rafmacalaba/datause-encoder-data huggingface dataset:
-87-

nutritionally adequac. foods that are also familiar to the extremely-poor? atAearch is also needed to determine location of PASSPA. The possibility of using an algor! hm to minimize P(a,y) like the one developed by Ravallion and Chao (1989) deserves attention. Given shortcomings in the coverage of the income-expenditure survey we need to ask whether data from the latest population census can be used for this purpose.

Five, rural labor markets. Since arable land is almost exhausted population growth implies that the marginal rural poor is landless. Returns to unskilled ruwral labor will become even more important determinants of the earnings of the rural poor. Yet, as remarked in section V, most household studies in Mexico have concentrated on land owning peasants. Relatively less is known about landless laborers. What is their behavior with regards to migration? How can they benefit the most from rural reform? Does more irrigation reduce the seasonality of labor iemand by allowing for double cropping and similar practices? A related issue concerns aba-specific participation rates. I remarked in section VI.1 that studies for other countries have found these rates to be higher for the extremely-poor, with effocts on their demand for educationi (Lipton (1983b)). Is this finding confirmed for Mexico? Are differences in age-specific participation rates importunt, and are they explained by differences in income levels, regions or asset ownership (land/no land)?

Six, the land tenure str-ucture. I have made a plausible but not rigorous case that currert institutional arrangements restriet the demand for unskilled rural labor and the returns to land. Clearly, it would be much better to have a formal model of the private/ejido land dichotomy to determine if there are equity/efficiency trade-offs associated with these forms of land tenure. Equally important, assuming it is desirable to develop a fuller market for land, how should this be done? Current market valuations for land may not reflect its scarcity value given existing distortions in prices, entry, land use, etc.. More work is needed on the appropriate sequence for reform. Should input and output prices be aligned first? Assuming ejidatarios are given marketable titles to their land, sbould there be an initial period where land sales are banned until information about the proper value of land is generally accessible?
- [10] ashraf.n, n.bau, c.low and k.mcginn (2017) Negotiating a Better Future: How Interpersonal Skills Facilitate Inter-Generational Investment, mimeo LSE.

- [11] atlani.l, m.carael, j.brunet, t.frasca, and n.chaika (2000) “Social Change and HIV in the Former USSR: The Making of a New Epidemic,” _Social Science & Medicine_ 50: 1547-56.

- [12] backer.j.a and j.wallinga (2016) “Spatiotemporal Analysis of the 2014 Ebola Epidemic in West Africa,” _PLOS Computational Biology_ .

- [13] baird.s.j, c.t.mcintosh and b.ozler (2011) “Cash or Condition: Evidence from a Cash Transfer Experiment,” _Quarterly Journal of Economics_ 126: 1709-53.

- [14] baird.s, e.chirwa, j.de hoop and b.ozler (2014) Girl Power: Cash Transfers and Adolescent Welfare, Evidence from a Cluster-Randomized Experiment in Malawi, NBER Chapters, in _African Successes_ : Human Capital, NBER.

- [15] bandiera.o, n.buehren, r.burgess, m.goldstein, s.gulesci and m.sulaiman (2018) “Women’s Empowerment in Action: Evidence from a Randomized Control Trial in Africa,” _American Economic Journal: Applied Economics_ , forthcoming.

- [16] banerjee.a.v, a.chandrasekhar, e.duflo and m.o.jackson (2018) Changes in Social Network Structure in Response to Exposure to Formal Credit Markets, mimeo, Stanford University.

- [17] bazzi.s and c.blattman (2014) “Economic Shocks and Conflict: Evidence from Commodity Prices,” _American Economic Journal: Macroeconomics_ 6: 1-38.

- [18] bledsoe.c (1990) “School Fees and Marriage Process for Mende Girls in Sierra Leone,” in _Beyond the Second Sex_ , Sanday.P and R.Goodenough (eds.), University Pennsylvania Press.

