rafmacalaba/datause-encoder-data huggingface dataset:
|PY - EDUCATION REFORM PROJECT|Mario Cristian Aedo Inostroza|
|---|---|
|PY - EDUCATION REFORM PROJECT|Mario Cristian Aedo Inostroza|
|PY - EDUCATION REFORM PROJECT|Mario Cristian Aedo Inostroza|
|PY - EDUCATION REFORM PROJECT|Mario Cristian Aedo Inostroza|
|PY - EDUCATION REFORM PROJECT|Mario Cristian Aedo Inostroza|
|PY - EDUCATION REFORM PROJECT|Mario Cristian Aedo Inostroza|
|Support for the Social Development AgencyProject|Nadine T. Poupart|
|Support for the Social Development AgencyProject|Nadine T. Poupart|
|Support for the Social Development AgencyProject|Nadine T. Poupart|
|Support for the Social Development AgencyProject|Nadine T. Poupart|
|Support for the Social Development AgencyProject|Nadine T. Poupart|
|Support for the Social Development AgencyProject|Nadine T. Poupart|
|Support for the Social Development AgencyProject|Nadine T. Poupart|
|Support for the Social Development AgencyProject|Nadine T. Poupart|
|Support for the Social Development AgencyProject|Nadine T. Poupart|
|Support for the Social Development AgencyProject|Nadine T. Poupart|
|Support for the Social Development AgencyProject|Nadine T. Poupart|
|Support for the Social Development AgencyProject|Nadine T. Poupart|
|EmergencyResponse Program|Majed El-Bayya|
|EmergencyResponse Program|Majed El-Bayya|
|The Czech PCF Umbrella Project - EnergyEfficiency|William Nicholas Bowden|
|The Czech PCF Umbrella Project - EnergyEfficiency|William Nicholas Bowden|
|Structural Fiscal Adjustment Loan Project|David Michael Gould|
|Structural Fiscal Adjustment Loan Project|David Michael Gould|
|Social Protection VI Project - Jefes de Hogar(Heads of Household)|Theresa Jones|
|Social Protection VI Project - Jefes de Hogar(Heads of Household)|Theresa Jones|
|Social Protection VI Project - Jefes de Hogar(Heads of Household)|Theresa Jones|
|Social Protection VI Project - Jefes de Hogar(Heads of Household)|Theresa Jones|
|CGAP-Nepal Nirdhan II|Jennifer Isern|
|CGAP-Nepal Nirdhan II|Jennifer Isern|
|CGAP-Nepal Nirdhan II|Jennifer Isern|
|CGAP-Nepal Nirdhan II|Jennifer Isern|
|CGAP-Nepal Nirdhan II|Jennifer Isern|
|CGAP-Nepal Nirdhan II|Jennifer Isern|
|AR SAL 1(Federal Provincial Fiscal Relations)|Peter M. Hansen|
|AR SAL 1(Federal Provincial Fiscal Relations)|Peter M. Hansen|
|Financial Sector SupervisoryAuthorityProject|Ahmet I. Soylemezoglu|
|Financial Sector SupervisoryAuthorityProject|Ahmet I. Soylemezoglu|
|Financial Sector SupervisoryAuthorityProject|Ahmet I. Soylemezoglu|
|Financial Sector SupervisoryAuthorityProject|Ahmet I. Soylemezoglu|
|Financial Sector SupervisoryAuthorityProject|Ahmet I. Soylemezoglu|
|HIV/AIDS,Malaria and Tuberculosis Control Project|Sameh El-Saharty|
|HIV/AIDS,Malaria and Tuberculosis Control Project|Sameh El-Saharty|
|HIV/AIDS,Malaria and Tuberculosis Control Project|Sameh El-Saharty|
|HIV/AIDS,Malaria and Tuberculosis Control Project|Sameh El-Saharty|
|HIV/AIDS,Malaria and Tuberculosis Control Project|Sameh El-Saharty|
|HIV/AIDS,Malaria and Tuberculosis Control Project|Sameh El-Saharty|
the cost of sending and receiving remittances and thus are associated with reduced poverty and increased consumption among recipients.

