rafmacalaba/datause-encoder-data huggingface dataset:
WPS3945 rates for girls rise by a whopping 65% (from .40 to .66) while for boys they rise by 15%(from .81 to .93) The net effect is a very substantial narrowing of the gender gap from .41 to .27. Again, migration not only has a positive impact on enrollment, overall, it generates a substantial catch up effect in enrollment for girls.

We turn next to school retention, conditional on enrollment. The group indicator now identi fi es all children who were 10 or older before fi rst migration and were thus less likely to bene fi t from changes in household resources or preferences towards schooling, particularly for girls. The sample consists of 770 children in 92 villages. 24% of these children are in group I and every age cohort has at least 10% of such children, most have about 20%. Given the smaller sample, we use the more restrictive village fi xed effects speci fi cation only.

School retention rates for girls rise dramatically after migration. While 55% of girls age 10-17 in group I dropped out of school, only 39% of girls who turned 9 after fi rst migration dropped out. In comparison, there is no change in the dropout rate for boys before and after migration. Once again, this closes the gender gap in retention rates substantially.

We also fi nd support for our results on accumulated schooling. Unconditional on enrollment, both boys and girl have signi fi cantly more grades for their age after migration, and once again, girls do a little better, but not signi fi cantly so, gaining 1.4 grades over their siblings in group I while boys gain about a grade. Note that boys remain ahead by a full grade when we restrict comparison to siblings.

Having found further and stronger evidence in support of our earlier results on schooling, we turn now to examining whether there are differences in labor market participation rates and work burden among same sex siblings who are differentiated by their age relative to the year of fi rst migration for the household. We again use age 9 as the cut-off point since school enrollment and labor market participation are, as one might expect, strongly negatively correlated. There are 963 children age 10 and up in 402 migrant households. Almost a third of this sample (31%) had turned age 9 before fi rst migration<sup>21</sup> and every age cohort has at least 15% of such children.

Focusing fi rst on labor market participation, we fi nd that 29% of girls and 24% of boys who had turned 9 or older before fi rst migration, report some labor market activity. As before, post migration, labor market activity drops for both boys and girls (p-value<.00). However, now we get sharply divergent rates of decline for girls and boys. Only 6% of girls who turned 9 after fi rst migration report any work. This represents a 79% decline in

> 21 Overall, there are slighly more boys in this group (33% of boys and 29% of girls are in this sample).

20
35 policies: those affecting vehicle ownership. Beyond this, they can be used as a source of data and modeling strategies for the component of a more comprehensive model. Regarding the ovnership decisions, the model contains a wide range of explanatory variables for examining the effects of policies. The cost-per-mile variable allows modeling of how policy-induced changes in costs affect the structure of vehicle ownership but does not permit discrimination of the effect of different policies on this structure. For instance, by not discriminating between fixed and variable costs of vehicle ownership, the effects of a gas tax and a vehicle registration fee equivalent to it in annualized terms (given baseline VMTs) cannot be distinguished. The "number of commuters" variable, income, and percent urbanized population can be used to help track vehicle fleet changes as a city grows. Changes in "ccupancy rates (ride-sharing) could perhaps be modeled through the commuter variable. The new-old car distinction would allow the age/model year effects on emissions to be estimated with respect to any policy change acceptable by the model.<sup>20</sup>

# Train (1990) (CARS Model). The Wharton-type model is dominated in

theoretical sophistication and breadth of choices by the disaggregate models of auto demand. These models are all based on models of consumer choice, estimating demand from household data. They may explain how many vehicles are owned per person or household, and the type of vehicle to own or purchase (makes and models, new and used). Train's review of these studies reveals 20. A few models (not reviewed here) may be classified as aggregate vehicle demand models based on individual utility functions (CRA, 1980). These models focus only on new vehicle decisions, which is of limited usefulness in a developing country context) and, while they incorporate non-price characteristics, they ignore socio-economic variables.
- 41 -

or total handing over of responsibility and authority for the management of the forest cover to the local community. If this were done, it would make the tas'. of regenerating forest cover around urban areas easier, provided financial incentives were used to encourage community initiatives.

3.12 The Covernment of Niger has decided, under a proposed IDA forestry project (Credit 1226-NR), to promote and support management of the wood stock by local people. A combined wood stock management and firewood supply system will be created through the following steps:

- (a) Zoning of areas around urban centers according to their firewood production potential.

- (b) Development of a system for controlling and monitoring the trade in firewood and assessing fees. Urban check points would be created and rural firewood markets would be sited in areas of high firewood production potential.

