rafmacalaba/datause-encoder-data huggingface dataset:
can construct a variable  = proportion of households in village  residing in settlement . Given this school allocation mechanism, we expect (|)  0 The validity of excluding  from equation (5) depends on the extent of intra-village mobility. If those households with a relatively strong demand for education tend to relocate to settlements already having schools or set up new settlements next to existing schools, then settlement population shares could reflect schooling preferences, rendering them inadmissible as instruments. While the establishment of new settlements is far-fetched in our context given long-standing land ownership patterns, the possibility of intra-village migration in response to school availability cannot be as easily dismissed.<sup>9</sup> However, in our analysis of village census data in the Appendix, we fail to find evidence of increased migration into settlements with newly established primary schools. This result supports our strategy of treating settlement population shares within a village as exogenous with respect to school availability.

To facilitate IV estimation and comparability across estimators we employ the linear probability model with standard errors clustered at the settlement, the lowestlevel sampling unit in the household survey.<sup>10</sup> However, for the final results in the paper we present the corresponding probit estimates as well.

# 4.2 Results

To investigate the endogeneity of school location, as just discussed, the first four specifications in Table 3 exclude distance to school. In the first column, we see that, conditional only on village fixed effects and child age, the presence of a school in the settlement increases girls’ enrollment rate by 18.6 percentage points, which is very close to the conditional gender gap in school enrollment. In other words, girls with a school in their settlement have practically the same enrollment rate as boys.

> 9Andrabi, et al. 2007, follow a related strategy of using information on village population in rural Pakistan to instrument the availability of schools at the village level. They assume that households do not migrate across villages to take advantage of schooling opportunities.

> 10 Specifically, we want to directly compare estimates derived from strategies 1 and 2. However, if we take the discrete choice route, we would have to use a fixed effect logit for strategy 1 (given the large number of settlements relative to children) and a probit IV for strategy 2 (noting that the former estimator does not produce marginal effects). Moreover, as we will see later, probit (or logit) estimation is only possible on a reduced sample, which compromises efficiency relative to a linear probability model.

12
- 13 -

- Tunisia have various restrictions to entry imposed on private cars a trend that has gained momentum in recent years (Jones and Hervik, 1992).

11. The most recent World Bank Urban Transport Policy Study paper notes that even though demand management measures such as road pricing and parking controls have been valued for some time, parking controls are the ones that have mainly been carried out in developing countries (World Bank, 1986, p. 42). While a combination of both regulatory and pricing approaches may ultimately be best suited for a particular transportation system, here we op for the prcing approach for two reasons. First, prcing is more lective and flexible than a regulatory approach in that it provides a better market mechanism, signaling the more efficient trips to be undertaken (Pozdena, Schmidt and Martin, 1990). Second, pricing yields revenues to the community in addition to the users' savings in travel time. These revenue transfers are beneficial to society, in contrast, for instance, to society's loss of travel dme due to the regulaory approach of gating" or planned deJays (May, 1986, p. 116). In particular, traffic restraint measures of banning certain vehicles in some cities mentioned above via the use of auto-free zones at certain places and times may create considerable inconvenience to individual drivers and are tantamoun **t** o settig prohibitively high prces on vehicle usage. Under road picing, on the other hand, motorists stl retain the freedom to choose the combination of mode, - route and time-of-day they best prefer provided, of course, they pay for the privelege of doing so. It appears that adminive simplicity and political acceptability are the principal reasons why tansport planners have traditionally embraced regulatory approaches.

12. Nevertheless, a cursory mention of other traffic management measures that include behavioral incentives such as staggered worldng hours, park-and-ride and vehicle sharing (carpooling and taxi sharing) is in order.<sup>6</sup> Flextime 'contains the seeds of its own destruction.' This measure, once deemed successful, would reduce congeston during the peak hour, thereby creating incentives for people to switch back to their preferred times (recall Downs' Iaw). It seems therefore that moal suasion would not be a sustaining force in the long run. Besides 6 A tdorouh mview of uufic _rot nm_ou_ can be ford **in** May (1986).
Darling-Hammond, L. Wei, R. C. & Andree, A. (2010). _How high-achieving countries develop great teachers_ . Stanford, CA: Stanford Center for Opportunity Policy in Education.

Retrieved from http://www.oup.hu/howhigh_doug.pdf. Accessed December 16<sup>th</sup> , 2016.

