rafmacalaba/datause-encoder-data huggingface dataset:
In January 2018, EMDE output was expected to grow by 4.6 percent in 2019. By the January 2019 forecast, this was revised down to 4.2 percent and further to 3.9 percent in June 2019. Similarly, ten-year-ahead EMDE growth forecasts have been repeatedly downgraded. This pattern of downward revisions to both short- and long-term EMDE growth projections points to both cyclical and structural factors weighing on EMDE growth.

Since 2016, there have been consistent downward revisions to growth projections for all EMDE regions, except East Asia and Pacific (EAP, Figure 1).<sup>4</sup> Regionally, the largest revisions in this period have been to projections for LAC, with growth downgrades averaging 1.2 percentage points, amid falling commodity prices and recessions in some of LAC’s largest economies in 2016 (World Bank 2019a). The second and third largest regional revisions since 2016 have been to growth in MNA and SSA, averaging 0.7 percentage point in both cases, with commodity-intensive countries suffering the largest downgrades.

In MNA, this reflected weak oil sector output and adjustments to lower oil prices, and more recently the intensification of U.S. sanctions on Iran (World Bank 2019a). In SSA, oil exporters were also affected by the oil price fall while the region’s largest economies struggled with idiosyncratic challenges. By contrast, downgrades since 2016 have been modest for South Asia (SAR), where growth has remained robust at or above its longer-term average rate since 1990 (World Bank 2019a). The absence of growth surprises in EAP reflects the steady slowing and rebalancing of growth in China, actively managed and broadly in line with official growth projections, and resilience of growth in Indonesia.

# 2.2 Short-term outlook for EMDEs

EMDE growth is expected to stabilize at 4.4 percent over from 2019-2021, marginally up from the average for 2016-18, but well below the above-6 percent during 2000-08 (World Bank 2019a; Figure 2). This outlook is premised on earlier financial pressures and policy uncertainties that have affected some large EMDEs dissipating, and global financing conditions remaining benign.

Many large commodity-exporting EMDEs face the lingering effects of recent financial stress and idiosyncratic headwinds (such as sanctions), postponing the expected recovery. As these fade, commodity-exporting EMDEs are expected to grow by 2.7 percent in 2019-21, significantly better than rates achieved in the 2016-18 but still more than 1 percentage point below the average since 2000. In commodity-importing economies excluding China, growth is expected to slow to 4.7 percent in 2019-2021, only slightly below the pre-crisis average although firmly below the average of the past three years (5.1 percent during 2016-18). Weakness among commodity importers has been most visible in Europe and Central Asia (ECA) where financial stress has undermined growth in Turkey, and binding domestic capacity constraints have particularly affected countries in Central Europe.

LICs that export energy and metals commodities tend to have more volatile growth.

> 4 Based on data from the World Bank’s Global Economic Prospects.
29 Table 6. 0Omraphic Trends In World Bank Regions and Country Deprtments