- [19] bowles.j, j.hjort, t.melvin and e.werker (2016) “Ebola, Jobs and Economic Activity in Liberia,” _Journal of Epidemiology and Community Health_ 70: 271-7.

- [20] brodeur.a, w.n.lekfuangfu and y.zylberberg (2018) “War, Migration and the Origins of the Thai Sex Industry,” _Journal of the European Economic Association_ , forthcoming.

- [21] buchmann.n, e.field, r.glennerster, s.nazneen, s.pimkina and i.sen (2017) Power vs Money: Alternative Approaches to Reducing Child Marriage in Bangladesh, a Randomized Control Trial, mimeo, Duke University.

41
# Table 10: BILATERAL COMPARISONS FOR CONSTRUCTION

|Types of Construction|China Price<br>(Yuanlsq.m)<br>_______|US Price<br>(S/sq.m)|Parity<br>_____~|China<br>Weight<br>~~~ ~~<br>(%/)|US<br>Weight<br> <br>(00|
|---|---|---|---|---|---|
|Residntial Houses|773.27|621.35|1.244|4.29|22.04|
|IndustnalBuidcg|442.03|493.90|0.895|||
|Conumn-ial Building|452.76|354.65|1.277|||
|OfficeBuilding|639.19|1,153.29|0.554|||
|EducationalBuilding|784.89|1,150.59|0.682|||
|Hospial andInsiutional Buldi|743.56|1,094.09|0.680|||
|Odtr Buildin|760.69|881.34|<br>0.862|||
|Total Nonresidential||||68.22|12.18|

- Note: 1. The selling pnce of resikential buildings in China is the gcometri mean of the selling prices ranging from 426 to 1,800 yuantsqm. in eight districts in China.

2. The sellig pnce of re-ndntial building in th U.S. was calcultd based on the data in Section 26: Constraction and Housing of the **_Satistical_** _Abstract of the United States, 1988._ 3. The price of non-resikdetial buidgs in Chna is the cos of buidig accrding to dt construction sumdard of China.

4. The prices of non-rsidntial buldig m the Uited States was computed based on the data on the value of construction and floor space of builings in Section 26: of _Statistical Abstract of the United States._

# **V. RESULTS** OF **THE BILATERAL COMPARLSON**

57. The purasing power parity for GNP and its components, as the resuk of the bfaitra comparisons, are presnated in Table 4 in Aimex. The per capita GDP of China is 909 yuan in 1986 (World Tables 1993). The estimated dollar per capita GDP of China in 1986 is 1$1,044, by using the converter of 0.8709.

_58._ If the estimate (IS 1,044) developed in this stdy is taken to be compared with other esimates cited in Table 2, one can see that oiher estimates differ substaialy fiom this estimate except Ahmad's estimate ($999). It is worthwhie to diss the reasons for the discpancies.

25
Aside from information on antidumping revocations (if any exist), there is nothing systematically missing from the Indian data for all investigations. Nevertheless, for any given investigation there may some missing elements such as dates, decisions or even product codes.

# **3.8 South Korea (KOR)**

In South Korea, the Korean Trade Commission is wholly responsible for anti-dumping investigations. This quasi-judicial agency determines if dumping and/or injury has occurred for each case. The initiation and outcomes of each investigation are published in the Korean Official Gazette (Gwanbo). The Korean Trade Commission also publishes information about ongoing antidumping cases online at its website. The source of the data was hard-copies of antidumping documents in Korean provided by the Korean Trade Commission. Summary information about Korea’s antidumping process is available on the Korean Trade Commission’s website.

In addition to the standard data described in section 2, the Korean file contains additional data described in the table below.

