rafmacalaba/datause-encoder-data huggingface dataset:
# **Table 6. Mercosur's** Average **Decile Regional Orientation Index and** RCA Index<sup>**Values for 128 Processed Product Groups**</sup>

||Mercosur Int<br>($000|ra-Trade<br>)|Regional Or<br>Inde|ientation<br>x|Percent of Industries<br>in Decile Rage with<br>an RCA Over Unity|RCA I|ndex|Regional<br>Orientation<br>Index<br>Change|
|---|---|---|---|---|---|---|---|---|
|Decile Range|1988|1994|1988|1994||1988|1994||
|First Decile Products|127,939|810,619|3.84|13.47|7.6|0.43|0.24|9.63|
|Second Decile Products|325,573|3,033,899|1.63|4.26|7.6|0.64|0.48|2.64|
|Third Decile Products|212,759|1,027,964|1.39|1.86|15.4|0.88|0.54|0.47|
|Fourth Decile Products|302,175|1,303,419|1.50|1.67|46.1|0.96|0.99|0.17|
|Fifth Decile Products|108,996|597,859|1.11|1.16|38.5|2.15|2.14|0.04|
|Sixth Decile Products|167,733|840,060|1.33|1.12|38.5|2.65|3.68|-0.21|
|Seventh Decile Products|287,832|595,436|1.15|0.78|69.2|3.04|3.60|-0.37|
|Eighth Decile Products|222,842|469,499|1.73|0.96|46.1|2.05|2.60|-0.77|
|Ninth Decile Products|373,557|516,184|3.48|1.33|46.1|0.86|2.06|-2.14|
|Tenth Decile Products|226,930<br>2,356,437|514,461<br>9,709,400|31.82|10.17|23.1|0.24|1.99|-21.65|

Source: Computed from the data presented in Appendix Table 1.
- _Financial inclusion_ : Our findings highlight the need for accessible financial services for migrants from and within Lesotho. Formal sector employment seems to offer a route to financial inclusion, as textile workers are much more likely to have bank accounts (set up with help from employers) and use savings groups. Two policy recommendations emerge. First, efforts to promote financial inclusion should leverage the fact that migration is so common and use remittances as their entry‐point, and should include informal migrant workers as a key underserved population. Lower‐cost remittance services, particularly using mobile money technologies, would benefit migrants and their families, although our findings indicate that special efforts may be needed for women to try them out. Second, female migrants could be targeted for specialized financial products to help meet their financial goals, such as financing and saving for children’s education.

- _Access to secondary education_ : The challenges associated with accessing education underpin female migration in Lesotho in a number of ways. Respondents interviewed for this study repeatedly emphasized that the reason why Basotho women live apart from their families, and the primary use of their remittances, are children’s educational expenses. Schooling also drives where children live: they tend to remain with grandparents in rural areas during primary school, which is fully government‐ funded, but later join their mothers in urban areas where secondary school is more accessible. In light of this, any efforts to improve access to quality education in rural areas, particularly secondary education, would greatly benefit the welfare of migrants and their families and potentially reduce the need for female migration.

The study’s findings point to a number of priority areas to support female migrants and their families:

- First, the sheer prevalence of migration as a livelihood strategy emphasizes the need for better migration indicators in nationally‐representative data. For example, embedding questions on family members living elsewhere and respondents’ former residence would allow for tracking of internal and external migration. Annex 1 makes specific and actionable recommendations.

- Second, the study further justifies the need to lower barriers to secondary education particularly in rural areas. The cost of secondary education is both a driver of female migration and consumes a significant portion of the remittances that female migrants are able to send home. Lowering the cost or otherwise increasing access to secondary education would ease this

7
the micro data showing remittances increasing over this same period. Köskal (2006) notes that in 2003 Turkey changed its method of accounting for remittances, with spending by migrants during their visits as tourists to Turkey now entered under “tourism” in the balance of payments, whereas prior to this date they were counted as remittances. This sum was estimated to exceed US$2 billion in 2003. Figure 6B shows Jamaica, which designated Building Societies as financial institutions that the Bank of Jamaica could supervise and examine in 1994 (McLean 2008). Macro remittances grew 167 percent between 1993 and 1996, compared to 34 percent growth in the micro data.