Darling-Hammond, L., Wei, R. C., Andree, A., Richardson, N., & Orphanos, S. (2009). _Professional learning in the learning profession._ Washington, DC: National Staff Development Council. Retrieved from http://www.ostrc.org/docs/document_library/ppd/Professionalism/Professional%20Learnin g%20in%20the%20Learning%20Profession.pdf. Accessed December 16<sup>th</sup> , 2016.

Evans, D. K. & Popova, A. 2016. What really works to improve learning in developing countries? An analysis of divergent findings in systematic reviews. _World Bank Research Observer_ . doi:10.1093/wbro/lkw004 Fryer Jr, R. G. (2016). _The production of human capital in developed countries: Evidence from 196 randomized field experiments_ (NBER Working Paper No. 22130). Cambridge, MA: National Bureau of Economic Research.

Gersten, R., Taylor, M. J., Keys, T.D., Rolfhus, E., and Newman-Gonchar, R. (2014). _Summary of research on the effectiveness of math professional development approaches._ Washington, DC: Institute of Education Sciences, National Center for Education Evaluation and Regional Assistance, U.S. Department of Education; and Regional Educational Laboratory Southeast at Florida State University. Retrieved from http://files.eric.ed.gov/fulltext/ED544681.pdf. Accessed December 16<sup>th</sup> , 2016.

Hanushek, E. A. & Rivkin, S.G. (2010). _Using value-added measures of teacher quality_ (CALDER Brief No. 9). National Center for Analysis of Longitudinal Data in Education 23
**Table S12. Relationship between the OECD Better Life Index and SPI scores, 2016-2022**

|**Model 1**|**Model 2**|**Model 3**|**Model 4**|**Model 5**|**Model 6**|
|---|---|---|---|---|---|
|Overall SPI Score<br>0.091***|0.000|0.000||||
|(0.03)|(0.01)|(0.01)||||
|SPI Pillar 1 Score (Data use)|||0.015|-0.004|0.001|
||||(0.03)|(0.00)|(0.00)|
|SPI Pillar 2 Score (Data services)|||0.008|0.002|0.001|
||||(0.01)|(0.00)|(0.00)|
|SPI Pillar 3 Score (Data products)|||-0.040***|0.012*|0.006|
||||(0.01)|(0.01)|(0.01)|
|SPI Pillar 4 Score (Data sources)|||0.039**|0.001|-0.003|
||||(0.02)|(0.01)|(0.01)|
|SPI Pillar 5 Score (Data infrastructure)|||0.051***|-0.008|-0.003|
||||(0.01)|(0.01)|(0.01)|
|Log GDP per capita (constant 2015 US$)||2.265**|||2.120**|
|||(0.86)|||(0.94)|
|Trade (% of GDP)||-0.001|||-0.001|
|||(0.00)|||(0.00)|
|Agriculture, forestry, fishing value added (% of<br>GDP)||0.090*|||0.106*|
|||(0.05)|||(0.05)|
|Manufacturing value added (% of GDP)||-0.050*|||-0.040|
|||(0.03)|||(0.03)|
|School Enrollment, Primary (% gross)||0.030|||0.025|
|||(0.02)|||(0.02)|
|Year 2017|-0.122***|-0.175***||-0.173***|-0.208***|
||(0.03)|(0.04)||(0.05)|(0.05)|
|Year 2018|-0.218**|-0.300***||-0.292***|-0.336***|
||(0.09)|(0.08)||(0.08)|(0.08)|
|Year 2019|-0.218**|-0.340***||-0.256***|-0.354***|
||(0.09)|(0.08)||(0.09)|(0.08)|
|Year 2020|-0.218**|-0.246***||-0.294***|-0.296***|
||(0.10)|(0.08)||(0.09)|(0.08)|
|Year 2021|-0.222*|-0.354***||-0.423***|-0.437***|
||(0.13)|(0.11)||(0.13)|(0.11)|
|Year 2022|-0.222*|-0.413***||-0.424***|-0.492***|
||(0.13)|(0.13)||(0.13)|(0.12)|
|Constant<br>-0.919|||0.126|||
|(2.72)|||(2.80)|||
|Sigmau|1.16|0.6||0.98|0.53|
|_<br>Sigmae|0.23|0.22||0.22|0.22|
|_<br>R2<br>0.127|0.978|0.982|0.432|0.979|0.982|
|Country FE<br>No|Yes|Yes|No|Yes|Yes|
|No of countries<br>43|43|43|43|43|43|
|No of observations<br>287<br>**Note**: * p<0.10, ** p<0.05, *** p<0.01. Standard errors are clus<br>Development Indicators (WDI) and SPI. In cases where data are m<br>the nearest available value.|287<br>tered at the c<br>issing for a p|287<br>ountry level.<br>articular cova|287<br>Data are from<br>riate, the data|287<br>the World<br>are imputed|287<br>Bank's World<br>forward using|

61
reviewed existing practice for collecting asset data through Living Standard Measurement Study surveys and surveys conducted by IFPRI and ICRW.

