rafmacalaba/datause-encoder-data huggingface dataset:
# **_7.1 References_**

Aksoy, M.A. and Izik-Dikmelik, A. 2007. Are low food prices pro-poor? net food buyers and sellers in low income countries. Mimeo, World Bank.

Atkinson, A. 1987. “On the measurement of poverty” Econometrica. 55(4):749-64.

Bertrand, Trent and Squire, L. 1980. The Relevance of the Dual Economy Model: A Case Study of Thailand, Oxford Economic Papers, New Series, Vol. 32, No. 3. (Nov., 1980), pp. 480-511.

Chen, S. and Ravallion, M. 2004. “Welfare Impacts of China’s Accession to the World Trade Organization.” in Bhattasali, D., Li, S. and Martin, W. eds. China and the WTO: Accession, Policy Reform, and Poverty Reduction Strategies., Oxford and Washington DC: Oxford University Press and the World Bank.

Dawe, D. 2008. Have recent increases in world cereal prices been transmitted to domestic economies? Experience in seven large Asian countries, Powerpoint Presentation, FAO, Rome, 14 March.

Denning, G. and Sachs, J. 2007. How the rich world can help Africa help itself. Financial Times May 29.

Deaton, A. 1989. “Rice prices and income distribution in Thailand: a non-parametric analysis.” Economic Journal. 99(Conference):1-37.

Deaton, A. 1997. The Analysis of Household Surveys. A Microeconometric Approach to Development Policy. Baltimore and Washington DC: The World Bank and Johns Hopkins University Press.

Deaton, A.S. and Laroque, G., 1992. On the behavior of commodity prices. Review of Economic Studies 89. 1–23.

Easterly, W. and Fischer, S. 2001. “Inflation and the poor.” _Journal of Money, Credit and Banking_ 33(2, Part 1): 160-78.

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# **Table 5.6   Equity markets in the focus countries at end-2006**

|Country|Stock market cap as<br>percent of GDP|Annual turnover ratio<br>(%)|Tally of listed<br>companies|Tally of listed<br>companies in<br>infrastructure sectors|Market cap of<br>infrastructure<br>companies as share<br>of total market cap of<br>listed companies (%)|
|---|---|---|---|---|---|
|BRVM total /3|9|3.3|40|6|47|
|of which:||||||
|Benin|—|—|1|0|0|
|Burkina Faso|—|—|0|0|0|
|Côte d’Ivoire|—|—|36|5|10|
|Niger|—|—|1|0|0|
|Senegal|—|—|1|1|100|
|Cameroon|0|0|1|0|0|
|Cape Verde|3|7.1|3|0|0|
|Ghana|29|2.1|32|0|0|
|Kenya|49|14.6|52|3|18|
|Malawi|27|3.5|11|0|0|
|Mozambique|1|0.04|1|0|0|
|Namibia|8|3.8|28|0|0|
|Nigeria|27|13.6|202|10|0|
|South Africa|245|48.8|377|25|8|
|Sudan|12|20.6|52|2|50|
|Tanzania|19|2.1|10|2|25|
|Uganda|26|5.2|8|1|33|
|Zambia|31|0.7|16|0|0|
|Chile|129|18.5||47|27|
|Malaysia|158|32.1||—|—|

Sources: Equity markets data are sourced from national securities exchanges and/or national regulatory authorities; S&P, _Global Stock Markets Factbook 2007_ .

Note: At the end of 2006, there were no organized equity markets in Chad, Democratic Republic of the Congo, Ethiopia, Lesotho, Madagascar, and Rwanda. Note: GDP figures for 2006 are sourced from World Bank DDP database (Development Prospects Group annual estimates). The turnover ratio is defined as the total value of shares traded during the specified one-year period, divided by average market capitalization for the specified one-year period and the preceding one-year period. Turnover ratios for Kenya, Tanzania, Uganda, Côte d’Ivoire, Ghana, Malawi, Nigeria, Namibia, South Africa, Chile, and Malaysia are calculated by dividing total 2006 U.S.-dollar value traded by average U.S.-dollar market capitalization for 2005 and 2006. Data for the BRVM cover all eight member countries. Côte d’Ivoire, Benin, Burkina Faso, Niger, and Senegal are members of the BRVM, headquartered in Côte d’Ivoire but with trading floors in each member country. Companies domiciled in Côte d’Ivoire, Benin, Burkina Faso, Niger, and Senegal have issued shares on the BRVM. — = Not available.

