rafmacalaba/datause-encoder-data huggingface dataset:
**Annex** : Variable definitions and sources

|Variable|Definition|Source|
|---|---|---|
|∆ Ln Child mortality|Log change in Mortality rate,<br>under-5 (per 1,000 live births)<br>between 1980 and 2010|World Development Indicators, World Bank;<br>http://data.worldbank.org/data-catalog/world-development-<br>indicators|
|Ln Initial Child<br>mortality|Log of Mortality rate, under-5<br>(per 1,000 live births) in 1980|World Development Indicators, World Bank;<br>http://data.worldbank.org/data-catalog/world-development-<br>indicators|
|∆ Ln school<br>enrollment|Log change in school<br>enrollment, secondary (%<br>gross)between 1980 and 2010|World Development Indicators, World Bank;<br>http://data.worldbank.org/data-catalog/world-development-<br>indicators|
|Ln Initial school<br>enrollment|Log of gross secondary school<br>enrollment in 1980|World Development Indicators, World Bank;<br>http://data.worldbank.org/data-catalog/world-development-<br>indicators|
|Health spending PC,<br>PPP|Public spending on health per<br>capita per year (2005 PPP<br>dollars)|World Development Indicators, World Bank;<br>http://data.worldbank.org/data-catalog/world-development-<br>indicators|
|Education spending<br>PC, PPP|Public spending on education<br>per capita per year (2005 PPP<br>dollars)|SPEED Database, IFPRI;http://www.ifpri.org/blog/speed-public-<br>expenditure-data-now-online|
|Population Density|Population per sq. km|World Development Indicators, World Bank;<br>http://data.worldbank.org/data-catalog/world-development-<br>indicators|
|Undernourishment|Prevalence of<br>undernourishment (% of<br>population)|World Development Indicators, World Bank;<br>http://data.worldbank.org/data-catalog/world-development-<br>indicators|
|Control of<br>Corruption|Control of Corruption:<br>Estimate of governance<br>(ranges from approximately -<br>2.5 (weak) to 2.5 (strong)<br>governanceperformance)|Worldwide Governance Indicators, World Bank;<br>http://info.worldbank.org/governance/wgi/index.aspx#home|
|GDP per capita<br>growth|GDP per capita growth (annual<br>%)|World Development Indicators, World Bank;<br>http://data.worldbank.org/data-catalog/world-development-<br>indicators|

23
# **Box 5:  The MTS System**

**<mark>MTS S.p.A</mark>** <mark>. is the wholesale interdealer electronic trading market for government bonds in Italy and was the first European electronic market for government bonds.  It is a private company that administers the electronic trading platform Tele-matico.  The company was founded in Italy in 1988, was privatized in 1997, and is today owned by around 60 major international financial institutions.</mark>

**<mark>EuroMTS</mark>** <mark>was launched in 1999 as an international trading platform for European benchmark government bonds (minimum outstanding volume EUR 5 billion) and is fully owned by MTS S.p.A.</mark>

<mark>There are also a large number of</mark> **<mark>local/national MTS companies</mark>** <mark>. These local trading platforms include MTS Amsterdam, MTS Belgium, MTS France and MTS Portugal.</mark> <mark>MTS is an example of a dealer market with hybrid features. One the one hand, it is a quote driven, multidealer system in which major market makers are obliged to display bid / offers continuously during operating hours. On the other hand, it can be characterized as a centralized, cross-matching system as market makers ́ quotes are aggregated in a single order book to match best anonymous bids and offers automatically subject to non-discretionary priority rules. This unique market architecture enables MTS markets to simultaneously benefit from the strengths of two distinct systems: transparency and cost-efficiency of a central electronic cross-matching system as well as liquidity and immediacy of the quote-driven system.</mark> <mark>MTS and/or EuroMTS provides electronic market-making in wholesale markets for government bonds in all 15 EU member states, except from United Kingdom, Sweden and Denmark and Luxembourg.</mark> Source: World Bank (2001): "Developing Government Markets – a Handbook" A “regulated market” benefits from the right to remote access into another member state. The directive requires member states to allow a regulated market from another member state to provide “appropriate facilities” (e.g., place trading screens and terminals on the desks of remote/overseas members) so as to allow the latter to participate fully in trading on the market (Article 15.4). Under Article 16 of the Directive, the Commission is required to publish a list of regulated markets on an annual basis.

