rafmacalaba/datause-encoder-data huggingface dataset:
data sources: household surveys (all Rounds), school surveys (Rounds 2 & 3), school ledgers (Round 3), independently developed achievement tests (Round 3), and qualitative interviews (Round 3).

The annual _household survey_ consisted of a multi-topic questionnaire administered to the households in which the sampled respondents resided. It consisted of two parts: one that is administered to the head of the household and another to the core respondent, i.e. the sampled girl from our target population. The former collected information on the household roster, dwelling characteristics, household assets and durables, shocks and consumption. The survey administered to the core respondent provides detailed information about her family background, schooling status, health, dating patterns, sexual behavior, fertility, and marriage.

During Round 2, we also conducted a _school survey_ that involved visiting every school attended by any of the core respondents (according to self-reported data from the household survey) in our study sample in 2008. This was repeated in Round 3 for a randomly selected sub-sample of core respondents reporting to be in enrolled in school in 2009.<sup>26</sup> Using Round 2 (Round 3) household survey data, we collected the name of the school, the grade, and the teacher’s name for the core respondent if she reported being enrolled in school at any point during the 2008 (2009) school year. These teachers were then located at the named schools and interviewed about each respondent’s schooling status (term by term) during the past school year. Furthermore, during Round 3, school ledgers were sought to check the attendance of respondents for each school term in 2009 and the first term of 2010.

To measure program impacts on student achievement, _mathematics and English reading comprehension tests_ were developed and administered to all study participants at their homes. The tests were developed by a team of experts at the Human Sciences Research Council (HSRC) according to

> 26 The reason why the school survey in Round 3 was conducted for a randomly selected sub-sample instead of every student who reported being enrolled in school in 2009 is that school ledgers were also sought to check the attendance of core respondents. As locating these ledgers, examining them, and recording attendance for each core respondent is time consuming and costly, the study team decided to reduce the sample size.

13
We first built a binary variable that takes the value 1 if the household-head is active (0 if he is inactive<sup>16</sup> ). Road access is supposed to entail labor opportunities. Therefore we expect that our road access variable (which in fact proxies isolation) will have a negative impact on this variable if our "Active" dummy really captures the opportunity of employment.

The World Bank Agriculture and Rural Development Department explains that "`Agriculture employs nearly one-half of the labor force in developing countries. Indeed, a high share of rural communities and especially the rural poor are directly or indirectly dependent on agriculture through farming, food processing, fishing, forestry, and trade."' (World Bank, 2009.2). Cameroon fits this overview since the agricultural sector represented 61% of total employment in 2001 (World Bank, 2009.3), about 41% of the household-heads in our sample are involved in agriculture. The proportion rises to 66.82 % among poor households and to 78.72 % among rural poor households.

We build binary variables to assess the impact road access has on the involvement in agriculture and diversification outside from this sector. Indeed, on the one hand diversification outside from agriculture is at the core of the debate on rural poverty; on the other hand, road access is found to significantly influence the diversification of income sources according to the brief literature review in Section 2. Our first agricultural dummy equals 1 if the household-head declares his main activity to be agriculture (0 if he declares it is not in agriculture)<sup>17</sup> . The second variable concerns the household-heads primarily involved in a farming activity and equals 1 for multi-active heads, 0 for the single-active ones. This variable aims at testing if diversification as a multiplication of income sources in addition to a main agricultural activity helps to reduce poverty and the impact isolation has on this decision.

# **_Econometric specification_**

Our intuition is that road access _per se_ does not have a direct impact on consumption expenditures at the household level. The impact should only be indirect and what matters is

> 16 Retired, students, unemployed, disabled, other inactive.

> 17 We also use two other dummies. The first restrict the sample to the single-active household-heads and equals 1 if he is involved in a farming activity; 0 otherwise. The second equals 1 if the household-head is a single-active farmer; 0 if he is a multi-active farmer or involved in non-farming activities. We find similar results with these alternative measures.