Digital payments make remitting easier and quicker. Instead of having to pay someone to carry cash back to the village or waiting until they have the time and money to travel home, senders using digital remittance payments can use their mobile phone to send money instantly. This ease of use is associated with higher remittance payments. For instance, a study in Bangladesh found that poor rural households received larger remittance payments when they opened a mobile money account. This in turn reduced their dependence on borrowing, allowed them to spend more on food, and made them less likely to experience extreme poverty (Lee et al., 2021). A similar finding from in Uganda showed that opening a mobile money account was associated with a 36 percent increase in the total value of remittances and a 13 percent increase in per capita consumption (Munyegera and Matsumoto, 2016).

Curiously, another study in Bangladesh finds evidence of the opposite: that mobile money decreases consumption among recipients. An explanation for this finding is that recipients and senders view digital remittances differently. Unlike cash, digital remittances may be earmarked for specific purposes like education or health. As a result, recipients consume less when under financial stress despite receiving a payment (Lee et al., 2023).

The G20 has also recognized the importance of efficient cross-border digital payments, including remittances, and has brought together various stakeholders and standard-setting bodies to advance these efforts (G20, 2020). For example, the World Bank and the IMF provide technical assistance to to promote digitalization and improve transparency, with the goal of lowering costs and increasing the speed of cross-border payments.

# **4.5 How digital payments enable deeper financial usage**

Previous iterations of the Global Findex database found that digital payment recipients tended to cash out the money they received into an account. Data from the Global Findex 2021 finds that is changing, with 83 percent of digital payment recipients in developing economies also making a digital payment. Furthermore, 63 percent of payment recipients stored money using an account and 42 percent saved formally. In other words, receiving a digital payment is associated with making a digital payment, and with using an account to save, borrow, and store money. This has 13
single group: large land owners, self-sufficient farmers, agricultural wage earners, and households that indeed do not derive income from agricultural activities. Additionally, the GIDD dataset identifies a welfare aggregate (income or consumption) _only at the household level_ . This posses a serious challenge since, as oppose to the information on food shares,  _h_ , we do not have information on the level and distribution of the proportion of total household income that is accrue to agricultural self-employment activities  _h_ . Both  _h_ and  _h_ vary across households but, as oppose to  _h_ there is no economic theory that we can use to estimate a relationship between  _h_ and other observable characteristics like household per capita income.

In order to get plausible values of  _h_ we rely on the information from the Rural Income Generating Activities (RIGA) project. RIGA is a FAO-World Bank funded project that uses LSMS household surveys to disentangle the sources of rural income with the purpose of understanding the relationship between the various income generating activities.<sup>10</sup> Taking the reported share of self-employed agricultural income at the household level for 19 countries located in 5 of the 6 World Bank developing regions, we estimate a simple polynomial relationship between the share of income that is attributable to self-employment agricultural incomes,  _h_ , and per capital household income (or consumption),<sup>_y_</sup> _h_ , and regional fixed effects: This simple specification is enough to give a rather good fit of the data with an R<sup>2</sup> of 0.5. According to the observed data, controlling for income differences, the share of selfemployed income in rural areas is highest in Sub-Saharan Africa and much lower in Latin America and South Asia. The results of this simple specification are used to impute the share of self-employed agricultural income in all rural households taking into account their per-capita household income (or consumption) and regional location.

Figure 4 shows the difference between the observed and imputed agricultural selfemployed income share for each percentile of per capita consumption in rural areas. The share labeled “all countries” shows that the average share in the poorest households in rural areas is close to 80 percent while this falls to 15 percent for households in upper percentiles. Figure 3 also shows the prediction power of the model by comparing the ˆ observed shares,  _h_ , versus the fitted values,  _h_ , for two rather different countries, Nigeria and Panama. The country-specific fitted values in Figure 3 are based on two separate regressions that excluded Nigeria and Panama, respectively. Overall, the

> 10 For more details on the LSMS household surveys see http://www.worldbank.org/LSMS/. For a complete description of the RIGA project including publication of the first results see Carletto et. al. (2007) and visit: <u>http://www.fao.org/es/ESA/riga/index_en.htm</u>

11
# Is foreign aid fungible? Evidence from the education and health

# sectors

## Nicolas Van de Sijpe<sup>_∗_</sup>

**Keywords:** foreign aid, fungibility, public education expenditure, public health expenditure. **JEL classification codes:** E62, F35, H50, O23.

