rafmacalaba/datause-encoder-data huggingface dataset:
Interstate Highway System”, _The Review of Economics and Statistics_ , 90(4): 683-701 Stelios Michalopoulus and Elias Papaioannou (2013). “Pre-Colonial Ethnic Institutions and Contemporary African Development”, _Econometrica_ , 81(1): 113-152.

Pigois, J.P., Groves, D.I., Fletcher I.R., McNaughton N.J., and Snee, L.W. (2003). “Age constraints on Tarkwaian paleoplacer and lode-gold formation in the Tarwa-Damang district, SW Ghana”, _Mineralium Deposita_ , 38: 695-714.

Taylor, A.A., 2006. _An Economic History of the Ashanti Goldfields Corporation, 1895-2004: Land, Labour, Capital, and Enterprise_ . PhD Thesis, London School of Economics.

United States Geological Survey, (1994-2010). “The Mineral Industry of Ghana” in: _Minerals Year Book_ , ed. United States Geological Survey, various years.

29
6 the probability of civil war (Muller & Weede, 1990; Hegre et al., 2001). This relationship can be deduced from the theoretical notion that war is a function of _identity formation_ of the competing groups, the _motivation_ to fight over an issue, and the _opportunity_ to fight. Variants of this scheme are found in the writings of Gurr (1970) on political violence, Collier & Hoeffler (2004)<sup>8</sup> and Ellingsen (2000)<sup>9</sup> on civil war and Most & Starr (1989) on interstate war<sup>10</sup> . If we assume that increased democracy provides improved opportunity for rebels to organize, while the lack of democracy provides a motive for rebellion against the autocratic leadership, the combined effect of opportunity and motivation can be written as d(1-d), where d is the degree of democracy, i.e. a parabolic relationship. The inverted U-curve has been confirmed in several studies (e.g. de Soysa, 2002; Fearon & Laitin, 2003). Hegre (2003) and Collier et al. (2003) argue that the relationship between democracy and civil war may be conditioned by economic development, and that at low levels of economic development increased democracy may even yield more conflict. There are relatively few poor democracies, so we regard the jury as still being out on this hypothesis. But if it is correct, it has implications for attempts to force democracy from the outside.

Finally, one-sided violence (the killing of unorganized people)<sup>11</sup> is not included in the Correlates of War data and is only available for the period after the Cold War in the Uppsala Conflict data Eck & Hultman, 2007; Mack, 2005). But such conflict is closely related to civil war in at least two ways: First, it frequently occurs in the same countries that are affected by civil war, for instance in order to disarm a minority group before it has a chance to rebel or after it has been defeated in battle. Second, one-sided violence seems to be associated with many of the same factors as internal violence. Rummel (1994) holds that the more authoritarian a country, the greater the probability of democide, while Fein (1995) argues that there is ‘more murder in the middle’, i.e. a pattern akin to the inverted U-curve posited for civil war. One could imagine that a stable autocracy might avoid politicide as well as civil war since the opposition is un-

> 8 Collier & Hoeffler refer variously to ‘greed and grievance’ and ‘opportunity and grievance’. 9 Ellingsen refers to identity, frustration, and opportunity.

> 10 Most & Starr refer to opportunity and willingness, identity presumably trivial given that nationstates are the obvious actors in interstate war. With the multilateralization of war, in particular the active involvement of NATO, the UN, and other international organizations, this may change.
Table 3: [990 Export Boom

|Answer|% of Total Exports|
|---|---|
|l___________________|_j|<br>-<br>-Involved"|
|The sameproduct<br>Diversionin1990|91<br>1<br>89|

IJ Total exports refer to the 1990 expons of the firms polled.

# _Investment Behavior_

An enduring fear has been that worker-controlled SOEs would decapicalize companies by paying out all surpluses: in wages. This fear has been justified by appealing. to. the governance of companies (worker-controlled firms with "no advocate for capital") and the assumed myopia of workers.