15
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|Clean Fuels and Environmental Improvement Project|Mohammad M. Farhandi|
|---|---|
|Clean Fuels and Environmental Improvement Project|Mohammad M. Farhandi|
|Clean Fuels and Environmental Improvement Project|Mohammad M. Farhandi|
|Clean Fuels and Environmental Improvement Project|Mohammad M. Farhandi|
|Clean Fuels and Environmental Improvement Project|Mohammad M. Farhandi|
|Clean Fuels and Environmental Improvement Project|Mohammad M. Farhandi|
|Clean Fuels and Environmental Improvement Project|Mohammad M. Farhandi|
|Land TitlingProject(03)|Keith Clifford Bell|
|Land TitlingProject(03)|Keith Clifford Bell|
|Land TitlingProject(03)|Keith Clifford Bell|
|Land TitlingProject(03)|Keith Clifford Bell|
|Land TitlingProject(03)|Keith Clifford Bell|
|Land TitlingProject(03)|Keith Clifford Bell|
|Land TitlingProject(03)|Keith Clifford Bell|
|Land TitlingProject(03)|Keith Clifford Bell|
|Land TitlingProject(03)|Keith Clifford Bell|
|Land TitlingProject(03)|Keith Clifford Bell|
|Universities Science and EngineeringEducation Project|Omporn Regel|
|Universities Science and EngineeringEducation Project|Omporn Regel|
|Universities Science and EngineeringEducation Project|Omporn Regel|
|Universities Science and EngineeringEducation Project|Omporn Regel|
|Universities Science and EngineeringEducation Project|Omporn Regel<br>|
|Universities Science and EngineeringEducation Project|Omporn Regel|
|Universities Science and EngineeringEducation Project|Omporn Regel|
|Universities Science and EngineeringEducation Project|Omporn Regel|
|Tonga Development Bank Project||
|Tonga Development Bank Project||
|Tonga Development Bank Project||
|Tonga Development Bank Project||
|Tonga Development Bank Project(02)|YulingZhou|
|Tonga Development Bank Project(02)|YulingZhou|
|Tonga Development Bank Project(02)|YulingZhou|
|Tonga Development Bank Project(02)|YulingZhou|
|Tonga Development Bank Project(02)|YulingZhou|
|Tonga Development Bank Project(02)|YulingZhou|
|Tonga Development Bank Project(02)|YulingZhou|
|Agricultural Extension and TrainingProject||
|Agricultural Extension and TrainingProject||
|Agricultural Extension and TrainingProject||
|Agricultural Extension and TrainingProject||
|Agricultural Extension and TrainingProject||
|Primaryand SecondaryEducation Project|RozanyR. Deen|
|Primaryand SecondaryEducation Project|RozanyR. Deen|
|Primaryand SecondaryEducation Project|RozanyR. Deen|
|Primaryand SecondaryEducation Project|RozanyR. Deen|
|Primaryand SecondaryEducation Project|RozanyR. Deen|
|Primaryand SecondaryEducation Project|RozanyR. Deen|
designated poor county in the central province of Henan, is presented in Table 6.

**Table 6.  Budgetary Expenditures in Huaxian, 2003**

|**Expenditure Category:**|**Per capita**<br>**(RMB)**|**Share of total**<br>**budget**|
|---|---|---|
|Administration|68|22%|
|Education|120|39%|
|Agriculture(incl. forestry,water cons.,meteorology)|23|7%|
|Health|10|3%|
|Social assistance/relief|15|5%|
|Capital construction|17|6%|
|Other|56|18%|
|Total|308|100%|

Source: fieldwork, December 2004.

Even though Huaxian devoted 39 percent of its budgetary expenditures to education, nearly twice the national average for counties, it managed to spend only RMB 678 per student enrolled in basic education, or 62 percent of the national average.<sup>19</sup> With education taking up a large part of available revenues, and administration taking another 22 percent, Huaxian was hard-pressed to find resources to meet all of its responsibilities. Compared to other counties, it spent proportionally less on capital investment, health, and economic services. Even though the county is a major grain producer, Huaxian also spent comparatively little on agricultural services. In 2003 the budget allocated only RMB 23 per capita for the operating costs of all departments related to agriculture, less than one-tenth of that spent in Ninglang county in Yunnan, a remote and mountainous locality that had little agriculture to speak of. The Huaxian county government provided no funding for any other economic services.

# **2.3.  Revenue Assignments**

In order for rural local governments to deliver the many assigned vital (and often costly) services, the IFS must assign sufficient revenues to them through own taxes and user charges as well as through transfers. Given the very large regional disparities in income and revenue capacity across regions, transfers play an important role in alleviating horizontal inequities. If this condition is not met (either because of inadequate own revenues and/or inadequate

> 19 See World Bank (2005a); national figure calculated from Chinese Finance Yearbook, 2004.

