rafmacalaba/datause-encoder-data huggingface dataset:
_31_

# **REFERENCES**

- Abdulkadiro ̆glu, A., Angrist, J. D., Hull, P. D., and Pathak, P. A. (2016). Charters without lotteries: Testing takeovers in new orleans and boston. _American Economic Review_ , 106(7):1878–1920.

- Abdulkadiro ̆glu, A., Pathak, P. A., and Roth, A. E. (2009). Strategy-proofness versus efficiency in matching with indi↵erences: Redesigning the nyc high school match. _American Economic Review_ , 99(5):1954–78.

- Acemoglu, D. and Angrist, J. (2000). How large are human-capital externalities? evidence from compulsory schooling laws. _NBER macroeconomics annual_ , 15:9– 59.

- Ajayi, K. F. (2014). Does school quality improve student performance? new evidence from ghana. _Unpublished working paper_ .

- Andrabi, T., Das, J., and Khwaja, A. I. (2008). A Dime a Day: The Possibilities and Limits of Private Schooling in Pakistan. _Comparative Education Review_ , 52(3):329–355.

- Andrabi, T., Das, J., and Khwaja, A. I. (2013). Students today, teachers tomorrow: Identifying constraints on the provision of education. _Journal of Public Economics_ , 100:1–14.

- Andrabi, T., Das, J., and Khwaja, A. I. (2015). Delivering education a pragmatic framework for improving education in low-income countries. (May).

- Andrabi, T., Das, J., and Khwaja, A. I. (2017). Report cards: The impact of providing school and child test scores on educational markets. _American Economic Review_ , 107(6):1535–63.

- Andrabi, T., Das, J., Khwaja, A. I., and Karachiwalla, N. (2018). The equilibrium e↵ects of grants to public schools. _Working Paper_ .

- Andrabi, T., Das, J., Khwaja, A. I., Vishwanath, T., and Zajonc, T. (2009). Learning and Educational Achievements in Punjab Schools (LEAPS): Insights to inform the education policy debate.

- Andrabi, T., Das, J., Khwaja, A. I., and Zajonc, T. (2011). Do value-added estimates add value? accounting for learning dynamics. _American Economic Journal: Applied Economics_ , 3(3):29–54.

- Angrist, J. D., Pathak, P. A., and Walters, C. R. (2013). Explaining charter school e↵ectiveness. _American Economic Journal: Applied Economics_ , 5(4):1–27.

- Athey, S. and Imbens, G. W. (2017). The econometrics of randomized experiments. _Handbook of Economic Field Experiments_ , 1:73–140.

- Banerjee, A., Banerji, R., Berry, J., Duflo, E., Kannan, H., Mukerji, S., Shotland, M., and Walton, M. (2017). From proof of concept to scalable policies: Challenges and solutions, with an application. _Journal of Economic Perspectives_ , 31(4):73–102.

- Banerjee, A. and Duflo, E. (2012). Do Firms Want to Borrow More: Testing Credit Constraints Using a Targeted Lending Program. _Review of Economic Studies_ , page Forthcoming.

- Barrera-Osorio, F., Blakeslee, D. S., Hoover, M., Linden, L., Raju, D., and Ryan,
COST RECOVERY, EQUITY, AND EFFICIENCY IN WATER TARIFFS IN AFRICA

|Country|Utility|Fixed<br>charge|Fixed charge as<br>% of 10m<br>3|Number of<br>blocks|Size of 1st<br>block|Size of nth<br>block|Price of<br>1st<br>block|Price of<br>nth block|
|---|---|---|---|---|---|---|---|---|
|ZAF|Johannesburg|0.00|0|6|6|40+|0.00|1.40|
|ZMB|SWSC|0.00|0|4|10|50+|0.30|0.47|
|ZMB|LWSC|1.24|32|5|6|170+|0.25|0.55|
|ZMB|NWSC|0.00|0|4|6|50+|0.25|0.37|
|**MIC average**|||26|4.00|6.89||0.61|2.29|
|**LIC average**|||28|3.03|11.29||0.24|0.61|

_Source:_ AICD WSS Survey Database, 2007.