We set up a direct test for decapitalization, defined simply as investment being less than depreciation. What is the relationship between investment. depreciation and profitability at the firm-level? Do more profitable firms invest more? And in cases where investment does exceed depreciation, does profitability play a positive role? Or is there no obvious link with profitability? If more profitable firms do invest more relative to depreciation. then one can conclude that any observed decapitalization is really a part of the normal adjustrnent one would expect to the change in economic regime. rather than a deliberate squandering of state assets. The following equation was estimated: Inv/Dep = f(7r) where Inv is irnvestment, dep is depreciation and 'r is. profit margin. To see whether one can.find changing patterns as incentives changed. we ran separate cross-section regressions for 1989, 1990, and 1991.

_INV DEP'_
have ever attended school in the richest quintile is 0.90 using both measures, and is 0.56 in the poorest quintile using per capita expenditures (for a gap of 0.34) and is 0.59 in the poorest quintile using the asset index (for a gap of 0.31). The difference for the fraction of illiterate adults is even smaller.

In contrast to these findings of similar results, Lindelow (2006) uses data from a largescale household survey in Mozambique to compare inequalities in health service utilization. He calculates concentration indices derived from expenditures and an asset index for several health behaviors: hospital visits, health center visits, complete course of immunizations children, use of antenatal care, and giving birth in a medical facility. In all cases the concentration indices are statistically significantly different when using the two approaches to measuring welfare. In all cases except health center visits, inequality as measured by the asset index is higher than that measured by expenditures. The author interprets the results as stemming from the fact that urban households tend to rank higher when using the asset based measure. Since urban households also tend to have more access to health facilities, using the asset index tends to strengthen the relationship between economic status and the use of higher level health facilities.

# _b) Aggregation Methods_

Much of the literature has followed Filmer and Pritchett (2001) and applied principal components to estimate the weights used to aggregate indicators into an index, that is to estimate (b1, b2, ... , bk) in equation (1). While principal components analysis is easy to implement, it remains a black box and various analysts have proposed alternative weighting schemes which are arguably better suited to the type of data typically available. The most similar alternative is factor analysis. Factor analysis has a theoretically attractive advantage in that the underlying model allows for a degree of error.<sup>3</sup> Despite relying on different mathematical models and computations, however, principal components and factor analysis yield asset indices that have virtually identical rankings and are therefore treated as the same approach in this paper.

One strand of the literature on aggregation methods focuses on finding a simple and straightforward approach. Two alternatives have been proposed. The first alternative is to use a count variable based on the number of assets owned. When assets have been aggregated in the demographic literature, this is typically the approach that has been taken (as described in the

> 3 For this reason, Sahn and Stifel (2000) favor factor analysis over principal components.

6
Regarding household usage of financial services, an important consideration is whether the identity of the survey respondent affects the accuracy of the information received. The most comprehensive approach to measuring household usage is a full enumeration, in which each member of the household reports on personal use of financial services and individual responses are then aggregated to the household level. Other approaches use an informant to provide information on the usage of financial services by all members of the household, typically either the head of household or a randomly selected adult. Another part of our experiment, therefore, tests whether the household financial usage information provided by the household head or a randomly selected informant is as accurate as that provided by a full enumeration. Because a full enumeration is more time consuming than reliance on an informant, these results will provide an indication of the services for which informants can provide reliable, costeffective information.

While our main objective is to offer information on how question format and the identity of the informant affect the accuracy of financial usage information and its comparability across countries and over time, we also hope to provide information on the sustainability of data gathering efforts by offering evidence on the time costs associated with different questionnaires. Reliance on an informant and the use of institution-based questions cuts down on survey costs, and so evidence on the reliability of those types of questionnaires could help shape future plans. Also, although the FinScope approach focuses on individual usage, the results regarding informants can also speak to the feasibility of including a short module on household use of financial services in those surveys. In this way, the FinScope surveys could be used as a cost-effective vehicle for 7
# **Unequal before the Law: Measuring Legal Gender Disparities across the World**

Sarah Iqbal<sup>a</sup> , Asif Islam<sup>b</sup> , Rita Ramalho<sup>c</sup> , Alena Sakhonchik<sup>d</sup> (DECIG, World Bank, Washington DC, USA) JEL: D63, I39 J16 K10 Keywords: Gender inequality, legal institutions, Women, Business and the Law

> a Women, Business and the Law, DECIG, World Bank Washington DC, USA. Email: siqbal4@worldbank.org b Enterprise Analysis Unit, DECIG, World Bank, Washington DC. Email: aislam@worldbank.org c Doing Business, DECIG, World Bank Washington DC, USA. Email: rramalho@ifc.org