The Johannesburg Stock Exchange in South Africa overshadows all other exchanges in the region. Its market capitalization of $621.6 billion at the end of 2006 accounted for nearly 90 percent of the total market capitalization in Sub-Saharan Africa. WAEMU’s eight member-country regional exchange, the BRVM, had a total market capitalization of only $4.16 billion and 40 equity listings at end-2006, 36 of which were from Côte d’Ivoire.

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Table 8a: Change in the volume of exports in 2030, percent change from baseline, ctd.

||Rest of<br>East<br>Asia|Bangladesh|India|Nepal|Pakistan|Sri<br>Lanka|Rest of<br>South<br>Asia|EU ECA|Russian<br>Federation|
|---|---|---|---|---|---|---|---|---|---|
|Agriculture|4.4|-10.2|7.8|0.5|-31.7|-0.8|3.6|2.0|5.9|
|Minerals n.e.s.|-0.6|11.5|0.1|-2.5|-6.4|-1.9|6.0|0.1|-0.3|
|Coal|19.5||0.4||11.9||12.8|-5.3|6.3|
|Oil|-2.3||-4.6||38.8||-5.9|2.8|0.8|
|Gas|2.7|-20.2|11.8||51.3||6.9|1.1|1.5|
|Textiles|-0.7|13.1|2.6|2.8|0.3|-2.0|22.6|0.4|1.6|
|Wearingapparel|3.2|7.8|-0.9|3.2|8.6|1.0|20.5|0.0|1.3|
|Leathergoods|-2.3|1.6|2.2|-0.7|-11.5|1.4|2.8|-1.3|-1.4|
|Processed foods|-3.0|4.9|6.5|-2.2|17.7|-1.6|-1.1|0.9|4.4|
|Woodproducts|3.6|-2.5|8.0|2.2|-40.9|2.5|13.1|0.1|4.1|
|Paper products,<br>publishing|-1.6|13.0|1.0|2.6|21.4|-1.4|20.7|0.3|3.1|
|Petroleum, coal<br>products|-2.6|55.4|3.8||17.9|2.7|9.0|0.2|1.9|
|Chemical, rubber,<br>plastic|-2.1|19.7|6.5|-8.0|72.9|4.0|29.1|-0.4|0.4|
|Energyintensive man.|-0.7|45.1|2.5|-6.2|17.9|-3.1|2.5|-0.5|0.4|
|Metalproducts|1.8|71.4|5.4|9.9|34.7|2.0|16.1|-0.8|0.8|
|Electronics|9.5|203.3|7.6|1.1|34.9|9.2|35.7|-6.5|-8.0|
|Machinery and<br>equipment|1.1|197.6|6.3|5.5|15.7|7.9|25.1|-1.7|-3.5|
|Transport equipment|1.3|51.8|-1.3|2.8|48.6|-0.6|26.1|-0.7|-1.2|
|Manufactures,n.e.s.|22.7|126.0|8.9|11.4|56.9|7.4|20.1|-1.6|1.7|
|Electricity|0.1||0.4||||1.1|0.5|0.7|
|Construction|-1.7|-9.9|3.7|0.7|7.4|0.4|2.7|1.7|0.4|
|Trade services|-0.9|-17.0|10.6|2.0|-6.8|2.2|1.6|2.2|1.1|
|Other transport|-0.6|-5.1|6.7|1.7|-7.0|2.5|5.4|0.2|0.3|
|Water transport|-2.5|-7.5|5.5|-0.7|-19.9|1.1|1.9|-1.0|1.3|
|Air transport|-1.5|-6.5|3.9|1.4|-10.4|3.2|9.6|0.3|-0.3|
|Hospitalityservices|-2.3|19.5|0.4|-1.8|41.2|-2.8|-0.3|3.3|4.2|
|Other business services|-2.1|-3.0|-0.9|-2.4|2.0|-3.4|-2.7|2.7|-0.6|
|Other services|-0.7|-4.2|-0.2|-0.5|0.9|-0.8|-1.6|0.8|0.0|
|**Agriculture**|4.4|-10.2|7.8|0.5|-31.7|-0.8|3.6|2.0|5.9|
|**Manufacturing**|2.5|10.1|4.2|0.2|14.2|1.9|7.7|-1.2|0.9|
|**Services**|-1.6|-3.4|0.4|-1.0|-1.6|-0.8|1.1|1.6|0.1|
|**Other**|2.9|-3.5|0.1|-2.5|-5.8|-1.9|5.4|-1.5|1.3|
|**Total**|1.1|8.7|2.9|-0.2|9.8|1.0|3.2|-0.7|1.2|

