rafmacalaba/data-use-mentions-extended huggingface dataset:
and demand will respond to price changes—even if the short-run elasticities are low, which would make prices stationary. If prices are stationary, however, it is optimal to maximize extraction when prices are high and to minimize it when prices are low. This would cause government revenues to be more volatile than price; if at the same time consumption is to stay largely unaffected, in accordance with the PIH, fluctuations in revenues should be absorbed largely by capital expenditure and the fiscal balance.

The theory of optimal resource abstraction assumes that the resources in the ground are finite and known. This is very much a matter of debate, particularly in relation to oil, where new technology such as fracking has made more reserves accessible.

In terms of assessing fiscal performance, a natural test is whether resource wealth is associated with higher government saving or, in other words, whether there is less government consumption expenditure relative to revenue, and whether the saving takes the form of a stronger fiscal balance or higher capital expenditure. This is the issue that we address here. A second aspect of the resource curse issue, which we do not discuss here, is the possibility that even when the revenues are largely saved, they may nevertheless be wasted—for example, in ill-conceived or inefficiently implemented investment projects.

# **3. Resource Wealth and Fiscal Performance**

In this section we examine the correlation between resource wealth and a number of fiscal variables, using annual data for low- and middle-income countries back to 1996. Fiscal data are scarce before that date, so the sample can be extended further back for only a very few countries.

We capture resource wealth by the share of exports represented by fuel or ores and metals, transformed into dummy variables that are equal to 1 if the export share is above a threshold level. For fuels, we use a threshold of 25 percent; for ores and metals, the threshold is 10 percent. Each of these dummy variables is equal to 1 for just over 20 percent of
A third component of the program is community development service (CDS). One day each week, instead of working at the place of primary assignment, corps members work on community service projects in teams. CDS teams serve in a variety of ways such as environmental sanitation and beautification projects, HIV sensitization, extra-mural classes for secondary school students, road safety campaigns, among others. Lastly, at the end of the year, upon receipt of a clearance letter from participants’ primary employers confirming satisfactory completion of their duties, NYSC issues a certificate of completion to corps members in a passing out ceremony (NYSC 2015a).

# **3 Data**

## **3.1 Alumni Data**

The data for this paper come from alumni administrative records and a phone survey with previous NYSC participants from a Nigerian university. This university is a large public university with fees subsidized by the government, so it attracts students from different socioeconomic backgrounds. The university is in a Yoruba majority region and about 75 percent of students are Yoruba. The analysis is limited to Yoruba participants as there were too few participants from each of the other ethnic groups for meaningful inferences to be drawn. Besides, since non-Yoruba participants had been living in a Yoruba region throughout their undergraduate studies, they have in some way been “treated” with intergroup exposure.

The administrative data includes the following variables: name, gender, date of birth, state of origin,<sup>12</sup> matriculation cohort, date of graduation, course studied at matriculation, course studied at graduation, and marital status at graduation. The university also had

> 12State of origin in Nigeria refers to the state in which an individual’s traditional hometown/ village is located, regardless of whether the person has ever lived there.

10
**Table A2:** Orthogonality Check: Untargeted vs Targeted

||(1)<br>Untargete|(2)<br>d HHs in...|(3)|(4)|
|---|---|---|---|---|
||Control<br>Clusters|Treated<br>Clusters|Targeted<br>HHs|p-value<br>of F-test|
|_Household Characteristics_|||||
|Household size|3.263|3.354|3.482|0.230|
|Household head is female|0.449|0.466|0.455|0.802|
|Education of head of household (years)|3.122|3.024|2.812|0.590|
|Satisfed with overall house quality (1=Yes)|0.280|0.236|0.270|0.442|
|Satisfed with quality of the house foor (1=Yes)|0.119|0.129|0.085|0.221|
|Satisfed with wall quality (1=Yes)|0.169|0.163|0.177|0.871|
|<br>Satisfed with roof quality (1=Yes)|0.145|0.163|0.169|0.919|
|Satisfed with quality of family life (1=Yes)|0.178|0.209|0.186|0.719|
|Quality of Life Index (ICV)|1.333|1.260|1.307|0.275|
|Hours at home per day|6.576|6.315|6.445|0.927|
|_House Characteristics_|||||
|House with dirt foor (1=Yes)|0.822|0
0.153)||
|Sexual activity index||||
|treatment x post|-0.097<br>(0.096)|-0.000<br>(0.071)|1,542|

_Notes._ The table presents estimates of _β_ 1 in column 1 from estimating equation 1 in Panel A and equation 2 in Panel B. Column 2 presents the outcome mean at endline in ELA only communities among females (males) who were not assigned to the _Goal_ treatment (whose connected female was not assigned to the _Goal_ treatment), and column 3 shows the number of observations. See Tables 2 and 3 for outcome definitions and control variables. Standard errors, clustered at the club level, are presented in parentheses below coefficients estimates in column 1. .01 ***, .05 **, .10 *. _Source._ Panel A: Female baseline and endline data, balanced panel. Panel B: Male baseline and endline data, balanced panel. The sample in the _Boys_ treatment arm is restricted to females with males in their network who enrolled in _Boys_ treatment in Panel A and to males who enrolled in _Boys_ treatment in Panel B.

