rafmacalaba/datause-encoder-data huggingface dataset:
net to include the whole set of outcomes covered in the literature: output micro and macro, labor market inequality and poverty, trade, human capital, population, environment, and land Value. Hundreds of papers and several literature reviews have been published and their focus has evolved over time. The first generation of research was mostly analyzing growth and productivity effects, based on a production function framework and using public capital data in a panel cross-section framework.<sup>1</sup> More recently, with the increasing availability of more granular information, including geospatial data, and the computing power to process very large databases, the focus has shifted to studies analyzing a wide array of outcomes, specific sectors, and implementing robust micro-econometric identification strategies.<sup>2</sup> We built a database of over a thousand estimates from 221 papers reporting infrastructure elasticities or semi-elasticities that can readily be converted into comparable elasticities. The papers included are the result of a systematic search through literature reviews and publication databases and were produced between 1983 and 2023.

We then analyze this data, starting with a visual examination through funnel plots, and distribution plots of test statistics following Brodeur et al. (2023). We then implement several econometric methods. We start by providing basic FAT-PET-PEESE type estimates (Stanley and Doucouliagos, 2012). FAT estimates and Caliper tests allow us to characterize potential publication bias and p-hacking. To provide estimates of specific “true” underlying effects of infrastructure, we report PEESE estimates. We then analyze in more details the heterogeneity in the sample, by introducing a large list of moderators related to both study design, and infrastructure sector and context characteristics. We report results based on several selection methods of moderators, including rigorous penalization for the LASSO, LASSO with 10-fold cross-validation for tuning parameter selection, and several Bayesian Model Averaging methods. We report results by sectors, as well as sectoroutcomes.<sup>3</sup>

> 1See Straub (2011) for a critical review, and Bom and Ligthart (2014) for a meta-analysis of that specific strand of applications.

> 2See Foster et al. (2023) for a recent qualitative review of this evolution.

> 3We only include sector-outcomes categories with enough observations, but note that all outcomes still

3
Human Capital Index score in 2020, it still ranks ahead of only six other countries. The fluctuating nature of budgetary allocations of the Federal Government in areas like health, education, water and sanitation, in Naira terms and in terms of the share of the total government budget, do not seem to be encouraging or indicative of strong commitment to improve on the condition of children or on human capital in general. The additional availability of data on state and local government budget allocations in these areas, as well as the donor communities’ initiatives, may allow more focused impact evaluations of these initiatives on monetary and multi-dimensional deprivation-based child poverty across the country.

Further analysis will also be needed to find whether the adoption of the Child’s Rights Act is correlated with the level of deprivation. Its adoption though indicates a higher level of commitment and also creates an enabling environment for interventions to address different areas of deprivations of children. The Federal Government along with the States that have adopted the Act should therefore make a concerted effort to encourage remaining states to adopt the Act and to live up to the obligation of the constitution and ensure uniform protection for the children in Nigeria.

# 7 References

<mark>Abdu, M., & Delamonica, E. (2018). Multidimensional child poverty: From complex weighting to simple representation.</mark> _<mark>Social Indicators Research</mark>_ <mark>,</mark> _<mark>136</mark>_ <mark>(3), 881-905.</mark> <mark>Abramovsky, L., Augsburg, B., & Oteiza, F. (2015).</mark> _<mark>Sustainable Total Sanitation - Nigeria: Baseline Report</mark>_ <mark>. Institute for Fiscal Studies, Centre for the Evaluation of Development Policies: London</mark> <mark>Adebowale, N. (2019). UPDATED: 11 states in northern Nigeria yet to pass child rights law — UNICEF Official. Premium Times Nigeria – May 11, 2019. Retrieved 21 February 2021: https://www.premiumtimesng.com/news/more-news/329511-12-states-in-northern-nigeria-yet-topass-child-rights-law-unicef-official.html</mark> <mark>Adetola, A., & Olufemi, P. (2012). Determinants of child poverty in rural Nigeria: A Multidimensional Approach.</mark> _<mark>Global Journal of Human-Social Science Research</mark>_ <mark>,</mark> _<mark>12</mark>_ <mark>(12-A).</mark> <mark>Ajakaiye, O., Jerome, A. T., Olaniyan, O., Mahrt, K., & Alaba, O. A. (2016a). Measuring Multidimensional Poverty in Nigeria. In Arndt, C. and Tarp, F. (eds) (Chapter 13).</mark> _<mark>Measuring Poverty and Wellbeing in Developing Countries</mark>_ <mark>.</mark> Oxford University Press: Oxford, <mark>194-214.</mark> Ajakaiye, O., A. Jerome, O. Olaniyan, K. Mahrt, and O. Alaba (2016b). Spatial and Temporal Multidimensional Poverty in Nigeria. In Arndt, C., McKay, A. and Tarp, F. (eds) (Chapter 10). _Growth and Poverty in Sub-Saharan Africa_ . Oxford University Press: Oxford, 218–237.

