rafmacalaba/datause-encoder-data huggingface dataset:
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The rest of the paper is organized as follows. Section 2 describes the data. Section 3 shows the main patterns of financial integration of LAC with the North and the South. Section 4 analyzes how much of the expansion in LAC’s global connections is due to the growth in the number of new connections. Section 5 explores the relation between bilateral trade and financial flows. Section 6 concludes.

# **2. Data**

To analyze LAC’s patterns of financial integration, we assemble a comprehensive dataset covering bilateral data on portfolio investments and sector-level cross-border transactions (FDI and syndicated loans) between LAC countries and the rest of the world.<sup>4</sup> For portfolio investments, we work with the Coordinated Portfolio Investment Surveys (CPIS) from the International Monetary Fund (IMF) on the stock of portfolio assets covering the period 2001-2011 for 75 source countries and 207 recipient countries.<sup>5</sup> The dataset includes 40,052 observations for debt contracts and 38,427 observations for equity contracts. Of these observations, 21,092 involve a LAC country (as a sender or a receiver). For FDI, we use firm-level transaction data on M&A from Thomson Reuters’ SDC Platinum and on (announced) greenfield investments from the Financial Times’ fDi Markets, which are aggregated to construct a bilateral country-level dataset. The former covers the period 1990-2011 for 139 source and 162 recipient countries; the latter covers the period 2003-2011 for 157 source and 193 target countries. For syndicated loans, we use Thomson Reuters’ SDC Platinum transaction-level data for 1996-2012 covering 111 source and 183 recipient countries, which is also aggregated to the bilateral country level.

Because the CPIS data are on stock holdings, the estimates on portfolio assets are much larger than the estimates on syndicated loans, M&A, and greenfield investment, which are based on annual transactions. Therefore, these different datasets cannot be compared in terms of size. Nonetheless, the overall patterns on their evolution across and within the different types of financial assets are still informative.

> 4 Appendix 1 provides a comparison of the new bilateral dataset assembled with the more standard aggregate balance of payments data on gross capital flows.

> 5 The CPIS covers portfolio investment securities held by monetary authorities but not their reserve assets. The central banks of many LAC countries (such as Brazil, Chile, Colombia, and Costa Rica) classify all their foreign securities as reserves assets. In these cases, the CPIS database does not cover the investments made by the central banks. Central banks from other LAC countries (such as Mexico, Panama, and República Bolivariana de Venezuela) do not classify all their holdings as reserves assets. For these countries, the CPIS survey covers all their holdings that are not reserves assets. As a consequence of these differences, the figures presented in this paper may be lower than LAC countries’ actual holdings in the rest of the world.

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established by the central government. In particular, the level of completeness in levy collection varies markedly across polluting firms: some firms pay 100% of the pollution charges they should be paying, while others will pay a much smaller percentage. Using database of plants located all across China, Dasgupta et al. (1997) and Wang and Wheeler (2000) have shown that the actual collection of pollution levies is sensitive to differences in economic development and environmental quality: air and water pollution levies are higher in areas which are heavily polluted. While this result supports the normative theory of regulation where it is assumed that the regulator seeks to maximize social welfare (Posner, 1974), these papers do not seek to explain how the characteristics of individual firms may impact their relative bargaining power with local authorities.

In this paper, we seek to analyze the determinants of the relative bargaining power that firms may have in their relation with local environmental authorities pertaining to the enforcement of pollution levy. We show that firms from the private sector appear to have less bargaining power than state-owned enterprises. We also show, contrary to Gray and Deily (1996), that firms facing an adverse financial situation have more bargaining power and are more likely to pay _less_ pollution levies than what they should be paying (less enforcement). Finally, we also show that the higher the social impact of a firm's emissions (as measured by the presence and number of complaints), the smaller the bargaining power of the firms with local environmental authorities.

The paper is organized as follows. The next section presents a short description of Zhenjiang municipality where the analysis takes place, and of the pollution levy system in China. The analytical and statistical models are presented in Section 3, while results are presented in Section 4. We briefly conclude in Section 5.
anticipated in total. Thus, although there are severe difficulties in obtaining reliable ages in many developing countries, it should be possible to classify most of the deaths into broad age-groups with reasonable reliability.

A further source of bias is the possibility that respondents may misreport the times at which deaths took place. Tbis some deaths occurring within the prescribed recall period may be missed, and others occurring outside the period may erroneously be included. Although this could have an important effect on estimation of rates, it seems unlikely to lead to serious distortions in estimating the proportions of deaths due to different causes.