65
(professional services and technical assistance);

- i) "Premios de Otros Seguros" (insurance for other risks);

- J) "Despesas com viagens e representacao"

- (travel and entertainment costs);

- k) "Indenizacao por dispensa" (reimbursement of expenses);

- 1) "Imposto Predial e Territorial Urbano" (urban real estate taxes);

- m) "Impostos e taxas" (excise duty and other indirect taxes);

- n) "Combustiveis e Lubrificantes consumidas no transporte proprio" (gasoline and oil consumption for enterprise vehicles);

- o) "Outros despesas" (other costs);

- 4) In order to arrive at the former national accounts concept of value added we must further deduct "Juros e correcao monetaria e despesas bancarias" (interest and monetary correction payments and bank service charges);

- ' See table 15 of Censo Industrial (1981a), which gives the figures for firms with 5 employees or more (or a gross output more than 640 times the minimum wage). Table 35 gives similar information in more aggregated form for firms with less than 5 employees (or with a gross output less than 640 minimum wages)
>0 Rep. Vietnam Peru Colo mbia 0 Vietnam Philippines Rep. Peru Colombia<br>50% 70% 90% 110% 80% 100% 120% 140%<br>Full-Cost Recovery Financial Operating Cost Recovery (Cash Collected)<br>e) Full-Cost Recovery and f) Financial Operating Cost Recovery and<br>Security of Supply Indicator Security of Supply Indicator<br>250% 250%<br>Uganda Uganda<br>Egypt, Arab Egypt, Arab<br>200% Rep. Kenya 200% Kenya Rep. R2 = 0.1828<br>150% 150%<br>Peru Peru<br>Vietnam Colombia<br>R2 = 0.0009 Vietnam Colombia<br>100% 100%<br>Senegal Senegal<br>50% Tanzania Philippines 50% Tanzania Philippines<br>Pakistan Pakistan<br>0% 0%<br>50% 70% 90% 110% 80% 100% 120% 140%<br>Full-Cost Recovery Financial Operating Cost Recovery (Cash Collected)<br>T&D Losses T&D Losses<br>Number of Outages per Month Number of Outages per Month<br>Security of Supply Indicator Security of Supply Indicator<br><!-- End of picture text --> _Note:_ Graphics only show subset of cases for which data is available. _Source:_ World Bank staff.

38
that are net-buyers gain nearly 1.1 percent of their consumption (Table 6, Panel B). These changes in their consumption are, however, a small fraction of their total consumption. As a result, these

> 5 Household expenditure is used as a proxy for income.

> 6 The results are similar in 2010/11 (IHS3) and included in Appendix Tables A.3 – A.5.

> 7 This does not necessarily mean that the amount of gain is higher for rural residents but that the gain is a larger share of their initially low consumption.

24
.09]<br>1,480<br>0.46<br>-0.09<br>[0.11]<br>1,708<br>0.48<br>Yes<br>Yes<br>Yes<br>Yes<br>No|
|lumn represe<br>o tarnish you<br>eyed househ<br>s. Panel B.2<br>ove the prog<br>y variable eq|Model 3<br>Overall<br>(7)|-0.02<br>[0.04]<br>2,316<br>0.49<br>0.07<br>[0.06]<br>1,466<br>0.5<br>0.00<br>[0.05]<br>1,690<br>0.51<br>Yes<br>Yes<br>Yes<br>Yes<br>No|
|fault. Each co<br>would this be t<br>sample of surv<br>ng land record<br>bservations ab<br>s and a dumm|Informal<br>lenders<br>(6)|0.10<br>[0.06]<br>2,439<br>0.35<br>0.17+<br>[0.09]<br>1,544<br>0.37<br>0.10<br>[0.08]<br>1,791<br>0.36<br>Yes<br>Yes<br>No<br>Yes<br>No|
|ences of de<br>how likely<br>ng the full<br>and matchi<br> 25% of o<br
- The first global map of mangrove forests using remotely sensed data (Giri et al. 2011): this map uses over 1,000 Landsat scenes acquired between 1997 and 2000, with supervised and unsupervised digital image classification, to construct a 30 resolution map of global mangrove distribution, and estimates a total mangrove extent of 13.7 million hectares in 118 countries and territories in the world’s tropical and subtropical regions. mm<sup>2</sup>

