rafmacalaba/datause-encoder-data huggingface dataset:
Republic of Congo where a passport costs 125 percent of per capita income.<sup>8</sup> Eleven out of the fourteen countries where passport costs are 10 percent or more of annual per capita income are located in Africa. Nevertheless, other African countries manage to maintain low costs: passport costs are only 1.4% of per capita income in Ghana, 1.17% in Kenya, 0.3% in Swaziland and 0.12% in Botswana.

**Table 2: Countries where a passport costs 5% or more of annual per capita income**

||% pcGNI||% pcGNI|
|---|---|---|---|
|Democratic Republic of Congo|125.0|Cameroon|11.4|
|Chad|60.2|Nigeria|10.0|
|Burundi|50.9|Turkey|8.9|
|Rwanda|41.5|Mauritania|8.7|
|Ethiopia|31.1|Benin|8.6|
|Nepal|26.3|Republic of Congo|8.5|
|Niger|19.8|Bosnia and Herzegovina|7.0|
|Central African Republic|17.7|Bolivia|6.7|
|Tanzania|13.4|The Gambia|6.0|
|Tajikistan|13.4|Papua New Guinea|5.3|
|Burkina Faso|12.7|Bangladesh|5.2|
|Lao PDR|11.8|||

pcGNI = annual per capita Gross National Income

# **3. What determines passport costs?**

Passport costs which are high relative to income are likely to act as a barrier to the ability of citizens to migrate. The question which then arises is why they are so high. One possible explanation is that passport costs are high relative to income in poorly governed countries. This may be due to poor capacity to efficiently carry out bureaucratic procedures, a repressive desire to stop citizens traveling, or to the inability to collect government revenue through standard taxation procedures. To investigate the relationship between passport costs and government, we employ the Governance IV indicators for the

> 8 Note that in the Democratic Republic of Congo, a passport has an official price of US$80, but the going price for an ordinary citizen is US$150 (Source: World Bank resident mission).

- 8 -
reproductive years are predicted to have approximately 6.7 children by the time they end child bearing, whereas women with access for 15 or more years will have approximately 5.5 children.<sup>21</sup> The differences in effects across age groups suggest that long-term access to family planning services leads to a substantial compression in the timing of births. One might a priori expect a uniform reduction in births across age or that the cumulative effect would become larger with increasing age. Instead there are large reductions for women younger than 20 and women older than 30. Because the outcome is cumulative births, women with access to family planning must have had more children in their early twenties than those without access to family planning. Women aged 15 to 19 with access are estimated to have 1 birth less than those without access; women aged 20 to 24 with access have only 0.3 cummulative births less than those without access. In other words, compared to those without access to family planning, women with access have, on average, given birth to 0.7 children _more_ between the ages of 20 and 25.<sup>22</sup> This compression is possible because the average birth spacing in Africa is substantially longer than in other areas with women relying on extended periods of breastfeeding and abstinence as methods for controlling fertility (Bongaarts, Frank and Lesthaeghe 1984). With access to family planning a woman can directly control both timing of births and when to stop having children and this allows for a compression of fertility.

Table 4 is restricted to the sample of women with no schooling. Including women with schooling, we find that for women who have passed first grade or above, there is no discernible impact of access to family planning on fertility.<sup>23</sup> OLS results show that for women with 1 to 5 years of education access to family planning increases fertility by approximately 0.1, whereas access decreases fertility by around 0.1 for women with 6 to 12 years of education. Using the IV results, the effect for women with 1 to 5 years of education is still an approximately 0.1 increase and for women with 6 to 12 years of education the effect is a reduction of 0.2. None of these results are statistically significant. Using the same age groups as above for the two education groups leads to no consistent results.

> 21Predictions based on average values of all variables except for age and access to family planning.

> 22For example, a woman without family planning has 1 child between 15 and 19 and an additional 1.3 child between

> 20 and 25, then a woman with access will have 0 children between 15 and 19 and 2 children between 20 and 25.

> 23Table A-2 presents results for the sample of all women.