The net effect of these biases is thought unlikely to be severe, but they require further investigation.

# 3.3 Multi-round surveys and continuous follow-up

The focus thus far has been on single round surveys, because they are relatively simple and inexpensive to conduct, and because it seems feasible to envisage the implementation of surveys of this kind in a range of developing countries. Brief consideration is given in this section to various alternative approaches.

Multi-round surveys involve repeated visits to the same sample of households. They avoid some of the difficulties inherent in single round surveys. Because the population at risk is clearly delineated at the first round, it is in principle possible at subsequent rounds to determine the vital status at follow-up of the complete sample, and thus to achieve complete ascertainment of all adult deaths occurring in the sampled households during the intervening period. For each ascertained death, the most appropriate reporter can then be selected and questioned with regard to symptomatology. This approach avoids the potential bias resulting from deceased persons with differing numbers of surviving relatives. It also ensures that attention is restricted to deaths occurring within the desired reference period.

However, the advantage of having a clearly delineated population at risk is lost where there is substantial migration, because then the population is not fixed but dynamic. Particular problems may result when complete households leave the area during the follow-up period, firstly because it may be difficult to establish whether any deaths occurred prior to their departure, and secondly because suitable reporters for any such deaths will not readily be available. This may be a serious source of bias if it is common for households to break up following the death of an adult member.

A further issue concerns sampling procedures. Because of the logistical difficulties involved in locating the same households for follow-up at successive surveys, multi-round surveys are most commonly conducted in a limited geographical area, often involving the complete population of a few selected communities. This contrasts with single round surveys, in which it is feasible to use multi-stage sampling techniques to provide a sample that is representative of the entire country.

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# **2. Data description and main variables**

# 2.1 Data and empirical strategy

We define informality as the lack of formal registration of firms. Simply put, unregistered firms belong to the informal sector whereas formal firms are those that comply with licensing regulations and register with the relevant authorities. Even though alternative definitions of informality exist, our definition is practically appealing because it can be implemented in various economic contexts. The merits and limitations of various definitions of informality are discussed in Mead and Morrisson (1996) and Benjamin and Mbaye (2012) among others.

We use firm-level data from the World Bank’s Enterprise Surveys (ES) on formal or registered firms with 5 or more employees. These surveys are representative of the non-agricultural and non-financial registered private economy –excluding firms with fewer than 5 employees. A common sampling methodology –stratified random sampling– and a harmonized questionnaire are used in all surveyed countries. This data set of formal firms is complemented with data on informal businesses –that are not registered with the relevant authorities. Data on informal businesses come from World Bank surveys carried out –using a random sampling scheme– in a few business centers (cities) in some countries, which may limit their representativeness.<sup>6</sup> We extend these data with the World Bank’s World Development Indicators and other sources discussed below.

The country coverage of the sample used in the empirical analysis varies. The harmonized informality surveys are available for 18 countries and are used for the assessment of formal versus informal productivity gap. The sample includes 3,291 informal firms and 7,326 formal firms. The informal enterprise surveys were carried out between 2009 and 2014, whereas data on formal firms

> 6 Most recent World Bank surveys on informal businesses in Zimbabwe, Mozambique and the Lao People’s Democratic Republic are representative. These countries are not included in this study.

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advanced economies (82 years). Although regions such as SAR and SSA have made large improvements, raising life expectancy by 4-7 years over the past two decades, it remains about one-eight below advanced-economy levels.

Policy interventions to improve public health, and to ensure productive working lives, range widely. Better sanitation and access to clean water would improve public health: 9 percent of the global disease burden may be attributable to unsafe water, inadequate sanitation, and insufficient hygiene (WHO 2008). In addition, improvements in health care provision can be spurred by well-defined and regularly monitored performance indicators (Bradley et al. 2010). Comprehensive coverage of health services has been followed by better health outcomes in countries with higher per capita incomes (Maeda et al. 2014).

At the local level, programs targeted at local health service providers or groups of patients have generated considerable improvements in health care services and outcomes. For example, in Rwanda, performance-based incentive payments helped significantly improve health indicators for children (Gertler and Vermeesch 2012). In India, enhanced training of primary health care providers led to better identification and treatment of patient ailments (Das et al. 2016).

In a stylized scenario of improved health, life expectancy is assumed to rise over 2018-27 in each EMDE by as much as its largest improvement over any historical ten-year period. This would imply an increase in life expectancy in EMDEs by 2.5 years, on average, but as much as 3.8 years in MNA over the next decade.