Our review showed that although most LSMS surveys collect data on the incidence of ownership of housing, land, livestock and consumer durables at the household level, gaps exist in the collection of data on the ownership of farm equipment, non-agricultural business assets and savings/financial assets. Although most surveys collect some data on the value of these assets, a number of different approaches are used, making it difficult to make inter-country comparisons. Almost none ask about decision-making or use and disposal rights over different types of assets.

Far fewer countries with an LSMS survey collect data on the various types of assets at the individual level. Only 7 countries in Latin America and 1 country each in Sub-Saharan Africa, Asia and the Pacific, Europe and Central Asia, and the Middle East and North Africa collect individual data on land ownership. Somewhat more in Latin America (10), Asia and the Pacific (2), and Europe and Central Asia (2) collect individual level ownership information on housing. Far fewer LSMS surveys collect any individual level data on non-farm business assets, financial assets, and physical assets. Although surveys conducted by other institutions (IFPRI and ICRW) collect more complete information on assets at the individual level, even they contain important limitations, missing for instance questions on some categories of assets, or focusing only on women in data collection efforts.

Finally, and perhaps most importantly, we show how existing multi-purpose household surveys can collect more systematic and consistent data on all classes of assets at the individual level. We illustrated our approach with LSMS questionnaires from Guatemala, Vietnam, and Ghana and demonstrated that in most cases it is feasible to add a minimal number of questions (2-3) in order to derive an estimate of the gender asset gap. At the very least, we recommend that survey designers add questions on individual ownership and value of each asset in order to ascertain a better measure of the degree of gender inequality in development opportunities and outcomes. Depending on the policy questions to be answered, additional questions can be added to ascertain the acquisition and depletion of assets, conflict over assets, and knowledge of property rights, which provides important information for poverty reduction, social welfare, and economic growth.

Collecting information on individual level asset ownership is both important and feasible. It will be important to field test the recommendations suggested in Section 5 to provide information to survey designers on the practical issues that arise in data collection in the field. Nonetheless that should not be an excuse for inaction. With political will and modest additional resources, data on the gender distribution of assets can become a reality in the next five years.

42
10 during the first 18 months after the opening of the sector to private operators under a price cap regime.

For ports, Estache et al. (2002b) focus on the effects of the 1993 port reform Mexico over the 1996-99 period. They rely on a stochastic production frontier to show that Mexico's ports achieved 2.8-3.3% average annual efficiency gains since reform under a price cap regime. In that experience, there was no renegotiation.

For water, Estache and Trujillo (2002) also rely on a _Tornqvist_ index to assess the efficiency gains achieved with reform in Argentina and find average annual TFP gains between 3.7% and 6.1% depending on which provinces are included in the sample. In one of the provinces covered by the study, the regulator has been in permanent renegotiation which has resulted in a regulatory regime which is moving slowly but surely towards a cost-plus regime. In another one, the company was returned to the public sector but continued to be in a price cap regime and has managed to continue improving efficiency under the renewed public management.

Overall, this overview of the studies on efficiency available for Latin America suggests that in the vast majority of cases, the reforms, including the introduction of price caps, generated improvements in efficiency. Why would then operators request so frequently renegotiations, in particular in water and sanitation and in transport? Three scenarios could explain the drive for renegotiations or unhappiness of the operators. Under the first scenario, they could not retain the efficiency gains, at least not long enough for the effort to be worth the cost. This implies that these gains might have been captured by another player in the regulatory game. Under a second scenario, the adoption of an incentive-based regulatory regime could have resulted in a cost of capital that was inconsistent with the rate of return generated by the business in spite of the efficiency gains achieved. The need to cut the cost of capital would be what leads them to review some cost categories as part of the renegotiation. Under the third scenario- a combination of the previous two scenarios-operators saw a favorable environment to secure additional benefits, using their effective leverage, through renegotiation of the terms of the contract. These possible explanations are explored next.

