rafmacalaba/datause-encoder-data huggingface dataset:
# **7. References**

Alasuutari, Hanna. 2020. Tackling inequity in education during and after COVID-19. Available online at https://blogs.worldbank.org/education/tackling-inequity-education-during-and-after- <u>covid-19.</u>

- Alexander, Karl, Sarah Pitcock, and Matthew C. Boulay. 2016. The Summer Slide: What We Know and Can Do About Summer Learning Loss. Teachers College Press.

- Al-Samarrai, Samer and Cerdan-Infantes, Pedro and Lehe, Jonathan David, Mobilizing Resources for Education and Improving Spending Effectiveness: Establishing Realistic Benchmarks Based on Past Trends. 2019. World Bank Policy Research Working Paper No. 8773. <u>(http://hdl.handle.net/10986/31399)</u>

- Al Tuwaijri, Sameera Maziad, Seemeen Saadat, Roberta V. Gatti, Laura Rawlings, Hana Brixi, Zelalem Yilma Debebe, Ramesh Govindaraj, Kelly Johnson, Maya Brahmam, Aaron F Buchsbaum, Amer Hasan, Kavita Watsa, Alexander Leipziger, Mohamed Abdel Jelil; Salina Giri, Junya Yuan, Nuoya Wu. 2020. Protecting People and Economies : Integrated Policy Responses to COVID-19. Washington, D.C.: World Bank Group. Available online at http://documents.worldbank.org/curated/en/879461587402282989/Protecting-People-andEconomies-Integrated-Policy-Responses-to-COVID-19

- Alter, George and William Becker. 1985. Estimating lost future earnings using new work life tables. Monthly Labor Review, February.

- Alradhawi, M., Shubber, N., Sheppard, J., & Ali, Y. (2020). Effects of the COVID-19 pandemic on mental well-being amongst individuals in society- A letter to the editor on “The socioeconomic implications of the coronavirus and COVID-19 pandemic: A review.” International Journal of Surgery (London, England), 78, 147–148. https://doi.org/10.1016/j.ijsu.2020.04.070

- McClain-Nhlapo, Charlotte. 2020. “An Inclusive Response to COVID-19: Education for Children with Disabilities | Blog | Global Partnership for Education.” 2020. Accessed June 9, 2020. <u>https://www.globalpartnership.org/blog/inclusive-response-covid-19-education-childrendisabilities.</u>

- <mark>Andrabi, T., Daniels, B., Das, J. 2020. Human Capital Accumulation and Disasters: Evidence from the Pakistan Earthquake of 2005. RISE Working Paper Series. 20/039. https://doi.org/10.35489/BSG-RISE-WP_2020/039.</mark>

- Andrew, Alison, Sarah Cattan, Monica Costa Dias, Christine Farquharson, Lucy Kraftman, Sonya Krutikova, Angus Phimister and Almudena Sevilla. 2020. Learning during the lockdown: realtime data on children’s experiences during home learning. Briefing Note. Available online at <u>https://www.ifs.org.uk/publications/14848</u>

- Asanov, Igor, Francisco Flores, David McKenzie, Mona Mensmann, Mathis Schulte. 2020. Remote-learning, Time-Use, and Mental Health of Ecuadorian High-School Students during the COVID-19 Quarantine. - -

- <u>http://documents.worldbank.org/curated/en/328261589899308503/pdf/Remote learning Time-Use-and-Mental-Health-of-Ecuadorian-High-School-Studentsduring-the-COVID-19Quarantine.pdf</u>

34
market volatility affect systematic liquidity by creating correlated trading patterns among investors. By examining the actual trades of investors, I can test whether there is systematic variation in the demand for liquid assets and whether liquidity shocks apply (or transmitted) systematically across investors that can potentially cause market-wide effects:

# **H3a:** _There is systematic variation in households’ trades of illiquid stocks._

If there is systematic variation in demand for liquid assets across investors, it is important to examine how this systematic demand varies over time with changes in aggregate level of market liquidity. If investors demand liquid securities at the same time when aggregate liquidity is low, the liquidity premium required to hold illiquid securities would be high. The literature, to a large extent, treats individual investors as noise traders who provide constant liquidity to the market. Kaniel, Saar, and Titman (2006), Campbell, Ramadorai, and Schwartz (2007), Stoffman (2008), and Griffin et al. (2003), investigating institutional and retail trades, provide evidence consistent with the notion that retail traders provide liquidity to meet institutional demand for immediacy. These studies, however, investigate short-term returns to institutional and individual buy/sell imbalances, and do not consider the liquidity level of the market or the liquidity level of the individual securities that are traded.<sup>10</sup> With individual trade data, I can examine the liquidity level of the securities bought and sold by individual investors, and examine whether there is a _flight to liquidity_ among households. With individual trade data, I can also test if households are net demanders or suppliers of liquid securities when aggregate market liquidity is low:

**H3b:** _Households are net buyers of illiquid stocks when the market level of liquidity is low._

There are likely to be cross-sectional differences in trading patterns in response to aggregate liquidity shocks. Investors with deep pockets can take advantage of investment opportunities during turbulent markets. The recent Goldman Sachs‟ agreement to sell $5

> 10 In most of these studies, investors cannot be identified and their transactions cannot be tracked over time.

8
# Bibliography and references

This country report draws upon a wide range of papers, databases, models, and maps that were created as part of the Africa Infrastructure Country Diagnostic. All of these can be downloaded from the project Web site: www.infrastructureafrica.org. For papers go to the document page (www.infrastructureafrica.org/aicd/documents), for databases to the data page (www.infrastructureafrica.org/aicd/tools/data), for models go to the models page (www.infrastructureafrica.org/aicd/tools/models), and for maps to the map page (www.infrastructureafrica.org/aicd/tools/maps). The references for the papers that were used to compile this country report are provided in the table below.

## General

AICD (Africa Infrastructure Country Diagnostic). _Africa’s Infrastructure: A Time for Transformation_ . www.infrastructureafrica.org.

- Foster, Vivien, and Cecilia Briceño-Garmendia, eds. 2009. _Africa’s Infrastructure: A Time for Transformation._ Paris and Washington, DC: Agence Française de Développement and World Bank.

## Financing

Briceño-Garmendia, Cecilia, Karlis Smits, and Vivien Foster. 2009. ―Financing Public Infrastructure in Sub-Saharan Africa: Patterns and Emerging Issues.‖ AICD Background Paper 15, Africa Region, World Bank, Washington, DC.

## Growth

Calderón, César. 2009. ―Infrastructure and Growth in Africa.‖ Policy Research Working Paper 4914, World Bank, Washington, DC.

- Escribano, Alvaro, J. Luis Guasch, and Jorge Pena. 2010. ―Assessing the Impact of Infrastructure Quality on Firm Productivity in Africa.‖ Policy Research Working Paper 5191, World Bank, Washington, DC.

Yepes, Tito, Justin Pierce, and Vivien Foster. 2009. ―Making Sense of Africa’s Infrastructure Endowment: A Benchmarking Approach.‖ Policy Research Working Paper 4912, World Bank, Washington, DC.
10.4% in 2018/19 (World Bank (2020)). According to a recent UNICEF report, most of the trained ECE facilitators have attended only short courses, and the intensity of facilitator training is not adequate (Poudyal et al. (2019)).

As it recovers from a war and devastating earthquake, Nepal has refocused on the importance of early childhood development in recent years. The national vision is to provide education, health, nutrition, water, sanitation, and hygiene to every child in Nepal (Unicef (2019)) However, despite the government’s devotion to ECD education, many barriers and challenges remain. Lack of parental and teacher knowledge about the importance of early childhood, lack of quality training for teachers, and lack of resources are cited as the most common barriers that mitigate the effects of ECED centers in Nepal (Guras (2019)). There are large gaps in knowledge about early childhood development and the importance of the first five years of a child’s life in Nepal. Beginning with pregnancy and childbirth, many parents are unaware that mothers need to eat a nutritious diet during pregnancy,that childbirth should occur in a healthcare facility, and that breastfeeding is important (Poudyal et al. (2019)).

Beyond infancy and pregnancy, parents and teachers are not informed about important factors for the cognitive and non-cognitive development of children in their early years. For instance, parents and teachers are unaware that water needs to be purified before children drink it, that providing children with local toys is important to their play and growth, and that both mothers and fathers should spend time with children (Unicef (2017)). Discriminatory practices towards girls and children with disabilities exist in both classrooms and homes and prevent these children from accessing quality early childhood education (Poudyal et al. (2019)).