The 1993 ISD does not address the regulatory and competitive issues that arise when exchanges start competing with each other and with new order-execution platforms. At the time of ISD adoption, competition between exchanges/trading systems was non-existent. Now, competition between different methods of trade-execution (exchanges, new trading systems, inhouse order execution by investment firms) is the principal regulatory challenge confronting EU securities regulators and supervisors. Box 6 contains a description of developments in EU financial trading since the adoption of the 1993 ISD.

36
Gini in 2017 from 62 to 67.<sup>34</sup> Panel B of Figure 6 shows trends that are broadly similar for the adjusted and unadjusted surveys, showing a robust decline in global inequality since about year 2000. The levels and patterns are in line with those of Lakner and Milanovic (2016) who use a different form of adjustment and aggregation, but only provide estimates until 2008. For 2008 they estimate a global Gini of 67.0 using 2011 PPPs, while our estimates are 66.7.<sup>35</sup> Their topincome adjusted estimates are 2.9 to 6.3 percentage points higher for 2008, within the same range as our top-adjusted estimate, which is 4.3 percentage points higher for 2008. Using the unadjusted distributions with national accounts means instead of survey means, global inequality is lower and declining faster. This is expected from the pattern of national accounts measures, which are larger and growing faster than survey measures, especially in middle-income countries. Notably, global inequality has continued falling rapidly using all measures. Our survey-based estimates have fallen 6 to 7 percentage points since 2000.

Generally, the larger HHS - NAS gap among middle-income countries leads to relatively larger adjustments to inequality measures in these countries. These systematic differences along the income gradient of countries also lead to insights into the relationship between economic development and levels of inequality. Evidence of the cross-sectional Kuznets curve – the hypothesis that income inequality first increases and then declines with development – has recently been questioned. Palma (2011, p.87) suggests that the “the ‘upwards’ side of the ‘Inverted-U’ between inequality and income per capita has evaporated.” This is indeed true for the unadjusted Gini coefficients in our sample. However, Gini coefficients from the top-income adjusted data, suggest that there is an upwards sloping segment and firmly re-establish a Kuznets-like relationship between economic development and observed inequality, as seen in Figure 7. The clearly inverted U-shaped curve results from the lowess regression of the adjusted Ginis. A quadric form regression of the Gini estimates from the adjustment on GDP per capita explains more than twice as much variation as the regression of the unadjusted measures.

> 34 We measure global interpersonal inequality, capturing inequality of individual incomes (or consumption), referred to as ‘concept 3’ inequality by Milanovic (2005). We estimate a global Gini coefficient giving each individual equal weight, regardless of where they live, using the same weights as used for estimating global poverty. The global distribution is generated using the reference year distributions for global poverty measurement in PovcalNet, using the method described in Section 2.

> 35 Lakner and Milanovic (2016) conduct most of their analysis using 2005 PPPs, but provide estimates based on 2011 PPPs as well.

26
informational playing field (and so raise competition and reduce moral hazard, that is they reduce the incentives to default).

Jappelli and Pagano (2000) find that public credit registers are more likely to arise where private arrangements are weak and that information sharing arrangements are more likely to arise where creditor rights are poorly protected (to compensate for poor protection ex-post).<sup>2</sup> But private arrangements may also serve as entry barriers –Jappelli and Pagano assert that in Mexico the banks have a vertically integrated arrangement with a monopolistic credit bureau system that prevent new banks (having an informational disadvantage) from entering. In an empirical study covering several countries Jappelli and Pagano (2002) find that information sharing leads to an increase in lending. This relationship holds even after accounting for country size and growth rate, and variables capturing respect for property rights and respect for the law. Galindo and Miller, 2001, find that improved assessment of credit risk as enabled by more information sharing translates into higher lending. Pinheiro and Cabral (2001) report that the postdated check market operates without collateral, without personal guarantees, and without legal sanctions of any type. It is based on an information sharing mechanism (a black list of people who write checks without funds to back them). Trivelli, Alvarado and Galarza (2001) find that the development of a public rating register in Peru has encouraged lenders to shift away from exclusive reliance on collateral towards information based lending.

The design of institutions such as credit registries discussed above affects the type of monitoring that takes place in countries since they affect the amount of information

> 2 The use of collateral can be justified as a response to information asymmetries, as can various types of contingent contracts.

6
linear regression of value added on the four input factors, with the following constraint: _βl_ + _βk_ + _βx_ + _βf_ = 1. In this manner, we assume that firms’ production function is constant returns to scale.