MIC = middle-income countries; LIC = low-income countries.

33
|Figure 18. Niger’s Internet market compares poorly with other ECOWAS countries|34|
|---|---|
|Figure 19. Niger’s infrastructure spending needs in the regional context|36|
|Figure 20. Niger’s existing infrastructure spending is relatively low|37|
|Figure 21. Patterns of capital investment in infrastructure, benchmarked against comparator countries|38|
|Figure 22. Underpricing of water in Niger is comparatively less burdensome|39|
|Figure 23. Consumption of infrastructure services in Niger varies by income quintile|39|
|Figure 24. Water subsidies that reach the poor|40|
|Figure 25. Affordability in Niger in comparison to other low-income countries|41|
|Figure 26. Niger’s power and water utilities burden of inefficiency|41|
|Figure 27. Niger has captured relatively low private sector participation|42|

# List of tables

|Table 1. The achievements and challenges of Niger’s infrastructure sectors|8|
|---|---|
|Table 2. Trading across borders in West African countries|10|
|Table 3. West African port indicators|11|
|Table 4. Niger’s international trade|12|
|Table 5. Road conditions along major transit ECOWAS corridors that run through Niger|13|
|Table 6. Niger’s road indicators|14|
|Table 7. Railway indicators for OCBN and select other railways|16|
|Table 8. Benchmarking air transport indicators for Niger and select other countries|18|
|Table 9. Niger's irrigation potential|21|
|Table 10. Benchmarking water and sanitation indicators|23|
|Table 11. Evolution of operational indicators associated with SPEN, Niger|24|
|Table 12. Power indicators, benchmarked against select country groups|28|
|Table 13. High fuel prices escalate domestic power production costs|29|
|Table 14. Benchmarking ICT indicators|31|
|Table 15. Mobile penetration in West African countries|33|
|Table 16. Illustrative investment targets for infrastructure in Niger|35|
|Table 17. Indicative infrastructure spending needs in Niger, 2006–15|35|
|Table 18. Financial flows to Niger’s infrastructure|36|
|Table 19. Niger’s potential gains from greater operational efficiency|38|
|Table 20. Funding gaps by sector|42|
|Table 21. Savings from innovation|43|

iv
While these results by themselves may not rule out a demand-side channel, they do substantially constrain the routes through which it can work. Fathers' education could not stimulate demand for children's education (since boys' schools have no eect); primary schooling for mothers could not be enough to stimulate demand; mothers' schooling must therefore have a non-linear eect on the demand for children's education.

# Price Margin

Table V provides further evidence for a supply channel by examining the price margin. Recall, in sharp contrast to a demand-channel, a supply channel would suggest that GSS construction would lead to a fall in private school teacher (i.e. skilled women) wages. We compare the average (log) teacher salary in private schools in villages with and without a GSS using data from the private school census. Column (1) presents the OLS results in the sample of villages for which we have teacher wage data. We include PC FEs in all specications. The results are large and signicant: Private schools in villages with a GSS report a 27 percent lower average (teaching) wage.

Columns (2) through (5) correct for selection into the wage sample. Columns (2) and (3) present results using Heckman's selection model, and Columns (4) and (5) use the control function approach (see Appendix I). In both approaches, identication is based on the non-linearity of the selection equation (see Duo [2001] as an example). Augmenting the instrument set with potential candidates that are correlated to the probability of having a private school but uncorrelated to the wage-bill can help with the identication and the eciency of the estimator. Following Downes and Greenstein (1996), we propose using the that have both. An alternate strategy is to check whether there is a dierence in the existence of a private school based on years of exposure to a GSS. Here, we do nd some suggestive evidence. In particular, private schools exist in 22 percent of villages with 15 years or less of exposure to a GSS , and in 33 percent of those with more that 15 years. Moreover, it is really only older GSSs' which have an impact. We can conduct a similar placebo exercise as in Table III, Column (7) except we now include villages in the non-program group if they or a village in their QH received a GSS less than 5 years ago. Similar to the Column (7) result, we nd that there is no reduced form eect of the instrument in this sample, i.e. it is only 5 years or more exposure to GSSs that matters. Finally, consistent with the supply channel, we nd from a smaller but more in-depth sample that the female private school teachers are in the age-group that would be consistent with the GSS construction period - the median private school female teacher age is 22 with over 90 percent between 18-32 years of age.