> d Women, Business and the Law, DECIG, World Bank Washington DC, USA. Email: asakhonchik@worldbank.org
increased integration brings the world<sup>economyclosertoanequilibrium with perfectrisk</sup> sharing. In the polar case of perfect risk sharing only aggregate or global risk matters, because risk from local factors can be diversified<sup>away.This meansthat domesticreturns,</sup> wage and interest rates, and consumption<sup>alldependonlyonglobalfactors.Inthe</sup> opposite extreme polar case of fully<sup>segmentedcapitalmarkets,investorscanonlyhold</sup> their own country's assets and must<sup>bear allt he risk fromlocalfactors. Thus, doinestic</sup> prices and quantities depend only on<sup>localfactors,and trivially,inthispolar casethere</sup> are no international capital flows.<sup>Inthemorerealisticintermediatecaseofpartially</sup> segmented capital markets, local and<sup>globalriskfactorsimpact domesticpricesand</sup> quantities as well as the decisions<sup>offoreign(anddomestic)investors.</sup> We build an empirical model of foreign direct investment<sup>thatnests severaltheories</sup> and estimate it using a large cross<sup>sectionandtimeseriesdatasetofdevelopingand</sup> developed countries. Particular<sup>careisputinidentifying andmotivatingtheroleof</sup> global and local factors as drivers<sup>ofdirectinvestment.Globalfactorscauseforeign</sup> direct investment to change across<sup>severalcountries,whereaslocalfactorsarecountry-</sup> specific and have no direct or indirect<sup>impactonforeigndirectinvestmentintoother</sup> countries.<sup>6</sup> To the best of our knowledge<sup>this is thefirstpaper thatstudies therelevance</sup> of global factors as determinants<sup>offoreigndirectinvestment.</sup> We proceed **by** estimating the exposure<sup>ofcountries,andthelevelof directinvest-</sup> ment, to global factors. To do this<sup>weconstruct a measureoft heexplainedvariancein</sup> foreign direct investment that is due<sup>to variationinthe global factors.This wecallthe</sup> globalization measure. To construct<sup>theglobalization measurewemaketheidentifying</sup> assumption that each country is small<sup>relative totheworld economy,whichimpliesthat</sup> local factors may have a global component<sup>themselves,butthereverseisnottrue,i.e.,</sup> there.is no feedback from local<sup>factorstoglobalfactors.Ourempirical approachuses</sup>

> 61n related literature Calvo, Leiderman, and Reinhart **(1993),** Fernandez-Arias **(1996),** and Calvo and Reinhart **(1996)** analyze pull versus<sup>push factorsin totalcapitalflowsemphasizingtheroleof</sup><sup>**US**short</sup> term interest rates. Griffin, Nardari<sup>andStulz(2001)analyze pull versus pushfactorsin portfolio equity</sup> flows. The definitions of pull<sup>and pushfactorsare usuallytied to the geographiclocationof thefactors.</sup> This is not the case in our analysis<sup>so wechoosenottousethesameconcepts for clarity.</sup>

**3**
**Figure 6: Growth rates at the sub-national level in China and India**

<!-- Start of picture text --> China provinces India states (rural) India states (urban)<br>7<br>6<br>5<br>4<br>3<br>2<br>1<br>0<br>0 10 20 30 40 50 60<br>Initial poverty rate (%)<br>(%)<br>Average annual income growth<br><!-- End of picture text -->

**_Source:_** China Statistical Yearbook (various years); Central Survey Organization, Government of India

While these observations from aggregate data are suggestive that such traps might exist, they can hardly be considered conclusive. More rigorous micro evidence of the geographic externalities that underlie such traps can be found in Jalan and Ravallion (2002) and Ravallion (2005), using farm-household panel data for rural China. The geographic attributes conducive to individual prospects of escaping poverty include both publicly-controlled endowments (such as the density of rural roads) and largely private ones (such as the extent of agricultural development locally).