||Popula|tion (milli|ons)|Stationary|Year||
|---|---|---|---|---|---|---|
|||||population|ihen||
|Regionard<br>country<br>department|1965|2100|Station-<br>ary|asof<br>1965<br>population|popula-<br>tion<br>dwbles|Year<br>when<br>NRR-i|
|Wortd total|4,843|10,560|10,837|224|2052|2045|
|Borrowers and non-borrowers|||||||
|Stb*Saharan Africa|457|2,168|2,264|474|2009|2045|
|AsiawidOceania|2.573|4,997|5,115|199|(a)|2035|
|Europe, Middle East,<br>ad North Africa|1,147|2,190|2.233|203|2160|2045|
|Amrica|667|1,205|1.224|181|(a)|2030|
|Borrowers only|||||||
|Africa Region|415|2.035|2,125|513|2008|2040|
|' Occidental and Central|40|i87|195|496|2008|2040|
|2 Eastem|106|520|544|515|2008|2040|
|3 South-Central and|||||||
|Indian Ocean|52|251|262|500|2009|2040|
|4 Westem|119|593|619|519|2007|2040|
|5 Sahelian|36|173|182|504|2011|2040|
|6 Southern|62|310|323|525|2008|2040|
|Asia Region|2.382|4,756|4,843|203|2107|2035|
|IOtherSouth|134|423|439|327|2019|2035|
|2 Southeast|274|626|641|235|2036|2035|
|3China|1,040|1,695|1,695|163|(a)|2000|
|4 Irdia|765|1,655|1,698|222|2048|2010|
|S Indonesia and Pacific|168|358|370|220|2052|2035|
|EimN<br>Reion|476|1,425|1,466|308|2022|2045|
|1 Pakistan and Turkey|147|519|535|365|2016|2045|
|2 North Africa|55|172|<br>177|322,|2016|2025|
|3 Niddle East|170|609|629|370|2013|2040|
|4Europe|105|125|<br>125|120|(a)|2020|
|LAC Region|388|879|898|232|2038|2025|
|1 Brazil|136|287|<br>306|226|2044|2015|
|2 Central America|104|263|<br>267|258|2027|2025|
|3 Caribbean and Other|70|159|<br>165|234|20-':|2030|
|4 Tarperate and Tropical|78|158|<br>160|205|2087|2015|

Note: World Bank regions and country departments are defined In Table 14.

(a) Population wilt not double with projected rates.
K scores with a mean of 52.8 (p-value 0.72). Thus, not only is there no evidence of selective attrition on baseline management practices, neither is there evidence of endline selective attrition based on first follow-up management practices. This strongly suggests that the assumption that it was all the best-managed firms in the control group that differentially attrited is very unlikely to hold, so that the Lee lower bound is unlikely to be applicable.

**<mark>Table A6.2: Lee Bounds of Impact on Anexo K Score</mark>**

||Individual Treatment Effect|GroupTreatment Effect|
|---|---|---|
|_Impact during intervention_|||
|Lee lower bound|6.303**|9.368***|
||(2.723)|(3.290)|
|Lee Upper bound|9.746***|16.610***|
||(3.065)|(2.851)|
|_Impact post‐intervention_|||
|Lee lower bound|1.076|4.784|
||(3.628)|(3.218)|
|Lee Upper bound|13.993***|13.913***|
||(3.011)|(3.158)|
|Sample Size|106|106|
|Proportion trimmed|||
|for during intervention|8.7%|16.7%|
|forpost‐intervention<br>Notes: robust standard error|35.0%<br>s in parentheses. *, **, and **|27.8%<br>* denote significance|

<mark>Notes: robust standard errors in parentheses. *, **, and *** denote significance at the 10, 5, and 1 percent levels respectively.</mark>

# : **Appendix 7 Impacts on World Management Survey and MOPS Management Measures**

## **WMS 2013 Data Collection**

We commissioned the London School of Economics (LSE) team responsible for the Bloom and Van Reenen (2007) World Management Surveys (WMS) to apply their methodology to a random sample of 180 firms representative of the Colombian manufacturing sector, as well as to a subsample of 77 firms in our sample, focusing on firms with 40 or more employees (Table A6.1).

Interviews were done by phone with a manager with thorough knowledge of the production process, typically the plant manager or production manager. The WMS interview is structured as a guided discussion, and is designed to be answered by a manager with thorough knowledge of the production process, typically the production or plant manager. Such discussion lasts between one hour and one hour and a half, and covers the 18 questions related to operations, monitoring, targeting, and people management. The interviewer guides the interviewee by means of open questions, letting him/her speak freely but making sure to have the necessary objective information to score each of the 18 topics using the provided scoring grid. Each of the 18 topics receives a score between 1 (no modern practice is implemented) and 5 (best practice).