59
and signs of amenities are clearly visible. The place is classified as urban in 56 of the 57 assessments we have for it. Conversely, Bahadurganj of Bihar is administratively urban, but its cropland areas are vast, the built-up area is relatively small, buildings are scattered, amenities are few, and the road network is limited both within and outside of the place (figure 4b). This place is considered rural in 42 out of 57 assessments available.

# **Figure 4. Examples of discrepancies with the administrative classification**

- a. **Jigani (Karnataka) is reclassified as urban**

- b. **Bahadurganj (Bihar) is reclassified as rural**

_Note_ : The yellow lines depict the digitized administrative boundaries for the respective administrative units.

According to the pooled classification, 43 percent of the 1,277 places in the sample are urban in practice, and 57 percent are rural (table 4). Therefore, the sampling strategy does ensure a balanced representation of rural and urban places. A nonnegligible fraction of statutorily urban places is classified as rural in practice. Discrepancies are also large for places deemed urban in terms of the census, many of which are 15
<!-- Start of picture text --> VA --- ¥YMOTIVADO UNA MAYOR DIVERSIFICACION DE<br>CONS Ame LAS CARTERAS DE LOS FONDOS DE PENSIONES<br>Ponderaciones por clase de activo en las Cartera de las Siefores<br>or 0.0%<br>100% ULTIMOS DOS ANOS JN<br>95% 9.0%<br><!-- End of picture text --> <!-- Start of picture text --> —_, 3.040<br>85%<br>8.6% 2.0%<br>80% 2.6% 55%<br>75% pli<br>TOM 4.1%<br>O65- 17.5%<br><!-- End of picture text --> <!-- Start of picture text --> 55%<br>59.2%<br>50M 50.7%<br>SSSSESSSRSSSRSSSESSASSSsrsggegagaa :<br>@ Gubernamental @ Privados rT] t m@ RV Nacional @ D | @ RV Internacional<br>Nacionales Ml Mercancias |<br>Cifras alcierre de julio de 2013. i2<br><!-- End of picture text -->

<!-- Start of picture text --> 90% +<br>B0% —<br>7O% +<br>60% —<br>50% —<br>40% -—<br><!-- End of picture text --> <!-- Start of picture text --> 30% +<br>20% 4+<br>10% — ‘<br>RSRKRFSRSERRSSSSSSSSSRSSRSAI9IRSA<br>SsSRSFRBSEFSEPSESCESFEFPSEFEPERESEE<br>—Foreign Investment Limit — Foreign Investment (% of Assets)<br><!-- End of picture text -->
Policy Research Working Paper 8266

# **Abstract**

This paper shows that reference letters from former employers alleviate information asymmetries about workers’ skills and improve both match quality and equity in the labor market. A resume audit study finds that using a reference letter in the application increases callbacks by more than 60 percent, with women driving the effect. Letters are effective because they provide valuable information about workers’ skills that employers use to select applicants of higher ability. A second experiment, which encourages job seekers to obtain and use a reference letter, finds consistent results. In particular, employment rates for women encouraged to obtain a letter increase by 49 percent, closing the gender gap in the sample.

This paper is a product of the Jobs Group and Africa Gender Innovation Lab. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://econ.worldbank.org. The authors may be contacted at mabel@middlebury.edu.

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
# **6 Conclusion**

In this paper, we estimate heterogeneous economic returns to SC programs in Colombia. We account for the self-selection of students across multiple higher education alternatives (bachelor’s programs, SC programs, and not enrolling in higher education). In line with the literature, we show that the effects of SC programs largely differ depending on the fallback alternative (next-best option) of students. We use an Instrumental Variables (IV) approach, where identification comes from the supply of SC programs at the municipal level. More specifically, we define a binary instrument to indicate whether a municipality has an institution specialized in offering SC programs in a 10-kilometer radius.