There is substantial data attrition in the estimation of the production function. On average, in a given year, only 21 percent of firms provide sufficient information to DGII in order to estimate the production function. The data required includes: total sales, total intermediate inputs, finished product and intermediate input inventories, wage bill, electricity expenditure, and fuel expenditure. Furthermore, for some 2-digit industries, we obtain negative elasticities for some factor inputs. Industries with negative elasticities are dropped from our analysis.<sup>13</sup> As a result of this data attrition, the sample of firms used for our quantitative analyses is substantially smaller, representing only 5.3 percent of firms in 2018. However, this sample still accounts for a substantial share of economic activity and firm emissions, representing 31.6 percent of value added and 27.6 percent of total firm emissions, as displayed in Table 1.

# **5 Existing Misallocations in the Dominican Republic**

This section presents evidence of allocative inefficiencies of factor inputs across firms in the Dominican Republic, including fuel and electricity inputs. Figure 5 displays large dispersion in marginal revenue products of inputs, computed as in (6). This reflects the variation in the estimated wedges _{τ_ ˆ _ji}j_ = _k,y,x,f_ , including electricity and fuel inputs, which suggests the presence of energy frictions in the Dominican Republic. Furthermore, there is also substantial dispersion of firm revenue-based total factor productivity in the Dominican economy. As derived in the Appendix A, revenue-based TFP is defined as: implying that heterogeneity in _tfpri_ reflects the combined variation in the estimated wedges _{τ_ ˆ _ji}j_ = _k,y,x,f_ . As explained by Hsieh and Klenow [2009], in the absence of distortions, revenue TFP would equalize across firms. Furthermore, differences in the input quantities demanded by firms would only depend on quantitybased TFP, so that firms that are more productive capture a larger share of factor inputs. Conversely, the presence of distortions may cause factors to be allocated not towards more productive firms (higher _ai_ ), as demanded input quantities would also depend on distortions. In turn, this can lead to a lower level of aggregate TFP, as the most efficient firms would not necessarily capture the largest shares of factor inputs in comparison to the frictionless economy.

> 13Service industries with a 2-digit ISIC code greater than 64 are excluded from our analysis as these are sectors with very low emissions. These sectors include financial services, real estate services, professional services, public administration, education services, health services, social services, arts and entertainment, and private home services.

17
magnitude to the findings of Choe et al. (2005) for the Republic of Korea between 1996 and 1998. The comprehensiveness of our data set allows us to go beyond just the documentation of aggregate trading losses and make several contributions relative to prior research. We begin by documenting that the disadvantage of foreign investors in our sample is attributed to passivelymanaged foreign funds, that is, those whose strategy consist of replicating the return on an index by buying and holding all (or almost all) index stocks in the official index proportions. In addition to paying higher prices for stock purchases and receiving less when they sell, these funds display inferior risk-adjusted returns than foreign active funds. Our evidence suggests that managers of foreign passive funds are paying a price for a trading style that differs from the trading style of other investors. In particular, worst trades are on days when they are trying to accommodate large flows in similar proportions to their benchmark index by (i) trading multiple stocks in the same direction, (ii) buying (selling) the same stock multiple times, and (iii) making large trades at the end of the trading session.

In addition to comparing performance across foreign investors with different styles of management, we also compare the performance of foreign versus local investors by level of active management. We find that the yearly returns of passive foreign funds are between 1.19 to 1.90 percentage points smaller than domestic funds with similar passive strategies. This suggests that index investing by itself cannot explain the under-performance of foreign investors.

In order to understand outstanding characteristics which may be driving performance, we analyze the timing of flows across funds. The key finding is that daily net flows of passive funds are strongly correlated in the cross-section. Specifically, we show that managers of passive funds trade more intensively on days when other passive funds are trading in the same direction. Furthermore, the large imbalance of daily flows by foreign passive funds appears to be generating a significant price pressure on the stocks that they trade. We show that trades by this group are correlated with same-day returns, which suggests that foreign passive funds are paying a price for accommodating their daily flows.

Importantly, both components —passive portfolio management and correlated flows – are necessary conditions to explain the magnitude of the under-performance of foreign investors. If flow imbalances by passive funds are large enough, in order to trade stocks in similar index proportions, managers pay higher transaction costs to cling to their benchmark before the end of the trading 3
# Lobbying for Capital Tax Benets and Misallocation of Resources during a Credit Crunch<sup>_∗_</sup>

Gabriel Zaourak<sup>_†_</sup> World Bank Please, click here for the latestversion

## JEL Classication: E44, E62; L25, O16.

Keywords: Financial Frictions, Misallocation, Lobbying, Credit Crunch.