60
_H_<sup>_G_</sup> = _G_<sup>_H_</sup> _._ (20)

# **6.  Market-Clearing Condition and Population Growth**

The asset-market clearing condition requires equality between savings and investment, or equivalently, that tomorrow's private capital stock be equal to today’s savings by adult workers. Given that _s_ is savings per family, and that the number of families is ( _N_<sup>_m_</sup> + _N_<sup>_f_</sup> )/2, we have The number of adults alive in period _t_ is itself given by that is, the number of children born in period _t_ -1, _n_ ( _t_ -1) _N_ ( _t_ -1), who survived to period _t_ .

Thus, there are two concepts of gender inequality in the model: a _time allocation gap_ to market work between adult men and women, measured by the ratio 1/ε<sup>_f,W_</sup> ; and a _core wage gap_ in the market place, as measured by the parameter _b_ . The first gap is endogenous and corresponds to the _(market) participation gap_ in de la Croix and Vander Donckt (2010), for instance. However, because ε<sup>_f,W_</sup> is determined residually in our setting, it also reflects gender bias in the allocation of time to _home activities_ —household chores and child rearing. Both measures can be viewed as pertaining to the concept of “economic participation and opportunity” for women incorporated in the Global Gender Gap Indicator proposed by the World Economic Forum (2010).<sup>31</sup> Most importantly, in our analysis, the time allocation gap is influenced by access to infrastructure, which affects the efficiency of time allocated to home production and child rearing.

# **IV. WOMEN’S TIME ALLOCATION AND GROWTH: EQUILIBRIUM**

An equilibrium of the economy requires the existence of a time sequence of prices, consumption in adulthood and in old age, physical capital stocks and female health status such that, given initial capital stocks _K_<sup>_P_</sup> (0) and _K_<sup>_I_</sup> (0) and initial health statuses _h_<sup>_C_</sup> (0) and _h_<sup>_f_</sup> (0), individuals maximize utility, firms maximize profits, markets clear, and the government budget is balanced. Individual and aggregate quantities must also coincide, so that _K_<sup>_P_</sup> = _K_<sup>_P,T_</sup> and _a_<sup>_f_</sup> = _A_<sup>_f_</sup> . In addition, in a balanced growth equilibrium, consumption and capital (both public and private), and output grow at the constant, endogenous rate γ, the rate of return on private capital is constant, and health statuses of children and adult females are either constant

> 31In the Global Gender Gap report (2010), the size of the gender gap is measured based on four dimensions of inequality between men and women: economic participation and opportunity (including salaries, participation levels, and access to high-skilled employment); education attainment (including access to basic and higher-level education); political empowerment (including representation in decision-making structures); and health and survival (including life expectancy and sex ratio).

24
# **c) Share of labor force in local wage labor by year, age and gender**

<!-- Start of picture text --> 1997 2000<br>2004 2006<br>16 20 25 30 35 40 45 50 55 60 65 70 75 16 20 25 30 35 40 45 50 55 60 65 70 75<br>Age<br> Men Women<br>.5<br>.4<br>.3<br>.2<br>.1<br>0<br>.5<br>.4<br>.3<br>Working as a Wage Labor .2<br>.1<br>0<br><!-- End of picture text -->

# **d) Share of labor force in family business by year and gender**

<!-- Start of picture text --> 1997 2000<br>2004 2006<br>16 20 25 30 35 40 45 50 55 60 65 70 75 16 20 25 30 35 40 45 50 55 60 65 70 75<br>Age<br> Men Women<br>.3<br>.2<br>.1<br>0<br>.3<br>.2<br>Working in Family Business<br>.1<br>0<br><!-- End of picture text --> 26
# **3 Measuring the incidence of graft**

We have presented evidence showing that using perceptions about the severity of corruption is an inaccurate gauge of the true extent of corruption. Since it is safe to say that corrupt practices have serious economic consequences and, hence, that the study of corruption based on reliable data merits careful attention, in this section we propose a measure of graft that is based on actual firm encounters with dishonest officials. To that end, we take advantage of detailed survey data on approximately 10,000 firms in 33 African and Latin American countries to calculate what we call a _Graft Index of Firm Transactions_ (GIFT). The data come from the World Bank Group’s _Enterprise Surveys_ , which collect information on whether businesses had to provide a bribe to complete a series of six different transactions: requests for an electrical connection, a water connection, telephone service, an import license, a construction-related permit, or an operating license.