14
———. 2013b. "Methodology – Understanding the HIV estimates." In.

UNAIDS Reference Group on Estimates, Modelling and Projections. 2012. "Technical Refinements for Spectrum 2013: December 2012." In. Geneva, Switzerland. United Republic of Tanzania Ministry of Health, National AIDS Control Programme. 2006. "Tanzania Surveillance of HIV and Syphilis Infections Among Antenatal Clinic Attendees 2005/06." In.

United Republic of Tanzania Ministry of Health National AIDS Control Programme. 2005. "Tanzania Surveillance of HIV and Syphilis Infections Among Antenatal Clinic Attendees 2003/04." In.

- ———. 2010. 'Tanzania Surveillance of HIV and Syphilis Infections Among Antenatal Clinic Attendees 2008'.

- Van Damme, Lut, Amy Corneli, Khatija Ahmed, Kawango Agot, Johan Lombaard, Saidi Kapiga, Mookho Malahleha, Fredrick Owino, Rachel Manongi, Jacob Onyango, Lucky Temu, Modie Constance Monedi, Paul Mak'Oketch, Mankalimeng Makanda, Ilse Reblin, Shumani Elsie Makatu, Lisa Saylor, Haddie Kiernan, Stella Kirkendale, Christina Wong, Robert Grant, Angela Kashuba, Kavita Nanda, Justin Mandala, Katrien Fransen, Jennifer Deese, Tania Crucitti, Timothy D. Mastro, and Douglas Taylor. 2012. 'Preexposure Prophylaxis for HIV Infection among African Women', _New England Journal of Medicine_ , 367: 411-22.

- Wambura, M., M. Urassa, R. Isingo, M. Ndege, M. Marston, E. Slaymaker, J. Mngara, J. Changalucha, T. J. Boerma, and B. Zaba. 2007. 'HIV prevalence and incidence in rural Tanzania: results from 10 years of follow-up in an open-cohort study', _J Acquir Immune Defic Syndr_ , 46: 616-23.

- Watson-Jones, D., H. A. Weiss, M. Rusizoka, J. Changalucha, K. Baisley, K. Mugeye, C. Tanton, D. Ross, D. Everett, T. Clayton, R. Balira, L. Knight, I. Hambleton, J. Le Goff, L. Belec, R. Hayes, H. S. V. trial team, Steering, and Committees Data Monitoring. 2008. 'Effect of herpes simplex suppression on incidence of HIV among women in Tanzania', _N Engl J Med_ , 358: 1560-71.

- Wawer, M. J., D. Serwadda, R. H. Gray, N. K. Sewankambo, C. Li, F. Nalugoda, T. Lutalo, and J. K. Konde-Lule. 1997. 'Trends in HIV-1 prevalence may not reflect trends in incidence in mature epidemics: data from the Rakai population-based cohort, Uganda', _AIDS_ , 11: 1023-30.

- Welfare, Ministry of Health and Social. 2008. 'ANC HIV and Syphilis Sentinel Surveillance Synopisis 2003, 2005 and 2007 '.

- WHO. 2006. 'Antiretroviral therapy for HIV infection in adults and adolescents

- Recommendations for a public health approach (2006 revision)'.

- ———. 2010. "Antiretroviral therapy for HIV infection in adults and adolescents

- Recommendations for a public health approach: 2010 revision." In.

- ———. 2013. "Consolidated guidelines on the use of antiretroviral drugs for treating and preventing HIV infection." In.

- WHO, and UNAIDS. 2013. "WHO/UNAIDS Technical Update on HIV

incidence assays for surveillance and epidemic monitoring." In.

- WHO, UNAIDS, and CDC. 2003. "Guidelines for Conducting HIV Sentinel Serosurveys among Pregnant Women and Other Groups." In.

79
# * Sustaining strong political backing for these reforms.

We begin with a brief analysis of the challenges of fighting "local capture", especially in very hierarchical settings. We continue by illustrating some key obstacles to effective local service delivery and how they can be averted, drawing on Wade's (1982, 1997) comparison of the South Korean and Indian canal irrigation agencies. This is followed by discussion of some country case studies of efforts to redesign local agencies' incentives and increase community participation in service delivery. These cases were selected because they offer examples of successful and sustainable governance reform for community-driven development, under quite different circumstances. We then draw out some of the generalizable lessons from these case studies, indicating reasons for success or failure.