# 5. Where **did** all the efficiency gains go?"<sup>6</sup>

> 16 For more details, see Estache, A. (2003)
political system. Sung (2003) shows that if one controls for rule of law, freedom of press, and electoral democracy, then the gender-related variables e.g. percent of women in cabinet, government, and parliaments do no help explain corruption. This result is in line with Treisman (2000) who finds that the length of exposure to democracy helps curb corruption. Mukherjee and Gokcekus (2004) using corruption perceptions of nearly 4,000 public officials in 90 public sector organizations across six countries show that increasing the proportion of women in the public sector reduces corruption only up to the point where women are not the majority. They conclude that corruption in organizations is minimized when genders are equally represented.

Recognizing the obvious problems with cross-country studies Duflo and Topalova (2004) provide further evidence that women care more about public goods, and are less corrupt using village- and household-level data. They take advantage of a policy with built-in randomization, whereby one third of Pradhans’ of Gram Panchayatt (GP)<sup>6</sup> positions are reserved for women to provide a gender difference estimate which is less prone to bias. They show that not only are women Pradhans significantly less likely to be corrupt<sup>7</sup> but also villagers in their GP are less likely to report they had to pay a bribe to access public services including medical services. However, despite these achievements, villagers are more likely to be dissatisfied with women Pradhans and poorly rate them. It is very likely that women Pradhans are aware of such a perception bias against them which may provide them with an incentive to work harder, refrain from and rein in corruption as much as they can. Duflo and Topalova (2004) result may therefore merely pick up the additional effort women exert to fight the negative bias instead of women’s intrinsic higher standard of honesty.

Because of its illegality, corruption is naturally a risky business. Workers who engage in corrupt activities risk being laid off or punished otherwise (including non-pecuniary sanctions) if caught. One should expect the presence of risk to have a strong impact on the

> 6 A Pradhan is the administrative chief of a Gram Panchayatt (GP) which is a collection of 5 to 15 Indian villages with an average total of 10,000 villagers, see Chattopadhyay and Duflo (2004) for more on the GP system and the reservation policy.

> 7 It is not clear from DT’s paper how the corruption of Pradhans is measured.

7
4 It is commonly anticipated that grants are likely to take on increased importance in the revenue structures of local governments over time.<sup>2</sup> Whether this has or will occur depends upon the income, population<sup>and</sup> inflation elasticities of grants vis-a-vis local taxes and user charges. Revenues from taxes which are most commonly reserved for local governments, e.g., property and local business taxes, generally are not found to grow automatically. Instead the structure of these levies often require discretionary changes in tax rates to realize revenue growth.<sup>3</sup> The same is generally true for user charges. Rather than attempt to impose politically unpopular tax increases, local leaders are likely to turn to higher level authorities and urge an increased flow of intergovernmental grants.

Whether or not such please are successful will depend upon political decisions made by the granting government. While there is little doubt that the fiscs of most developing countrieo are strapped for funds, it is also argued that higher level governments commonly retain broader-based, more elastic revenue sources "or themselves. If revenues do, in fact,

> 2 See, for example, Kenneth J. Davey, Financing Regional Government: International Practices and Their Relevance to the Third World (Chichester: John Wiley and Sons, **1983),** p. 131. 3For a review of local revenue elasticity in developing countries, see Larry Schroeder and Elizabeth Dalton, "Local Government Tax Revenue Buoyancy and Stability in Developing Countries," Regional Development Dialogue, Vol. 7 (Autumn 1986), pp. 32-33.

> 4 Davey, Financing Regional Government: International Practices and Their Relevance to the Third World. See, however, Edward B. Prpntilla, "Financing Local and Regional Development: A Preliminary Survey of Comparative Performance of Selected Countries" (Nagoya: United Nations Centre for Regional Development, 1984), p. 52, who reports higher tax buoyancy coefficients for local than for central governments. The results probably reflect tax rate and base policy changes made by local governments rather than inherently more elastic revenue sources used by lower-level jurisdictions.
Crime and Local Inequality in South Africa Gabriel Demombynes and Berk Ozler* Key **Words:** Crime, inequality, South Africa