### **Sector Board:** Economic Policy (EPOL).

> _∗_ Departmental Lecturer in Development Economics, Department of International Development, and Research Associate, Centre for the Study of African Economies (CSAE), University of Oxford. Address: Queen Elizabeth House, 3 Mansfield Road, Oxford, OX1 3TB, United Kingdom. E-mail: nicolas.vandesijpe@qeh.ox.ac.uk. I am grateful to Sudhir Anand, Channing Arndt, Steve Bond, Maarten Bosker, Paolo de Renzio, Markus Eberhardt, Bernard Gauthier, Benedikt Goderis, Clare Leaver, Anita Ratcliffe, M ̊ans S ̈oderbom, Francis Teal, Dirk Van de Gaer, David Vines, John Wilson, the participants at various conferences and seminars, and especially Chris Adam, Paul Collier, Shanta Devarajan, Jon Temple, Frank Windmeijer, Adrian Wood and three anonymous referees for useful comments and discussions. I am also grateful to Ali Abbas, Nicolas Depetris Chauvin, Ibrahim Levent and Gerd Schwartz for assistance in obtaining data. I would like to thank the people at the OECD Development Assistance Committee (DAC), especially C ́ecile Sangar ́e, for patiently answering my questions about their development assistance data and Brian Hammond for comments on the aid data construction. I gratefully acknowledge funding from the Department of Economics, the Oxford Centre for the Analysis of Resource Rich Economies (OxCarre), the Oxford Institute for Global Economic Development (OxIGED) and St. Catherine’s College, University of Oxford. This paper presents the research results of the Belgian Programme on Interuniversity Poles of Attraction (contract no. P6/07) initiated by the Belgian State, Prime Minister’s Office, Science Policy Programming.
- 37 -

# References

Bryan, I. (1974). "Ocean Liner Freight Rates," Journal of Transport Economics and Policy, vol. III, No. 2., (May).

Deakin, B.M. (1974). "Shipping Conferences, Some Economic Aspects of International Regulation," Maritime Studies and Management, 2 (May).

Fashbender, Karl and Wolfgang Wagner (1973). Shipping Conferences, Rate Policy and Developing Countries, (Hamburg: Verlag Weltarchiv).

- Finger, J.M. and Alexander Yeats (1976). "Effective Protection by Transportation Costs and Tariffs: A Comparison of Magnitudes," Quarterly Journal of Economics, XC (February).

- Janssont Jan and Dan Shneerson (1978). "The Effective Protection Implicit in Liner Rate Shipping." Review of Economics and Statistics, 60 (November).

- Lipsey, R. and M. Weiss (1974). "The Structure of Ocean Transport Charges." Exploration in Economic Research, vol. 1., (Summer).

- Livingston, Ian (1986). International Transport Costs and Industrial Development in the Least Developed Countries, (UNIDO/IS.616) (Vienna: UNIDO, 6 March).

- Moneta, C. (1959). "The Estimation of Transportation Costs in International Trade." Journal of Political Economy vol. LXVII, No. 1 (February).

- Sampson, Gary and Alexander Yeats (1976). "The Incidence of Transport Costs and Tariffs on the United Kingdom's Exports," Journal of Transport Economics and Policy, 10 (September). I

- Sampson, Gary and Alexander Yeats (1977). "Tariff and Transport Barriers Facing Australian Exports," Journal of Transport Economics and Policy,<sup>11</sup> (May).

- UNCTAD (1969). Level and Structure of Freight Rates, Conference Practices<sup>and</sup> Adequacy of Shipping Services. (New York: United Nations).

- UNCTAD (1978). Protection of Shipper Interests: Guidelines for Developing Countries, (Geneva: UNCTAD).

- UNCTAD (1984). Small Vessels Regional Shipping Development Project: Caribbean, (UNCTAD/SHIP/603) (Geneva: UNCTAD).

- Yeats, Alexander (1976a). "The Incidence of Transport Costs on Indonesia's Exports to the United States," Bulletin of Indonesian Economic Studies,<sup>12</sup> (November).