- (c) Creation of incentives for local people to manage firewood resources rationally by vesting them with property rights contingent on adequate management, guaranteeing them stable urban market demand for fuelwood produced, and earmarking taxes levied on the trade to finance resource management costs.

3.13 Fiscal details have not yet been finalized, but the approximate firewood fee levels are to be as follows: Table 3.5: PROPOSED NIAMEY REGION FIREWOOD FEE

|Component||FCFA/k|g|
|---|---|---|---|
|Development fee||5||
|Resourcemanagement<br>fee||2||
|Distance-related fee|variable:|0-2||
|Administration<br>fee||1||
||Total:|8-10||
|Source: Niger Hous|ehold Energy|Conservati|on and|
|Substitulon<br>January<br>1988|,<br>Report 0082/8<br>.|8, UNDP/Worl|d<br>Bank,|

The proposed levies are to be phased in gradually, and adjusted annually thereafter following an established formula. The first three fee elements are an attempt to capture at least part of the economic stumpage value. The last element is designed to cover the costs of administration and fee collection.
|Table 1. C<br>LF|ase 1 Resilience Indicator Data|||
|---|---|---|---|
|o<br>Indicators|Relevant Data|Data Source|Content|
||Traffic volume per min under theordinarystate (x�)|Design traffic<br>volume|13.68 pcu/min<br>(19,700 pcu/day)|
||Traffic volume per minwithoutthe project under thedisrupted<br>state (x�)|Simulation|6.84 pcu/min|
|Economic|Travel time between representative OD (Asago – Toyooka)without<br>the project under theordinarystate (t<sup>�����</sup>)|Route search<br>system|50 mins|
|Loss|Travel time between representative OD (Asago– Toyooka)withthe<br>project under theordinarystate (t<sup>����</sup>)|Route search<br>system|42 mins|
||Travel time between representative OD (Asago – Toyooka)without<br>the project under thedisruptedstate (t<sup>�����</sup>)|Route search<br>system|79 mins|
||Travel time between representative OD (Asago – Toyooka)withthe<br>project under thedisruptedstate (t<sup>����</sup>)|Route search<br>system|42 mins|
||Population of coverage area (Tajima Area) (Pop��<br>����)|Population<br>statistics|180,607|
||The percentage ratio of population who can access major hospitals<br>in 30 minuteswithoutthe project under theordinarystate|Route search<br>system|45.1%|
|Saving<br>Lives|The percentage of population who can access major hospitals in<br>30 minuteswiththe project under theordinarystate|Route search<br>system|52.2%|
||The percentage of population who can access major hospitals in<br>30 minuteswithoutthe project under thedisruptedstate|Route search<br>system|35.7%|
||The percentage of population who can access major hospitals in<br>30 minuteswiththe project under thedisruptedstate|Route search<br>system|47.3%|
|Relief|The number of isolated populationwithoutthe project under the<br>disruptedstatePop�<br>�����|0|8162|
|Goods|The number of isolated populationwiththe project under the<br>disruptedstatePop�<br>����|0|8162|

22
(4%)

||(3%)|(4%)|
|---|---|---|
|Pearson chi-squared test|0.00||
|Fisher's exact test|0.00||

_Note_ : The last two rows report the p-value for a test of proportion testing the null hypothesis that the distribution of employers’ responses is equal across both genders.

# _Differences between female and male applicants in response time_

In attempting to determine whether the length of time taken by employers to contact applicants was affected by gender, the study team performed mean comparison tests for each major and occupation. The tests were evaluated under t-tests that presume large samples and Wilcoxon tests that provide a nonparametric perspective, thereby increasing the confidence in the robustness of the results.

Table 6 reveals that there are no gender differences in the time taken by employers to respond to applications. Across all resumes, employers took an average of 21 days to respond to women from the time of the application submission and an average of 23 days to respond to men. However, this difference is not statistically significant. No differences were found by major or occupation, with the exception of computer engineering, where employers took an average of 14 days to respond to females and an average of 24 days to respond to males.