16
grandfathering.<sup>5</sup> Third, any socioeconomic classification based on a distribution of labor earnings may be endogenous to the very transition that it is intended to capture, which can be reasonably assumed to be strongly (even if not exclusively) motivated by wanting to improve individual or household earnings. So can other categorizations based on consumer goods and assets that are collected in the Colombian survey and whose acquisition may also depend on increased disposable incomes after transitions take place. Of course, a relative poverty measure will not eliminate endogenous concerns, but to the extent that it limits the number of categories to analyze (only two categories, below or above the median, instead of five or ten as in income quintiles and deciles), biases should be less critical.

Results disaggregating transitions by category and poverty status confirm that poor and non-poor workers transition in different fashions (Table 6). For each category of informality and occupation, only the informal salaried, the informal self-employed and individuals out of the labor force have comparable diagonal results. In contrast, there are substantive differences in the relative proportions of those who did not transition among formal salaried, formal self-employed and unemployed. Among the former two, the non-poor in 2008 seem to have transitioned more than the poor, while the unemployed poor transitioned more than the non-poor. Results confirm a high volume of transitions when considering socioeconomic status. Again, the out-of-labor-force category is the most stable of all, followed by salaried workers (with non-poor being more stable than the poor). Very few of the remaining categories changed their labor condition. The magnitude of these transitions is not negligible and, again, transitions are asymmetric: a transitioning worker is more likely to remain within the same socioeconomic category in which the individual started in 2008 than to change socioeconomic status. A quarter of individuals moved into 5 As seen above (Table 1), classifications of workers based on SISBEN and poverty lines differ substantially (even though trends move in similar directions) given that the official poverty lines are well below the median of per capita household incomes in the sample: COP 281,384 and COP 850,999 respectively for 2009. Also, the estimated poverty incidence from the FSLS sample, at 70.5 percent, doubles the official poverty incidence for the 13 metropolitan areas, estimated by MESEP (2010) as 30.6 percent.

15
Table C.1: Summary Statistics

|||All||Small (5|-10)|Medium (|11-99)|Large (100+)|
|---|---|---|---|---|---|---|---|---|
||N|Mean|p50|N|Mean|N<br>|Mean|N<br>Mean|
|Total # of employees|18570|33.95|9.00|9909|8.45|5477|38.03|3184<br>492.04|
|% of workers with college<br>|17686|30.15|20.00|9520|30.79|5144|27.71|3021<br>28.12|
|Management practice (z-score)|20739|0.00|0.27|11029|–0.09|6098|0.25|3610<br>0.53|
|Sales per worker|15355|11.45|11.43|8121|11.47|4545|11.39|2689<br>11.25|
|||Share||Share||Share||Share|
|Multi-establishment||18.4%||12.1%||20.5%||33.9%|
|Multinational||17.6%||16.4%||16.4%||23.7%|
|Exporter||16.8%||8.1%||18.1%||41.0%|
|_Age:_|||||||||
|1–5 Years||17.9%||22.2%||15.2%||9.3%|
|6–10 Years||21.3%||24.1%||19.6%||15.4%|
|11–15 Years||17.9%||18.4%||17.2%||17.4%|
|16+ Years||42.9%||35.3%||47.9%||57.9%|
|Has electricity, computer and in|ternet|77.1%||67.0%||85.7%||95.0%|
|_Sector:_|||||||||
|Agriculture||5.1%||5.1%||5.2%||5.1%|
|Livestock||1.9%||2.2%||1.7%||1.4%|
|Food Processing||10.2%||8.9%||11.8%||11.3%|
|Apparel||7.4%||6.9%||6.4%||10.5%|
|Motor vehicles||2.9%||2.0%||3.2%||5.0%|
|Pharmaceuticals||2.7%||1.5%||3.2%||5.3%|
|Wholesale or retail||14.7%||18.0%||12.4%||8.6%|
|Financial services||3.4%||3.2%||4.0%||2.6%|
|Land Transport||5.0%||5.0%||5.2%||4.3%|
|Health Services||4.4%||2.1%||5.5%||9.5%|
|Leather||2.2%||2.2%||1.8%||2.7%|
|Other Manufacturing||15.8%||16.1%||15.1%||16.1%|
|Other Services||24.4%||26.7%||24.3%||17.6%|

Notes : The table reports summary statistics of establishment-level measures and distribution of establishments, in the overall sample, and by size-groups. The top panel consists of summary statistics calculated using establishment-level sampling weights. The bottom panel reports the unweighted shares of establishments belonging to the various groups.