**<u>Table 3.8.1 : Additional Korean Data Included in AD-KOR-v1.0.xls</u>**

|**Column**|**Variable Name**|**Description**|
|---|---|---|
|**In AD-K**|**OR-Master :**||
|**U.**|**P_AD_DUTY**|The maximum (or range) of preliminary anti-dumping duty (duties)<br>imposed|
|**V.**<br>**W.**|**F_AD_DUTY**<br>**REVIEW_DUTY**|The maximum (or range) of final anti-dumping duty (duties) imposed<br>The range and schedule of anti-dumping duties maintained after a sunset<br>review|
|**X.**|**REVIEW_F_DATE**|The date when a sunset review final decision was taken|
|**Y.**<br>**Z.**|**REVIEW_DUTY_DATE**<br>**TYPE**|The date when reviewed antidumping duties became effective<br>A variable indicating if a sunset review was performed on the case<br>(Review=Sunset Review was carried out)|
|**In AD-K**|**OR-Foreign-Firms:**||
|**D.**|**F_AD_MARGIN**|The maximum (or range) of firm-specific dumping margin(s) found at the<br>final stage|
|**E.**|**F_AD_DUTY**|Details on the firm-specific antidumping duty (measures) imposed at the<br>final stage.|
|**F.**|**COUNTRY**|The country in which the foreign exporting firm is located|

26
Table 1 Socio-Economic and Development Indicators by country <u>(2005 year).</u>

|**Country/**<br>**industry**|**Total**<br>**population**<sup>**1**</sup>|**GDP per**<br>**capita,**<br>**PPP**<sup>**2**</sup>|**Industry,**<br>**value added**<sup>**3**</sup>|**Merchandis**<br>**e exports**<sup>**4**</sup>|**Merchandise**<br>**imports**<sup>**4**</sup>|**School**<br>**enrollment,**<br>**primary**<sup>**5**</sup>|**Road**<br>**density**<sup>**6**</sup>|**Domestic**<br>**credit private**<br>**sector**<sup>**7**</sup>|**Inflation,**<br>**consumer**<br>**prices**<sup>**8**</sup>|**Procedures**<br>**to enforce a**<br>**contract**<sup>**1**</sup>|
|---|---|---|---|---|---|---|---|---|---|---|
|Bulgaria|7781000|8737.161|4022807808|9932382032|14453494993|94.98052791|40.48639206|36.31128868|6.346133143|34|
|Czech Republic|10206923|19094.62|22018136064|68986459239|69967456060|..|165.3908879|32.61472877|2.833643175|22|
|Estonia|1348999|15107.31|1911966336|5932476581|8335935795|93.90955231|134.0858693|40.01893348|3.048071707|25|
|Hungary|10107095|16306.48|15011529728|55566718661|60538321226|89.09593776|..|45.82225836|6.780023712|21|
|Latvia|2312791|11885.7|2287386624|4009170454|7095505106|..|111.6262642|50.77709798|6.191878487|24|
|Lithuania|3435585|12967.48|4650113536|9301566446|12386991757|88.62493488|126.5650925|28.80164646|1.195219124|24|
|Moldova|3925170|2012.422|290329920|986255000|1773742000|92.37393608|38.73745056|21.23095682|12.5283047|37|
|Poland|38182200|13091.86|53077282816|75046614430|89696102001|97.51612288|..|28.14845|3.576547231|41|
|Romania|21684884|8977.659|15057262592|23553215092|32690617860|90.9535242|86.44217391|15.6740974|11.87686787|43|
|Slovak<br>Republic|5382449|14989.53|8776060928|27744734233|29861579419|..|89.3970894|30.54339454|7.548500882|27|
|Slovenia|1997000|22132.83|7092050944|16361365166|17758527740|95.54712377|190.9126156|48.77266733|3.589026796|25|
|1Number.<br>2Constant 2005 in<br>3Constant 2000 U<br>4Current US$.<br>5% net.<br>6Km of road per 1<br>7% of GDP.<br>8Annual %.|ternational $.<br>S$.<br>00 sq. km of land ar|ea.|||||||||

Source: DDP Quick Query database of WDI & GDF, World Bank.

