rafmacalaba/datause-encoder-data huggingface dataset:
live without fences dividing family plots, and local traditions regarding proper employeremployee relationships. Ellickson (1991) usefully distinguishes three elements of any legal order: self-control based on norms (voluntary compliance), punishments and rewards enacted by the party to an agreement (actions taken by the parties to a contract themselves), and third-party dispute resolution and enforcement. All three exist in any legal system; social order is particularly stable when they are mutually supportive and when the meta-rules regarding their selection and use are widely and clearly understood. This paper focuses on triadic (third-party) dispute resolution, perhaps unnaturally isolating it from the other mechanisms of social control, and attempts to compare its operation in state and non-state settings.

_Formal and informal legal institutions: A stylized account_ Local-level legal institutions in the developing world take a variety of forms whose origins generally predate colonial state-building. Generally speaking, European colonists layered their own legal systems and codes on top of local and “traditional” practices, with the former more often applied in the cities (especially for commercial and criminal law), while the latter was used to maintain social order in the bush, the interior, and the countryside. The simultaneous existence of two or more legal orders – a situation of “legal pluralism” – continues in many places. In places where state authority is weak or distant, people tend to prefer locallevel legal institutions to official channels and use them to address most day-to-day conflicts, including disputes related to land, inheritance, and domestic and family issues. A 2001 survey in Indonesia, for instance, found that 86% of respondents preferred these informal procedures to formal legal processes. (Stephens 2003) In many cases, people take the more costly, 4
need to control for the removal of quotas at the end of the ATC. In a post-quota world, US and EU markets are expected to be flooded by apparel from larger exporters, such as China and India, which were previously bounded by quotas. Export data and tariff data were compiled from IDB-WTO and TRAINS/WITS at the HS6-digit. However, because 95% of the volume of apparel exports is accounted for by the 7 major exporters, we report results of estimates on this reduced sample where data quality is arguably superior not only because there are positive aggregate exports by each country every year, but also because these countries export a larger number of products.

# **4.2. Econometric Strategy**

Two constraints guided our estimation strategy. First, a lack of plausible instruments at this detailed product level, precluded us from implementing a two-stage procedure in which a decision to export a specific apparel product to a given destination is taken in a first step, then a decision is taken on volume in a second step<sup>10</sup> . Second, we were confronted to a large number of zero-exports –or zeroes– in the data disaggregated at the HS-6 level: 95% of zero observations for the whole sample of 22 exporters, and 86% for the reduced sample of the top7 exporters. However, the product-specific RoO under AGOA were defined at the HS-4 level and the VC rule under EU preferences was defined at the HS-4 level. This led us to aggregate data to the HS-4 level. As a result, the number of zero trade flows is brought down to 60 percent of observations for the top 7 exporters.

Since this is still a large number of zero observations, we deal with it by contrasting several estimators in table 2. Two benchmark estimates are reported. Column 1 reports OLS estimates with ln �Xi,tj,k�as the dependent variable that considers observation for positive-only exports11, and column 2 reports Tobit estimates. To overcome the sensitivity of estimates to the arbitrary

> 10 Ideally, one would want to implement a two-stage procedure in which a decision to export a specific apparel product is taken in a first step, then in a second step a decision is taken on volume and destination.  To satisfy the exclusion restriction in such a 2-stage Heckman estimation method, would require an appropriate exogenous instrument that would influence only the decision to export in the first-stage and not the volume of exports in the second stage. Such an instrument is not available at this level of disaggregation.

> 11 Another benchmark is to shift up all export values are shifted up by one unit (i.e. fixing av=1 in (1)) before applying the logarithmic transformation and proceed with OLS (see for instance Frankel et al. (1997)). The results are close to those reported in column 1 in table 2. While this approach has the advantage of including all observations, it does not solve the problem that the resulting estimates are inconsistent.