## **3.1 How is the** **_Graft Index of Firm Transactions_ calculated?**

Formally, the index is defined as the sample probability that a firm in country _k_ will be asked to provide a bribe, conditional on the firm undertaking one of the six aforementioned transactions. Mathematically, (1) is the GIFT for country _k_ , where the sub-indices and _i j_ represent firm _i_ and transaction type _j_ , respectively. The binary variable _xijk_ is equal to 1 if firm was requested to make an informal payment _i_ when undertaking transaction type _j_ in country _k_ and 0 otherwise. The denominator is the sum of all transactions of type _j_ in country _k_ that occurred between the time the survey took place and up to two years prior.

In words, the _Graft Index of Firm Transactions_ is the proportion of instances in which firms were either expected or requested to pay a gift or informal payment over the number of total solicitations for public services, licenses or permits for that country. We emphasize that the index is based on the respondent’s direct experience with corruption. As such, this index does not have the disadvantages that are present in perceptions indexes. In addition, the index can be compared across countries. All firms
effort is critical and should inform the mix of incentive mechanisms used in the school system. Ignoring the differential impacts of, say, greater teacher autonomy and monitoring mechanisms may produce the undesirable (and unanticipated) effect of lowering teacher effort.<sup>36</sup> Moreover, further differentiation of incentives can reveal more. For example, we find that considering the issues that PTAs focus on (such as if they pay more attention to “deeper” issues such as instructional methods show that teachers may prefer to spend more hours on after-school activities that are less visible to monitors but might produce better teaching.

Promising avenues for future research include more investigation into the strategic behavior of teachers under different incentive mechanisms. To do this, better measures of time spent in activities that are not directly observable to PTAs and the principal but have positive impact on student learning, such as hours spent preparing lessons, are needed. Moreover, because of measurement issues related to self-reported effort, direct observation methods akin to those used in time-allocation studies—although these methods are admittedly costly to implement—would help strengthen the quality of future studies. Lastly, following the results chain to the desired end of more learning, the impact of teacher effort on student performance is undoubtedly multifaceted and may require learning measures that do not rely on single performance test scores (Koretz, 2002).

> 36 See, for example, Benabou and Tirole (2006) for a literature review and evidence.

30
|Traditional*Achievement|||||||||0.006||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
||||||||||(0.50)||||
|Traditional*Power motiva,||||||||||-0.011|||
|||||||||||(-1.63)|||
|Traditional*Organized|||||||||||0.007||
||||||||||||(0.80)||
|Traditional*Optimism||||||||||||-0.016|
|||||||||||||(-1.11)|
|Constant|7.223***|4.722***|6.646***|4.385**|5.987***|7.356***|5.265***|6.137***|5.177**|3.183**|5.725***|3.970|
||(26.14)|(3.99)|(4.54)|(2.41)|(3.87)|(4.79)|(2.87)|(4.16)|(2.36)|(2.34)|(2.84)|(1.50)|
|Controls included|NO|YES|YES|YES|YES|YES|YES|YES|YES|YES|YES|YES|
|R<sup>2</sup>|0.014|0.277|0.321|0.279|0.283|0.292|0.278|0.286|0.281|0.290|0.281|0.311|
|N|276|276|276|276|276|276|276|276|276|276|276|276|

t statistics in parentheses: * p<0.10, ** p<0.05, *** p<0.010; errors clustered at cluster level 43
points out Richard Cooper, whose chapter explains that over US history trade policy has had considerable importance for and influence on major foreign policy questions. Creating a national identity was, in our early histcry, an important object of trade policy, e.g., trade boycotts during colonial days to protest the Stamp Act and the Townsend Act. Cooper sees trade policy from about 1820 to WWII as aimed chief .y at trade objectives -- to protect US manufacturing and at the same time promote US exports. After WWII came liberalization under the GATT, liberalization motivated more by a desire to preserve peace and to assure international stability through economic means than by an appreciation of the economic gains from trade.