**Table 6 Gender differences in the average number of days employers take to respond**

||Time to res|pond(days)||P-values||
|---|---|---|---|---|---|
|||||Wil||
||Male|Female|Ratio|coxo<br>test|<br>T-test|
|_Major_||||||
|Engineering|23.56|19.16|1.23|0.14|0.26|
|Finance/economics|7.50|16.15|0.46|0.23|0.06|
|IT|25.81|19.56|1.32|0.28|0.17|
|Marketing|25.50|26.06|0.98|0.39|0.91|
|_Occupation_||||||
|Civil engineer|17.83|21.56|0.83|0.67|0.69|
|Computer engineer|23.68|14.25|1.66|0.03|0.03|
|Electrical engineer|26.24|24.07|1.09|0.73|0.83|
|Industrial engineer|29.50|49.50|0.60|1.00|0.74|
|Mechanical engineer|30.00|36.25|0.83|1.00|–|
|Accountant|8.35|19.08|0.44|0.25|0.10|
|Economist|2.00|3.50|0.57|1.00|–|
|Financial officer|5.17|11.92|0.43|0.51|0.18|

29
56

||(0.04)|(0.04)|
|---|---|---|
|EXPRORMS|0.12|0.77|
||(0.33)|(0.77)|
|INFL|-0.03|0.05|
||(0.03)|(0.06)|
|INFLMS|-0.21|0.28|
||(0.18)|(0.34)|
|AVRETAGE|-0.0003|0.001|
||(0.01)|(0.01)|
|AVRETAGMS|0.08|-0.18|
||(0.31)|(0.57)|

Olivia S. Mitchell - Public Pension Governance and Performance
**Table 3.9:  Variation in Test Scores, 1995/97 and 1997/99**

||**Ch**<br>**199**<br>|**ange**<br>**5-97**<br>|**Ch**<br>**199**<br>|**ange**<br>**7-99**<br>|
|---|---|---|---|---|
|**Region**|**Portuguese**<br>**(percent)**|**Mathematics**<br>**(percent)**|**Portuguese**<br>**(percent)**|**Mathematics**<br>**(percent)**|
|**Paraíba**|0.7|1.8|-6.2|-4.2|
|**Northeast**|-0.1|0.9|-11.4|-6.7|
|**Brazil**|-0.9|0.1|-8.4|-5.1|
|**Paraíba**|1.3|0.1|-6.2|-1.0|
|**Northeast**|4.4|3.3|-6.7|-1.7|
|**Brazil**|-2.4|-1.3|-6.8|-1.5|
|**Paraíba**|-0.1|5.9|-3.3|-2.0|
|**Northeast**|3.8|11.0|-8.3|-8.5|
|**Brazil**<br>_Source:_Authors|-2.1<br>calculations based|2.4<br>on SAEB.|-6.1|-2.9|

**_Parent’s education._** Research has shown that parent’s education is an important quality factor in a child’s education and more so the education of the mother than the father, even after controlling for differences in income levels.  Since the large majority of poor children have parents that completed very little formal education, the poor children are at much greater risk of not completing any level of education themselves, for example due to lack of support at home. Research reveals the returns to education are positive and increasing with level of completed education in Brazil. Moreover, for tertiary education they continue raising very rapidly (for example, Blom and Verner 2001). Hence, children from poor families need special support such as tutoring in order not to be left behind children from poor families.

**_Teachers._** While the quality of education as reflected in test scores, repitition rates, agegrade distortion, school attainment, and functional literacy leaves much to be desired, the dedication of the teachers were found to be generally good, though the teachers did not always make the best use of school time (Box 3.1). Improving the quality of education in Paraiba’s decentralized system requires addressing the shortage of teachers skills and lack of formal division between state and municipal functions and removing political influence over staff appointments.

The quality of Paraíba’s teachers, as measured by their own education level varies highly as well as in Brazil as a whole. For example 6 and 3 percent respectively, of the teachers at primary level had themselves been educated below secondary level in 2000. However, it is impressive that 43 percent of the teachers in Paraíba have completed higher education, given the state’s level of economic development, and it is 26 percentage points higher than in the Northeast as a whole (28 percent) and only 6 percentage points lower than the national average of 49 percent. This is particularly impressive given that the difference between teachers’ salary of these that have completed primary only and those that hold a masters degree is only R$25 in 2000.

24
# **Figure 3. Infrastructure Indices by Sector in Egypt (1971-2005)**

## **<u>Infrastructure Indices by Sector</u>**

### **_(a) Components of Transport Index_**

<!-- Start of picture text -->
1.0<br>0.8<br>0.6<br>0.4<br>0.2<br>0.0<br>-0.2<br>-0.4<br>-0.6<br>-0.8<br>-1.0<br>-1.2<br>1971 1974 1977 1980 1983 1986 1989 1992 1995 1998 2001 2004<br>Transport & Telecommunications  Electricity<br><!-- End of picture text -->