119
# **Appendix Figure B.   WTO Membership Use of Countervailing Duties (CVD), 1995 - 1Q 2009**

# **CVD Historically, by year: 1995-2008**

<!-- Start of picture text --> 45<br>40<br>35<br>30<br>CVD Initiations<br>25<br>20 CVD Measures<br>15<br>10<br>5<br>0<br>1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008<br><!-- End of picture text -->

**CVD During the Crisis, by quarter: 1Q 2007- 1Q 2009**

<!-- Start of picture text --> 9<br>8<br>7<br>6<br>CVD Initiations<br>5<br>4 CVD Measures<br>3<br>2<br>1<br>0<br>1Q- 2Q- 3Q- 4Q- 1Q- 2Q- 3Q- 4Q- 1Q-<br>2007 2007 2007 2007 2008 2008 2008 2008 2009<br><!-- End of picture text --> Sources: data in top panel taken from the WTO member reports to the Committee on Subsidies and Countervailing Measures and comprehensively covers the full WTO membership. Data in bottom panel compiled by the author from the _Global Antidumping Database_ and covers only 18 using countries. According to data from the WTO, these 18 Members initiated 93 per cent (97 per cent) of all countervailing duty investigations (new measures imposed) by the WTO membership during 1995-2007. Unlike figure 1, the unit of observation is a WTO member country’s CVD action over a given product from a single exporting country.

26
The Muslim Family Ordinance of 1961 provides for arbitration councils to deal with family matters, including divorce, dowry, and maintenance. Arbitration council panels are comprised of three members: the UP chairperson and two others, one of whom is chosen by each party. Like the village courts, arbitration councils also have the power to issue binding decisions, though the Muslim Family Ordinance does not set a limit on the size of judgments (Muslim Family Law Ordinance 1961).

Administratively, the nodal department in charge of UPs is the Local Government Division (LGD) within the Ministry of Rural Development and Local Government. Village courts and arbitration councils are also under the supervision of LGD, rather than of the Ministry of Law, Justice, and Parliamentary Affairs. This placement reflects the distinctiveness of the village courts and arbitration councils from the rest of the judicial system: Village courts and arbitration councils are more local and less legal.

The Madaripur Legal Aid Association (MLAA), founded in 1978, has long engaged in facilitating shalish and in providing legal assistance. In recent years, the MLAA has worked in 100 Unions in Madaripur, Shariatpur, and Gopalganj Districts to activate and strengthen village courts and arbitration councils. MLAA trains UP chairpersons and council members in dispute resolution, monitors the functioning of **Figure 4: Cases in MLAA village courts July 2006-June 2007** village courts and arbitration councils, **OtherSource: MLAA Second** and popularizes the institutions through **Social dispute6.4% 4.8% marriage** drama and awareness campaigns. **Assault 0.4% Dowry 29.3%** MLAA also provides each village court **7.9%** with a full-time ―court clerk‖ – a functionary who accepts case **Financial** applications, conducts outreach, and **dispute9.8%** keeps court records. The village courts have a very high disposal rate. Between July 2006 and June 2007, for **Land dispute Family Dispute** example, the 100 Unions in which **13.6% 27.8%** MLAA works carried over 347 cases from prior months and received 5,133 applications for new cases. Out of those 5,480 cases, 4,670 were decided, 343 were dropped, one was referred for certificate, and 489 remained pending. MLAA‘s work was the inspiration for a recently established EU-LGD partnership to activate village courts at a larger scale.

It is widely held that, outside of MLAA‘s coverage area, village courts are largely defunct and UP members have little knowledge of the Village Courts Act (Bode, 2002; Lewis and Hossain, 2005; Hassan, 2006; Hossain, Moran, and Stapleton, 2007).