# Impact on potential growth

These stylized scenarios suggest that improvements in education and health outcomes— via their effect on labor supply and TFP growth—could lift global and EMDE potential growth by 0.2 percentage point on average. In some EMDE regions with a strong track record of boosting human capital and ample room for improving education and health outcomes, such as in EAP, potential growth could rise by one-and-a-half times as much.

# 5.3. Raising labor supply

At 49 percent, on average, in 2013-17, global female labor force participation remains twothirds that of men (75 percent), and it is even lower in EMDEs. Similarly, in both EMDEs and advanced economies, the average labor force participation rate among workers aged 55 years or older is about one-half that of 30-45-year-old workers, and labor force participation among 19-29 year-olds is only four-fifths that of their 30-45-year-old peers. Labor supply can be raised by drawing a greater share of the working-age population into the labor force. This can be achieved through policies to “activate” discouraged workers or groups with historically low participation rates, such as women and younger or older workers.

In advanced economies and EMDEs, active labor market policies and reforms to social benefits were followed by higher labor force participation rates (Betcherman, Dar, and 15
examine the determinants of survival in self-employment for more than one year, comparing individuals who made it through their first year as small business operators and individuals who exited before their second year of business. The appendix provides definitions, means, and standard deviations for all variables in Table A1. Table A2 presents a correlation matrix between key variables.

# 4.1 _<u>Wealth, Access to Finance and Financial Institutions</u>_

An important branch of the literature has examined the links between wealth and entrepreneurship. Evans and Jovanovic (1989) argue that borrowing constraints imply that personal assets will be positively related to the propensity of individuals to engage in entrepreneurial activities. Survey evidence from Thai households indicates that individuals who switch to self-employment are more likely to be wealthier (Paulson and Townsend, 2004).

The wealth proxy we use is the logarithm of equivalized per capita household consumption, LHHCONS, which is calculated by adjusting household consumption to the number of equivalent adults.<sup>5</sup> In transition countries, income under-reporting and nonreporting biases the calculations based on income. We therefore utilize household consumption in the beginning of the panel as an indicator of overall financial wealth. Using other wealth proxies, such as those that reflect property ownership or the ability to “make ends meet”, do not change our main results.

While there is significant evidence on the positive impact of wealth – instrumented or not (i.e., credit constraints) on entrepreneurial activity, empirical evidence on the role of financial institutions is relatively scarce. Notably, Paulson and Townsend (2004) examine the impact of particular financial institutions on overcoming financial constraints and starting a business. Departing from their work, we utilize household affiliation with particular financial institutions and sources of finance in the past and examine their impact on the likelihood of starting a new business. The role of financial institutions is of particular interest in transition economies where the financial sector has undergone major reforms, and in BiH in particular, where the creation of

> 5 For full information concerning welfare in Bosnia and Herzegovina and the construction of the 2001 consumption aggregates, see “Welfare in Bosnia and Herzegovina, 2001: Measurement and Findings”, 2001. The equivalized measure is calculated by adjusting household consumption to the number of equivalent adults: EA=(A+aK)<sup>θ</sup> , where A: number of adults; K: number of children; a: economies of scale parameter; θ: share of public goods consumed parameter.

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16 countries, this number will be considerably larger. Indeed, Ferreira and Gignoux (2011), in their table 8, present their comparable measure to , using the mean logartithmic deviation of income as the inequality measure, for a set of six Latin American countries. Their set of circumstances is denser than mine. For some countries (Guatamala), the degree of inequality attributable to circumstances is over 50%.

Figure 2 presents the income CDFs of the three types for one of the least developed countries in sample, Hungary, and for one of the most developed, Denmark.

We see that the inter-type dispersion is considerably more dramatic in Hungary than in Austria, while the CDFs in Denmark are very close together. The graphs of the three CDFs for the other countries in the sample are presented in an online appendix.

Figure 3 plots the ordered pairs for all 22 countries in the sample<sup>13</sup> . Some comments:

1.  The eastern European countries are the worst off with respect to the index : these comprise Lithuania (LT), Estonia (EE), the Czech Republic(CZ), Poland (PL),  Latvia (LV), and Hungary (HU).    (Slovenia (SI) does somewhat better.)  But Spain (ES) is also very low on this measure.  With respect to the degree of development, η , the eastern European countries span a range from about 92% to 99.5% .