Figure 7 shows micro and macro remittance growth for Ghana, the only African country for which we were able to find data. Macro remittances grow an astounding 5,138 percent in real terms over 1987 to 2005. Yet the household survey data measures of remittances fluctuate around a constant value in real terms over this period, with remittances per capita in 2005 actually 3 percent lower in real terms than those in 1987. Ghana is the only one of our nine countries for which macro remittances per capita are consistently lower than micro remittance data. The macro data for many African countries are widely believed to undercount remittances due to poorer statistical systems and a higher incidence of informal transfers. Mohapatra and Ratha (2011) report that there are even sizeable discrepancies in official data, with Ghana’s central bank reporting remittance inflows in 2009 that are more than 10 times the levels reported in its balance of payments statistics.

Remittance growth for Paraguay, the last of our nine countries, is shown in Figure 8. In contrast to the other cases, the macro and micro remittance data exhibit similar trends over most of the 2000s, only diverging somewhat in 2010. We were unable to find any discussion of major changes in regulations affecting remittance reporting to the central bank in Paraguay during this time, and the fact that Paraguayan migrants are more likely to go to Argentina than the United States may have meant that remittance transactions were less affected by changes in U.S. AMLs than Mexico or countries in Central America.

19
<!-- Start of picture text --> ly<br>D<br>II<br>x I<br>| Ill<br>1*<br>lnc Jee<br>| | Share of loan<br>B A C 100% applicants<br>ln<br>D<br>I I Il<br>|<br>OSi* |<br>~ | || Share of loan<br>A B C 100% applicants<br><!-- End of picture text -->
**Table** 4.3 **Ranking** of **Schools by** Actual **and Predicted ZJC Gradess anglish and Katheaatics (Rankings)**

||||_ EQL|ISH|||MATH|||
|---|---|---|---|---|---|---|---|---|---|
|School<br>In|School<br>zm29L_|Predi<br>_cr_|cted<br>_ror_|Actu<br>Scor|al<br>|Pred<br>Sc|icted<br>ore|Actu<br>EQQL|al<br>r_|
|1)||5.34|(8)|6.41|(3)|3.17|(10)|2.69|(9)|
|2)|CpA|4.51|(10)|5.60|(8)|2.59|(13)|3.68|(7)|
|3)||5.65|(6)|5.99|(6)|3.89|(8)|2.35|(11)|
|S)||3.09|(17)|2.96|(17)|2.17|(14)|1.79|(20)|
|6)|GpB(u)|2.62|j24)|3.30|(13)|1.86|(23)|1.75|(22)|
|7)||3.22|(14)|3.05|(16)|2.00|(16)|1.97|(15)|
|8)||4.0S|(12)|2.89|(19)|3.23|(9)|1.85|(18)|
|10)||2.93|(20)|3.16|_(15)_|1.51|(28)|1.90|(16?|
|13)|GpB(r)|3.97|(13)|3.76|(11)|2.89|(11)|2.51|(10)|
|14)||3.00|(18)|2.72|(22)|1.97|(17)|1.53|(29)|
|15)|HP|7.17|(1)|8.53|(1)|4.78|(1)|6.36|(2)|
|16)||6.17|(4)|5.20|(9)|4.08|(5)|2.92|(8)|
|19)||5.73|(5)|6.05|(5)|4.16|(4)|5.54|(3)|
|20)||5.16|(9)|4.67|;10)|4.06|(6)|4.03|(6)|
|21)|mission|6.23|(3)|6.65|(2)|4.45|(3)|6.75|(1)|
|22)||4.11|(11)|3.58|(12)|2.62|(12)|1.87|(17)|
|23)||6.65|(2)|5.95|(7)|4.48|(2)|4.24|(5)|
|24)||5.49|(7)|6.16|(4)|4.04|(7)|4.64|(4)|
|25)||2.08|(32)|2.39|(27)|1.49|(29)|2.25|(13)|
|27)||2.18|(31)|2.51|(24)|1.33|(32)|1.56|(28)|
|28)||2.97|(19)|2.79|(20)|1.94|(20)|2.29|(12)|
|30).||2.66|(23)|1.73|(32)|2.09|(15)|1.78|(21)|
|32)||2.56|(25)|2.05|(31)|1.92|(21)|1.36|(33)|
|33)||3.09|(16)|2.92|(18)|1.94|(19)|1.61|(26)|
|36)|D.C.|3.12|(15)|3.22|(14)|1.95|(18)|1.98|(14)|
|38)||1.75|(33)|1.36|(33)|0.73|(33)|1.45|(30)|
|39)||2.31|(29)|2.31|(28)|1.55|(27)|<br>1.73|<br>(23)|
|40)||<br>2.91|<br>(21)|<br>2.73|<br>(21)|<br>1.41|<br>(31)|<br>1.82|<br>(19)|
|41)||2.49|(27)|2.21|(30)|1.67|(26)|1.68|(25)|
|42)||2.52|(26)|2.23|(29)|<br>1.92|<br>(22)|<br>1.57|<br>(27)|
|45)||2.25|(30)|2.44|(26)|1.43|(30)|1.39|(31)|
|46)||2.44|(28)|2.45|(25)|1.84|(24)|1.37|(32)|
|48)||2.68|(22)|2.57|(23)|1.75|(25)|1.69|(24)|