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countervailing duties, as well as safeguard measures. As Table 2 indicates, some of the heaviest users of trade remedies such as antidumping are now developing economies. At the same time that the use of trade remedies has proliferated across the WTO membership, the application of trade remedies increasingly faces legal challenges through formal WTO dispute settlement. Indeed, Table 3 indicates that almost half of the WTO disputes initiated between 1999 and 2006 involved challenges to trade remedies. Furthermore, in most trade-remedy cases that make it through the panel process, the Dispute Settlement Body has found some WTO-inconsistent element of the investigation undertaken and/or measure imposed by the respondent country.<sup>16</sup> Thus there is little evidence from the WTO caseload that a country that applies a trade remedy is likely to have it ruled as being consistent with its WTO obligations.

Given this context, one particularly interesting feature of the data is that a developing country’s use of a trade remedy is unlikely to be formally challenged under the WTO Dispute Settlement Understanding (DSU). For example, developing countries are some of the most frequent new users of antidumping. If we assume developing country government agencies are just as likely as developed countries to apply WTO- _inconsistent_ measures,<sup>17</sup> we would expect many of these measures to be challenged at the WTO. While the data in the right hand column of Table 2 suggest that some developing country use of antidumping is being challenged by WTO litigation, the number of challenges is small – especially when we consider that over half (38 of 69) of the challenges reported in the table were brought up in only two disputes (DS304 and DS318) against India that never made it past the stage of the EU and Taiwan requesting consultations. For the most part, the explosion in developing economy use of newly-imposed and potentially WTO-inconsistent antidumping measures is going unchallenged by WTO litigation.

There are many possible reasons why developing country use of antidumping is going unchallenged by formal WTO trade disputes. As a specific example, Bown’s (2006a) crosscountry study of determinants of DSU challenges to the use of antidumping presents evidence, consistent with the concerns raised here, that an antidumping measure is less likely to be challenged the smaller is the value of export market access lost to the measure. Exporters are

> 16 For a review of some of the jurisprudence, see Cunningham and Crib (2003), Durling (2003) and Sykes (2003).

> 17 There is little ex ante reason to expect that the investigative agencies in developing countries are more likely than those in the US or EU, for example, to implement a WTO-consistent investigative procedure and apply a WTOconsistent trade restriction. If anything, given the lack of historical familiarity with the interaction between national trade remedy laws and GATT/WTO law, one would expect developing countries to be _more_ likely than developed countries to implement measures that are inconsistent with WTO obligations.