2. Greece appears to do very well on the degree of development: I question whether the data are reliable.

> 13 EU-SILC also contains data for Cyprus, but there are so few observations that I do not consider the CDFs to be meaningful. I excluded as well Ireland from the sample, because I believe the data have been miscoded: according to the data, the middle type in Ireland is worse off than the most disadvantaged type.
1. Carbon storage value of the preserved Amazon rainforest

2. Recreational value (of “eco-tourism”) for international tourists 3. Non-use value in the international context, including the biodiversity value of the forest.<sup>10</sup> The carbon storage (item 1) is to be assessed separately from our preference elicitation studies, based on estimates of the Social Costs of Carbon (SCC) in terms of global carbon emissions costs. SP experts were told that they should not consider the carbon storage value when stating their WTP. Thus, the Delphi CV survey and the planned SP studies values items 2 and 3 (but mostly 3 since very few households in a random population sample would actually have visited the Amazon Rainforest).

# **3. The European Delphi Contingent Valuation (CV) Survey**

The Delphi CV survey comprised 48 European environmental valuation experts from 20 different countries in Europe. The survey, further detailed in Appendix 1 and Appendix 2 below, proceeded in two steps. In step 1, each expert answered to a set of questions so as to provide his or her “best guess” about the mean and median WTP, among the population of their own country and among the entire European population, in terms of annual per-household **WTP to avoid further forest losses** up to 2050 in the Amazon rainforest region.

We define a “business-as-usual” **(BAU) alternative of 25% further loss** of forest area by 2050, on top of the 15 loss that already has occurred since the 1970s: There are **two avoidance alternatives:**

- **i) Plan A** - **_No further_ forest losses by 2050, beyond what has already been lost (15% relative to the pristine state).**

- **ii) Plan B** - Some further forest losses, so that, by 2050, **25% will have been lost relative to the pristine state.** Alternative i) is clearly the better and more valuable, and more challenging, outcome to be achieved.

58 experts were contacted during May and June 2012, and 48 of them (83 %) replied in Round 1. Two reminders were issues. 10 did not reply; out of which 2 refused to answer, 1 was on

> 10 In addition to these international components of the Total Economic Value (TEV) of avoiding further loss of the Amazon rainforest; global quasi option context; there is also the quasi-option value (QOV); which can be viewed as a correction factor to TEV. The QOV is the economic value of increased information about the biodiversity value of the Amazon rainforest for medicinal purposes, food security etc that can be gained from _not_ undertaking projects with irreversible effects like extinction of species.

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37 of aggravating factors and the passing of legislation excluding certain bondholders that deprived them of their equal ranking.<sup>129</sup> For practical purposes, this ruling equates to a ranking interpretation. Under English law, it seems the clause would also receive the ranking interpretation.<sup>130</sup> In the Russian case this means, at the onset, that for a _pari passu_ argument to exist there must be an attempt to discriminate bondholders by law. A scenario where there are holdouts to some future restructuring and Russia continues having some form of discrimination embodied in law could present an opening for this argument. This would be the same case as Argentina’s Elliott saga, and it is unlikely to happen, not least because for a restructuring to happen much has to change, and Russia would be aware of this rule. Another scenario in which the argument could exist is if some Russian bondholders are receiving their payments, while others are blocked by law because the money cannot leave the local clearinghouse. Making that argument at this point is superfluous because not receiving the money should already be a default.

In the past, the _pari passu_ clause has been used more effectively to block payments going to other creditors in order to pressure the debtor to settle.<sup>131</sup> Whether this strategy could yield similar results is unclear, experts in the United Kingdom seemed to conclude such injunctions would be undesirable under their laws.<sup>132</sup> One observer opined that U.K. courts would grant monetary relief as opposed to such injunctions.<sup>133</sup> In any case, these interdictions would only be relevant if the debtor was paying someone else in an amenable jurisdiction.

> 129 _See id_ .

> 130 _See_ Financial Markets Law Committee (UK), note 127 _supra_ , at 22 (March 2005); Lam, note 54 _supra_ , at 92-96 (2019).

> 131 _NML Capital, Ltd. v. Republic of Argentina_ , 727 F.3d 230, at 238 (2013) ( _NML II_ ) (affirming payment injunctions on Argentina).

> 132 _See_ Financial Markets Law Committee (UK), note 127 _supra_ , at 16.

> 133 Lam, note 52 _supra_ , at 96 (2019).