<!-- Start of picture text --> 0.0 0.9<br>-0.2 0.8<br>-0.4 0.7<br>-0.6 0.6<br>-0.8 0.5<br>-1.0 0.4<br>-1.2 0.3<br>-1.4 0.2<br>-1.6 0.1<br>-1.8 0<br>1971 1974 1977 1980 1983 1986 1989 1992 1995 1998 2001 2004<br><!-- End of picture text -->

**Roads, sqrt of 1000 workers x surface area (in logs) Paved roads (the ratio to total road length)**

### **_(b) Components of Telecommunications Index_**

### **_(c) Components of Electricity Index_**

<!-- Start of picture text --> 6.0<br>5.5<br>5.0<br>4.5<br>4.0<br>3.5<br>3.0<br>1971 1974 1977 1980 1983 1986 1989 1992 1995 1998 2001 2004<br>Main lines per 1,000 workers (in logs)<br><!-- End of picture text --> <!-- Start of picture text --> 0.0 18.0<br>16.0<br>-0.2<br>14.0<br>-0.4<br>12.0<br>-0.6 10.0<br>-0.8 8.0<br>6.0<br>-1.0<br>4.0<br>-1.2<br>2.0<br>-1.4 0.0<br>1971 1974 1977 1980 1983 1986 1989 1992 1995 1998 2001 2004<br>EGC per 1,000 workers (in logs) Power loss (% of output)<br><!-- End of picture text --> 24
think that most parents can be trusted?" In addition to directly asking teachers and parents about the trustworthiness of each other, we also construct a measure of responsibility. At the core of parent-teacher relationships is the shared responsibility of educating children. Thus, we hypothesize that parent and teacher trustworthiness are likely to be closely related to how well they are perceived to be carrying out this shared responsibility of supporting children’s learning. We construct a responsibility index separately for teachers and parents using the first principal components from principal component analyses of several survey items. For parental views of teacher responsibility, we use the following survey items: (i) teachers are available for meetings, (ii) teachers support extra-curricular activities, (iii) teachers handle conflict resolution between students, (iv) teachers provide additional classes for struggling students, (v) teachers care about student achievement, and (vi) teachers provide feedback on student assignments. For teacher views of parent responsibility, we use the following survey items: (i) parents are available for meetings, (ii) parents help children with school work, (iii) parents make sure that children are completing school assignments, and (iv) parents support extra-curricular activities. For this exploratory analysis, we re-estimate equation (1) using trust and job responsibility as the outcome of interest. The results are presented in columns (1) and (3) in Table 7.

In the double grant experiment, parents’ view of teacher trustworthiness significantly declined by 9.6 percentage points from a high baseline level of 91.9%. This negative impact on teacher trustworthiness persists into years 2 and 3 of the double grant intervention. We observe a similarly sharp decrease in teachers’ view of parent trustworthiness, between 8.5 and 10.0 percentage points. These declines in trustworthiness seems to track with perceptions of responsibility, as parents are significantly less likely to believe that teachers are carrying out their duties to support their children’s education. Moreover, the diminished trust between parents and teachers may explain why the temporary increase in year 1 for parental involvement in school decision-making was not sustained in subsequent years. While speculative, the double grant intervention’s negative effect on trust suggests that parental involvement interventions can backfire if institutional rules are unclear about the expectations of parents and teachers as parents increase their involvement in schools.

In the information experiment, parents’ trust towards teachers significantly improved, which is consistent with the theoretical prediction above. Parents in treatment schools are 14.8 percentage points more likely to believe that most teachers can be trusted, from a baseline level of 81.2%.

20
organizations such as the Association of Community Organizations for Reform Now (ACORN). These organizations realized that they could be much more successful in pressuring banks to expand their sub-prime loans, if the banks were able to sell the mortgages on the secondary market.<sup>9</sup> In addition, Fannie and Freddie, through their PACs during the 1989 to 2008 period, cumulatively contributed over $3 million to the campaigns of Congressional supporters (and their employees contributed an additional $1.8 million).<sup>10</sup> In the end, the legislation that was passed in the early 1990s provided for the GSEs to lend to low and moderate income lenders, and in return their regulator lacked the authority routinely given bank regulators.<sup>11</sup> As the problems with the GSEs rose and became evident over the years, the bargain that was struck, that Congress would not regulate seriously and the GSEs would undertake an affordable housing objective (which was implemented through lower mortgage standards), continued until the GSE bankruptcies in September 2008 (and maybe beyond since the fundamental political failure regarding the GSEs has not been resolved).