11
Figure 3 (a): Thailand Skill Premiums – basic controls <!-- Start of picture text --> Thailand: Skill Premium and Skilled Workforce- Basic controls<br>only<br>1.4<br>1.2<br>Skilled-1: Upper<br>1 Secondary and above<br>0.8 Skilled-2: Tertiary and<br>above<br>0.6<br>Skill Premium-1<br>0.4<br>Skill Premium-2<br>0.2<br>0<br>1990 1994 2000 2004<br>Year<br>Workers<br>Skill Premium and<br>Proportion of Skilled<br><!-- End of picture text --> Figure 3 (b): Thailand Skill Premiums – industry controls <!-- Start of picture text --> Thailand: Skill Premium and Skilled Workforce- With Industry<br>controls<br>1.2<br>1<br>Skilled-1: Upper<br>0.8 Secondary and above<br>Skilled-2: Tertiary and<br>0.6 above<br>Skill Premium-1<br>0.4<br>Skill Premium-2<br>0.2<br>0<br>1990 1994 2000 2004<br>Year<br>Workers<br>Skill Premium and<br>Proportion of Skilled<br><!-- End of picture text --> 24
**Table 20 Non-Agricultural Self-employment: Lithuania against Selected Countries**

||Self-employment|
|---|---|
||%oftotalemployment|
|Lithuania(2001)|10.5|
|CzechR.|13.2|
|Denmark|6.9|
|France|8.2|
|Gennany|9.4|
|Hungary|13.1|
|Netherlands|9.7|
|Poland|12.0|
|Spain|17.6|
|UnitedKingdom|11.4|
|UnitedStates|7.0|

Note: Data refer to 1998 unless stated otherwise Source: Lithuania: LFS May 2001, Bank staff calculations.

Poland: LFS February 1999, Bank staff calculations OECD: OECD Employment Outlook 2000 The limited incidence of flexible forms of employment reflects the existing regulatory restrictions on the use of fixed-tern contracts, possibly unfavorable treatment of part-time employment with respect to the entitlement to various work-related benefits, and probably the lack of tradition and incentives to use flexible contracts. The low share of self-employment is somewhat surprising given the innovative system of so called "patents", i.e., licenses (permits) to carry out short-term economic activity. These "patents", which are relatively cheap and easy to obtain, are intended to formalize activities usually carried out in the informal sector (small trade, some services, etc.). One would have expected that this system will result in an increased scope of selfemployment, which apparently is not the case (although one does not know the counterfactual).

The presented data show that there is still room in Lithuania to increase employment through a more widespread utilization of flexible employment contracts and self-employment options. In this context, the recent plans to restrict the use of fixed-term contracts by limiting the number of permissible renewals to one seem counterproductive.

56
children want to have at the age of 25 to the data on wages and other characteristics of these jobs in the LFS for the same year. Using a natural log of median wage for the occupation as a dependent variable, we estimate equations (8) – (10). As we highlight in the discussion of our empirical strategy, the idea behind this line of questioning is not to claim that the aspirations of boys and girls at age 12 are based on having perfect information on earnings and the non‐monetary characteristics of jobs. It is rather to ask a tangential question: _if_ boys and girls made education and career choices based on their aspirations at the age of 12, would we still observe a gender wage gap?

As the results in Table 1 show, there is a reverse gender gap in aspirations among the 12‐year‐olds in our study ‐ at age 12 girls aspire to jobs that have higher median wages than boys, even after controlling for levels of ability. These results suggest that if girls and boys aged 12 were to pursue and realize their career aspirations and the relative wages for different occupations remained the same, female earnings would on average exceed male earnings. Interestingly, the coefficient on the interaction term between the female dummy and the measure of cognitive ability is negative, although smaller in magnitude than the coefficient on ability. Although girls aspire to higher paying jobs than boys (and girls with higher levels of measured cognitive ability aspire to higher paying jobs), the difference in aspirations between the genders becomes smaller at higher levels of ability.

