rafmacalaba/datause-encoder-data huggingface dataset:
# **Table A15:  Global Integrity Index  (GII)**

**Data Provider Description**

**Website Data Source Type Respondents Frequency Coverage Public Access Description**

Global Integrity Nongovernmental organization located in Washington, United States, advocating integrity and accountability in government. www.globalintegrity.org Global Integrity Index Expert Assessment Local country experts and peer reviewers recruited by Global Integrity Annually since 2006 Mostly developing country sample Yes The Global Integrity Index uses some 300 indicators to assess the existence and effectiveness of anti-corruption mechanisms that promote public integrity. They typically pair an indication of the "in law'" existence of a particular institutions with an "in practice" assessment of its functioning. We use a simple average of the "in practice" components of each of the indicated GII indicators, in keeping with our practice of relying purely on perceptions-based data in the WGI. Note that in 2007 & 2008 we have carried forward scores for those countries that were covered in previous year but not in current year.

|**Voice and Accountability**|2008|2007|2006|2005|2004|2003|2002|2000|1998|1996|
|---|---|---|---|---|---|---|---|---|---|---|
|Civil Society Organizations|X|X|X|..|..|..|..|..|..|..|
|Media|X|X|X|..|..|..|..|..|..|..|
|Public Access to Information|X|X|X|..|..|..|..|..|..|..|
|Voting & Citizen Participation|X|X|X|..|..|..|..|..|..|..|
|Election Integrity|X|X|X|..|..|..|..|..|..|..|
|Political Financing|X|X|X|..|..|..|..|..|..|..|
|**Political Stability and Absence of Violence**|||||||||||
|NA|..|..|..|..|..|..|..|..|..|..|
|**Government Effectiveness**|||||||||||
|NA|..|..|..|..|..|..|..|..|..|..|
|**Regulatory Quality**|||||||||||
|NA|..|..|..|..|..|..|..|..|..|..|
|**Rule of Law**<br>Executive Accountability|X|X|X|..|..|..|..|..|..|..|
|Judicial Accountability|X|X|X|..|..|..|..|..|..|..|
|Rule of Law|X|X|X|..|..|..|..|..|..|..|
|Law Enforcement<br>**Control of Corruption**|X|X|X|..|..|..|..|..|..|..|
|Anti-Corruption Agency|X|X|X|..|..|..|..|..|..|..|
|**Country coverage**|**79**|**66**|**41**|**..**|**..**|**..**|**..**|**..**|**..**|**..**|
|**Year of Publication**|**2008**|**2007**|**2006**|**..**|**..**|**..**|**..**|**..**|**..**|**..**|

54
Policy Research Working Paper 9098

# **Abstract**

Using a cross-section of more than 29,000 manufacturing firms in 64 developing and emerging countries from the World Bank’s Enterprise Surveys, this paper assesses whether trading firms have a female labor share premium relative to non-trading firms. It focuses on four types of trading firms: exporters, importers, global value chain participants, and foreign firms. The study finds a female labor share premium for all four trading types, controlling for firm output, capital intensity, total factor productivity, and fixed effects. The findings also hold after controlling for differences in relative wages between men and women and excluding traditional export sectors (apparel and electronics) from the sample.

The female labor share premium is much higher for production workers compared with non-production workers, implying that women specialize in low-skill production. In line with these findings, the study finds that the female labor share premium for exporters and global value chain participants is highest in low-tech sectors. And female ownership and management expand the female labor share premium for trading firms. Finally, the results suggest that although average wage rates are lower for firms with higher female labor shares, this negative correlation is smaller for trading firms.

This paper is a product of the Macroeconomics, Trade and Investment Global Practice. 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://www.worldbank.org/prwp. The authors may be contacted at nrocha@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
28

# **Table 3. Tests for validity of instruments, Linear IV model**

||**Tests**|||
|---|---|---|---|
|**Instruments**|**Anderson LM**<br>**(Under-**<br>**identification)**|**Cragg-Donald**<br>**(Weak**<br>**identification)**|**Sargan**<br>**(Over-**<br>**identification)**|
|**International remittances**<br>**(from African or other**<br>**countries) as percent of**<br>**household income**<br>**International migrants (to**<br>**Africa or other countries) as**<br>**percent of population**|Chi^2 (1)<br>12.73|Wald F Stat<br>6.32<br>Stock-Yogo<br>(2005) values<br>10% max IV<br>7.03<br>15% max IV<br>4.58|NA<br>(exactly<br>identified)|
This study focuses on the dissemination and use of _Mirt_ stoves in rural Ethiopia. _Mirt_ (translated as “best”) stoves are a locally developed technology specifically designed to cook _injera,_ the staple bread of Ethiopia. The stove was designed by the Ethiopian Ministry of Water and Energy, is produced from locally available raw materials, and sells at a market price of 100-250 birr (approximately $10.00 USD at the start of the study). Repeated controlled cooking trials done is a laboratory setting suggest the _Mirt_ reduces fuelwood use by 50.7 percent, carbon monoxide emissions by 92.3 percent, and particulate matter by 41 percent compared to traditional open-fire or three-stone technology (Teshome, 2007). Given the estimated fuel savings and a typical _injera_ baking frequency of two to three times per week, the break-even period of two months compares favorably with the stove’s five-year life expectancy.