25
45

# Table 3 Capital Flows to Highly Indebted Countries, 1951-88 ($ millions)

|Public'Sector|1981|<br>1982|<br>1983|<br>1984|<br>1985|1986|'1987|1988|
|---|---|---|---|---|---|---|---|---|
|Multilateral|2,719|<br>3,881|3,069|<br>4,522|<br>3,997|5,150|<br>3,370|<br>4,082|
|Bilateral|3,158|<br>1,719|2,539|<br>1,525|<br>697|1,158|<br>1,919|<br>2,738|
|IMF|1,213|<br>2,110|6,517|<br>3,334|<br>1,686|-206|-1,384|-1,077|
|Total|7,000|<br>7,710|12,125|<br>9,381|<br>6,380|6,102|<br>3,905|<br>5,743|
|Banks (a)|20,205|23,263|13,575|10,427|<br>5,345|3,455|<br>4,931|<br>5,450|
|Total|27,205|30,973|25,700|19,808|11,725|9,557|<br>8,836|11,193|

Source: World Bank, World Debt Tables 1988, Vol. I, pp. xliii, 30-31 and by communication; table 2.

a. For 1981-82: net disbursements from "financial markets". For 1983-88: disbursements under new money packages.
income, official poverty would be on average 2.8 percentage points higher, and for rural residents – 5.9 percentage points higher.

_Figure 21: In‐kind income, in real terms, 2014 set to 100_ <!-- Start of picture text --> 140<br>135<br>130<br>125<br>120 Minsk<br>115 Large cities<br>110 Small cities<br>105 Rural<br>100<br>95<br>90<br>2014 2015 2016 2017<br><!-- End of picture text --> Note: In‐kind income is measured in real 2014 roubles per capita and converted into the index with the 2014 level set to 100 Source: Authors’ calculations based on quarterly HBS.

In‐kind income was particularly important for the vulnerable groups during the crisis: residents of small cities and rural areas, non‐employed and retirees increased their in‐kind income by more than 20 percent during the crisis. Only Minsk residents did not increase their in‐kind income during the recession, while other socio‐ economic groups, including the residents of large cities, relied on in‐kind incomes to smooth income fluctuations during the crisis. Households with children increased their in‐kind income to a limited extent (the increase is lower than average); this might have to do with lower availability of spare time among these households.

# 5.2. Consumption

Households reported reducing expenditures as the main instrument of adjustment to the crisis environment. There are differences across social groups in what types of expenditures households cut. Better off households adjust through reducing their savings and purchases of durable goods, while less wealthy households have to cut their consumption. Household micro data support this view.

The structure of household expenditure does not differ significantly across the population, highlighting the low level of inequality in Belarus (Figure 22). Only the richest 10<sup>th</sup> decile stands out, as it spends a significantly lower share than the population on average on food and much more on savings, investments and the purchase of personal cars (Shymanovich, Chubrik, 2019). The bottom decile spends a higher share of income on food, as well as basic services such as utilities, public transportation and communication services. Differences between the 2<sup>nd</sup> and 9<sup>th</sup> deciles are not very large, but they increase with disposable income. The main difference is related to the falling share of food in households’ expenditures with growing household incomes. We focus our analysis of the consumption behavior during the crisis on the expenditures of the 1<sup>st</sup> and 10<sup>th</sup> deciles. Other deciles we will aggregate into three groups, representing 2<sup>nd</sup> and 3<sup>rd</sup> deciles, from 4<sup>th</sup> to 7<sup>th</sup> deciles, and 8<sup>th</sup> and 9<sup>th</sup> deciles.