49
that incorporate uncertainty about the errors in our income model. The bounds are highly likely to contain the true value of the probability estimates, as was confirmed in other settings by Dang et al. (2014) and Hérault and Jenkins (2019). In addition, sample sizes for each round are large, so that the standard errors of our estimators are generally small.

# 4. Data

Our study analyzes six rounds of cross-sectional data from the Household Income and Basic Amenities Survey (HIS) collected by the Department of Statistics Malaysia. The data are for the years 2004, 2007, 2009, 2012, 2014 and 2016; we consider the five pairs of adjacent survey rounds.<sup>16</sup> One requirement for analyzing welfare changes over time is that the measure of welfare, income in our case, is measured in a consistent and comparable manner. The Malaysian data are of high quality and satisfy this requirement. In addition, the sample sizes of the surveys are large, ranging from 36,000 to over 80,000 household-level observations per survey year (see Table 1).

At the start of our analysis, the official Malaysian poverty line was very low; poverty was virtually non-existent by those standards.<sup>17</sup> Given that this line had not been updated in real terms since 1977, it was not an appealing yardstick for the purpose of our analysis. Present-day discussions about poverty and mobility in Malaysia often refer to the living standards of the bottom 40 percent of the income distribution. Accordingly, we have chosen to employ a poverty line corresponding to the income level of the 40th percentile in the first year of our analysis, 2004. This line is then kept constant in real terms for the subsequent years. Hence, it is initially set as a relative line, but is treated as absolute poverty line thereafter. In 2016 prices, the line stands at MYR 527 per capita per month. This is roughly equivalent to MYR 17 per day, or USD 10.5 when converted at 2016 PPP exchange rates. Table 1 gives an overview of the resulting poverty headcount rate for each of the six survey years, both for the whole country and for subgroups. These aggregate numbers are estimated by applying the household sampling and population weights contained in the dataset. We use the same weights to estimate aggregate transition probabilities.

The dependent variable in our analysis is the natural log of monthly household pre-tax income per capita, which is evaluated against our poverty line to determine the poverty status of a household.

> 16 Surveys may extend into the subsequent year. When we refer to ‘round 1’, this indicates the first round of any pair, not necessarily the 2004 survey (and similarly for ‘round 2’).