―A system of formal village courts located at the union _parishad_ , which has rarely been effective, has now in most cases disappeared. This leaves the traditional informal _shalish_ as the dominant means of adjudication for small-scale civil and criminal disputes.‖ (Lewis and Hossain, 2005: 19-20).

However, no study has a large enough sample to assert this with representative empirical validity.

16
structure of the US immigration to the immigration to the other OECD countries (transposition problem); ii) immigration to EU countries was estimated based on OECD statistics reporting the number of immigrants for the major emigration countries only, which led to underestimate immigration from small countries (under reporting problem).

Docquier and Marfouk (2006) generalized this work and provided a comprehensive data set on international skilled emigration to the OECD. The construction of the database relies on three steps: i) collection of Census and register information on the structure of immigration in all OECD countries (this solves the transposition and under reporting problems noted for Carrington Detragiache); (ii) summing up over source countries allows for evaluating the stock of immigrants from any given sending country to the OECD area by education level, and iii) comparing the educational structure of emigration to that of the population remaining at home, which allows for computing emigration rates by educational attainment in 1990 and 2000.

The DM06 data relies on assumptions, some of which were relaxed in a couple of extensions. Most of these extensions required additional assumptions but con...rmed, to a large extent, the reliability of using DM06 data in descriptive analysis and empirical regressions.

- First, with only two points in time, DM06 does not give a precise picture of the long-run trends in international migration. To remedy this problem, Defoort (2006) computes skilled emigration stocks and rates from 1975 to 2000 (one observation every 5 years). She uses the same methodology as in DM06 but only focuses on the six major destination countries (the USA, Canada, Australia, Germany, the UK and France). Her study shows that, at the world level or at the level of developing countries as a whole, the average skilled migration rate has been extremely stable over the period. This suggests that the heterogeneity in the brain drain is mostly driven by the cross-section dimension, thus reinforcing the value of the DM06 cross-country data set based on a much more comprehensive set of destination countries.

- Second, counting all foreign born individuals as immigrants independently of their age at arrival, DM06 does not account for whether education has been acquired in the home or in the host country. Controlling for the country of training can be important when dealing with speci...c issues such as the ...scal cost of the brain drain. Beine, Docquier and Rapoport (2006) use immigrants’ age of entry as a proxy for where education has been acquired and propose alternative measures of the brain drain by de...ning skilled immigrants as those who left their home country after age 22, 18 or 12. Data on age of entry are collected in a dozen countries. For OECD countries where such data cannot be obtained, Beine et al. estimate the age-of-entry structure using a gravity model. They ...nd that corrected skilled emigration rates are highly correlated

5
5 where a creditor receives payment is consequential. Still, many of the issues presented would require the application of English law. Section 6 concludes, finding that several factors point towards a lengthy road to resolution.

2. Know thy borrower: A brief history of Russian debt and defaults Russia is no stranger to external debt defaults and all their pains. Since the year 1900, Russia has defaulted three times on private external creditors if we consider the debts of the sovereign and its instrumentalities (i.e. the public sector at large).<sup>3</sup> During the nineteenth century, Russia sought _to integrate_ itself with Europe and was seen as one of the innovators of sovereign finance.<sup>4</sup> It was the first to issue a “Eurobond” – a security listed in multiple European exchanges – and, in the 1890s, it issued gold bonds to allow for their free and fungible circulation inside and outside Russia.<sup>5</sup> Its time as a sophisticated actor in global capital markets ended when the Soviet government repudiated all tsarist debts on January 21, 1918 and turned inward – _the autarkic stance_ .<sup>6</sup> Despite numerous talks and agreements in principle, Russia only implemented solutions on the repudiated debt question in 1986 with British creditors and in 1996 with French creditors for pennies on the dollar.<sup>7</sup> In the interim, the USSR regained

> 3 It is worth noting that “external” default can be defined along three lines: residency of the creditor, currency of denomination, and governing law of the contracts.

> 4 Andrey D. Ukhov, _Financial innovation and Russian government debt before 1918 (Working Paper No. 03-20)_ [Electronic version]. New Haven, CT: Yale International Center for Finance, at 16-17 (2003).