While the quantity of ECD centers has expanded, it is not clear that quality has expanded alongside this. While access is important, it is not useful if under-trained teachers, lacking resources, are unable to provide quality education in these centers. Teachers in ECED centers in Nepal are largely responsible for the success of the children under their care; they interact 4
low-income countries, 37% for lower-middle-income countries, 41% for upper-middle-income countries, and 26% for high-income countries. (We note that the set of countries in our data is not representative of regions or country income groups.) In addition to work stoppage, we examine other measures of the labor market effects of COVID-19 available from the HFPS data. We find that a substantial share, 20% of wage workers, report partial or no payments for work performed in the LAC region where this information was collected. In some countries, up to 21% of respondents report changing jobs during the pandemic (on average 9% report changing jobs), another sign of disruptions and a possible coping mechanism. Taking the simple average across countries, 22% of agricultural workers reported stopping work as opposed to 40% for industry and 38% for services. Examining broader measures of income loss, we find that a high share of respondents reported total income loss (62%), as well as loss from farming (62%) and non-farming (75%) family businesses, and wage incomes (49%), conditional on having a specific source of income.

To better understand what the HFPS data are saying about the initial impacts of the crisis on labor market outcomes, we examine the relationship between HFPS measures of economic impact and external measures of crisis impact. We find that work stoppage in the HFPS data exhibits the expected negative relationship with GDP growth projections in the LAC region. In contrast, we find that work stoppage is weakly and positively correlated with GDP growth projections in the SSA region. Furthermore, we see the same pattern when it comes to household farm income reductions: The expected negative correlation in LAC and a positive correlation in SSA. We hypothesize that GDP growth projections may not be accurately capturing income changes in the agriculture sector and the informal economy, with informal labor market arrangements and self-employment, which are prevalent in many countries in the SSA region. This also highlights that the HFPS data, despite their limitations, are an important complement to macroeconomic projections. In particular, they can help identify household impacts “on the ground” that may not be picked up by GDP growth projections in low-income contexts. Looking at labor market statistics, we compare 4
Stewart, W. M., D. W. Dibb, A. E. Johnston, and T. J. Smyth. 2005. “The Contribution of Commercial Fertilizer Nutrients to Food Production.” _Agronomy Journal_ 97 (1): 1–6.

_Takeshima, H., & Liverpool-Tasie, L. S. O. (2015). Fertilizer subsidies, political influence and local food prices in sub-Saharan Africa: Evidence from Nigeria. Food Policy, 54, 11-24._ Van Meter, K. J., Van Cappellen, P., & Basu, N. B. (2018). Legacy nitrogen may prevent achievement of water quality goals in the Gulf of Mexico. Science, 360(6387), 427-430 Verner, D., Roos, N., Halloran, A., Surabian, G., Tebaldi, E., Ashwill, M., Vellani, S., Konishi, Y.(2021). Insect and Hydroponic Farming in Africa : The New Circular Food Economy. Agriculture and Food Series;. Washington, DC: World Bank.

Willett, W., Rockström, J., Loken, B., Springmann, M., Lang, T., Vermeulen, S., ... & Murray, C. J. (2019). Food in the Anthropocene: the EAT–Lancet Commission on healthy diets from sustainable food systems. _The Lancet_ , _393_ (10170), 447-492.

Zaveri, E. D., Russ, J. D., Desbureaux, S. G., Damania, R., Rodella, A. S., & Ribeiro Paiva De Souza, G. (2020). The nitrogen legacy: the long-term effects of water pollution on human capital. _World Bank Policy Research Working Paper_ , (9143).

Zaveri, E., Russ, J., & Damania, R. (2020). Rainfall anomalies are a significant driver of cropland expansion. Proceedings of the National Academy of Sciences, 117(19), 10225-10233.

Zhang, X., Zou, T., Lassaletta, L., Mueller, N. D., Tubiello, F. N., Lisk, M. D., ... & Davidson, E. A. (2021). Quantification of global and national nitrogen budgets for crop production. _Nature Food_ , _2_ (7), 529-540.

Zhang, X., E. A. Davidson, D. L. Mauzerall, T. D. Searchinger, P. Dumas, and Y. Shen. 2015. “Managing Nitrogen for Sustainable Development.” _Nature_ 528 (7580): 51.