19
25 firms. Chile is in fact an outsider in Latin America in this regard as most countries have now completely liberalized interest rates, including Brazil, Argentina, Peru, Bolivia, Mexico, and Ecuador.

**Figure 21:  A Regional Comparison of Microfinance Interest Rates**

<!-- Start of picture text --> Countries (avg rate per country)<br>Average interest rates on microfinance loans<br>Brazil (59%)<br>across Latin America<br>Bolivia (29%)<br>90% Colombia (46%)<br>Dominican Republic (52%)<br>80% El Salvador (45%)<br>Nicaragua (44%)<br>70% Paraguay (45%)<br>Peru (46%)<br>60%<br>Uruguay (37%)<br>50% Mexico (60%)<br>40%<br>30%<br>20%<br>10%<br>0%<br>Sources: IDB, World Bank, websites of individual institutions<br>CrediamigoCEAPEBanco da MulherPortoSolBluSolVivaCredRioCredSindCredBancoSolAndesAgrocapitalFIEFinamericaWWB BucaramangaWWB PopayanWWB CaliWWB MedellinWWB BogotaAdopemCalpiaEnlaceConfiaCMAC ArequipaFindeVisionCMAC TrujilloCMAC SullanaCMAC CuscoEdyficarCMAC IcaCMAC TacnaProempresaCrear TacnaCrear ArequipaConfianzaMibancoCompartamosFucacIndependenciaFincomun Admic<br><!-- End of picture text --> The stamp tax levied on almost all financial transactions also penalizes borrowing by micro and small firms. Chile levies a stamp tax of maximum 1.7 percent (“ _impuesto de timbre”_ ) on nearly all financial transactions<sup>15,16</sup> . This tax penalizes small value loans that are renewed often as the credit history of new small borrowers is being built with the bank. As such it creates a distortion in favor of larger loans, which usually go to large firms.

Finally, the quality and trustworthiness of the financial statements of micro, small and medium firms is a key obstacle for them accessing any type of financing. Credit bureaus function well, so that bankers often prefer relying on scoring systems (and offering consumer

> 15 According to the law the stamp tax is levied on the issuance of promissory notes and other similar commercial papers. Notwithstanding, this tax is charged on all financial transactions because in practice banks request all debtors to sign a note, which is an executory instrument ( _título ejecutivo_ ), so as to allow the bank the eventual use of an enforcement proceeding in case of the debtor’s default (see Appendix 1).

> 16 The stamp tax is progressive and depends on the loan amount and its maturity.  It varies from 0.14% per month to a maximum of 1.7% of the credit value.
Munshi, K., and Rosenzweig, M. R. (2006): “Traditional Institutions Meet the Modern World: Caste, Gender and Schooling Choice in a Globalizing Economy,” _The American Economic Review_ , 96(4): 1225– 1252.

Mutatkar, R. (2005): “Social Group Disparities and Poverty in India,” Working Paper Series No. WP-2005004, Mumbai: Indira Gandhi Institute of Development Research.

Rao, V., and Ban, R. (2007): “The political construction of caste in South India,” _Mimeo._ Washington DC: World Bank.

Sanyal, P., Rao, V., and Majumdar, S. (2015): “Recasting culture to undo gender: A sociological analysis of Jeevika in Rural Bihar, India,” <mark>Working Paper 7411. Washington DC: World Bank.</mark> Shorrocks, A. (1980): “The class of additively decomposable inequality measures,” Econometrica, 48(3): 613–625.