6
# **Social Tariffs**

4.9 A number of Argentina provinces, and most recently the Metropolitan Area, have experimented with the introduction of various forms of social tariffs. These amount to some 10 cases in all. A brief description of the mechanics of each of these schemes is provided in Table A3 of the Appendix but most of them identify beneficiaries based on a range of characteristics such as income, housing, location, and assets.

4.10 The OPSM survey included a special question designed to identify the beneficiaries of these schemes, and found that barely 2% of households surveyed claimed to be beneficiaries. This result is consistent with what is known about the relatively small scope of these schemes, which are estimated to reach no more than 100,000 households nationwide. The small number of observations that appear in the survey do not make it possible to evaluate the incidence of these schemes directly. However, what can be done is to simulate the application of the eligibility criteria for each scheme to the sample of the population from the corresponding jurisdiction, in order to assess the extent to which these are successful in targeting resources towards the poor. This simulation proves to be rather artificial, given that most of these programs use household income as an eligibility criteria, and that this is accurately observed in the survey, but may not be so accurately measured by these schemes in practice. Consequently, the results obtained should be regarded as an optimistic upper bound on the targeting performance of these social tariff programs.

4.11 The results indicate that the eligibility criteria used in the social tariff schemes appear to be quite effective at targeting resources towards the poor. In particular, the criteria used in the northeastern and northwestern provinces of Argentina (namely, Chaco, Formosa, Salta y Tucumán) perform particularly well. Assuming that they are able to measure household income as precisely as is done in the survey, the simulation suggests that 70% to 90% of the beneficiaries belong to the bottom income quintile (Figure 7).

21
## I. COUNTRY CONTEXT

### Economic Growth

Rapid economic growth and poverty reduction over the 1990s has meant that Vietnam has met — or nearly met — some of the MDGs within a decade of the internationally-chosen starting point of 1990. The real economy doubled in size during the decade, savings rates rose six-fold to around 25 percent of GDP, exports rose by an average of 25 percent per year, and Vietnam moved from a food deficit nation to become the second largest exporter of rice. Vietnam was highly vulnerable to the crisis in East Asia, since more than two-thirds of foreign investment inflows and two-thirds of export earnings come from the region. Government reacted to this challenge by adopting a highly cautious macroeconomic policy to avoid the possibility of a crisis. Figure 1 shows the evolution of GDP growth rate and inflation during this period.

Figure 1. GDP Growth Rate (percent) and Inflation (annual average percent) <!-- Start of picture text --> 10.02<br>82<br>8.0 8 :<br>60+ 4s —_ 48<br>4.0 5 .<br>0.0 ——<br>-4.0<br>1997 1998 1999 2000/r 2001/e<br><!-- End of picture text --> Source: World Bank (2002)

# Trends in poverty reduction and social indicators

Economic growth over the 1990s generated significant improvements in living standards. The incidence of poverty was halved from 70 percent to around 35 percent and the proportion of the population living in severe poverty fell to 15 percent. Across a broad front there were widespread and visible improvements in the lives of Vietnamese citizens (World Bank 1999). Preliminary evidence emerging from qualitative research suggests a continuation of improvements in living standards since the last household survey in 1998 (Shanks and Turk 2002).

A number of factors underlie these impressive gains in living standards. First, growth in the agriculture sector was an important driver of economic growth over this period. Higher incomes from agriculture brought benefits to the rural poor, nearly all of whom had access to agricultural land following the decollectivisation of agricultural production in the late 1980’s. Secondly, many of the poor were concentrated just below the poverty line in the early 1990s. A relatively small improvement in per capita expenditures was sufficient to push a large number of households into non-poor categories. Their proximity to the poverty line means, however, that these households remain highly vulnerable to the shocks and crises that impose heavy costs or undermine the livelihoods of rural households. Thirdly, though the gains were not evenly spread across regions, all groups and all parts of the country experienced improvements in living standards. The rate of decline in poverty was faster in urban areas, but rural populations also saw dramatic improvements in material well-being (Figure 2).