_Table 1: gender wage gap, based on aspirational occupations_

|||Log Med<br>|ian Wage<br>||
|---|---|---|---|---|
||(1)|(2)|(3)|(4)|
|Female|0.079***|0.080***|0.263***|0.256***|
||(0.012)|(0.012)|(0.091)|(0.091)|
|PPVT||0.002**|0.003***|0.003**|
|||(0.001)|(0.001)|(0.001)|
|Female*PPVT|||‐0.003**|‐0.003**|
||||(0.002)|(0.002)|
|Other controls||||_Yes_|
|R2|0.035|0.038|0.042|0.075|
|N|1,180|1,180|1,180|1,180|

The absence of a gender wage gap, extrapolated from the aspirational occupations of boys and girls at age 12, at first glance appears at odds with the abundance of informal evidence on the prevalence of norms and gender stereotyping in most societies. However, one mitigating factor here may be that the extent of stereotyping varies between societies and may change overtime. Further research is needed to explore this phenomenon in Vietnam.

How is a gender gap in aspirational earnings favoring girls at the age of 12 compatible with lower earnings for women as adults in Vietnam? A few explanations seem plausible and we test two in this paper. Girls may make human capital accumulation decisions similar to boys, so that streaming does not occur before the labor market. When women enter the labor market, however, they may face difficulties in finding jobs within their field of study. We explore this hypothesis in the subsequent section. On the other hand, 22
of the employees. Segmentation is most directly measured by the extent to which the gender of owners influences their decision to hire workers of the same gender. For female-owned establishments, for instance, this is measured as the share of female employees in total employment, while for male-led businesses segmentation is computed as the share of male employees in total employment. A shortcoming of this measure, however, is that we need information on the gender of the owner, which, unfortunately, is unavailable for the organized manufacturing surveys.

In an alternative setting, we view gender segmentation through the perspective of an average employee. For an average employee, we compute the share of people that this employee works with who are of his/her gender. For example, for an average female worker, we measure segmentation as the share of other workers at her establishment that are also female, while we compute a similar metric for an average male employee. In our work, we sometimes also consider the segmentation of the combined group, that is, for an average employee we compute the percent of co-workers in the establishment who are of the same gender.

Since trade and domestic industry reforms have been widely known to impact primarily the organized manufacturing sector (e.g., Topalova, 2007; Tewari and Wilde, 2015), we measure segmentation in our regressions using metrics that are possible to calculate with the ASI data. Nevertheless, it is useful to clarify here that our industry level regression work includes industry level information from both the formal and the informal manufacturing sectors, as trade reforms could have indirectly impacted the informal sector via reallocation effects.

∆�� in equation (1) is the related change in the industry level reforms, which could take the form of change in tariff protection or an index measuring the change in de-reservation of products exclusively for SSI. We follow Topalova and Khandelwal (2011) in using three alternative indices for measuring trade protection: (i) output tariffs, (ii) input tariffs, and (iii) effective rate of protection. Topalova and Khandelwal (2011) use the industry specific nominal levels of tariffs on output and intermediate inputs. Although using nominal tariffs is attractive since both tariffs are well-measured and comparable across time, nonetheless it is less apt for measuring the effective protection on an industry when both output and input tariffs change drastically and simultaneously. Topalova and Khandelwal (2011), therefore, construct an index on the effective rate of protection (ERP) to capture the net effect of lowering tariffs on output and intermediate inputs, defined as where ����,� is the effective rate of protection in industry _i_ at time _t_ and ��,� is the share of input _s_ in the value of output in industry _i_ . Input tariffs are constructed as: 18
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new market "niches" are being created everyday, that there are excellent business opportunities related to the transfer of both "hard" and "soft" technologies and to the marketing of ideas already proven in developed countries, and that the lack of more trained entrepreneurs provides good opportunities for those few who are willing to take tne risk and take advantage of their training and capabilities. Recent entrepreneurial surveys in some fast growing economies in the Far East as well as in Latin America, although restricted and incomplete, have identified dozens of cases of fast growing small enterprises which show thaat entrepreneurial talent is always latent and that it can be easily stimulated through appropriate macroeconomic policies and specific incentives.