> _∗_ Gabriel Zaourak is a Young Professional at the Macroeconomics, Trade and Investment Global Practice at the World Bank. I am extremely grateful to Francisco Buera, Ariel Burstein and Lee Ohanian for their comments and guidance. I am thankful to Andrew Atkeson, Devin Bunten, Sam Choi, Pablo Fajgelbaum, Roger Farmer, Fernando Giuliano, Federico Grinberg, Andreas Gulyas, Gary Hansen, Ioannis Kospentaris, Dennis Kuo, Musa Orak, and Liyan Shi for insightful discussions, and participants at the Macro Proseminar and Macro student seminar at UCLA. Last, I want to thank the Center for Responsive Politics (CRP) for providing the lobbying data. The views expressed herein are only my own and should not be attributed to the World Bank, its executive directors, or the countries they represent.

> _†_ Email: gzaourak@worldbank.org
remains significant for most of the indicators above and often at the 1% level for all these permutations.;

**Table 9a. Transparency and Legal Origin Terms**

||_DATASET_|_:KAUFMANN,K_|_RAYANDZOI_|_DO-LOBAT_|_ON_||
|---|---|---|---|---|---|---|
||Howauthoritie<br>re|sareselectedand<br>p**l** ced<br>-|Capacityof <br>implementso|thestateto<br>undpolicies|Respectofthe s<br>citizensfor|tate andthe<br>the rules|
||Voice and<br>Accountability|Political Instability<br>andViolence|Government<br>Effectiveness|Regulatory<br>Burden|RuleofLaw|Graft|
|SocialistLegalCode|-.31|-.06|.-62***|-.67***|_-.51***_|-.80**|
||(-1.77)|(-.32)|(-4.28)|(-4.3)|(-3.57)|(-5.91)|
|FrenchLegalCode|-.02|-;13|-.10|-.<br>11|-.29**|-.35***|
||(-.14)|'(-.91)|(-.84)|(-1.18)|(-2.74)|(-317|
|GermanLegalCode|.29|.24|.20|-.31**|.29|-.11|
||(-1.51)|(1.10)|(.84)|(-2.27)|(1.65)|(-.38)|
|ScandinavianLegalCode|.65**|49**|.62**|-.07|.48***|79***|
||(4.1)|_(3.53)|(493)|(-.63)|(4.08)|(4.82)|
|Income|.34**|_.51***_|40***|.25***|54***|44***|
||(4.22)|(7.05)|(6.73)|(4.94)|(10.18)|(7.65)|
|Transparency|Ig**|-.06|-.17***|-20***|-.06|-.16***|
||<br>(-2.371|(-.98)|(-3.23)|(4.1)|**_*_**<br>(-1.38)|(-30|
|Constant|-2.16**|-4.06***|-2.79***|-1.34**|4.14*0*|-3.03***|
||,~(-2.77)|(-5.45)|(-4.75)|(-2.51)|(-7.71)|(-5.51)|
|#obs|136<br>|125<br>|126<br>|131<br>|131<br>|125<br>|
|=R|<br>.46|_.55_|.63|.55|.69|.69|