While GIZ, a German governmental organization, has supported the stoves since 1998, very few households in rural settings have access to the _Mirt_ technology or other improved cookstoves. No improved stoves were present in our study households at baseline, and data from the 2013 Ethiopian Rural Socioeconomic Survey indicate that 98.4 percent of households in rural areas cook exclusively over traditional open-fires (Central Statistics Agency of Ethiopia, 2013).

# **2.2 Initial randomized controlled trial and adoption estimates**

In 2013 we conducted an initial one-year randomized evaluation of _Mirt-_ stove adoption, its fuel savings, and users’ willingness to pay for the product. The baseline of the study surveyed households from 36 communities ( _Gots_ or sub- _Kebeles_ ) randomly selected to represent the forest cover in Amhara, Oromiya, and Southern Nations, Nationalities, and Peoples’ (SNNP) regional states. The three states cover approximately 70 percent of the land area and 80 percent of the population of Ethiopia.

Within each enumeration area, we randomly drew 14 households from a local census, and assigned them into treatment and control groups at the household level within each community. The 10 households in the treatment group received a _Mirt_ stove and were allocated an additional behavioral treatment based on price (free vs. subsidized), incentives based on use (none vs. payment for recorded use), or a social networking intervention (home training only vs. home training plus community training). The control and treatment households were balanced on covariates at baseline, as well as across arms within the treatment group (see Beyene et al., 2015 for detail on the sampling and baseline analysis).<sup>4</sup> Initial adoption of the stoves was assessed from both self-reports by the primary cook within

> 4 Balance implies baseline demographics are unrelated to treatment status. At the household level, a regression of treatment status on baseline characteristics returns a _p_ -value of 0.19 for the joint overall significance of household factors. A similar test at the individual level including age, gender, and parental characteristics returns a _p-_ value of 0.35.

5
we exclude children ( �� �0 ) as they should not contribute to the family income, and that there is no intercept in the formula: where �� is an error term that depends on the household.

For most countries, the �� are all positive as expected and – since there is no intercept – they can be interpreted as the average per capita income brought to the household by each category of people. In some countries �� �0 or �� �0 in the regression, suggesting that people unable to work (category 7) or the elderly (category 8) may reduce the income of other household members, possibly due to caretaking obligations. In these cases, however, we force �� �0 or �� �0 and we re‐estimate the other �� .

The per‐capita revenue in each household _j_ can therefore be expressed as:

# 3. The impact of natural disasters

We model the impact of the following six natural disasters on people’s income: cyclones, storm surges, tsunamis, floods, droughts, earthquakes. The share of people affected by each event is calculated based on data from GAR (for earthquakes, tsunamis, cyclones and storm surges) and GLOFRIS (for floods and drought). The impact on people’s income is the same as for the resilience indicator, for each country. We represent the vulnerability bias between poor and non‐poor households but no exposure bias.

For each natural disaster, we model each event, in each country, independently. For floods we have data for events with return periods between 5 and 1,000 years. For droughts, we have events with return periods of 5, 25, 50 and 100 years. For cyclones, storm surges, earthquakes, and tsunamis, we model events with return periods between 2 and 1,500 years. The assumption that each event can only happen alone and once every year means that we underestimate the real impact.

All events but droughts are modeled as a shock on income for affected households, during the year of the event.

It is first necessary to select affected households. In order to avoid exposure bias, all households in the country are duplicated, i.e. affected households are “created” similar to the existing ones while the weight of existing households is reduced. The weights of affected and unaffected households are adjusted to reflect the share of people affected and to keep the total number of people in the country unchanged. This method avoids a random selection of households, which would require running the scenarios many times. The income of affected households is then changed using the vulnerabilities calculated for the resilience indicator. Those differ for the poorest 20% and the rest of the population.