The second dimension of undoubted importance relates to inequalities in human resource development—often linked to credit market failures on the demand side but also reflecting governmental failures in service delivery. We argued above that the rising returns to schooling and increasing dispersion of wages represent ‘good’ inequalities because they reflect freer labor markets with increased incentives for work and skill-acquisition. But naturally, those with relatively little schooling and few assets, or little access to credit are less able to respond these incentives and are less well positioned to take advantage of the new opportunities unleashed by market-oriented reforms. And thus, inequalities in human capital are ‘bad ineqaulities’ in that they have retarded poverty reduction through growth in both countries.<sup>20</sup> Basic schooling was far more widespread in China at the outset of the reform period than in India, and China has achieved close to universal primary education. But inequalities in educational attainment beyond primary school remain, and these have become an increasingly important source of disadvantage because a junior high school education, and in some instances, a senior high school education, has become a de facto prerequisite for accessing non-farm work particularly in urban areas, where wages far exceed the shadow wages in farming. Thus, lack of

> 20 Note that the claim that inequalities in human capital are “bad” is not inconsistent with our earlier point that certain inequalities in outcomes, reflected for instance in increasing wage dispersion, are “good.”  The latter stem from variation in returns that reflect differences in effort. The former arises from differences in endowments that are the results of both supply-side governmental failures and demand-side market failures (especially credit-market failures).

18
Policy Research Working Paper 6965

# **Abstract**

A large fraction of the total supply of paper is produced with technologies that have serious adverse consequences on the environment and cause significant health problems, such as cancer. This paper reports on how Internet adoption affects paper consumption. The study used country-level panel data on Internet penetration and paper consumption disaggregated into various paper categories. The empirical strategy is to use fixed-effect models to study whether countries with faster Internet penetration growth have experienced faster declines in paper consumption. The analysis finds that Internet penetration significantly decreases aggregate paper consumption. Further, the estimates show that Internet growth reduces consumption for the paper categories that are more likely to be affected by the diffusion of the Internet (paper used to print newspapers and books and magazines), whereas the growth of the Internet does not have a statistically significant impact on a paper category unlikely to be affected by the Internet (such as sanitary paper).

This paper is a product of the Sustainable Development Department, South Asia Region. 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 Landres@worldbank.org, azentner@utdallas.edu, and joaquinzentner@hotmail.com.

_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
IEG outcome ratings are meant to assess the extent to which “there were [. . .] shortcomings in the operation’s achievement of its _objectives_ , in its _efficiency_ or in its _relevance_ ” (World Bank 2005). In other words, the outcome rating reflects the extent to which a project reached its (predefined) objectives, and with what degree of efficiency and relevance to broader development goals.

IEG outcome ratings are based on an ordinal six-point scale, ranging from “highly satisfactory” to “highly unsatisfactory.”<sup>28</sup> Figure 4 shows the distribution of PSM and non-PSM project ratings along this scale for the 3,202 projects reviewed.<sup>29</sup> It shows that the majority of projects (~ 68.3 percent) are rated either “satisfactory” or “moderately satisfactory,” whereas only about 25.3 percent are rated either “moderately unsatisfactory” or “unsatisfactory.” The ratings at both extremes of the scale are used rarely—only about 1.9 percent of projects have “highly unsatisfactory” ratings and only about 4.5 percent are rated “highly satisfactory.”

**Figure 4. Distribution of IEG Outcome Ratings for Public Sector and Non-Public-Sector Projects**

<!-- Start of picture text --> Highly Unsatisfactory<br>Unsatisfactory<br>Moderately Unsatisfactory<br>Moderately Satisfactory<br>Satisfactory<br>Highly Satisfactory<br>0 200 400 600 800<br>Number of projects<br>Non Public Sector Public Sector, excluding PSGB-mapped<br>PSGB-mapped Public Sctor<br><!-- End of picture text --> _Source_ : Author’s own compilation, based on World Bank Project Data.

_Note_ : PSM projects mapped to the Public Sector Governance Board (PSGB) are typically “upstream” projects; others are typically “downstream” projects.

> outcome ratings, because they bear less weight within the Bank and are more vaguely defined than the latter. In addition, these ratings are not available for about one-third of the projects in the sample underlying this review.

> 28 The exact ratings, in descending order, are “highly satisfactory,” “satisfactory,” “moderately satisfactory,” “moderately unsatisfactory,” “unsatisfactory,” and “highly unsatisfactory.”