12
Policy Research Working Paper 7124

# **Abstract**

A long literature in demography debates the importance of place for health. This paper assesses whether the importance of dense settlement for child mortality and child height is moderated by exposure to local sanitation behavior. Is open defecation, without a toilet or latrine, worse for infant mortality and child height where population density is greater? Is poor sanitation an important mechanism by which population density influences health outcomes? The paper uses newly assembled data sets to present two complementary analyses, which represent different points in a trade-off between external and internal validity. The first analysis concentrates on external validity by studying infant mortality and child height in a large, international child-level data set of 172 Demographic and Health Surveys, matched to census population density data for 1,800 subnational regions. The second analysis concentrates on internal validity by studying child height in Bangladeshi districts, with a new data set constructed with Geographic Information System techniques, and controls for fixed effects at a high level of geographic resolution. The paper finds a statistically robust and quantitatively comparable interaction between sanitation and population density with both approaches: open defecation externalities are more important for child health outcomes where people live more closely together.

This paper is a product of the Water Global Practice Group. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://econ.worldbank.org. The authors may be contacted at dean@riceinstitute.org.

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
Cumming (2008) find a strong link between bankruptcy laws and entrepreneurship in their study of 15 countries in Europe and North America, suggesting that the legal environment is an important factor for VC activity. Similarly, we hypothesize that there is more buyout activity in countries with stronger institutions and better governance. As buyout transactions typically involve a large transfer of ownership and private contracting, investor protection and contract enforcement would be particularly important for PE investors. Hence, we use investor protection and contract enforcement reforms in addition to rule of law to measure the overall strength of the regulatory and institutional environment in a country.<sup>10</sup>

# **3 Data and Descriptive Statistics**

The PE investment data come from Burgiss, a financial services company providing record keeping and performance analysis support to large institutional investors. There are two major advantages of this data set over others. First, Burgiss sources its data exclusively from limited partners, as opposed to general partners (GP), so the typical biases associated with GP-sourced data sets are not present.<sup>11</sup> Second, Burgiss has provided us a complete data set of investments, by country, by industry, by year for their entire database of funds and these data are unavailable from any other source.

The primary variable from Burgiss data for our study is the annual amount of buyout capital invested (measured in US$) at the country level for 61 countries over the period 1990 to 2017.

> 10 The use of reforms rather than other traditional measures of regulatory quality, which are typically highly correlated with rule of law, also allows us to perform a difference-in-differences analysis where we compare buyout activity pre- versus post-reform in countries that implemented a reform versus others that did not.

> 11 GP-sourced databases on private equity may have significant biases as GPs strategically stop reporting. In many cases, Burgiss cross-checks data across different investors in the same fund, which leads to a high level of data integrity and completeness. Recently, Brown et al. (2015) compare different commercial PE data sets. For detailed information about Burgiss and its coverage of the PE universe, see Harris et al. (2012) and Brown et al. (2011).

11
<!-- Start of picture text --> Average Prices, Eggs<br>(December 1991 -- August1992)<br>-30.<br>X;L................. .... ........ . . . .. ........................... ............................... ................... .<br>29e ~~~~~~~.. 7.................................. .................................<br>. . *...<br>0-,............................................................... ................................... ,--.---...........<br>Dec91 01/28 02/11 02/25 03J31 04J14 0/805/12' 0602 06/1I6 06J30 07/14 07M 08/11 MIS2<br>Date<br>- Market Price .... State Price |<br><!-- End of picture text -->

47
# **Table A17:  Heritage Foundation Index of Economic Freedom (HER)**

|**Data Provider**|Heritage Foundation|
|---|---|
|**Description**<br>|The Heritage Foundation is a nongovernmental research and educational institute<br>headquartered in Washington, United States, advocating conservative public policies.<br>|
|**Website**|www.heritage.org|
|**Data Source**|Index of Economic Freedom|
|**Type**|Expert Assessment|
|**Respondents**|Staff of Heritage Foundation|
|**Frequency**|Annual since 1995|
|**Coverage**|Global sample of countries|
|**Public Access**|Yes|
|**Description**|Heritage constructs an Index of Economic Freedom consisting of 10 components. There<br>were major revisions to the methodology in 2006 and 2007. We use data from the three of<br>these components that are based on subjective assessments of Heritage staff and are<br>comparable over time: Investment Freedom, Financial Freedom, and Property Rights.<br>These indicators are scored on a 100-point scale. Note that the indicators refer to data from<br>the previous year: we therefore lag the data from this source by one year.|