21
- Miyauchi, Y., Nakajima, K., and Redding, S. (2020). Consumption Access and Agglomeration: Evidence from Smartphone Data. Working paper, _Princeton University_ .

- Monte, F., Redding, S. J., and Rossi-Hansberg, E. (2018). Commuting, Migration, and Local Employment Elasticities. _American Economic Review_ , 108(12):3855–3890.

- Moreno-Monroy, A. I. and Posada, H. M. (2018). The effect of commuting costs and transport subsidies on informality rates. _Journal of Development Economics_ , 130(C):99–112.

- Pérez Pérez, J. (2018). City minimum wages. _Unpublished paper, Brown University, http://jorgeperezperez. com/files/Jorge_Perez_JMP. pdf (viewed July 19, 2018)_ .

- Perry, G. E., Maloney, W. F., Arias, O. S., Fajnzylber, P., Mason, A. D., and Saavedra-Chanduvi, J. (2007). _Informality : Exit and Exclusion_ . Number 6730 in World Bank Publications. The World Bank.

- Ramírez, S. B., Rojo, M. H., and Gault, D. A. (2017). Decisiones e Implementación en la Construcción de las Primeras Once Líneas de la Red del Metro en La Ciudad de México Hacia la Desorganización del Metro (1967-2000). Working Paper, _Centro de Investigaci ón y Docencia Económicas CIDE_ .

- Redding, S. J. and Turner, M. A. (2015). Transportation Costs and the Spatial Organization of Economic Activity. In Duranton, G., Henderson, J. V., and Strange, W. C., editors, _Handbook of Regional and Urban Economics_ , volume 5 of _Handbook of Regional and Urban Economics_ , chapter 0, pages 1339–1398. Elsevier.

- Restuccia, D. and Rogerson, R. (2008). Policy Distortions and Aggregate Productivity with Heterogeneous Plants. _Review of Economic Dynamics_ , 11(4):707–720.

- Santamaría, M. (2020). The Gains from Reshaping Infrastructure: Evidence from the division of Germany. Working paper, _University of Warwick_ .

- Suárez, M., Murata, M., and Campos, J. D. (2016). Why do the poor travel less? Urban structure, commuting and economic informality in Mexico City. _Urban Studies_ , 53(12):2548–2566.

- Świ ̧ecki, T. (2017). Intersectoral distortions and the welfare gains from trade. _Journal of International Economics_ , 104(C):138–156.

- Train, K. and McFadden, D. (1978). The goods/leisure tradeoff and disaggregate work trip mode choice models. _Transportation Research_ , 12(5):349 – 353.

- Tsivanidis, N. (2019). Evaluating the Impact of Urban Transit Infrastructure: Evidence from Bogotá’s Transmilenio. Working Paper, _UC Berkeley_ .

- Ulyssea, G. (2018). Firms, Informality, and Development: Theory and Evidence from Brazil. _American Economic Review_ , 108(8):2015–47.

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- Gelb, A., C. Meyer, and V. Ramachandran (2016). Does Poor Mean Cheap? A Comparative Look at Africa?s Industrial Labor Costs. _Revue d?économie du développement 24_ (2), 51–92.

- Gelb, A., C. Meyer, V. Ramachandran, and D. Wadhwa (2017). Can Africa be a Manu.

- facturing Destination? Labor Costs in Comparative Perspective. _Working paper_

- Kaur, S., M. Kremer, and S. Mullainathan (2015). Self-control at Work. _Journal of Political Economy 123_ (6), 1227–1277.

- Khandelwal, A. and M. Teachout (2016). Special Economic Zones for Myanmar.

- Kohli, A. (2004). _State-Directed Development: Political Power and Industrialization in the_ .

- _Global Periphery_ Cambridge University Press.

- .

- Oqubay, A. (2015). _Made in Africa: Industrial Policy in Ethiopia_ Oxford University Press, USA.

- Oyer, P. and S. Schaefer (2010). Personnel Economics: Hiring and Incentives. _NBER_ .