> 29 <mark>As evaluation methods used by the IEG for establishing these ratings vary</mark> , this review systematically employs the “highest-quality” IEG evaluation available for each project. Document-based desk reviews by the IEG (conducted since 1995) are called “Evaluation Summaries” (ES) or “Evaluation Memoranda” (EVM). In addition, “a sample of about 25 percent of projects completed each year are selected by IEG for a more detailed ex-post evaluation” (Denzier, Kaufmann, and Kraay 2011), called “Project Performance Audit Reports” (PPARs). PPAR evaluations are typically conducted several years after project completion and based on field visits. Out of the total project universe of 3,202 projects underlying this review, 597 ratings are based on PPARs, 2,592 on ES or EVMs, and 13 on “Project Completion Reports/Notes” (PCRs/ PCNs), which were used for a few projects until the mid-1990s.

19
Table 5: Program Impacts on School Characteristics by Region, First Follow-Up

||South|North|Dierence|
|---|---|---|---|
|Panel A: School Characteristics||||
|Age of youngest infrastructure|1.135|0.298|0.837|
||(1.500)|(0.928)|(1.764)|
|Number of teachers|-0.975|0.823|-1.798|
||(1.085)|(0.564)|(1.223)|
|Number of students|-29.100|51.321<sup>_∗_</sup>|-80.421|
||(49.317)|(29.009)|(57.216)|
|School has library|0.201<sup>_∗∗_</sup>|0.120<sup>_∗∗_</sup>|0.081|
||(0.086)|(0.049)|(0.099)|
|Number of books in library|15.343<br>|85.753<sup>_∗_</sup><br>|-70.410<br>|
||(80.607)|(44.284)|(91.971)|
|Amount spent on infrastructure|40.337|53.156|-12.819|
||(39.718)|(40.678)|(56.853)|
|Amount spent on electricity/water|-10.421|29.550<sup>_∗_</sup>|-39.972<sup>_∗∗_</sup>|
||(7.867)|(15.735)|(17.592)|
|Amount spent on manuals|27.388<sup>_∗∗_</sup>|23.019<sup>_∗∗_</sup>|4.369|
||(11.112)|(10.507)|(15.293)|
|Amount spent on tutoring|50.230<sup>_∗_</sup>|13.512<sup>_∗_</sup>|36.718|
||(29.365)|(7.731)|(30.366)|
|Amount spent on teacher training|30.487<sup>_∗∗_</sup>|27.856<sup>_∗_</sup>|2.630|
||(13.825)|(14.315)|(19.901)|
|Teacher composition changed in past year|-0.201<sup>_∗∗_</sup>|-0.064|-0.138|
||(0.086)|(0.042)|(0.096)|
|Percent teachers female|-0.031|0.012|-0.043|
||(0.040)|(0.025)|(0.048)|
|Average teacher age|0.273|0.315|-0.041|
||(0.772)|(0.432)|(0.885)|
|Percent of teachers with Baccalaureate|-0.043|-0.008|-0.035|
||(0.049)|(0.025)|(0.056)|
|Average teacher experience|0.224|0.098|0.126|
||(0.583)|(0.396)|(0.705)|
|Panel B: Third Grade Teacher Chara|cteristics|||
|Minutes spent preparing lesson|3.226|1.894|1.332|
||(2.941)|(2.061)|(3.591)|
|Number of manuals|10.475|4.990|5.486|
||(7.647)|(4.980)|(9.125)|
|Number of measuring instruments|0.805<sup>_∗∗_</sup>|-0.039|0.844<sup>_∗∗_</sup>|
||(0.338)|(0.208)|(0.397)|
|Times per day ask for silence|-5.060<sup>_∗∗∗_</sup>|-0.774|-4.287<sup>_∗∗_</sup>|
||(1.847)|(0.699)|(1.975)|
|Times per day punish a student|0.263|-0.242|0.505|
||(0.792)|(0.268)|(0.837)|

Column 3 reports the dierence between the impact of the program in the south and the north. Clustered standard errors in parentheses,<sup>_∗_</sup> _p <_ 0 _._ 10 ,<sup>_∗∗_</sup> _p <_ 0 _._ 05 , _∗∗∗ p <_ 0 _._ 01 . Amounts in CFA.

24