1
# <u>Notes:</u>

> **a** The World Health Report 2005, World Health Organization, 2005. (http://www.who.int/whr/2005/en/index.html) b World Development Indicators, The World Bank.

As expected, Malaysia, Singapore and Thailand have the highest per capita expenditure on healthcare. However, Cambodia spends as much as 12 percent of GDP on healthcare, far more than other countries in the group. The Thai and Cambodian governments devote over 17 percent of public spending to healthcare—again, far more than other governments in the region.

In Singapore, Laos, Cambodia, Philippines and Indonesia, most of the healthcare expenditure comes from private sources, the majority of which is out-of-pocket (Table 6). In Cambodia and Laos, a substantial share of healthcare funding also comes from foreign donors and NGOs. Only in Malaysia and Thailand is the public sector the most important source of healthcare financing.

**Table 6: Sources of healthcare financing (in percent)**

||**Singapore**<br>|<br>**Thailand**<br>|**Malaysia**<br>|**Vietnam**<br>|**Cambodia**<br>|**Indonesia**|**Laos**<br>|<br>**Philippines**<br>|
|---|---|---|---|---|---|---|---|---|
||(2001)|(2002)|(2001)|(1998)|(2002)||(1999)|<br>(2003)|
|Government (including<br>subsidized public<br>insurance where<br>applicable)|33.5|67.5|53.7|19.5|8.8||9.0|37.5|
|Social Insurance||||||||7.8|
|Private Sources|66.5|32.5|46.3|80.5|72.9||55.7|54.8|
|_of which are:_|||||||||
|_Out-of-Pocket_|_97.0_|_84.6_|_92.8_|||_70.0_|_60.0_|_78.1_|
|_Private Insurance_||_10.0_|_7.2_|||_<2.0_||_2.4_|
|_Health Maintenance_||||||||_7.3_|
|_Organization_|||||||||
|NGOs|||||18.2||35.2||

<u>Sources:</u> Philippines’ National Statistical Coordination Board (PSY 2003); WHO World Health Report.

Notwithstanding the overall strong reliance on out-of-pocket financing, public health insurance is playing an increasing role in a number of ASEAN countries. In Thailand, 80.4 percent of the population is covered by the ‘Universal Care’ scheme, which was introduced in 2001. By 2002, this mechanism reduced private out-of-pocket spending of the uninsured households by 14.2 percent, while increasing government spending on health by 24.4 percent. In Indonesia, 27.6 percent of the population is covered by various public health insurance schemes. Vietnam has compulsory public health insurance for civil servants, state-owned enterprises and large private companies, covering around 12 percent of the population. In Cambodia, health insurance was introduced in 1991 but the system has not taken off due to its high cost and the lack of trust in public health facilities (Chea, 2005). The Philippine Government has initiated a compulsory National Health Insurance Program (NHIP) in 1995, targeting those in the lower income brackets. By 2002, 54 percent of the population was enrolled.

9
- Baier, Scott L., Yoto V. Yotov, and Thomas Zylkin (2019), “On the Widely Differing Effects of Free Trade Agreements: Lessons From Twenty Years of Trade Integration.” _Journal of International Economics_ 116, 206–226. url: https://doi.org/10.1016/j.jinteco.2018.11.002.

- Baldwin, Richard E., Simon Evenett, and Patrick Low (2009), “Beyond Tariffs: Multilateralizing Non-Tariff RTA Commitments.” _Multilateralizing Regionalism: Challenges for the Global Trading System_ . Ed. by Richard E. Baldwin and Patrick Low. Cambridge University Press.

- Bergstrand, Jeffrey H., Mario Larch, and Yoto V. Yotov (2015), “Economic Integration Agreements, Border Effects, and Distance Elasticities in the Gravity Equation.” _European Economic Review_ 78, 307–327. url: https://www.sciencedirect.com/science/article/pii/ S0014292115000847.