**Figure 1. State-community alliances for development and improved local public service delivery**

<!-- Start of picture text --> Central / State government<br>(reward: political support)<br><!-- End of picture text --> <!-- Start of picture text --> Organizational streamliningX<br>Political & economic incentives\<br>Strategic use of resources<br><!-- End of picture text --> <!-- Start of picture text --> INFORMATION, & OTHER SUPPORT<br><!-- End of picture text --> <!-- Start of picture text -->
- stimulate  local  development initiatives<br><!-- End of picture text -->

- raise aspirations, demand generation - information on services offered

<!-- Start of picture text --> Local public agencies<br>& grassroots workers<br>(rewards: public image, material<br>hfRnpfitv)<br><!-- End of picture text --> <!-- Start of picture text --> Communities<br>(rewards: development and<br>nnlitirnl Pmnnwrnrmunt) Pressure for quality services<br>& peer monitoring<br><!-- End of picture text --> 3
The evidence (looking at the individual components of the complexity index) suggests that reforms to decrease formalism, by decreasing the written component in procedures, simplifying rules for the presentation of evidence; and simplifying and limiting the appeals process in the group of African countries may show results in terms of faster adjudication and less corruption, ceteris paribus.

# <u>Latin America (LAC)</u>

As Figure 6 shows, judicial efficiency is rated higher in wealthy countries than in the LAC countries in the sample. Similar conclusions are reached with respect to the perception of citizens’ access to justice, corruption, and the level of contract enforcement.

<!-- Start of picture text --> Figure 6. Perceptions of Judicial Figure 7. Formalism Index<br>10.00 9.14 Efficiency 8.55 4.504.00 3.88 4.04<br>9.008.00 6.70 7.50 7.62 3.50 3.05 3.28<br>7.00 3.00<br>6.00 4.80 4.58 2.50<br>5.00<br>4.00 2.75 2.00<br>3.00 1.50<br>2.00<br>1.00 1.00<br>0.00 0.50<br>Judicial Citizens' Enforcement Control of 0.00<br>Efficiency Index Access to Index Corruption Check Eviction<br>Justice Index<br>High Income Countries LAC Countries High Income Countries LAC Countries<br><!-- End of picture text --> _Fig.5 Sources: Judicial Efficiency Index: ICRG; Citizens’ Access to Justice: World Business Environment Survey; Enforcement Index: Business Environmental Risk Intelligence; Control of Corruption: ICRG. Fig.6 Source: Djankov et al. (2003)_ The data show that the degree of procedural complexity in the LAC region is significantly higher than in the sample of high income countries (at the 5% confidence level) and in some of its major subcategories – notably in the amount of statutory regulation of evidence required for these simple cases, as well as other statutory interventions; the use of appeals; and in the overall number of independent procedural actions required for resolution (Figure 2). In the Central and South American countries, in particular, there is an almost universal right to superior review (appeals) for even the 33
# **5. REFERENCES**

Azevedo, J.P. & Mitra, S. (forthcoming). Global poverty estimation theoretical and empirical validity of parametric Lorenz curve estimates and revisiting nonparametric techniques. World Bank, Mimeo.

Beegle, K., Olinto, P., Sobrado, C., Uematsu, H., Kim, Y. S., & Ashwill, M. (2014). Ending Extreme Poverty and Promoting Shared Prosperity. Could There Be Trade‐offs Between These Two Goals? Inequality in Focus, 3(1). World Bank, Washington, DC.

Cruz, M., Foster, J., Quillin, B. and Schellekens, P. (2015). Ending Extreme Poverty and Sharing Prosperity: Progress and Policies. Policy Research Note 101740. World Bank, Washington, DC.

Datt, G. (1998), “Computational Tools for Poverty Measurement and Analysis,” FCND Discussion Paper No. 50.

Deaton, A. & Zaidi, S. (2002). "Guidelines for Constructing Consumption Aggregates for Welfare Analysis," World Bank Publications, The World Bank, number 14101, November.

Deaton, A. (1997). The Analysis of Household Surveys: A Microeconometric Approach to Development Policy. Baltimore, MD: Johns Hopkins University Press.

Dollar, D. T. Kleineberg, Kraay, A. (2013). “Growth Still is Good for the Poor.” Policy Research Working Paper 6568. World Bank, Washington, DC.