- Yeats, Alexander (1976b). "An Analysis of the Incidence of Specific Tariffs on Developing Country Exports," Economic Inquiry, 14 (March 1976).
**Table 7: Ease of Getting Credit, Doing Business, World Bank**

|Year|Public registry<br>coverage(%of adults)|Private bureau<br>coverage(%of adults)|Recovery rate in case of<br>insolvency (cents on the dollar)|
|---|---|---|---|
|DB2004|--|--|7.1|
|DB2005|9|--|8.5|
|DB2006|8.7|52.2|13.3|
|DB2007|10.6|52.2|15.4|
|DB2008|11|48.7|14.6|
|DB2009|9.7|48.6|20.7|
|DB2010|10.9|47.4|20.7|
|DB2011|13.9|50.5|16.1|
|DB2012|15.7|48.5|16.6|
|DB2013|16.7|47.5|15.3|

_Source:_ authors.

We see that private credit bureau coverage, although declined somewhat since 2006, has been well above 33.8 percent average coverage in the Latin America and Caribbean region. At the same time, the public registry has picked up the slack by increasing its coverage from 9 percent in 2005 to 16.7 percent in 2013. This number now stands well above the 11 percent public registry coverage in Latin America and the Caribbean.

Government spending and the trade balance wedge computed from equation (3) show little change through the early 1990s, but increase in the late 1990s and remains well above 1 throughout the 2000s. The increase reflects mainly the improvement in the Paraguayan net exports starting mid1990s. Namely, in the 1990s net export was at about 5 percent of GDP, but almost doubled reaching 8.8 percent of GDP in the 2000s. Its peak was at 14 percent of GDP in year 2000. During the same period, government consumption did not show much change, and in fact declined somewhat from 8.5 percent of GDP to 7.5 percent of GDP. Thus, our government consumption and net exports wedge reflects mainly the changes in net exports over the period.

Turning to the sectoral efficiency wedges given by equations (4a)-(4b) and plotted in Figure 1.8(b), we find that there are substantial differences in the dynamics of agricultural and non-agricultural wedges. During 1991-2010, agricultural efficiency wedge is increasing a lot, while nonagricultural efficiency wedge is declining. These trends just reflects the fact that the measured agricultural productivity has been improving during this period, averaging 3 percent per year; while the measured non-agricultural productivity has been falling, averaging -1.5 percent annually. Of course, we must note that this productivity measure reflects not only total factor productivity (TFP) but also all other factors that are not captured directly by our measures of capital and labor. These include human capital, weather conditions, omitted inputs, misallocation of resources, institutional factors, and in fact everything that may lead to inefficient human and physical capital stocks in each sector.

Lastly, we discuss inter-sectoral labor and capital allocation wedges derived in equation (5a)-(5b) and presented in Figure 1.9. Recall that the two wedges compare the value marginal products of labor and capital between agriculture and non-agriculture. Both wedges are less than 1, suggesting
cointegration analysis and explain the lack of cointegration prior to 1990. We therefore report the findings for four different subsamples and test for cointegration between the three sectors inclusive and exclusive of the oil industry. The four different subsamples are 1965:Q1 to 1986:Q4 1965:Q1 to 1989:Q4, 1973:Q1 to 1986:Q4, 1973:Q1 to 1989:Q4 and the findings of the individual cointegration tests are reported in column III (inclusive oil) and column IV (exclusive oil) in Table 3.

The findings of the different tests reveal an unanimous picture. The findings are unaffected if the oil industry is included or excluded from the analysis. And even if we exclude the time period prior to the foundation of the national oil industry or post the 1987 earthquake, we fail to establish a cointegration relationship in the data prior to 1990.