Spalding, Blasco and Field (1997) estimate that there are 880,173 hectares of mangrove forest in the 29 countries and territories selected for this study. Of these, Cuba and The Bahamas have the most extensive mangrove areas, with approximately 556,900 and 211,400 hectares, respectively. Giri et al. (2011), on the other hand, find that mangroves extend over 616,440 hectares in the 26 Caribbean countries and territories studied (excluding Dominica, Montserrat, and Sint Maarten). They also estimate that Cuba (440,641 hectares) and The Bahamas (82,408 hectares) have a larger mangrove areas, although these differ from Spalding, Blasco and Field (table 2).

**Table 2. Mangrove areas in Caribbean countries and territories (hectares)**

|Country/Territory|Spalding, Blasco<br>and Field (1997)|Giri et al.<br>(2011)|Country/Territory|Spalding,<br>Blasco and<br>Field(1997)|Giri et al.<br>(2011)|
|---|---|---|---|---|---|
|Anguilla|90|5|Haiti|13,400|15,496|
|Antigua and Barbuda|1,316|973|Jamaica|10,600|9,817|
|Aruba|420|79|Martinique|1,587|1,197|
|
constant with respect to time. More recently, observational data has been used to estimate potentially non-constant time-discount functions. This literature, which restricts itself to estimating quasi-hyperbolic discount functions, includes Paserman (2008), Fang and Silverman (2009) and Laibson et al. (2007). We depart from this literature by adopting experimental methods for eliciting intertemporal choices and working with non-parametric measures of patience and “present”-bias.

The experimental literature on time preference is large. Frederick et al. (2002) offer a review. More recent examples include, Andersen et al. (2008), Benhabib, et al. (2010), and Andreoni and Sprenger (2011). As noted above, we adapt to our field environment the methods that Andreoni and Sprenger (2011) developed for use in the lab. A key advantage of their design is that, with a convex choice set, it permits the relatively rapid collection of information on intertemporal choice in the face of several different rates of return. The method thus allows analysis of the consistency of choice with the law of demand as well as quantitative measures of the degree of dynamic inconsistency.

Most recently, experimental studies of time preference have been taken into the field, often in developing countries. Prominent examples include Harrison et al. (2005), Ashraf et al. (2006), and Tanaka et al. (2009). Two such field experiments are closely related to ours and thus merit special consideration. The first, Ashraf et al. (2006), asked a sample of 1,777 in the Philippines hypothetical time preference questions on a survey. Later, a subset of this sample was offered a commitment saving product. Women who exhibited present-biased preference reversals on the survey questions were, as predicted by theory, more likely to take up the commitment saving product. Our paper differs from this prior study, most importantly, by studying directly the link between incentivized intertemporal allocation decisions and revision of prior choices. We measure the extent
undermine democratic institutions and the rights of the poor, and thereby lower public investments in pro-poor policies (Stokes, 2005, 2007; Vicente and Wantchekon, 2009; Banerjee et al, 2011; Vicente and Collier, forthcoming).<sup>11</sup> Baland and Robinson (2006) provide related evidence that the introduction of the secret ballot, in Chile around 1958, which presumably reduced the efficacy of clientelist strategies, reduced the vote share of right-wing parties. Another strand of the literature examines clientelism as a form of inefficient redistribution which arises from the lack of credibility of political promises (Acemoglu, 2001; Robinson and Verdier, 2003; Robinson and Torvik, 2005; Keefer and Vlaicu, 2008). In these models, the inherent inefficiency in clientelistic redistribution has negative implications for broad public goods, such as institutions of good governance (rule of law, protection of property rights, etc.), and progrowth policies.

However, it is also conceivable that some forms of vote buying could be a result of political responsiveness to the needs of the poor (Schaffer, 2005, 2007). The selection of vote buying political strategies could, potentially, go hand-in-hand with pro-poor public policies. The received theory is insufficient to draw firm conclusions in this regard. This paper is the first to provide direct empirical evidence on the issue, using a deliberately designed survey to measure both vote buying and service delivery at an appropriate jurisdictional level. It reveals that where political contestation using vote buying strategies—offers of money in exchange for votes during elections—is more widespread, politicians reduce investments in primary health services. The service delivery instruments around primary health that municipalities in the Philippines are responsible for, are particularly likely to be broadly pro-poor in delivering benefits.<sup>12</sup> Indeed, poverty research suggests that these types of health services have the potential to serve as effective instruments to combat poverty, particularly when poverty is widespread (Besley and Coate, 1991, and Van DeWalle and
, require major liens and collateralization, and place guaranteed debt repayments in state-owned enterprises (G30 2021). For example, since 2015, Chinese lenders have made heavy use of confidentiality clauses in their debt contracts (Gelpern et al. 2021). From 2015 onwards, all of the more than 30 debt contracts by Chinese lenders to EMDE sovereigns that Gelpern et al. (2021) examined included unusually restrictive confidentiality clauses.