- Borchert, Ingo, Mario Larch, Serge Shikher, and Yoto V. Yotov (2020), “The International Trade and Production Database for Estimation (ITPD-E).” _International Economics_ .

- Breinlich, Holger, Valentina Corradi, Nadia Rocha, Michele Ruta, J.M.C. Santos Silva, and Tom Zylkin (2021), “Machine Learning in International Trade Research.” _World Bank Policy Research Working Paper 9629_ April. url: https://openknowledge.worldbank.org/handle/ 10986/35451.

- De Melo, Jaime and Alessandro Nicita (2018), “Non-Tariff Measures: Data and Quantitative Tools of Analysis.” _F.R.E.I.T. Working Paper_ . url: UNCTAD/DITC/TAB/2017/2.

- Dhingra, Swati, Rebecca Freeman, and Hanwei Huang (2021), “The impact of non-tariff barriers on trade and welfare.” 17.

- Dür, Andreas, Leonardo Baccini, and Manfred Elsig (2014), “The Design of International Trade Agreements: Introducing a New Dataset.” _Review of International Organizations_ 93, 353– 375.

- Ederington, Josh and Michele Ruta (2016), “Nontariff Measures and the World Trading System.” _Handbook of Commercial Policy 1b_ . Ed. by Kyle Bagwell and Robert W. Staiger. 1st ed. Vol. 1A. Elsevier B.V., 211–277. url: http://dx.doi.org/10.1016/bs.hescop.2016.04. 010.

- Egger, Peter H. and Mario Larch (2008), “Interdependent Preferential Trade Agreement Memberships: An Empirical Analysis.” _Journal of International Economics_ 762, 384–399. url: http://dx.doi.org/10.1016/j.jinteco.2008.08.003.

- Egger, Peter H., Mario Larch, and Yoto V. Yotov (2022), “Gravity Estimations with Interval Data: Revisiting the Impact of Free Trade Agreements.” _Economica_ 89353, 44–61.

27
Although the representation of up to 60% of total stock value in the economy would theoretically allow for the possibility that banks represent a majority in just about every company's share-holder meetings, this is not true in reality, as most of the value of stock is accounted for by the 10 largest firms, 8 of which are majority owned by the general public. Table 2 was compiled by Immenga [25,n. 1041 for the data of 1975, and replicated from Appendix II for the data of 1988, and shows those firms, in which banks could conceivably wield influence either through direct ownership, or by proxy vote.

Table 2: Possibilities of banks influencing the top **100 rwms** via ownership or proxy votes Rank 1-10 11-25 _26-50_ 51-100 Total

# A. Firms controlled by small investors

|Firms with bank|1975 1|0|6|14|21|
|---|---|---|---|---|---|
|ownership_>25 %_|1988 1|2|2|4|9|
|Firms w/o known|1975 3|2|1|0|6|
|large investor|1988 0|0|0|3|3|
|Firms, where small inv-|1975_5_|0|0|2|7|
|estors hold>_50%_|1988 7|7|6|7|27|

# B. Firms controlled by large investors

|Firms with large inves-|1975|1<br>3|3|2|9|
|---|---|---|---|---|---|
|tors holding 50% - _75%_|1988|1<br>3|3|15|22|
|Firms with large inves-|1975|0<br>10|15|32|57|
|tor holding_75%_or more|1988|1<br>3|14|21|39|

# source: Immenga (1975) [25,p. 104]; Table lb (1988)

. . **.** . .. . . **.** . . . . . .. ... .

It becomes clear that banks cannot have voting power in the second set of firms, which outnumber the first set of firms. This means that also the voting proxies do not fundamentally alter the conclusion that banks do not own - or control - German industry. There is, however, an interesting trend observable in Table 2, namely a move towards decentralization. There are less firms with 75% majority investors, less firms with significant bank stakes, less firms with one or a few non-bank investors holding the majority of shares, but more firms with an atomistic ownership structure. Hence, voting proxies are becoming more important for banks these days.

14