We present three main findings. First, we document 3.7-4.5 pp increase in SC program enrollment as the local supply of these programs rises. Students who respond to the supply increase (compliers) are concentrated in municipalities where bachelor’s programs were already available. Second, at least 70% of compliers would react along the diversion margin, switching from bachelor’s programs into SC programs. The remaining 30% would react along the expansion margin, entering the higher education system. These patterns are similar for males and females. Third, females experience gains from SC programs in terms of formal employment while males experience losses in formal employment and wages. Based on the high diversion share and the fact that males are more advantaged and better prepared academically than females, we argue that SC programs might constitute an “undermatch” for males, who might have otherwise attended good bachelor’s programs, but a better match for females, who might have otherwise attended low-quality bachelor’s programs.

While different from findings for the U.S., our findings can be reconciled with those. Using data from Texas, Mountjoy (2022) finds that the expansion margin share is about two-thirds, much higher than our 30%. One possible explanation for this discrepancy is that SC programs (typically taught at community colleges in the U.S.) are often viewed as an entry point into the higher education system, with students intending to transfer to bachelor’s programs. In Colombia, in contrast, SC degrees are viewed as terminal and rarely offer a pathway towards a bachelor’s program, as they mostly focus on facilitating the school-to-work transition. Another possible explanation is that many community colleges in the U.S. are located outside large cities, where they constitute the only higher education option for local students. In contrast, during our sample period SC programs in Colombia were mostly offered in large and medium cities that already other higher education options, leaving little room for newly entering students into the system. Further, Mountjoy (2022) finds that compliers along the expansion margin are more likely than those on the diversion margin to benefit in terms of average earnings and years of 19
Kose, M. A., and M. E. Terrones. 2015. Collapse and Revival: Understanding Global Recessions and Recoveries. Washington, DC: International Monetary Fund.

Kose, M. A., and K.-M. Yi. 2006. “Can the Standard International Business Cycle Model Explain the Relation between Trade and Comovement?” Journal of International Economics 68(2): 267295.

Laeven, L., and F. Valencia. 2018. “Systemic Banking Crises Revisited.” IMF Working Paper 18/206, International Monetary Fund, Washington, DC.

Lane, P. R., and G. M. Milesi-Ferretti. 2018. “The External Wealth of Nations Revisited: International Financial Integration in the Aftermath of the Global Financial Crisis.” IMF Economic Review 66(1): 189-222.

Levchenko, A. A., L. T. Lewis, and L. L. Tesar. 2010. “The Collapse of International Trade during the 2008–09 Crisis: In Search of the Smoking Gun.” IMF Economic Review 58(2): 214-253.

Martínez-García, E., V. Grossman, and A. Mack. 2015. “A Contribution to the Chronology of Turning Points in Global Economic Activity (1980-2012).” Journal of Macroeconomics 46: 170185.

Mauro, P., R. Romeu, A. Binder, and A. Zaman. 2015. “A Modern History of Fiscal Prudence and Profligacy.” Journal of Monetary Economics 76: 55-70.

Medas, P., T. Poghosyan, Y. Xu, J. Farah-Yacoub, and K. Gerling. 2018. “Fiscal Crises.” Journal of International Money and Finance 88: 191-207.

Meller, B., and N. Metiu. 2017. “The Synchronization of Credit Cycles.” Journal of Banking and Finance 82: 98-111.

Milesi-Ferretti, G.-M., and C. Tille. 2011. “The Great Retrenchment: International Capital Flows during the Global Financial Crisis.” Economic Policy 26(66): 285-342.

Mumtaz, H., S. Simonelli, and P. Surico. 2011. “International Comovements, Business Cycle and Inflation: A Historical Perspective.” Review of Economic Dynamics 14(1): 176-198.

Mussa. M. 2009. “World Recession and Recovery: A V or an L?” Paper presented at the fifteenth semiannual meeting on Global Economic Prospects, Peterson Institute of International Economics, April 7, Washington, DC.

OECD (Organisation for Economic Co-operation and Development). 2019. Tax Policy Reforms 2019: OECD and Selected Partner Economies. Paris: OECD Publishing Owyang, M. T., J. Piger, and H. J. Wall. 2005. “Business Cycle Phases in U.S. States.” Review of Economics and Statistics 87(4): 604-616.