**Table** 3: **Cointegration tests for different subsamples**

|Null<br>Hypothesis|Alternative<br>Hypothesis|X,|"<br>(excl. oil)|95%<br>Critical<br>Value|90%<br>Critical<br>Value|
|---|---|---|---|---|---|
|-|II|III|IV|V|VI|
|||**1965Q1**-|1989Q4|||
|tracetest||||||
|r = 0|r > 0|32.38|25.87|35.10|31.88|
|r < 1|r> 1|9.90|12.33|20.17|17.79|
|r < 2|r>2|2.70<br>**1973Q1 -**|4.24<br> 1989Q4|9.10|7.50|
|tracetest||||||
|r = 0|r > 0|34.36|27.64|35.10|31.88|
|r•I|r> 1|16.61|15.27|20.17|17.79|
|r s 2|r>2|3.79<br>**1965Q1**-|3.91<br> 1986Q4|9.10|7.50|
|tr acetest||||||
|r=0|r>0|25.97|26.20|35.10|31.88|
|r s I|r> 1|10.13|11.31|20.17|17.79|
|r s 2|r>2|2.99<br>**1973QI -**|3.21<br> **1986Q4**|9.10|7.50|
|Xtracetest||||||
|r = 0|r > 0|30.20|31.76|35.10|31.88|
|r s I|r> 1|14.24|12.76|20.17|17.79|
|r s 2|r>2|4.72|3.82|9.10|7.50|

_Source:_ Authors' calculations.

11
intra-African trade which is especially large when they settle in countries far away from their countries of origin.

# 4.4. Robustness checks

We have performed several robustness checks (presented in Table 4). We have first introduced variations in the set of instruments, using only two of them, namely _Network_ and _BSSA_ (column 1). We have then corrected for multilateral trade resistance by including timevarying country-fixed effects, instead of using the Baier and Bergstrand (2009) method, in the IV-OLS estimation (column 2). Finally, given the large prevalence of zero trade flows in our data set, which are undefined when converted into logarithms, we have used the Poisson Pseudo Maximum Likelihood estimator in its IV form to take into account the information provided by the zero trade flows (column 3). The estimations show that our results are robust.

**Table 4 - Impact of African Diaspora on African Exports – Robustness Tests (different sets of instruments and inclusion of time-varying-country fixed effects)**

||IV-OLS|IV-OLS|IV-PPML|
|---|---|---|---|
|VARIABLES|(1)<br>Ln(Exports)|(2)<br>Ln(Exports)|(3)<br>Exports|
|**Migrants_ij (log)**|**0.175****|**0.137****|**0.182****|
||**(2.291)**|**(0.0661)**|**(0.0753)**|
|GDP_i (log)|0.929***||0.867***|
||(9.459)||(0.0585)|
|GDP_j (log)|0.0152||0.597***|
||(0.129)||(0.119)|
|FTA|0.325***|0.331**|0.591**|
||(2.815)|(0.135)|(0.233)|
|Distance (log)|-1.178***|-1.289***|-0.495**|
||(-7.099)|(0.151)|(0.219)|
|Contiguity|0.980***|0.823***|-1.037***|
||(3.929)|(0.224)|(0.372)|
|Common colony|0.235*<br>(1.698)|0.349***<br>(0.134)|0.294<br>(0.453)|
|Colony 1945|0.981***|0.963***|1.094***|
||(3.338)|(0.287)|(0.375)|
|Common language|0.428***<br>(2.807)|0.431***<br>(0.139)|-0.742***<br>(0.151)|
|Constant|-12.40***<br>(-11.74)|8.260***<br>(1.492)||
|MR terms|yes|no|yes|
|Year FE|yes|yes|yes|
|Country FE|yes|yes|no|
|Country x year FE|no|yes|no|
|Sargan (p-val.)|0.614|0.231||
|Underidentification test (Kleibergen-|0.000|0.000||
|Paap p-val.)||||
|Observations|6,204|6,596|10,437|
|R-squared|0.580|0.630|0.113|

_Notes_ : Robust t-statistics in parentheses. *** p<0.01, ** p<0.05, * p<0.1. Observations are clustered by country-pair.

19
respectively called _Mehta I_ and _Mehta II_ in legislative digests, and are together known as the “Ganga Pollution Cases” **–** the foundational water pollution litigation in the Indian court system. In October 1987, the Court invoked the Water Act and Environment (Protection) Act as well as Article 21 of the Indian Constitution to rule in Mr. Mehta’s favor and order the tanneries of Jajmau to clean their wastewater within six months or shut down entirely. This was followed by a January 1988 judgment that required the Kanpur local municipal bodies to take several immediate measures to control water pollution: the relocation of 80,000 cattle housed in dairies or the safe removal of animal waste from these locations; the cleaning of the city’s sewers; the building of larger sewer systems; the construction of public latrines; and an immediate ban on the disposal of corpses into the river. The court also required all schools to devote one hour each week to environmental education and awareness.