Several chapters review historical attempts by the US to use trade embargoes to influence the economic, political or military behavior of other countries. Examples are the 1965-78 trade embargo against Rhodesia, the trade embargo to protest the Stamp Act imposed on the American colonies by Great Britain, the Jackson-Vanik amendment of 1974, seeking increased Jewish emigration from the Soviet Union, various trade and financial measures against Iran in an attempt to gaOn release of American hostages. Such sanctions have had diverse and zometimes imprecise objectives, and there are several disagreements among authors as to whether or not a particular sanction achieved its objective.

Much of this discussion draws on information from Gary Hufbauer and Jeffrey Schott's book on US export sanctions and ends up more or less with their conclusion -- in about 1 case in 3 sanctions were successful in achieving their objective. Is this a good or a bad score? Stephen Krasner's evaluation is, "Since economic sanctions are likely to be used only when other policy instruments fail, this level of success is indeed surprising." (p. 329)
Policy Research Working Paper 8303

# **Abstract**

The reversal of the gender gap in educational attainment is becoming a global phenomenon. Its drivers, however, are not well understood and remain largely untested empirically. This paper develops a unified conceptual framework that allows to formulate and test two main hypotheses for the reversal. It introduces the tail hypothesis, which builds on the lower dispersion of scholastic performance among females observed globally. It also formalizes the mean hypothesis, which states that females’ average scholastic performance and returns to education have increased over time relative to males’. The paper theoretically shows that both hypotheses can explain the reversal in our framework. The parameters of the two hypotheses derived from the model are then estimated using educational attainment data from 1950 to 2010 in more than 100 countries. The authors find that both hypotheses strongly predict the gender gap dynamics in educational attainment when estimated separately. When jointly estimated, accounting for the tail hypothesis significantly increases the model’s predictive power. The contribution of the tail hypothesis to the gender gap reversal, while the mean hypothesis appears to prevail in high-income countries.

This paper is a product of the Social Protection and Labor 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 lbossavie@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
Estimating the Social Profitability of India’s Rural Roads Program: A Bumpy Ride Clive Bell<sup>_∗_</sup> First version: August, 2010 This version: August, 2012

**Abstract**

India’s rural roads program, _Pradhan Mantri Gram Sadak Yojana_ , aims to draw villagers into the mainstream by improving not only their terms of trade, but also their educational attainments and health. Treating each all-weather feeder road as an isolated element within the larger network, and using shadow prices to value the main components of costs and benefits, this paper demonstrates that further investments in the program are, with high probability, socially profitable, especially in poorer and more densely settled regions. Taking the entire set of new individual roads together, qualitative arguments suggest that their external and spillover effects on the system as a whole probably generate some net additional benefits, but of very uncertain magnitude.

Keywords: Rural roads, social cost-benefit analysis, India JEL Classification: D61, H54, O18, O22 Sector Board: Transport

> _∗_ University of Heidelberg, INF 330, D-69120 Heidelberg, Germany. clive.bell@urz.uni-heidelberg.de Earlier versions of this paper were presented at the Delhi School of Economics, the Institute of Economic Growth, the Indian Statistical Institute (Delhi), the Planning Commission, the World Bank (Delhi Resident Mission) and the Christian Michelsen Institute, Bergen. I am much indebted to the participants for valuable comments, and to Simon Ellis, Ashok Kumar, Abhiroop Mukhopadhyay, Indira Rajaraman and Roberto Zagha for extensive and insightful discussions during the course of the work, while absolving them all of any responsibility for any errors that remain. The previous version of the paper formed part of the documentation for a World Bank loan proposal. The views expressed herein are not, however, necessarily those of the World Bank or its Board.

1