Pagan, A., and K. A. Sossounov. 2003. “A Simple Framework for Analysing Bull and Bear Markets.” Journal of Applied Econometrics 18(1): 23-46.

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Perry, G., and C. L. Schultze. 1993. “Was This Recession Different? Are They All Different?” Brookings Papers on Economic Activity 1993(1): 145-211.

Rachel, Ł ., and L. H. Summers. 2019. “On Falling Neutral Real Rates, Fiscal Policy, and the Risk of Secular Stagnation.” BPEA conference draft, Brookings Institution, March 7-8, Washington, DC.

28
**Figure 1: Petroleum Proven Reserves and Figure 2: Natural Gas Proven Reserves Production (1980-2009) (1980-2009)**

<!-- Start of picture text --> 40 1000 6<br>900<br>35 5<br>800<br>30<br>700 4<br>25<br>600<br>3<br>20 500<br>400 2<br>15<br>300<br>10 1<br>200<br>5 0<br>100<br>0 0<br>Proven Reserves Petroleum Production Nigeria Other Africa<br>Sources: BP 2010. Sources: BP 2010.<br>Proven Reserves Billion Barrels Production MillionBarrels Trillion cubic meters<br>1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008<br><!-- End of picture text --> 9. Approximately 70 percent of Nigeria‘s oil production is accomplished by joint ventures (JVs) and another 25 percent by production-sharing contracts (PSCs). Five major international oil companies (IOCs)—Shell, Exxon-Mobil, Chevron-Texaco, Total, and Agip—currently are engaged in JV operations with the Nigerian government. In these JVs, the Nigerian government (via NNPC) holds 60 percent of the equity. The government has created many efforts to bring indigenous companies into oil production via marginal fields and other schemes, but so far they are not major players in the industry.

10. The Federal Government holds all mineral rights and is responsible for the allocation of exploration and development licenses. Oil revenue consistently accounts for over two thirds of public revenues. Similarly, oil and gas exports accounted for 97 percent of total exports in 20082009 (Figure 3). While rents have increased by almost fourfold from US$ 20 billion in 2000 to 47 billion in 2008, petroleum rents as a share of gross national income has generally decreased during the same period (Figure 4).

10
<!-- Start of picture text --> Figure 1: Aggregate Activity Share of Value Added Figure 2: Formal Employment by Skill Level (2000)<br>60.0%<br>55.0%<br>4% 50.0%<br>45.0%<br>27% 40.0%<br>35.0%<br>30.0%<br>25.0%<br>20.0%<br>69%<br>15.0%<br>10.0%<br>5.0%<br>0.0%<br> Legislators, senior Professionals Technical and associate Semi-Skilled Elementary Occupation<br>Agriculture Industry Service officials and managers professionals Skill Levels<br>Source: Authors’ calculations from a Social Accounting Source: Authors’ calculations from LFS 2000.<br>Matrix (SAM) for South Africa, 2003.<br>% o f fo rm a l e m p lo y e d<br><!-- End of picture text -->

**_Labor in South Africa._** There are three types of labor (formal, self-employed, and informal) and three skill levels (high-skilled, semi-skilled, and low-skilled) within each type of labor. Value added is allocated to primary factors and summarized in Table 2.

Table 3 shows the distribution of employment by sector and occupation. About 6 people out of ten are employed in the services sector. About the same ratio are engaged in formal sector work. With respect to the distribution of skills, the data show that about 12 percent of those employed are highly skilled; over 45 percent of labor in South Africa is employed in the lowskilled and medium-skilled formal sector and another 19 percent in the informal sector.

**Table 2: Value Added Shares**

||Agriculture|Industry|Services|
|---|---|---|---|
|Capital|0.76|0.54|0.45|
|High-skilled formal labor|0.03|0.12|0.25|
|Semi-skilled formal labor|0.02|0.12|0.18|
|Low-skilled formal labor|0.11|0.15|0.04|
|Self-employed labor*|0.04|0.03|0.04|
|Informal labor*|0.04|0.04|0.04|

*Self-employed and informal labor are further distributed by skill (not shown).

Source: Authors’ calculations from a SAM for South Africa, 2003.

- 9 -
that, many argue, forces companies to export the oil, since exports are not subject to the sales tax. As a result local demand is met by imported oil.