Even in that case, what will be needed, as was the case in Europe in the late 1970s, is an active participation of governments in creating or/and in stimulating the appropriate environment, the road towards venture capital should not be expected to be either rapid or easy. As an example, a recent survey by IFC of its accumulated experience through participation in nine VCCs, from 1978 up to date, concludes, as it could be expected, that: "venture capital is not suited for all developing countries." In fact, IFC's results have been mixed. While at least four out of nine investments appear to be doing reasonably well, some others are yet too new to be assessed and at least three of them are considered failures. The cases of failure have been mainly attributed tr.: lack of commitment by local partners, lack of involvement in the monitoring of affiliates, poor macroeconomic performance of some countries, inefficiencies in the single-tiered structure of VCCs which was used in the early IFC investments, and worse-than-expected divestment results. But in spite of the failures IFC's experience has been positive in demonstrating the viability of venture capital in cultural and economic environments as varied as Korea, Kenya, Malaysia, and Argentina.

Other limited results available from LDCs, plus the recent results from Europe and the Far East and the long experience in the U.S., appear to indicate that, after overcoming the initial launching difficulties, venture capital can make a significant contribution to the economic development of those countries which are willing te provide an encouraging economic environment for entrepreneurial development. Moreover, recent privatization trends all over the world, have reached developing countries. In order to facilitate privatization and, at the same time, avoid excessive concentration of wealth in a few large investors, local entrepreneurship needs to be further stimulated. Venture capital could be one of the best sources of funds and assistance to help new entrepreneurs and to facilitate buy-outs of existing firms. Furthermore, in the absence of true risk capital, expanding businesses, as well as startups and buy-outs,
Vietnam and Cambodia."<sup>8</sup> 1 China was Southeast Asia's "major customer, some eight times more than Europe."<sup>82</sup> Southeast Asia's role was also vital in that a number of its ports served as important entrep6ts in trade among China, Japan, other parts of Eurasia, and the Americas. Major among these was Malacca, founded in 1403, which served as a turnaround point for Chinese shipping (halted temporarily in 1433) and used by Gujaratis, Turks, Armenians, Arabs, Persians, and Africans as a trading center with Southeast and East Asia.<sup>83</sup> In support of this trading system Southeast Asia's financial system included a "sophisticated and reliable money market" where money could be borrowed at an interest rate of about 2 percent a month, similar to that in Europe.<sup>84</sup> As is evident in the above descriptions of the trade patterns and products of these four economies, there was a robust intra-Asian trade at the core of a broader global trade. Furthermore, although one or another of these players pulled back at certain points from the global arena, the gap was soon filled by other Asian traders so that the flow of goods continued unabated. The regional/global nature of trade at that time is further demonstrated by the flow of precious metals and their role in trade promotion.

# **The Monetary Side of Trade: Precious Metals**

Precious metals (as well as copper, coins, and shells<sup>85</sup> ) were used as money to "'settle the accounts' of the trade deficit at each link of the chain by those who wanted to import from the next link but did not have enough to export in return."<sup>86</sup> Most notable among those needing "money" to pay for their imports were the Europeans who, it has been claimed by some, had nothing to sell that was of interest to Asians, who in their turn produced a considerable quantity of goods desired by the Europeans. Consequently, Europe imported more from Asia than Asia did from Europe. This resulted in a significant balance of payments problem for the Europeans. In order to finance their purchases of the large amounts of goods they wanted from Asia, Europeans used precious metals.<sup>87</sup> Attman (1991) found evidence of this in the actual export and import figures from port records of the 17th and 18th centuries. There were three markets that had high demand for bullion at that time: Asia, the Baltic, and the Levant (Eastern Mediterranean). Invoices from that period reflect the amounts various European countries owed to Asia and the Baltic for imports. He estimates payment in silver and gold from Europe was two-thirds the invoiced amount for Asia and between one-half and one-third for the Baltic. Table 1.8 shows Attman's estimates for the export of precious metals from Europe to Asia and the Baltic.<sup>88</sup> Estimates for the Levant, for which there are no precise invoice values, are included based on the actual amounts of precious metals transported from European ports to the Levant.

17