> 5 Russia also consistently monetized deficits during the nineteenth century, which though negative was also innovative for the period. It built a complex liability structure with a complete yield curve and issued domestic and foreign debt consistently. The mechanisms through which it issued bonds in foreign markets since the time of Katherine the Great became the standard for the period – placing a large loan with a finance house in a financial center which would then issue local, smaller face value bonds to investors collateralized by the Russian loan. Another notable innovation was the lottery bonds used to collect liquidity from the Russian population at large. For a complete accounting of Russia’s financial innovations prior to 1918. S _ee id_ .

6 Yulia Sinyagina-Woodruff, _Russia, Sovereign Default, Reputation and Access to Capital Markets_ , Europe-Asia Studies, Vol. 55, No. 4, at 532 (2003).

7 The resolution was in fact signed with the respective governments. With the British, the USSR agreed to forgo 5.5 tons of Nicholas II’s own gold in exchange for that government’s agreement to settle all the claims of private British holders of tsarist debt (10% of the value of claims presented). With the French, a similar agreement was reached for a measly US$400 million (1-2% of the value of the claims presented). _Id_ . at 535.
Standardization leads to a slight change in food expenditures in all countries. With non-food nondurables, standardization slightly increases the share of non-food non-durables in Bangladesh, Bhutan, India, and Sri Lanka, but decreases in other countries. Standardization does not affect health care expenditures, and the proportion of housing expenditure changes little with standardization. However, Indian housing expenditure is much higher than that seen in the national consumption aggregate, and this is driven mainly by the inclusion of imputed rent among urban households. To study this point further, we reproduce Tables 8 and 9, but only for the poor in each country. The tables are presented in the Appendix and show that much of the increase in consumption expenditure among the poor in urban India is driven by imputed rent.

While standardization of consumption aggregates does not affect international poverty rankings for most countries, it has a significant effect on the poverty numbers for India. Table 11 shows the international extreme poverty rates calculated using national consumption aggregates and standardized consumption aggregates. In some cases, the standardization increases the poverty rate, like in Bangladesh, Bhutan, Pakistan, and Sri Lanka. However, in the cases of India, Maldives, and Nepal, the standardization process decreases the international extreme poverty rate.

**Table 10. Budget shares** **<u>by categories</u>**

||**B**|**anglad**|**esh**|**Bhutan**||**Ind**|**ia**|**Maldives**|**Nepal**|**Pakistan**|<br>**Sri**<br>|
|---|---|---|---|---|---|---|---|---|---|---|---|
||**All**|**Rural**|**Urban**||**All**|**Rural**|**Urban**||||<br>**Lanka**|
||**2010**|**2010**|**2010**|**2012**|**2011/12**|||**2009**|**2010**|**2011/12**|**2012/13**|
|_National Consumption Exp_|_enditu_|_re_||||||||||
|- Food|58|61|53|45|51|54|46|37|57|52|45|
|- Non-food non-durables|19|19|20|28|25|24|27|53|27|21|25|
|- Health|4|4|3|4|5|6|5|7|0|3|2|
|- Education|5|4|8|3|4|2|4|3|5|2|2|
|- Durable goods|1|1|1|<1|3|3|3|0|4|0|1|
|- Housing|14|13|18|19|13|12|16|33|6|21|22|
|Total|100|100|100|100|100|100|100|100|100|100|100|
|_Standardized Consumption_|_Aggr_|_egate_||||||||||
|- Food|57|59|52|44|46|51|34|29|53|48|50|
|- Non-food non-<br>durables|20|20|20|30|28|28|28|28|20|23|24|
|- Health|3|3|3|3|5|5|4|7|9|3|5|
|- Education|6|5|8|2|2|2|3|3|4|3|5|
|- Durable goods|2|2|2|3|2|2|2|12|7|2|3|
|- Housing|14|13|19|19|17|12|29|21|8|21|18|
|Total|100|100|100|100|100|100|100|100|100|100|100|

Source: Authors’ own estimates based on South Asia Harmonized Micro Dataset (SARMD). India’s consumption aggregates reported are based on the Uniform Recall Period (URP).

For the most part, the standardization process preserves the poverty rankings. When we use the national consumption aggregates to estimate the international extreme poverty rate, Sri Lanka has 16