Some commodity traders or large financial firms lending to EMDE governments similarly fail to share contract information (G30 2021). Opaque lending is compounded by contractual obligations that preclude restructuring of some debts. For example, of 100 debt contracts by Chinese lenders to 24 EMDE sovereigns since the early 2000s examined by Gelpern et al. (2021), three-quarters included clauses that explicitly exclude the debt from Paris Club restructuring agreements.

Governance shortcomings. Many EMDEs, particularly LICs, still fall short in the strength of institutions that create distance between borrowing decisions and political pressures, as reflected in the low share of LICs that meet minimum requirements for debt administration, legal frameworks, and audit practices (World Bank 2019). This increases the risk that borrowing is excessive and not used for productive purposes. The perceptions of quality of public services are the worst in SSA, where most LICs reside. An index of government effectiveness suggests that the effectiveness of government services in SSA is almost twice as bad as that in MNA and SAR, on median (Kaufmann, Kraay, and Mastruzzi 2010). ECA and LAC are the best performers in terms of the perceptions of service quality, but they are still well behind advanced economies.

Global debt resolution practices. In several dimensions, the playing field is currently tilted in favor of creditors and discourages prompt and comprehensive debt resolution. For example, financial centers that adjudicate disputes related to debt restructuring—especially New York, where twothirds of outstanding sovereign bonds are governed—have provisions that favor hold-out bond holders. These include prejudgment penalties, large exemptions for buying bonds at steep discounts before
# Migration and Urbanization in Post-Apartheid

# South Africa<sup>_∗_</sup>

Jan David Bakker, Christopher Parsons, Ferdinand Rauch

**JEL Codes:** R12, R23, N97, O18

**Keywords:** Economic geography, migration, urbanization, natural experiment

> _∗_ Jan David Bakker is a Phd student at the University of Oxford (email: jan.bakker@economics.ox.ac.uk), Christopher Parsons is Associate Professor at the University of Western Australia (email: christopher.parsons@uwa.edu.au), Ferdinand Rauch (corresponding author) is Associate Professor at the University of Oxford (email: ferdinand.rauch@economics.ox.ac.uk). We gratefully acknowledge the support of the Africa Research Program on Spatial Development of Cities at Oxford and the London School of Economics funded by the Multi Donor Trust Fund on Sustainable urbanization of the World Bank and supported by the UK Department for International Development. We thank Daniel de Kadt and Melissa Sands who shared census data from 1991. We thank Frederic Giraut and Celine Vacchiani-Marcuzzo who shared the Dysturb dataset. We are grateful to Matteo Escudé, James Fenske, Doug Gollin, Vernon Henderson, Leander Heldring, Daniel Kaliski, Daniel de Kadt, Lu Liu, Chris Roth, Ludvig Sinander, Andrea Szabo, Tony Venables, Helene Verhoef, Johannes Wohlfart and seminar participants at Oxford, the Economic Geography and International Trade Research Meeting 2017 and the Annual Bank Conference on Africa 2016 for useful comments and discussion.
randomization strata. In Panel A, Psychological abuse often (in last year), Physical abuse often (in last year), and Forced sex often (in last year) are binary indicators for the female reporting experiencing psychological abuse, physical abuse, or forced sex often (in last year) within the 12 months prior to survey, respectively. In Panel B, the measures are binary indicators for the female reporting ever having sex, having a current partner, and having a partner in the past 2 years; and continuous indicators for total number of sex partners ever and reported hours spent with her boyfriend in the past day. Standard errors, clustered at the club level, are presented in parentheses below coefficient estimates in columns 2 and 4. The _χ_<sup>2</sup> p-value in the last row is the p-value from a test of the joint significance of all outcomes in Panel A and B in predicting treatment assignment to the _Boys_ arm in column 2 and to the _Goal_ arm in column 4 using a logit model, controlling for randomization strata and clustering standard errors at the club level. .01 ***, .05 **, .10 *. _Source._ Female baseline data.