<mark>Srinivas, M.N. (1976):</mark> _<mark>The remembered village</mark>_ <mark>(No. 26). University of California Press.</mark> <mark>Subramanian, S., and Jayaraj, D. (2006): “The distribution of household wealth in India,” Research Paper 2016/116. Helsinki: UNU-WIDER.</mark> <mark>Teltumbde, A. (2007): “Reverting to the Original Vision of Reservations,”</mark> _<mark>Economic and Political Weekly</mark>_ <mark>, 2383-2385.</mark> <mark>Thorat, S. (2009):</mark> _<mark>Dalits in India: search for a common destiny</mark>_ <mark>. SAGE Publications India.</mark> <mark>Thorat, A., Vanneman, R., Desai, S., and Dubey, A. (2017)” “Escaping and Falling into Poverty in India Today,”</mark> _<mark>World Development</mark>_ <mark>,</mark> _<mark>93</mark>_ <mark>: 413-426.</mark> <mark>Wilson, W. J. (1987):</mark> _<mark>The truly disadvantaged: The inner city, the underclass, and public policy</mark>_ <mark>. University of Chicago Press.</mark> <mark>Zacharias, A., and Vakulabharanam, V. (2011): “Caste stratification and wealth inequality in India,”</mark> _<mark>World Development</mark>_ <mark>,</mark> _<mark>39</mark>_ <mark>(10): 1820-1833.</mark> 12
and manufacturing production, which is closely tied to the performance of its key trading partners and the inflow of remittances. The country is particularly susceptible to external shocks due to its heavy reliance on imports and exposure to extreme weather events like hurricanes, droughts and floods.

In the past two decades, the Honduran economy has shifted from subsistence agriculture to work in the service sector. While the share of in wage jobs agriculture dropped 10 percentage points (36% to 26%), the share of jobs in services increased from 41% to 52% (Michel & Walker, 2020). Nonetheless there is persistently high informality across all sectors. Informal employment is among the highest in Latin America and the Caribbean (LAC), with approximately 4 out of 5 workers in the informal sector.

The prevailing narrative of economic performance in the country over the last two decades is that the above-average economic growth at 4-5% per year registered, when compared to other countries in LAC, was not enough to raise welfare levels for a population that grew at 2-3% yearly: poverty rates remain very high for regional levels, with almost half of Hondurans living on less than $6.85 a day (2017 PPP) (Figure A.1). Moreover, since the 1960s, Honduras has been diverging from wealthier countries, with per capita income (in constant US$) equal to only 4% of U.S. levels, below the shares of Guatemala (7.2%), El Salvador (6.8%) and Costa Rica (21.3%) (Hernandez Ore _et al._ , 2015). At the same time, survey measures show a decrease in income inequality measured by the Gini coefficient of household income from .6 in 2005 to .5 by 2019 – which is similar to that observed by Brazil, a country that also reduced poverty rates by half in the same period.

# **3 Data sources**

The measures discussed in this on income dis- inequality paper rely comprehensive tributions for Honduras over the 2003-2019 period. To obtain these distributions, we combine several sources of information described in detail below.

## **3.1 EPHPM: Household survey**

The EPHPM ( _Encuesta Permanente de Hogares de Prop ́ositos M ́ultiples_ ) is Honduras’ annual household survey since 1990. It surveys approximately 6,000 households, is nationally representative and allows for disaggregations for the two main cities ( _Distrito Central_ and _San Pedro Sula_ ), other urban and rural areas. This survey is used to track and monitor labor market outcomes as well as socioeconomic indicators of the Honduran population, including official poverty and inequality estimates.

Similar to most household surveys, it includes detailed information on households’ dwelling characteristics, access to basic services, asset ownership, household compo4
incentivize students to pursue higher education. Previous evaluations of these programs have found that they have positive impacts on the native population (Dinkelman and Mart ́ınez A, 2014). Thus we want to understand if migrants and forced migrants can benefit in the same way. We exploit the adjudication of financial aid given a cutoff at students’ scores on the college admission test to create a sharp RDD. This design allows us to compare the students right around the cutoff to evaluate if financial aid disproportionately affects migrants’ access to tertiary education compared to natives.