> 17 As noted earlier, a new official poverty line was adopted in 2020, which is roughly USD 10 per person per day at 2011 PPPs and close in value to ours.

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Learning from Developing Country Power Market Experiences: The Case of Colombia

|**Power Market**<br>**Implementation**<br>**Element**|**Colombia**|
|---|---|
||System and short-term market operation by XM, a subsidiary of major<br>government-owned Transco ISA.|
|**Investment**<br>**responsibility and risk**<br>**allocation**|Gencos borne risks and responsibility of investment, incentivized by short-<br>term power market and capacity auctions.<br>However, fuel price risk in the reliability options was exceptionally passed-<br>through directly to final customers in 2015 due to falling oil prices and<br>increasingstress of system reliability.|
|**Barriers to investment**<br>**and entry**|•<br>Regulatory uncertainty (lack of confidence on political commitment to<br>reforms)<br>•<br>Lack of upstream infrastructure<br>•<br>Complicated and lengthy processes for permits and licenses<br>•<br>Public opposition to new generation projects|
||•<br>Limits have been imposed to vertical and horizontal integration|
|**Open access inpractice**|Regulated open access to the transmissiongrid. Access tariffs set byCREG.|
|**Market transparency**|Market and system operation data and procedures are publicly disclosed.<br>Bilateral contract details are confidential.|
|**Approach to market**<br>**monitoring and**<br>**oversight**|The Superintendence of Domestic Public Services (SSPD) oversees and<br>monitors the Colombian power market.|
|**Provisions for market**<br>**intervention and related**<br>**events**|•<br>2009-10: threat of rationing led the CREG to intervene in the market by<br>disallowing the reliability mechanism specifically designed as part of<br>solvency in periods of critical hydrology to operate.<br>•<br>2015, October: Government enables CREG to intervene the Reliability<br>Charge by placing a temporary lower bound on the Scarcity Price, and a<br>new (higher) temporary Scarcity Price for Thermal Generators<br>operating with Liquid Fuels. The costs of this intervention were passed-<br>through to final customers.<br>•<br>2015, November: Government intervenes through SSPD by taking<br>control of thermal power plant Termocandelaria to ensure supply<br>reliability, after the said plant was declared unavailable by the Genco<br>(for financial reasons) during El Niño event, despite having collected<br>reliability payments.<sup>13</sup>In this case, intervention is allowed explicitly by<br>Law 142, 1994.<sup>14</sup><br>•<br>2016: to ensure supply reliability, the Ministry sets forth a two-month<br>demand program which penalizes electricity consumption above<br>historical means, and rewards customers in the opposite case; with the<br>target of reducing 400 GWh of electricity consumption.<br>•<br>2016: Government intervenes Distco Electricaribe due to its<br>deteriorated financialposition.<sup>15</sup>|

> 13 <u>http://www.eltiempo.com/archivo/documento/CMS-16436994</u>

14 <u>http://www.contraloria.gov.co/documents/20181/467249/INFORME+ACTUACION+ESPECIAL+DE+FISCALIZA CION+DEL+CARGO+POR+CONFIABILIDAD.PDF.pdf/8fd5cc08-809f-4351-9602-9d898eb6e38f?version=1.0</u> 15 <u>http://www.eltiempo.com/economia/empresas/debate-a-electricaribe-41967</u> 32
- Oresi, Samuel (2007), “Railway Services in Kenya,” paper presented at the Trade in Services Workshop in Nairobi, Kenya, sponsored by the Ministry of Industry and Trade of Kenya and International Lawyers and Economists against Poverty, Nairobi, March 26, 27.

- Panagariya, A  and D. Rodrik (1993), “Political-Economy Arguments for a Uniform Tariff,” _International Economic Review_ .

- Romer, Paul. (1994),  “New Goods, Old Theory and the Welfare Costs of Trade Restrictions,” _Journal of Development Economics_ ,” 43(1), February, 5-38.

- Rutherford, Thomas F. and David G. Tarr (forthcoming), "Poverty Effects of Russian WTO accession: modeling “real” households with endogenous productivity effects,” _Journal of International Economics_ .