48
of age who received at least 2 milk feedings and had at least the minimum dietary diversity not including milk feeds and the minimum meal frequency during the previous day.

> 37 Chawanpaiboon S, Vogel JP[1], Moller AB, Lumbiganon P, Petzold M, Hogan D, Landoulsi S, Jampathong N, Kongwattanakul K, Laopaiboon M, Lewis C, Rattanakanokchai S, Teng DN, Thikhamthrop J, Watananirun K, Zhang J, Zhou W, Gülmezoglu AM. Global, regional and national estimates of levels of preterm birth in 2014: a systematic review and modelling analysis. Lancet Glob Health. 2018. 30 Oct. doi.org/10.1016/S2214-109X(18)30451-0

> 38 In contrast to the DHS survey, the NNS’s indicator of LBW prevalence uses the denominator of all living children (rather than all live births).

> 39 Katz J, Lee ACC, Kozuki N, et al. Born too small or too soon: a pooled analysis of mortality risk among preterm and small-for-gestational-age infants in low- and middle-income countries. Lancet. 2013

> 40 World Bank (2018) “Operationalizing a Multi-Sectoral Approach for the Reduction of Stunting in Indonesia: An application using the 2007 and 2013 Riskesdas” The World Bank, Washington D.C. http://documents.worldbank.org/curated/en/docsearch/report/114207

> 41 World Bank (2018) “All Hands on Deck: Reducing Stunting through Multisectoral Efforts in SubSaharan Africa.” The World Bank, Washington D.C. Report: http://documents.worldbank.org/curated/en/260571530132166786/ Annex: http://documents.worl <u>dbank.org/curated/en/467711529406437446/</u>

> 42 Skoufias, E., K. Vinha, and R. Sato (2019) “Reducing Stunting through Multisectoral Efforts in SubSaharan Africa.” Journal of African Economies (forthcoming)

> 43 Prendergast, Andrew J and Jean
2017 <!-- Start of picture text --> Total<br>Men<br>Women<br>Richest<br>Q4<br>Q3<br>Q2<br>Poorest<br>Non Poor<br>Poor<br>0 20 40 60 80 100<br>Percent<br>Salaried labour or labour paid in kind Run a non-farm business<br>Help in any kind of non-farm business Apprenticeship<br>Farming or hunting or fishing at own account<br><!-- End of picture text --> Source: Authors’ calculations based on HFSSS 2015, 2016 and 2017

# Figure A10: Hunger incidence over the past 4 weeks

<!-- Start of picture text --> 100<br>80<br>60<br>40<br>20<br>0<br>2015 2016 2017<br>Never Rarely (1-2 times) Sometimes (3-10 times) Often (more than 10 times)<br>Poorest Q2 Q3 Q4 Richest Poorest Q2 Q3 Q4 Richest Poorest Q2 Q3 Q4 Richest<br><!-- End of picture text --> Source: Authors’ calculations based on HFSSS 2015, 2016 and 2017 22
**<u>Figure5.1 Seasonal Fluctuation of Average Sales: Farm and Nonfarm</u>**

<!-- Start of picture text --> Farm Nonfarm<br>4<br>3<br>2<br>1<br>Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec<br><!-- End of picture text --> _Source:_ 2010 Yemen RIC Survey _Notes:_ 4 is the highest sales level, 3: the average sales level; 2 the low sales level; and 1 no sales Finally, rural income generation activities need to overcome seasonal fluctuation in sales by promoting farm and nonfarm enterprises together, and focusing on value addition activities by nonfarm enterprises (figure 5.1). Knowing the constraints for farm and nonfarm enterprises are similar, promotion activities should be focused on small rural enterprises of both farm and nonfarm. Farm and nonfarm enterprises need business management knowledge to earn more or improve profitability. Delgado et al. (1998) conclude that farm and nonfarm enterprises have economic multiplier effects. That is, when promoting rural enterprises, both farm and nonfarm enterprises should be targeted simultaneously in order to generate synergy effects to the rural economy, rural livelihood, and well-being of the poor.

# **6. Conclusion**

Through this study, four critical RIC components are identified to be improved: weak market demand, poor access to market, limited access to finance, and missing management service to rural entrepreneurs. Among those critical RIC components, providing business management services is a key component because management knowledge can increase market demand using marketing knowledge, increase access to market and inputs identifying appropriate transportation and technology, and increase access to finance improving financial literacy of rural entrepreneurs. The management knowledge would help rural entrepreneurs start, operate, and expand their farm and nonfarm businesses. Without increasing market demand, supply-side RIC improvement may not do any good. It is important to focus on increasing both demands and