The impact of droughts is modeled through two channels: a shock on the income of farmers and a shock on food prices for consumers. The vulnerability of poverty reduction to food price hikes has already been demonstrated, for instance in (Ivanic and Martin 2008; Ivanic, Martin, and Zaman 3
**Table 2: Attrition Analysis**

||(1)|(2)|(3)|(4)|
|---|---|---|---|---|
||Completed Midline<br>Survey|Completed Endline<br>Survey|Business Closed at<br>Midline Survey|Business Closed at<br>Endline Survey|
|Assigned Handbook|-0.022|-0.035<br>|0.011|0.005|
||(0.024)|(0.035)<br>|(0.020)|(0.029)|
|Assigned Handbook & Movie|-0.028|-0.008<br>|-0.003|-0.003|
||(0.025)|(0.035)<br>|(0.019)|(0.029)|
|Assigned Handbook & Assistance|-0.021|-0.021<br>|0.009|-0.001|
||(0.024)|(0.035)<br>|(0.020)|(0.028)|
|Assigned All Three|-0.034|-0.033<br>|-0.005|-0.009|
||(0.025)|(0.035)<br>|(0.019)|(0.028)|
|R-squared|0.032|0.043<br>|0.034|0.043|
|N|1301|1301<br>|1301|1301|
|Dependent Variable Mean in Control Group|0.927|0.805<br>|0.054|0.126|
|F-test (p-value): Book = Book & Movie|0.822|0.452<br>|0.499|0.805|
|F-test (p-value): Book = Book & Assistance|0.982|0.702<br>|0.947|0.843|
|F-test(p-value): Book = Book & Movie & Assistance|0.642|0.952<br>|0.444|0.643|

**Notes:** This table shows OLS regression results for the relationship between completing the midline (columns 1) & endline (columns 2) surveys and assignment to different treatment arms. The table also presents the association between business closures at midline (column 3) and endline (column 4) and treatment assignments. All specifications include stratification controls.
# **APPENDIX: VARIABLE DEFINITION AND DATA SOURCES**

This appendix provides a description of the variables and data sources. The political variables were constructed using the following sources: Keesing's Record of World Events (various issues), the Political Handbook of the World (1998), and Szajkowski (1994).

# **TIME VARYING VARIABLES:**

**_AID:_** foreign aid as a percentage of GNP. Source: World Bank, World Development Indicators Database, 1998.

**_COHESION:_** index of government cohesion assuming values from 0 to 2. It is constructed in the following vvay: 2 is assigned to single party governments in parliamentary systems or "not divided" governments in presidential systems; the value 1 is assigned to coalition govenments in parliamentary systems or "divided" governments in presidential systems; and 0 is assigned to minority or caretaker governments. Source: see above.

**_COHESIDEOL:_** interaction between **_COHESION_** and a dummy equal to zero for former Communist governments, and equal to zero otherwise.

**_EBRDINDEX:_** Index of economic liberalization constructed as the sum of four indices: large and small-scale privatization, enterprise restructuring, trade and foreign exchange system, and banking reform. Source: EBRD Transition Report, various issues.

**FREEDOM:** The sum of two seven-points indices for civil liberties and political rights published by Freedom House (previously, by R. Gastil). Since the two indices are highly correlated with each other (with a correlation coefficient is 0.95), they are here summed together to get **FREEDOM,** a variable which assumes values from 2 (no freedom) to 14 (complete freedom). Note that the values of the original Freedom House indices have been reversed. Source: Freedom House.

**_FREESTAB:_** interaction between **_FREEDOM_** and **_GOVCHANGE._** The variable is constructed as follows. First the original (i.e. not reversed) Freedom House index of freedom is multiplied by the nLmber of significant govermment changes. Second, this product is multiplied by (-1), se that higher values of **_FREESTAB_** are associated with countries with more freedom aind fewer significant government changes. Source: see above.

**_GOVCHANGE:_** number of significant government changes, i.e. changes that produce a transfer of power from one leading party to another. A government change is considered significant if the following conditions hold: for a parliamentary system if there is a change in the party of the prime minister and in the coalition of parties supporting the government; for a presidential system, if there is a change in the party of either the prime minister or the president. Also irregular transfers of governments (coups) are recorded as significant government changes. Source: see above.

26
side, the government recruited more teachers,<sup>6</sup> built additional classrooms in existing schools, and new government schools where none existed before. For example, between 2002 and 2011, the number of primary schools in Lesotho increased by about 10 percent, and the primary school pupil-teacher ratio dropped from 48 to 34 pupils per teacher (MOET, 2011). This increase in infrastructure also helped to reduce the average distance to schools, and hence transportation costs. In addition to school infrastructure, the government provides annual capitation grants, furniture and teaching materials to all schools, including church/private schools (Jopo _et al._ , 2011; Lekhetho, 2013). Except for the differences in years of exposure, the supply-side program components benefited everyone at school while fee eliminations and free stationery and textbooks exclusively benefited those covered by FPE.