||2007|2006|2005|2004|2003|2002|2000|1998|1996|
|---|---|---|---|---|---|---|---|---|---|
|**Voice and Accountability**||||||||||
|NA|..|..|..|..|..|..|..|..|..|
|**Political Stability and Absence of Violence**<br>NA|..|..|..|..|..|..|..|..|..|
|**Government Effectiveness**||||||||||
|NA|..|..|..|..|..|..|..|..|..|
|**Regulatory Quality**||||||||||
|Foreign investment|X|X|X|X|X|X|X|X|X|
|Banking / Finance|X|X|X|X|X|X|X|X|X|
|**Rule of Law**||||||||||
|Property Rights|X|X|X|X|X|X|X|X|X|
|**Control of Corruption**||||||||||
|NA|..|..|..|..|..|..|..|..|..|
|**Country coverage**|**157**|**157**|**157**|**155**|**155**|**156**|**155**|**161**|**150**|
|**Year of Publication**|**2008**|**2007**|**2006**|**2005**|**2004**|**2003**|**2001**|**1999**|**1997**|

55
Policy Research Working Paper 8329

# **Abstract**

This paper presents a comprehensive analysis of economic and social mobility in countries in the South Caucasus by complementing available household survey data in each of the countries in the subregion with other sources, such as the Life in Transition Survey (2016). The first part of the paper—concentrated on intragenerational mobility—finds that despite progress made in reducing poverty over the past decade, there appears to be a significant amount of churning around the poverty line. Moreover, in Georgia and Armenia, roughly one in eight individuals lived in a state of chronic poverty in 2015, and in the case of Georgia, chronic poverty is not an exclusive phenomenon for rural areas. In addition, although social programs have provided a lifeline for the chronic poor, the ability to tap into labor market opportunities has been the ticket out of poverty. The second part of the paper expands the analysis to intergenerational or social mobility. The main findings are that (1) a higher proportion of the population in this subregion considers their pre-transition family life and the lives of their parents when they were of similar age as appropriate benchmarks to evaluate their current economic situations in comparison with the other transition countries, and (2) over half of the Georgian and Armenian population disagreed with the statement that asked their views on having a better in life than their parents, aligning with the “growing but unhappy” trend that has been reported for the region.

This paper is a product of the Poverty and Equity Global Practice Group. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://econ.worldbank.org. The authors may be contacted at afuchs@worldbank.org.

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
than 34 percent in 1990, to less than 11 percent in 2013. The estimated poverty rates in 2013 are less than 5 percent in one-fourth of the 131 countries for which the World Bank monitors extreme poverty. As the global proportion of people in extreme poverty declines further, this assessment of global poverty may become increasingly less socially relevant as societies across the world define the cost of basic needs at levels much greater than the international poverty line.

A global poverty line that allows for the poverty threshold to vary across countries, essentially allowing for the cost of meeting basic needs or functionings to be increasing with the economic development of societies, would result in a definition of poverty that is more closely aligned with each country’s own assessment of needs. A few important proposals for such lines are detailed in Atkinson and Bourguignon (2001), Ravallion and Chen (2011), Chen and Ravallion (2013) and Garroway and de Laiglesia (2012), and summarized in Figure 1 and Table 1. Borrowing notation from Ravallion and Chen (2011), all of these proposed global relative poverty lines, (��,����), follow a similar form that can be summarized as _max(Z*, α+kM i,t ). Z*_ defines a floor, _α_ is a fixed intercept _, kM i,t_ defines for country _i_ in year _t_ the relativist portion of the schedule which is upward sloping ( _k>0_ ) in the level of economic development, typically measured by the national average (or median) value of per capita expenditure, consumption or income ( _M_ ). The Atkinson-Bourguignon and Ravallion-Chen proposals define _Z*_ to be equal to the international poverty line (set at $1 in 1985 PPPs or $1.25 in 2005 PPPs). More specifically, Atkinson and Bourguignon (2001) propose a global relative poverty line that sets _Z*_ at a dollar a day (in 1985 PPP terms), _α=0, k_ =0.37 and _M_ = mean per capita private consumption expenditure from national accounts. The resulting global relative poverty line, (��,����), takes the value of $1 for all countries with average per capita expenditure of less than $2.70 per day and then increases 6
foreign asset holdings of the Central Bank, and public sector domestic debt net of holdings of such debt by the same Central Bank. Similarly, deficits and the ensuing liabilities for the state may be seriously mis-measured if the quasi-fiscal deficit of the Central Bank is excluded. This is a major shortcoming of the recent IMF approach to sustainability (IMF 2002,2003)).

