Table 8. We present the endogeneity test statistics, which show that adoption of microenterprise activity as an additional activity is endogenously determined (at least for two outcomes as per capita expenditure and extreme poverty) by the same characteristics affecting the outcomes itself. Thus, we find that household adoption of a microenterprise activity <u>causally</u> increases both income and expenditure, and thus reduces poverty. For example, the adoption of microenterprise activities increases household per capita expenditure by over 50 percent. If we assume that the growth in income or expenditure has been accumulated over the duration of microenterprise operation, which is an average of 10 years, we can infer that a household’s adoption of an enterprise activity increases per capita income by 6 percent per year and per capita consumption by 5 percent per year. Consequently, the reductions in moderate and extreme poverty have been 2.4 percent and 3.6 percent per year, respectively, because of microenterprise adoption. These findings bolster our hypothesis that besides farm income growth, microenterprise expansion is an effective way to accelerate poverty reduction in rural Bangladesh.

# <u>4. Rates of return to investment using productivity measures</u>

To understand whether income and consumption gains (or alternatively poverty reduction) are substantial with microenterprise growth, we must analyze the profitability of microenterprise investment, or alternatively the rates of return to investment in microenterprise, as it is the return

> 7 The instruments are the program placement of microcredit, commercial and other development banks in a village. We also interact these variables with household characteristics (head’s age, education, land and non-land assets) to create additional instruments. It is assumed that the availability of a credit program in a village is expected to influence household welfare such as income, consumption, and poverty only through adoption of enterprise and its growth and performance.

> 8  We use ‘thana times year’ as the unit for fixed-effects as it is more appropriate than simple thana-level FE.

13
69 Thus, th measurement of **the** optimal duration of breastf eding and time to introduce supplementary foods in the child's diet depend on the education of the *sther who must manage to provide sanitary substitutes for her own supply of ilk. In other words. the duration of unsupplemented breastfeeding and education appears to be substitutes in producing child health. This fihding may partially account for why more *ducated mothers breastfeed less (larrera, 1988b: Table 25).

Nutrition and labor productivity **are** positively related at the individual or household level. With the recent use of simultaneous equation estimation techniques (Strauss, 1986) it has been shown convincingly in three studies that nutrition raises labor productivity, at least at very low levels of income (Strauss (1986) in Sierra Leone; DeolaliLar (1988) in India; and Sahn and Alderman (1988) in Sri Lanka). Since the demand for nutrition is also influenced by prices and incoms, the standard assumption that production decisions and consumption decisions can be sequentially and separately solved by the farm household may need to be studied further (Singh, n; al 1986). .o analyze intrahousehold allocation of nutrition, data are needed either on individual food intakes or on measures of nutritional status. Most analysis has beon based on the latter anthropometric indicators of nutritional status, such as height for age, or weight for height, thickness of skinfolds, etc. that can be readily **measured** in a single **survey.** But these anthropometric indicators of nutrition reflect more than **the** adequacy of curront nutritional inputs. They also incorporate **the** past pattern of nutrition, as modified by individual differences in metabolism, absorption **rates** possibly related to infectious and' parasitic diseases, and activity lovels. Studies such as Barrera (1988), Struass (1987) and Thomas, Qt_al. (1987) analyze such
<!-- Start of picture text --> Ant % Cleared Cleared<br>A VW es es After Road Upgradi Road Upgradi Upgradi<br>so<br>3 AS @ 23 - 30<br><!-- End of picture text --> Ant % Cleared Cleared A VW es es After Road Upgradi Road Upgradi Upgradi so 3 AS @ 23 - 30 i #R A Sip @ 31-38 Od ~, ForeAw.Aw. “9 G. G. ce-yi es @ 81-90 81-90 be Y aE aE i ieeSeS @ 91-100 91-100 =—= Delorme Road Road Link Se one ye yh ye yh yh RRs - \ 4 4 , heLeLe aes Cag <!-- Start of picture text --> Od ~, ForeAw.Aw. “9 G. G. ce--<br>yi es @ 81-90 81-90<br>be Y aE aE i<br> ieeSeS @ 91-100 91-100<br><!-- End of picture text --> <!-- Start of picture text --> =—= Delorme Road Road Link Se one ye yh ye yh yh<br>RRs - \ 4 4 ,<br><!-- End of picture text --> <!-- Start of picture text --> heLeLe<br>aes<br>Cag<br><!-- End of picture text -->
|LAO PDR: Rice ProductivityImprovement Project<br>Paavo Eliste|
|---|
|LAO PDR: Rice ProductivityImprovement Project<br>Paavo Eliste|
|LAO PDR: Rice ProductivityImprovement Project<br>Paavo Eliste|
|MA-IDF Modernization of Public Procurement II<br>Abdoulaye Keita|
|MA-IDF Modernization of Public Procurement II<br>Abdoulaye Keita|
|MA-IDF Modernization of Public Procurement II<br>Abdoulaye Keita|
|MA-IDF Modernization of Public Procurement II<br>Abdoulaye Keita|
|MA-IDF Modernization of Public Procurement II<br>Abdoulaye Keita|
|Tblisi cityDevelopment Strategy<br>Ahmed A. R. Eiweida|
|Tblisi cityDevelopment Strategy<br>Ahmed A. R. Eiweida|
|Tblisi cityDevelopment Strategy<br>Ahmed A. R. Eiweida|
|Tblisi cityDevelopment Strategy<br>Ahmed A. R. Eiweida|
|Tblisi cityDevelopment Strategy<br>Ahmed A. R. Eiweida|
|ZM:Results Oriented Monitoring& Eval<br>Jutta Ursula Kern|
|ZM:Results Oriented Monitoring& Eval<br>Jutta Ursula Kern|
|ZM:Results Oriented Monitoring& Eval<br>Jutta Ursula Kern|
|Regional Network for CapacityBuildingof National Statistical SystemJoao Pedro Wagner De Azevedo|
|Regional Network for CapacityBuildingof National Statistical SystemJoao Pedro Wagner De Azevedo|
|Regional Network for CapacityBuildingof National Statistical SystemJoao Pedro Wagner De Azevedo|
|Regional Network for CapacityBuildingof National Statistical SystemJoao Pedro Wagner De Azevedo|
|Enhancement of M&E System in the Roads Administration<br>Aliya Karakulova|
|Enhancement of M&E System in the Roads Administration<br>Aliya Karakulova|
|Enhancement of M&E System in the Roads Administration<br>Aliya Karakulova|
|Services Support Project(Co-Financingand Restructuring)<br>Philippe Auffret|
|Services Support Project(Co-Financingand Restructuring)<br>Philippe Auffret|
|Guinea Bissau BiodiversityConservation Trust Fund Project<br>Liba Chaja Strengerowski|
|Regional Network for Education Research Initiative<br>Juan Manuel Moreno Olmedilla|
|Regional Network for Education Research Initiative<br>Juan Manuel Moreno Olmedilla|
|Regional Network for Education Research Initiative<br>Juan Manuel Moreno Olmedilla|
|Lagos Urban Transport Project 2<br>Roger Gorham|
|Lagos Urban Transport Project 2<br>Roger Gorham|
|Lagos Urban Transport Project 2<br>Roger Gorham|
|Lagos Urban Transport Project 2<br>Roger Gorham|
|Lagos Urban Transport Project 2<br>Roger Gorham|
|Lagos Urban Transport Project 2<br>Roger Gorham|
|Lagos Urban Transport Project 2<br>Roger Gorham|
|Lagos Urban Transport Project 2<br>Roger Gorham|
|Lagos Urban Transport Project 2<br>Roger Gorham|
|Lagos Urban Transport Project 2<br>Roger Gorham|
|Lagos Urban Transport Project 2<br>Roger Gorham|
|Lagos Urban Transport Project 2<br>Roger Gorham|
|Lagos Urban Transport Project 2<br>Roger Gorham|
|Lagos Urban Transport Project 2<br>Roger Gorham|
|IRF Road SafetyTraining<br>Tawia Addo-Ashong|
|Kazakhstan Moinak ElectricityTransmission Project<br>Mirlan Aldayarov|
|Kazakhstan Moinak ElectricityTransmission Project<br>Mirlan Aldayarov|
|Kazakhstan Moinak ElectricityTransmission Project<br>Mirlan Aldayarov|
- 19.s