**OLS regressions** For the OLS regressions, we estimate the effects of migrant status on both school advancement between Grades 1–11 (Equation (1)) and access to higher education for those in the 12th grade (Equation (2))<sup>3</sup> . For the former, we use the entire sample of students in the Chilean education system between 2017–2018; for the latter we focus only on those in the last grade who could potentially enroll in higher education. In both instances, we add fixed effects by school ( _βj ∗ Schoolj_ ) and they could affect enrollment status. The school level fixed effect will be a good variable to control for the environmental, educational and community factors that students face, as well as the income as Chile has one of the most segregated educational systems in the world (OECD, 2020).<sup>4</sup> Standard errors are clustered at the school level so we can control for similar errors patterns in our data.

_Grade Advancement_ 2018 _ij_ = _β_ 0 + _β_ 1 _∗ Migranti_ + _β_ 2 _∗ Forcedi_ + _βj ∗ Schoolj_ + _εi_ _Higher Education Enrollment_ 2018 _ji_ = _β_ 0+ _β_ 1 _∗Migranti_ + _β_ 2 _∗Forcedi_ + _βj∗Schoolj_ + _εi_ We also run Equation 2 including controls for an individual’s college admission test and whether they applied for financial aid to provide a stronger test of our second hypothesis. We retained the same controls as before and kept the standard errors

> 3While there is a discussion between the use of Linear Probability Models and Probit models, we have chosen to use the first as we want to highlight the important magnitude of the effect, something that could be less evident with Probit or Logit models. Future work should analyze in detail these effects using binary models

> 4 We originally we proposed to include the parental income level at the school level as a control, however the school will control for income

12
NIGER’S INFRASTRUCTURE: A CONTINENTAL PERSPECTIVE The inadequate implementation or **Table 4. Niger’s international trade** simply the lack of enforcement of some of **Product Value (CFAF** the rules and procedures agreed to by the **billions) tonnes)** various member states of the Economic **Imports 503.3** Community of West African States Petroleum products 83.3 (ECOWAS) and the West African Rice and related products 157 630,000 Economic and Monetary Union Consumption goods 99.9 138,750 (UEMOA)—rules and procedures that Intermediate and capital goods 163.1 aim to promote efficiency and **Exports 263.5** competition among transport carriers— Uranium 78.5 3,400 augment the costs of trading to and from Cattle 29.1 40,152 Niger. The abolishment of the queuing Cowpeas 11.4 23,940 ( _tour de role_ ) mechanism, a significant Onions 33.8 83,248 step toward trade facilitation, has not been Other exports 110.7 _Source:_ World Bank 2008c. effectively implemented by Niger. Trade flows are not balanced: import volumes total more than 20 times export volumes (table 4). Niger has to undertake urgent transport facilitation policies to phase out the many logistical and other barriers that impede the country’s economic development (World Bank 2008c).

|**Product**|**Value (CFAF**<br>**billions)**|**Volume (in**<br>**tonnes)**|
|---|---|---|
|**Imports**|**503.3**||
|Petroleum products|83.3||
|Rice and related products|157|630,000|
|Consumption goods|99.9|138,750|
|Intermediate and capital goods|163.1||
|**Exports**|**263.5**||
|Uranium|78.5|3,400|
|Cattle|29.1|40,152|
|Cowpeas|11.4|23,940|
|Onions|33.8|83,248|
|Other exports|110.7||

# Roads

## **Achievements**

The condition of Niger’s portions of regional corridors is generally higher than these same corridors’ overall condition. Niger’s portion of the Lomé-Niamey corridor is entirely paved and almost 100 percent in good condition, while only 52 percent is in good or fair condition on the Togo side. Of the CotonouNiamey corridor, 100 percent of the Nigerien part is in good or fair condition, but only 40 percent of the Beninese part is. The country’s portion of the Nouakchott-Ndjamena corridor is 70 percent in good or fair condition, and it is only 38 percent so in the Senegalese portion (table 5). Clearly, the incentives for the coastal country to maintain hinterland road corridors do not seem to be strong, since the coastal countries’ economies are typically concentrated along the coast, making the up-country segments regional public goods, in effect. The relatively poor condition of the corridors in the coastal countries puts Niger at a disadvantage and calls for further regional coordination and collaboration.

12