**JEL Classification Numbers:** D63, D74, R12

* University of California, Berkeley and The World Bank, respectively. The authors would like to thank Statistics South Africa and Dr. Anne Letsebe from the Office of the President with help in the generation of our data set. We are grateful to Jere Behrman, Eliana La Ferrara, Peter Lanjouw, Misha Lokshin, and Martin Ravallion for comments on previous drafts of this paper. Correspondence: gabriel@demog.berkeley.edu and bozler@worldbank.org.
<u>Table 7. Changes in the schools: governance</u>

||Chec|k 1|Chec|k 2|Che|ck 3|
|---|---|---|---|---|---|---|
||Control Mean<br>and SD<br>(1)|Treatment-<br>Control<br>(2)|Control Mean<br>and SD<br>(1)|Treatment-<br>Control<br>(2)|Control Mean<br>and SD<br>(1)|Treatment-<br>Control<br>(2)|
|Presence of BOG|0.94|-0.074|0.96|-0.09|0.93|-0.037|
||(0.24)|(0.06)|(0.21)|(0.06)|(0.25)|(0.06)|
|BOG meets seldom|0.51|-0.027|0.55|-0.038|0.44|0.055|
||(0.51)|(0.13)|(0.50)|(0.13)|(0.50)|(0.13)|
|BOG discusses infrastructure|0.53|0.241*|0.62|0.026|0.71|-0.358**|
||(0.51)|(0.14)|(0.49)|(0.14)|(0.46)|(0.14)|
|BOG discusses teacher motivation|0.38|0.102|0.46|0.022|0.39|0.313**|
||(0.49)|(0.14)|(0.51)|(0.15)|(0.50)|(0.14)|
|Perce of BOG members absent last|0.21|0.027|0.24|0.023|0.18|0.026|
||(0.17)|(0.04)|(0.21)|(0.06)|(0.11)|(0.03)|
|Ownership change|0.02|0.021|0.07|-0.015|0|0.038|
||(0.14)|(0.05)|(0.25)|(0.06)|(0.00)|(0.04)|
|Max. Number of observations|48|96|46|93|46|95|
|Region Fixed effects and baseline controls||Yes||Yes||Yes|

Note. Columns (1) include the mean and SD for each variable for the control group. Columns (2) present the coefficient of the regression of each variable of governance against treatment status. All regression controls for baseline characteristics and fixed effects at the region level.

24
using panel data. Most of these studies have found that higher aid levels reduce tax effort (e.g. Remmer, 2004; Brautigam and Knack, 2004; Devarajan, Rajkumar and Swaroop, 1999; Feyzioglu, Swaroop and Zhu, 1998; Boone, 1996), but a few others find no effect or even a positive effect (e.g. Gupta, 2007). The implications of those studies are unclear, in any event. It would not be surprising, or necessarily bad policy, if governments choose to use at least a small part of aid to stimulate private sector activity by reducing tax rates. It should concern us more, however, if high levels of aid erode the quality of tax systems, because recipient governments then become even more dependent on aid revenue (Azam, Devarajan and O’Connell, 2002). Inefficient tax policies and administration are not as easily reversed as deliberate decisions regarding tax rates. This study’s major contribution to this literature is to introduce a new dependent variable on the quality of tax policy and administration, updated annually by World Bank staff for all of its active borrowers. The following section describes this indicator and other data used in the analysis.

# **3. Data**

The World Bank’s “Country Policy and Institutional Assessments” (CPIA) is conducted annually for approximately 135 developing countries. The CPIA includes 16 questions, but this study uses only question 14, titled “Efficiency of Revenue Mobilization” (henceforth abbreviated ERM). Ratings are determined by Bank staff familiar with each country, but are reviewed and sometimes revised by staff in central departments for consistency across countries and regions. Assessments are on a 1 to 6 scale, including half-point increments. For example, a 3.5 rating would be appropriate 5
# **Governance in the Health Sector: A Strategy for Measuring Determinants and Performance**

by William D. Savedoff* JEL: I18, D01, D23 and H11 Keywords: Governance, Health, Public Sector, Performance, Indicators ________________________________________________________________________

*Senior Partner, Social Insight and Senior Fellow, Center for Global Development. The author gratefully acknowledges Ariel Fiszbein and Sebastian Martinez for commissioning and guiding this work. Conversations with April Harding were essential to developing the framework on authority, information and motivation and bringing the work to completion. Ethan Joselow provided important research assistance by reviewing a wide range of material on governance and indicators. Andrea Feigl prepared a background note on surveys and methods for measuring indicators, contributing a significant part of Section 5. Feedback from World Bank staff at a workshop in September 2009 was also gratefully received. All errors remaining in the work are the author‟s sole responsibility.