the "upper income" group (8% of the cohort's population) received 14% of all educational expenditure, "middle income" group (67% of the population) received 74% of expenditure, while the poor (25% of population) received only 12% of expenditure. Education in Egypt, as elsewhere, subsidizes the middle and upper classes.

# 67.

67. It is difficult to determine the rural-urban equity aspects of higher education, since no data are available on the geographical origin of university students. However, some indirect information may be obtained by looking at the enrollment ratios at the secondary level; there is a marked 'urban bias" in such ratios: 61.2% of urban youth of this age are so enrolled, while only 25% or rural youth are enrolled. Since agriculture, the main rural economic activity, is taxed (Dethier, 1989), subsidies to higher education may be construed as a transfer from rural to urban areas, and hence, as disequalizing.20

# 68.

68. Within higher education itself, a principal equity issue is the gender question. Here some progress appears to have been made during the 1980s. Although women are still a minority of university students, they are slightly better represented now than in the mid-1970s. (See Table 10) Women now constitute over a third of all university students; although the absolute numbers of women students declined along with total enrollments after 1985, they declined proportionally less than the numbers of men.

# 69.

69. An important equity (and efficiency) issue has been raised in Egypt as elsewhere concerning charging "user fees" for higher education. Given the generally higher socio-economic status of most university students, such a change would be desireable. Indeed, the current structure of fees (charged for primary, but not for higher education) is precisely the opposite of what a genuine concern for equity would dictate. The problem of change is, as usual, political. Midd'e-class people are everywhere more vocal and politically active than the poor. Since many of the "middle class" people who enjoy university subsidies are far from wealthy, they feel very threatened by the prospect of university fees.

# 70.

70. This question is linked to another issue which has been publicly discussed but upon which no action has been taken or is even seriously contemplated: the creation of private universities. As previously noted, one such institution already exJcs: the American University in Cairo. Despite receiving grants and funds from the United States, tuition is high: some US$5,000 per semester, equivalent to tuition at less-expensi ., private universities in the United States. Such fef-s are far above the means of the vast majority of Egyptian families. However, enrollments in the AUC have grown rapidly, and demand for entrance is strong. It is conceivable tha. other private universities, charging lower fees than the AUC but more than the public universities, might be able to attract students and to be self-financing.

> X Average urban incomes are about 46% above rural averages. (World Bank, 1991, p. 11).