Figure 3: Changes in Pupil-Teacher Ratio and enrollment <!-- Start of picture text --> Trends in Secondary School Enrolments Rates Trends in Pupil−Teacher Ratios<br>60 60<br>50 50<br>40 40<br>30 30<br>Gross Enrolment Rate Primary school<br>20 Net Enrolment Rate 20 Secondary school<br>2000 2005 2010 2015 2000 2005 2010 2015<br>Year Year<br>Enrolment Rate<br>Pupil Teacher Ratio (PTR)<br><!-- End of picture text --> _Source_ : Own representation using data from various Education Statistics Reports (MOET, 2010, 2011, 2016).

Figure 3 shows changes in secondary school enrollment (demand for education), on the left panel, and pupil-teacher ratio (supply of education), on the right panel, since the introduction of the FPE program. From the left panel of the figure, we can see that, while the secondary school gross enrollment rate was on the increase between 2001 and 2011, the increase was much faster between 2006 and 2010. The figure further shows that, while the net enrollment rate increased through out the period, the gross enrollment rate plateaued between 2011 and 2015, and then began the upward trend. The year 2007 is when the first cohort of FPE children entered secondary school level.

> 6More young and qualified teachers were recruited. Between 2000 and 2007, the proportion of teachers with tertiary qualifications increase from 6 percent to 14 percent, but teacher quality, as measured by teacher performance on SACMEQ reading test, declined (see Moshoeshoe, 2015).

7
Policy Research Working Paper 8483

# **Abstract**

This paper links the literatures on technical assistance and access to finance by examining a Mexican program that provided capacity-building grants to nonbank financial institutions (NBFIs) serving micro, small, and medium enterprises (MSMEs). Using ten years of data from 81 credit unions and a staggered difference-in-differences approach, the analysis shows that the program improved NBFIs’ efficiency, enabling them to obtain more funding from private sources and leading to a 79 percent increase in lending. The findings suggest that technical assistance initiatives can strengthen NBFIs’ ability to expand credit access for underserved MSMEs.

This paper is a product of the Development Research Group, Development Economics. 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://www.worldbank.org/research. The authors may be contacted at mbruhn@worldbank.org, rreddy5@worldbank.org and cruizortega@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
- 19 -

In sum, regulation need not take on the overwhelming task of control of all of a railroad's rates, simply to assure an appropriate choice of prices in those circumscribed arenas requiring regulatory attention. Elsewhere, the forces of competition and the self interest of railroads constitute powerful mechanisms which can do the job efficiently and automatically, using the crucial demand information possessed by the railroads, which is certain to be more complete and more accurate than any demandl ddid a regulatory agency can hope to assemble.

# 2.12 **Contestability and the Scope and Structure of Regulation**

Contestability is an apt benchmark for the railroad industry, while the familiar perfect competition benchmark is neither attainable nor desirable for the railroad industry where economies of scale and scope are substantial. In this industry, attempts to approximate perfect competition may in fact be highly inefficient and contrary to the public interest. In any case, the theory of contestable markets demonstrates quite clearly that neither large size nor fewness of firms necessarily means that markets need function unsatisfactorily. Indeed, a variety of market forms far removed from perfect competition may perform well for the public interest so long as such markets are structurally contestable. If an industry is contestable, then it is best left on its own devices with no government interference, even if it is composed of a very small number of large firms. Impediments to entry and exit, not concentration or scale of operations alone, are a primary source of interference with the public-interest workings of the invisible hand.

Contestability focuses increased attention upon entry barriers and their defining characteristics. High fixed costs and the consequent economies of scale, for example, have traditionally been considered as impediments to entry; contestability analysis shows, however, that they need not permit excessive profits or prices or any of the other manifestations usually associated with market power. It is the presence of sunk costs rather than economies of scale that is of vital importance for market performance.

The theory of contestability offers an improved set of guidelines for appropriate government intervention in the structure and conduct of firms and industries, that is, of the rules to be followed by the regulators in those cases in which their intervention is called for. In addition, it provides economically sound criteria distinguishing between those cases in which intervention by the public sector is warranted and those in which it is not. The theory of contestability is the framework from which was derived the following precepts for railroad regulation already discussed above:

- (i) Permit a private sector railroad to have freedom of pricing and operations on services that face effective competition in the relevant market, whether from other railroads, other transportation modes, other origins, other destinations, or other commodities.