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A.1
The concentration index of income from governmen **t** ransfas is -0.7 which implies that this income component is more or less distributed on a per capita basis with no focus o the poor.9 Although the overall effect of govemment transfers is to reduce the inequality of total income, the magnitude of the effect is small. The progressivity of government rnsfers can easily be increased by focusing them on the poor rather than distributing them on a per capita basis. It is unfortunate that the progressivity of government benefits in fact fell considerably in 1992. The value of the conentration index for governmen **t** ransfers changed from _-0.5_ in 1991 to 14.2 in 1992. From the quintile shares we note that the share of the goverment transfers going to the bottom 20% of individuals reduced dramatically in 1992 while the share of the top 20 percent of people increased from 20.87 percent in 1991 to 29.16 percent in 1992. During recession the government should target its scarce resources but in Ukraine exacty the opposite happened. The greater proportion of governmen **t** ransfers went to the richer fa_m in 1992. Since we do not have the breakdown of governmen **t** ransfers, it is not possible to explain why the govemmen **t** ransfers became less progressive in 1992.

The last column in Table 10 gives the % contribution of each income componen **t** o the total inequality. In 1989, the contribution of salary income of blue and white collar worker was 70.7 percent which fel substantally to only 62.1 percent in 1992. This shows that the changes in wage and salary income strucure led to a consderable reduction in total income inequality. In 1992, the share of smallholding income was 19.8 percent but it contributes only 16.6 percent to total inequality. It would seem then that any policy that increases the smaiholding income has an equalizing effect on the size distribution of total income.

Table 11 presents inequality of total income by its expenditure components. The personal income tax paid by the families is shown as an item of expenditure. It can be seen that the share of xs to total family income declined from 7.3 percent in 1989 to only 5.1 perent in 1991. Smce the concentration index of taxes is considerably larger han the Gini index for towal income, taes can be said to be highly progressive. So the decline in the share of aes woud have the effect of incrsing the inequality of total income in the 1989 and 1991 period. In the subsequent period (from 1991 to 1992) the share of taxes remained more or less the same whereas their concentration increased from 32.1 percent in 1991 to 38.7 percent in 1992. This would have an effect of decreasing the inequality of total income in the 1991-92 period.

'The absence of targetting of govemment trnsfers is a common finding for sociaist counties, see for instance Mlanovic (1993).

23
high in upper-middle and high-income countries (44 and 36 percent, respectively), possibly driven by a demand-side impediment, such as costly power generation that results in high electricity tariffs.

This paper estimates the impact of electricity consumption on the value added in the following three sectors: agriculture, manufacturing, and services. It uses panel data on 126 countries for 1996-2014 obtained from the WDI and the International Energy Agency (IEA). Choosing electricity consumption as an explanatory variable instead of other related indicators, such as electrification rates, outages, or electricity generation, helps capture both the supply- and demand-side constraints while also accounting for electricity import and export. At the same time, estimating value added-electricity consumption elasticities for individual sectors is important, given large sectoral differences in electricity intensity and the distinct sectoral compositions of GDP across countries.

The estimation approach uses two-step difference and system panel generalized methods of moments (GMM) techniques to address endogeneity and reverse causality problems. Estimating the impact of contemporaneous electricity consumption on value added growth in reduced form equations by ordinary least squares (OLS) might generate bias in the coefficients due to reverse causality or endogeneity issues. For example, increased electricity consumption in countries with high electricity gaps might raise countries’ value added, as firms would consume more electricity and expand their production of goods and services. At the same time, higher value added growth will generate higher demand for electricity, as firms will increase their electricity consumption along with their production. In terms of endogeneity, there might be other factors driving both electricity consumption and value added, such as the discovery of oil resources. To address these econometric problems, the paper applies the two-step difference and system panel GMM econometric approaches, which improve the OLS estimators by using the lags of regressors as instruments and address the bias from omitting country fixed effects in the estimations.

There are two streams in the literature that discuss the impact of electricity on economic growth: countryspecific studies that cannot be replicated across countries given data limitations and cross-country studies that mostly rely on co-integration methods. The country-specific literature generally uses an instrumental variable approach to estimate the importance of electricity for economic growth. Urrunaga and Aparicio (2012) estimate the impact of installed electric power and other infrastructure components, such as telecommunication, on GDP per capita in a panel of Peruvian regions using multiple approaches, including System GMM with internal instruments, and find an elasticity of around 0.1. The cross-country literature on the electricity-growth nexus primarily relies on co-integration methods to estimate the long-run relationship between electricity and GDP. These studies find a strong link between economic growth and 3