# **Table 9b. Transparency and Legal Origin Terms**

_DATA SET: ICRG, Averaged over the period 1984-1997_

||ICRG|Corruption|RuleofLaw|Bureaucmcy<br>Quality|Contract<br>Repudiation|Expropriation<br>Risk|
|---|---|---|---|---|---|---|
|SocialistLegalCode|.44<br>(1.63)|.73<br>(2.57)|1.16**<br>(5.27)|.01<br>(.06)|.32<br>(.92)|68e<br>(2.64)|
|FrenchLegalCode|-.40**|-.20|-.31|-.73***|-.28*|-.38***|
||(-2.53)|(-.92)|(-1.43)|(-3.31)|(-1.82)|(-2.81)|
|GermianLegalCode|.67**|_.51_|.86**|75***|.92**|54***|
||(3.7)|(1.43)|(2.43)|(2.8)|(6.17)|(4.3)|
|ScandinavianLegalCode|840**|1.47e*|1.17***|.88***|59**|39**|
||(4.<br>12)|(5.32)|(4.49)|(2.98)|(3.1)|(2.65)|
|Income|.53"<br>(4.2)|_51**_<br>(3.17)|78***<br>(5.20)|.66***<br>(4.02)|.525*<br>(4.12)|45*5*<br>(4.51)|
|Transparency|-.42***|-.47***|-.39***|-46**|-.39***|-.37*0|
||(-6.04)|(4.85)|(-3.82)|(4.77)|(-4.88)|(-5.57)|
|Constant|.81|.53|-1.54|-.24<br>|1.02|1.89*|
||(.8|1)<br>(.41|)<br>(-1.25)|(-19)|(1.01)|(2.29)|
|#obs|94|94|94|94|94|94|
|R<br>|.68<br>|.54<br>|.62<br>|.61|.65|.67|
|_*indicatessignifcance_**_at.I _**_l_|_evel,_******_at.05_|_leveland_<sup>_55 5 _</sup>|_at.01 level._||||

Controlling for various regional dummies (such as Africa, the Middle East and North Africa, East Asia, South Asia or Eastern Europe) does **not** alter these results significantly. Adding years since independence as an additional variable in **the** specifications (does reduce the 25
# **2.  Women’s Participation in the Labor Force and Politics in India**

# **2.1 Women’s Socio-Economic Status and Political Representation**

Historically and even today, women remain a disadvantaged section of Indian society. Women were significantly underrepresented in political institutions in India, accounting for only 10% of the membership of national legislatures in 2009. Over the period 1985-2007, only 5.5% of state legislators were women. Women were also significantly disadvantaged in terms of human development indicators: in 2007, India had only 940 women for every 1000 men in the 2011 Census. Only 65% of women in India were literate in 2011, compared with 82% of men.

# **2.2 Mandated Political Representation in Local Councils**

At the national level, reservations for women in elected bodies in India originated with the 73rd and 74th Constitutional Amendment Acts. These Amendments gave national support to the formalization and implementation of an historical decentralized governance structure known as the panchayat (or, more formally, Panchayati Raj Institutions). Traditionally, panchayats operated at the village level and consisted of a small number of individuals chosen by a village to oversee a wide range of local affairs. However, panchayats were not standardized in their structures, organization, operations, or responsibilities, nor were they necessarily elected bodies. By the mid-20th century panchayats were recognized often to embody “concealed forms of social prejudice, oppression and exploitation that were firmly rooted in local power structures” (GOI 2008). In the latter half of the 20th century there was support for the revival of a reformed panchayat system, with some states indeed restructuring their local government systems to provide for the decentralized panchayat system. By 1989 there was strong support at the national level to give constitutional status to a broad panchayat system.

In 1993, two pieces of national legislation came into effect: the 73rd Constitutional Amendment Act instituted a three-tiered system of local government at the village, sub-district (block), and district levels in rural areas of the country, while the 74th Constitutional Amendment Act instituted a revised local governance structure in municipalities (hereafter “the Amendments”). The Amendments intended to provide large-scale devolution and decentralization of administrative powers to local bodies. Responsibilities of the Panchayat include administration 6
That said, it is important to confirm that our (absence of) results for the impact of the treatments on migration overseas are robust to including responses from the “log” surveys of neighbors, which were administered when neither respondent nor proxy surveys could be successfully completed. Log surveys were very limited in content, asking only whether the respondent was currently living overseas and what they were doing abroad. Inclusion of the log survey responses on whether the respondent was working abroad raises our endline response rate to 98.5%.

We report the impact of our treatments on whether respondents were currently working abroad, including log survey responses, in column 1 of Table A6. The results confirm our previously reported findings that use only the respondent and proxy surveys: there is no evidence of positive statistically significant impacts of any treatment on migration overseas. Indeed, we find that some information treatments may have actually reduced international migration. Those assigned to treatments [T2] + [T3] are 1.2 percentage points less likely to have migrated overseas, which is significantly different from zero at the 5% level. Some of these differences could have resulted from the differential attrition observed in Table A2, column 2, though it is possible that the information we provided respondents with new information on the difficulties involved in overseas labor migration, discouraging some respondents from seeking to migrate. However, we cannot reject the null hypothesis that all of the treatment effects are jointly zero.

# **A6. 2013 supplementary survey of job-offer recipients**

At the time of the endline survey, 13.8% of those who had received overseas job offers but had not yet migrated reported that their migration was still pending (row 2, Table 37