- Rutherford, Thomas F. and David G. Tarr (2003), "Regional Trading Arrangements for Chile: Do the Results Differ with a Dynamic Model?" _Integration and Trade,_ Vol 7, Number 18, 117-139.

- Rutherford, Thomas F. and David Tarr (2002), "Trade Liberalization and Endogenous Growth in a Small Open Economy," _Journal of International Economics_ , 56 (2), March, 247-272

- Rutherford, Thomas F. (1999), "Applied General Equilibrium Modeling with MPSGE as a GAMS Subsystem:  An Overview of the Modeling Framework and Syntax", _Computational Economics_ .

- Tarr, David (2007a), “Policy Note on the Kenyan Telecommunications Sector,” Washington D. C.: World Bank Country Economic Memorandum for Kenya, forthcoming.

- Tarr, David (2007b), “Policy Note on the Kenyan Transportation Sector,” Washington D. C.: World Bank Country Economic Memorandum for Kenya, forthcoming.

- Tarr, David (2002), "On the Design of Tariff Policy: Arguments for and Against Uniform Tariffs,”  in B. Hoekman, A. Mattoo  and P. English (eds.), Development, Trade and the WTO: A Handbook, Washington: World Bank.

- Telecommunications Management Group, Inc.(2007), “Trade in Information and Communication Services: Opportunities for East and Southern Africa,” Chapter on Kenya, Draft report to the World Bank, January 31, pp.15-39.

- United Nations Conference on Trade and Development and World Bank (1994), _Liberalizing Trade in Services: A Handbook_ , New York and Geneva: United Nations.

- United Nations Conference on Trade and Development, Division on Transnational Corporations and Investment (1995 and 1996), World Investment Report 1995 and 1996, New York and Geneva: United Nations.

Vernon, R. (1960), _Metropolis 1985_ , Cambridge: Harvard University Press.

- Warren, Tony (2000), “The Impact on Output of Impediments  to Trade and Investment in Telecommunications Services,” in Findlay, Christopher and Tony Warren (eds), _Impediments to Trade in Services: Measurement and Policy Implications_ , (London: Routledge).

27
countries in global output will increase steadily and China’s output will exceed that of the European Union and that of the United States sometime around 2015 (in purchasing power parity terms). Global integration is likely to enter a new phase. In virtually every growing economy the importance of trade—captured by the ratio of trade to GDP—will rise, continuing the trend of the past two decades.

Global trade in goods and services, growing faster than output, is likely to rise more than threefold to $27 trillion in 2030. Roughly half that increase will come through developing countries, with the share of developing countries in global exports rising from 32 percent now to 45 percent in 2030 (Figure 4). This means that a growing share of global production of goods and services will be performed in those developing countries able to take advantage of new opportunities and respond to the emerging challenges. Whether countries exceed projections—or fall short—depends heavily on the policies they adopt over this long period.

**Figure 4: Developing countries share of world trade will rise as global integration intensifies**

<!-- Start of picture text --> Exports from developing and developed countries, 2005-2030<br>US$2001 trln.<br>30<br>$27 trln<br>25<br>High-income<br>countries<br>20<br>15<br>10 Developing<br>countries<br>45%<br>5<br>32%<br>0 22%<br>1980 2005 2030<br>Source: World Bank Global Economic Prospects 2007<br><!-- End of picture text --> The new wave of globalization brings important challenges for developing countries. Developing countries with wages higher than those in China and India risk losing ground following the entry of these countries into the global marketplace. The sheer size of China and India may also preclude the diversification of the poorest countries into manufactures and so close of a route to growth and development (Cline (2006)). However, what matters is productivity. In middle income countries is the wage gap with China greater than the difference in productivity and can productivity differentials be maintained? Similarly, least developed countries in Africa that have lower wages than China and India, will be able to compete in the global market if levels of productivity are close to those in India and China.