Until 2005, the government took an active part in negotiations between the ginners and the cottonseed‐processing companies, in order to ensure that seed supplies were sufficient to keep the processing companies in business. Currently, the price of cottonseed is a result of negotiations between the ginning and seed‐ processing industries. While it has been reported that ginners often do not honor the agreement and export part of their cottonseed if that will yield them a higher price, the figures reported in Table C1 indicate that this does not happen on a large scale. In fact, during 2009, more seed was crushed in Benin than domestic production—perhaps reflecting unrecorded imports of cottonseed from neigh‐ boring countries, assuming that the statistics are accurate.

Table C2 reports detailed price and quantity statistics for one of the two companies surveyed. Prices paid for seeds increased considerably during the past three seasons from 22,500 CFAf per ton in 2006/07 to 46,000 CFAf per ton in 2007/08 and 70,000 CFAf per ton in 2008/09 (the prices paid to farmers in these three seasons were 170, 170, and 190 CFAf per kg). However, the prices received by the company for cotton oil did not increase much: they rose from 500,000 in 2006/07 to 600,000 in 2007/08 and then declined back to 500,000 CFAf per ton in 2008/09. If the numbers are correct, they imply that the domestic market is somewhat isolated from the international markets of edible oils.

**Table C2**

**Price and Quantity Statistics for Benin and SHB, 1999‐2009**

||**_‐‐‐‐‐‐‐‐‐‐‐_**<br>|**_‐ Quantitie_**<br>|**_s (tons)‐‐‐‐_**<br>|**_‐‐‐‐‐‐‐‐‐‐_**<br>|**_‐‐‐‐‐‐‐‐‐‐‐_**<br>|**_‐‐‐ Prices (_**<br>|**_CFAf/kg) ‐_**<br>|**_‐‐‐‐‐‐‐‐‐‐‐_**<br>|
|---|---|---|---|---|---|---|---|---|
||**_Cotton_**|**_Seed_**|**_Oil_**|**_Meal_**|**_Cotton_**|**_Seed_**|**_Oil_**|**_Meal_**|
|**1999/00**|364,000|27,000|4,000|14,700|185|26|—|—|
|**2000/01**|336,000|62,000|12,000|29,000|200|29|390|90|
|**2001/02**|415,000|100,000|16,000|32,000|200|28|440|66|
|**2002/03**|334,000|75,000|13,000|32,000|180|33|390|56|
|**2003/04**|332,000|92,000|14,000|37,000|190|37|500|37|
|**2004/05**|427,000|105,000|9,700|26,000|201|30|445|40|
|**2005/06**|191,000|33,000|9,800|22,000|170|23|450|37|
|**2006/07**|271,000|57,000|9,600|23,000|170|23|500|54|
|**2007/08**|269,000|78,000|12,000|22,000|170|46|600|100|
|**2008/09**|216,000|57,000|8,500|22,000|221|70|500|100|

**Notes:** The first and fifth columns refer to the entire country’s seed cotton crop while the remain‐ ing columns refer to SHB. The seed price during 2006/07 ranged from CFAf 15 to 30 per kg. ‘—’ means not reported. Cotton prices refer to final payments (base price plus supplement). **Source:** Zanfongnon (2009).

**_Page 42_**
## (b) Per Capita Food Consumption

<!-- Start of picture text --> 6000<br>Urban Rural<br>5000<br>4000<br>3000<br>2000<br>1000<br>0<br>SDGs<br><!-- End of picture text --> _Source:_ Authors’ calculations using NHBPS 2014/15. _Note:_ Calculations use yearly equivalents based on consumption in the last 10 days.

# Assets

Asset ownership is generally lower for the poor than the non-poor, and lower for rural households than urban households (Figure 18Figure 18). Assets that improve connectivity and increase access to information, such as televisions, satellite dishes, radios, mobile phones, phones, and computers, are more common in urban areas than in rural areas, while the poor have very little access to these resources. This means that sharing agricultural information with farmers, especially poorer farmers, can be a challenge. However, cell phones are now common in rural areas, with 70 percent of rural households owning one. Cell phone coverage is only 60 percent for the rural poor.

Motorized transport assets, such as motor vehicles, rickshaws, and motorcycles, remain low throughout Sudan but are more common in urban areas and are almost nonexistent among the rural poor. Rural areas have significantly higher rates of asset ownership of animals used for transportation; this is especially true for the rural poor. Limited ownership of transportation assets and an inadequate transportation network can impede access to productive inputs, such as fertilizers and pesticides, and reduce the opportunity to market surplus agricultural produce.

19