Although the GSEs were willing accomplices, in the 1990s, HUD Secretary Mario Cuomo used the implicit bargain of the GSEs to add pressure on them to take on a higher share of its mortgages to low and middle income borrowers. As early as 1999, astute journalists warned that this meant that banks had to loan to progressively riskier borrowers and provide riskier mortgages, increasing the risks to Fannie and Freddie.<sup>12</sup> In 2003 and 2004, the GSEs were caught in Enron style accounting scandals that eventually led to the resignation of Fannie CEO Franklin Raines, and there were calls for tougher

> 9 Community organizations such as ACORN, NACA and the  Greenlining Institute had much at stake in advancing the affordable housing mandate of the GSEs and in putting teeth into enforcement of the Community Reinvestment Act (as discussed below). They successfully negotiated agreements with various banks to provide tens of billions in mortgages to underserved communities, typically serving as mortgage servicers for these agreements.  In addition, ACORN received $40 million in grants from various banks for dubious “counseling” services. See US House of Representatives (2010),  Capital Research Corporation (2009) and the Washington Examiner, April 12, 2010, available at: http://www.washingtonexaminer.com/opinion/columns/Uncle-Sam-opens-the-bank-vault-to-activists90655894.html.

> 10 Center for Responsive Politics (2008) calculations based on Federal Election Commission data. A complete list of all 354 active members of Congress who received contributions (and the amounts they received) is available in the article.

11 The 1992 Federal Housing Enterprises Financial Safety and Soundness Act, also known as the GSE Act. For further details of this act see: http://online.wsj.com/article/SB10001424052748703298004574459763052141456.html

> 12 See articles by Steven Holmes in the New York _Times_ , September 30, 1999 and Ronald Brownstein in the Los Angeles _Times_ , May 31, 1999.
# Policy Research Working Paper Series

|Tite|Author|Date|Contact<br>for paper|
|---|---|---|---|
|WPS1006 Preparing Muftiyear Railway<br>Investment Plans: A Market-Oriente<br>Approach|Jorge M. Rebelo<br>d|October 1992|A. Turner<br>30933|
|WPS1007 Global Estimates and Projections<br>of Mortality by Cause, 1970-2015|Rodolfo A. Bulatao<br>Patience W. Stephens|October 1992|0. Nadora<br>31091|
|WPS1 008 Do the Poor Insure? A Synthesis of<br>the Literature on Risk and<br>Consumption in Developing Countrie|Harold Alderman<br>Christina H. Paxson<br>s|October 1992|C. Spooner<br>32116|
|WPS1009 Labor and Women's Nutrition:<br>A Study of Energy Expenditure,<br>Fertility, and Nutritional Status in Gha|Paul A. Higgins<br>Harold Alderman<br>na|October 1992|C. Spooner<br>32116|
|WPS1010 Competition and Efficiency in<br>Hungarian Banking|Dimitri Vittas<br>Craig Neal|October 1992|W. Pitayatonakarn<br>37664|
|WPS1 011 How Tax Incentives Affect Decisions<br>to Invest in Developing Countries|Robin Boadway<br>Anwar Shah|November 1992|C. Jones<br>37754|
|WPS1012 The Brady Plan, the 1989 Mexican<br>Debt Reduction Agreement, and Bank<br>Stock Returns in the United States<br>and Japan|Haluk Unal<br>Asli Demirguc-Kunt<br>Kwok-Wai Leung|November 1992|W. Patrawimolpon<br>37664|
|WPS1 013 The lmpact of Mexico's Retr;.ining<br>Program on Employment and Wages|Ana Revenga<br>Michelle Riboud<br>Hong Tan|November 1992|D. Young<br>30932|
|WPs1014 Ethnicity, Education, and Earnings<br>in Bolivia and Guatemala|George Psacharopoulos|November 1992|L. Longo<br>39244|
|WPS1015 Benefit Incidence Analysis in<br>Developing Countries|Thomas M. Selden<br>Michael J. Wasylenko|November 1992|C. Jones<br>37754|
|WPS1 016 Europe and Central Asia Region,<br>Middle East and North Africa Region<br>Population Projections, 1992-93<br>Edition|My T. Vu<br>Eduard Bos<br>Ann Levin|November 1992|0. Nadora<br>31091|
|WPS1 017 Rural Poverty, Migration, and the<br>Environment in Developing Countries:<br>Three Case Studies|Richard E. Bilsborrow<br>|November 1992|WDR<br>31091|
|WPS1018 Tariff and Tax Reform: Do World<br> <br>Bank Recommendations<br>Integrate<br>Revenue and Protection Objectives?|Anand Rajaram|November 1992|P. Pender<br>37851|