9
can significantly increase the signal-to-noise ratio. However, going beyond equal-weights can also serve another goal, namely improving the perceived credibility and legitimacy of multidimensional poverty indicators. Yet, these methods come with their own issues, which limit the impact they may yield on the indicators’ perceived credibility. There will always be doubts about the relationship between the preference data and “true” wellbeing (see footnote 64). Furthermore, applying preference information in another context than the one in which it is obtained is bound to raise questions on its external validity.

Finally, although the dimension-by-dimension approach to policy making is unlikely to change overnight, it might still be worth conducting policy analysis in a multidimensional way. Indeed, some of its insights may be productively used. And even if it is not immediately the case, these insights could raise awareness of the potential gains of an integrated approach to policy making.

# **5 Research papers**

In this section, we outline a list of seven research papers based on the opportunities

1. Empirical implications of going beyond the dichotomous counting methodology Dichotomizing non-binary variables “wastes” well-being relevant information. The solutions listed in section 3.2 provide ready-to-use conceptual improvements on the dichotomous counting methodology underlying mainstream multidimensional poverty measures. They will thus help improve the targeting of policies across households. One open question is the empirical significance of these solutions. By how much do they affect inter-household and cross-region well-being comparisons? How different are the households they identify as poor when compared to those identified under the counting methodology? This could be investigated both for the World Bank’s MPM as well as for national multidimensional poverty measures.

2. Harnessing separate surveys through hybrid well-being indices Hybrid well-being indices, which are part-synthetic and part-objective, are one way of avoiding “wasting” part of the data available in separate surveys, like LSMS and DHS. Sections 3.3 and 3.4.1 list solutions for the construction of hybrid multidimensional indices. They may thus help improve cross-regions well-being comparisons as well as a region’s well-being trend. The paper should study how to apply this kind of solutions in practice and quantify their impact on well-being comparisons.

39
practices. Durnev and Kim (2005) find that firm-level governance and disclosure is positively related to a firm‟s growth opportunities, need for external financing, and concentration of cash flow rights. The market seems to recognize and reward better disclosure practices since in their sample, firms with higher governance and transparency rankings are valued higher in stock markets.

A second group of studies have proxies for the quality of disclosure practices. In his study on the East Asian financial crisis, Mitton (2002) uses two measures of disclosure quality. The first is that a firm has a listed American Depositary Receipt (ADR). Listing as an ADR can improve disclosure quality as a result of having to meet disclosure requirements mandated by the SEC and the listing exchange.<sup>16</sup> Moreover, the larger pool of potentially more sophisticated investors also increases disclosure quality. The second measure of disclosure quality is that the firm‟s auditor is one of Big Six international accounting firms. Prior research has associated the Big Six Auditors with higher audit quality and greater transparency (e.g. Reed et al. 2000; Titman and Trueman, 1986). Mitton also shows that higher disclosure quality is associated with a better stock price performance during the crisis period.

Finally, in the third group of studies largely focused on US data, a large literature has used the number of analysts following the firm and the accuracy of analyst forecasts as measure of the information environment of the firm (see Lang and Lundholm, 1996; Healy, Hutton, and Palepu, 1999; Gebhardt, Lee, and Swaminathan, 2001, Lang, Lins, and Miller, 2003). International finance scholars have in turn used analyst coverage in the US as a measure of the quality of information available on foreign firms listing in the US as ADRs (Baker, Nosfinger, and Weaver, 2002; Lang , Lins, and Miller, 2003; Bailey, Karolyi, and Salva, 2006).

Overall, the literature on disclosure practices has suggested that higher accounting standards in a country and more extensive disclosure practices of individual firms, as measured in the studies cited above are associated with better governance. Furthermore, there is strong evidence to suggest that firm valuation is also closely linked to the quality of disclosures.

Understanding specific disclosure practices is typically only useful in the study of corporate governance in large public firms. For small firms in developing countries, a second

> 16 We elaborate more on the benefits associated with an ADR listing in Section 8 of the paper.

32