After that consolidation, increases in net public debt (i.e. measured net of the net foreign asset and public debt holdings of the central bank) can be decomposed in various contributing factors, which in turn can be linked to the macroeconomic projections available. Switching to ratios to GDP and indicating that by a tilde above the relevant variables, public debt dynamics can be broken down in several components: (A) the primary fiscal deficit net of seigniorage revenues, (B) growth adjusted real interest rate payments on domestic debt; and (C) the real cost of external borrowing, including capital gains and losses on net external debt due to changes in the real exchange rate. In formulas:<sup>4</sup> ~ ~ where _d t_ is the net public debt-to-GDP ratio, _pd t_ is the primary deficit as a share of GDP, g is the real GDP growth rate, _r_ is the real interest rate on domestic debt, _r_ * is the real interest rate on _EP_ * external debt and _e_ is the real exchange rate, _P_<sup>with obvious definitions of variables.</sup> Equation (5) separates the different factors contributing to the evolution of public debt to GDP ratio: (i) the primary fiscal balance; (ii) the revenue from seignorage; and (iii) automatic debt dynamics, which includes factors such as the real GDP growth; the real interest rate on domestic and external debt and the real exchange rate. It also includes a catch all term, O(ther) F(actors). OF collects residuals due to cross product terms arising because of the use of discrete time data (see Annex A.1 in Bandiera e.a. (2006) for an elaboration) and the impact of debt increasing factors that in a perfect accounting world would be included in deficit measures, but in the real world are not. Examples are contingent liabilities that actually materialize, such as the fiscal consequences of a bank bail out, one-off privatization revenues, and so on. Of course if countries borrow in more than one foreign currency (e.g. dollars and Euros, or Yen), more than one foreign debt stock should be kept track of in analogous manner.

> 4 Note that to simplify the exposition we present a continuous time formula. However, as shown in the Annex, in the FS template we use the discrete time formulas for deriving the public debt dynamics.

9
# 1. Introduction

Since 1990, Bangladesh experienced a 20 percentage point increase in access to drinking water sources that are considered “improved” by global standards, with current access at 98 percent (WHO/UNICEF 2017). The transition from unimproved sources such as ponds, rivers, open wells, and other unprotected water to improved water infrastructure is considered as an important stride in Bangladesh’s development and is thought to have significantly lowered the disease burden of waterborne illness and infant mortality rates (Field et al 2011). Although the water that Bangladeshis consume is safer today than in recent decades, it is still plagued by widespread fecal contamination. A nationally-representative cross-sectional survey on water quality estimates that 56 percent of all improved water sources are contaminated with _Escherichia coli_ (E. coli) bacteria (UNICEF 2016).

Poor water quality is a stubborn barrier to reducing preventable enteric infections and sometimes chronic ailments that debilitate and kill children. Exposure to fecal contaminants in drinking water has mostly been linked to diarrheal diseases, which are a leading cause of child mortality in low-income countries like Bangladesh. Systematic reviews and meta-analyses on the effectiveness of water, sanitation, and hygiene (WASH) interventions conclude that point-of-use water treatment is among the most effective WASH interventions for reducing diarrheal disease (Fewtrell et al 2005; Clasen et al 2007; Gruber et al 2014; Wolf et al 2018). Massive increases in water and sanitation coverage and delivery of oral rehydration therapy are likely to have lowered child deaths from diarrheal diseases globally (Victora et al 2000; Askeer et al 2017).

However, good quality water could have additional benefits for child well-being, such as improving nutritional outcomes including stunted growth, a measurement of low height-for-age and marker of chronic undernutrition. Observational studies have shown the effects of poor sanitation, particularly high rates of open defecation, on rates of stunting in a number of countries (Spears et al 2013; Heady et al 2016; Rah et al 2015; Chambers et al 2013). However, a systematic review evaluating the effectiveness of WASH on improving nutrition concluded that improvements in microbial water 2