Global Poverty Working Group 2015. “Methodology for computing the indicator on Shared Prosperity for the Global Database of Shared Prosperity (GDSP) circa 2007–2012”, available at: http://www.worldbank.org/content/dam/Worldbank/poverty/GDSP_Methodology_Sep2015%20(2).doc x.

Mitra, S. R. Katayama, and Yoshida, N. (2010). “A Short Note on International Poverty Estimation,” mimeo.

Narayan, A., Saavedra‐Chanduvi J. & Tiwari, S. (2013). “Shared Prosperity: Links to Growth, Inequality and Inequality of Opportunity”. Policy Research Working Paper 6649. The World Bank.

PovcalNet (2015). PovcalNet: an online analysis tool for global poverty monitoring, available at: http://iresearch.worldbank.org/PovcalNet/ Ravallion, M. (1992). "Poverty Comparisons ‐ A Guide to Concepts and Methods," Papers 88, World Bank ‐ Living Standards Measurement.

Ravallion, M. (1996). "Issues in Measuring and Modelling Poverty," _Economic Journal_ , Royal Economic Society, vol. 106(438): 1328‐43.

Serajuddin, U., Uematsu, H., Wieser, C., Yoshida, N., and Dabalen, A. (2015). “Data Deprivation: another deprivation to end“. Policy Research Working Paper 7252. The World Bank.

World Bank. (2008). Poverty data: A supplement to the World Development Indicators, 2008. World Bank.

World Bank. (2015a). _A Measured Approach to Ending Poverty and Boosting Shared Prosperity: Concepts, Data, and the Twin Goals_ . Policy Research Report. Washington, DC: World Bank. doi:10.1596/978‐1‐4648‐ 0361‐1.

World Bank Group. (2015b). _Global Monitoring Report 2014/2015: Ending Poverty and Sharing Prosperity._ Washington, DC: World Bank. doi:10.1596/978‐1‐4648‐0336‐9.

20
from potential AD duties. This finding demonstrates that exporters are willing to avoid the threat of retaliation by decreasing their dumping margins in a particular country with importers that are named in AD petitions in the exporters’ home country. We also show that the pricing effect of retaliation threats is increasing in firms' shares of each industry's product in their total exports. This price increase is higher for exporters serving the developed world and heavy AD users.

1 See Blonigen and Prusa (2003) for an extensive survey.

2 India and the United Stated are the top two AD users in the world.

3 Studies on retaliation and AD also use filing behavior as the dependent variable.

- 4 See table 1 for the AD duties of importing countries.

5 Most of the AD cases are filed for multiple products. Therefore, the number of cases does not always represent the number of six-digit HS products investigated.

6 See Molina and Muendler (2009) and Hirakawa, Muendler and Rauch (2010) for more information about SECEX and RAIS data.

7 http://econ.worldbank.org/ttbd/gad.

8 See Feinberg and Reynolds (2006).

9 Given the large costs associated with initiating AD investigations, firms often come together via lobbies to file petitions and share the cost of filing. 10 Our results are insensitive to treating each European Union country as a different market and to removing European Union countries from the sample.

11 The linked employment data also report the wage bill paid by the firm. However, the availability of this variable is so limited in our sample that it is unusable.

12 Although we do not report the results here, the alternative measure of the use of total revenue that a firm earns from the same product in the destination does not alter our findings.

13 The linked employment data also report the wage bill paid by the firm. However, the availability of this variable is limited in our sample, which does not allow us to utilize the data.

14 While we do not report the results here, the use of total revenue that the firm earns from the same product in the destination as an alternative measure does not alter our findings.

15 See Manova and Zhang (2009) for the same argument.

16 Individual exporting activities are unit observations where there is no firm code.

17 We use the formula in Kennedy (1981) to convert the coefficient of the dummy variable to its true marginal effect. 18 Instead of using the AD duty in force, which is one until the duty is revoked, the AD variables are now defined as follows: AD duties for one year or two years after the affirmative AD decision.

19 See Vandenbussche and Wauthy (2001) for the same argument.

# **_<<A>>_ REFERENCES**

Aggarwal, A. 2007. “The Antidumping Agreement and Developing Countries.” Oxford University Press.

Bastos, P. and J. Silva. 2010. “The Quality of a Firm’s Exports: Where You Export to Matters.” _Journal of International Economics_ 82 (2): 99-11.

15