Of the 87 tanneries named in Mr. Mehta’s petition, approximately 20 were shut down and at least 60 established primary treatment plants (PTPs). Moreover, several initiatives were undertaken in 1987 and 1988 to clean drains, expand the number of handpumps, and build latrines to improve sanitation systems in Jajmau (Alley 2002). Subsequent litigation in the Supreme Court over the past 25 years, and indeed many academic researchers of pollution in Kanpur, have argued that these projects were a failure and that newly established technologies were not appropriately maintained or used (Alley 2002; Singh 2007).

# **2 Data**

To assess the relationship between policy, water quality, and health in Kanpur, we collect and combine three types of data: infant mortality, river pollution, and other variables to be used as controls. In most of our analysis, we restrict our sample geographic area to the Ganga Basin, which is defined as the area that drains the Ganga and all of its tributaries. We make this restriction because of the singularity of this area in the context of our analysis. The Ganga Basin is not only a much more densely populated region than anywhere else in India, but also a region in which water issues have received special government attention: the National River Conservation Plan (NRCP) focused exclusively on the Ganga Basin (including the Ganga, Yamuna, Damodar, Gomti, and Mahananda Rivers) throughout its first 10 years (1986-1995). Extending the analysis beyond this region might confound the effect of the Supreme Court ruling with the effect of broad scrutiny in the Ganga Basin during this time period.

6
- 20 -

# Figure 2

EXPORT GRONTH FOR 40 TRADE ADJUSTMENT LENDING COUNTRIES <!-- Start of picture text -->
#Korea<br>29<br>Togo  Bradl  Turk.y<br>19  X  *  Thoail  d<br>i  i  *  *+,  ^9  xMeico<br>Tanzania  4  *.,  *Pakiatan<br>3  .9w  '.,  Mauritius<br>GChana<br>-la19  _  _  _  _  __  _  ___  _  _  -_  _  _  19812-Be<br>-19  0  10  20  30<br><!-- End of picture text -->

Source: World Bank **data.** overall export growth was weaker in the 19809 (3.6 percent average annual rate) than in the 1970s (6.8 percent), performance -as stronger for recipient countries (4.5 percent) than for nonrecipients (2.8 percent) in the 1980s. About one-third of the trade loan recipients also managed to increase their exports in recent years (1982-88) compared with the longerterm trend (1965-81, figure 2). Among the ten intensive trade adjustment loan recipients (those that received three or more trade loans), more than half increased their shares in total exports to industrial countries from nonoil-exporting developing countries.

Manufacturing exports from developing countries grew at an average annual rate of 7.6 percent during 1982-87, while the rate of
**Appendix 1 Table 5: Summary statistics on classroom conditions during SDI observations of the**

||Mean<br>All (N|SD<br>=400)|Mean<br>Rural (|SD<br>N=271)|Mean<br> Urban (|SD<br>N=129)|
|---|---|---|---|---|---|---|
|Blackboard in class (1=yes)|0.98|(0.13)|0.99|(0.10)|0.97|(0.17)|
|Blackboard has sufficient contrast for reading (1=yes)|0.90|(0.30)|0.87|(0.34)|0.97|(0.17)|
|Chalk available during the lesson (1=yes)|0.97|(0.18)|0.97|(0.18)|0.97|(0.17)|
|Classroom has a working electricity connection (1=yes)|0.04|(0.20)|0.03|(0.17)|0.07|(0.26)|
|Hygiene in class (1 = reasonably or extremely clean)|0.70|(0.46)|0.65|(0.48)|0.80|(0.40)|
|Pupils work displayed on the the wall|0.20|(0.40)|0.21|(0.41)|0.19|(0.39)|
|Charts displayed on the walls|0.28|(0.45)|0.27|(0.44)|0.31|(0.46)|
|Corner Library|0.03|(0.18)|0.03|(0.18)|0.03|(0.17)|
|Source: SDI 2016|||||||

A1-7