rafmacalaba/data-use-mentions-extended huggingface dataset:
Barrera-Osorio, F., and L. L. Linden. 2009. The Use and Misuse of Computers in Education: Evidence from a Randomized Controlled Trial of a Language Arts Program. Cambridge, MA: Abdul Latif Jameel Poverty Action Lab (JPAL) 20. http://www.leighlinden.com/Barrera-Linden%20Computadores_2009-03-25.pdf Bassi, M., C. Meghir, and A. Reynoso. 2016. “Education Quality and Teaching Practices.” NBER Working Paper No. w22719, National Bureau of Economic Research, Cambridge, MA. http://www.nber.org/papers/w22719 Beede, D. N., T. A. Julian, D. Langdon, G. McKittrick, B. Khan, and M. E. Doms. 2011. “Women in STEM: A Gender Gap to Innovation.” Economics and Statistics Administration, Issue Brief No. 04-11 Washington, DC: U.S. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1964782.

Berg, A., and F. M. Mensah. 2014. "De-marginalizing science in the elementary classroom by coaching teachers to address perceived dilemmas". Education Policy Analysis Archives, 22 (57): 1-57 Berlinski, S., and M. Busso. 2017. "Challenges in Educational Reform: An Experiment on Active Learning in Mathematics". Economics Letters, 156 (C): 172-175.

MET Project. 2012. "Asking Students about Teaching: Student Perception Surveys and Their Implementation. Policy and Practice Brief". Bill and Melinda Gates Foundation.

http://www.metproject.org/downloads/Asking_Students_Practitioner_Brief.pdf.

Brown, M. W. 2009. “The Teacher-Tool Relationship: Theorizing the Design and Use of Curriculum Materials.” In Mathematics Teachers at Work: Connecting Curriculum Materials and Classroom Instruction, edited by J. T. Remillard, B. A. Herbel-Eisenmann, and G. M. Lloyd.
Buddenberg and Byrd (2006) note that in Afghanistan, national accounts are presumed to underestimate the economic value of the illegal drug industry, resulting in a potential downward bias of about one third in national income estimates. In contrast, they note that self-reports of poppy production by farmers in the national household survey for Afghanistan are substantial and do not appear to suffer from significant nonresponse problems. Despite these measurement concerns, it is useful to note that unlike household consumption and income surveys, the global community has invested significant efforts in research, training and in general human capital development to produce reasonably harmonized measures of national income.

A final point to make on the observed gaps between household surveys and national accounts is to recognize that the objectives of both instruments differ. Likely of greatest relevance, household surveys are meant to measure the distribution of well-being of people (along many dimensions and frequently with a greater emphasis on the less well off), while national accounts are focused on measuring aggregate income and productivity (not the distribution of well-being). There is a long tradition of critiquing national accounts as a measure of well-being.

Stiglitz, Sen and Fitoussi (2009) summarize many of these points noting that national income does not account for within-country distribution of income, is not monotonically increasing in well-being (e.g. traffic jams consume fuel, increasing national income but do not improve well-being), nor does it capture certain types of activities that contribute to well-being (e.g. unpaid household labor).

The overall objective of the System of National Accounts (SNA) is to produce an aggregate statistic. Deaton (2005) notes that SNA data tend to include larger transactions with greater probability than smaller transactions, and that to some extent this is intentional. The SNA training instructions specify that greater effort should be directed at larger transactions. Deaton cites OECD (2002, p. 179) where the SNA training instructions with respect to valuing home-production state that the time expended to collect this information should only be expended if the amount
was stratified by district and trade and designed to fill all available program slots.

Both the selected applicants and potential training providers were invited to a series of matching meetings in mid- to late 2013. Separate meetings were organized for each trade within each of the 32 evaluation districts. In these meetings trainers would make a brief presentation outlining their location, experience, and other characteristics of their business. Choosing among trainers within walking distance, the treatment group participants would then list those they were interested in training with (that is, a preference set). They were then assigned to train with a provider randomly selected from their preference set. Training began shortly after these meetings.

We examine the impact of the NAP training on youth labor market outcomes using the baseline applicant data collected during the application process in 2012, the baseline

> 4 In our analysis we pool carpentry, welding, and masonry into one group, which we refer to as construction.

2
|$1,837|$720|$1,385|
|**Botswana**|Botswana Multi-Topic Household Survey 2015/16|Nov 2015|Oct 2016|$3,107|$1,797|$2,654|
|**Burkina**<br>**Faso**|Enquête Multisectorielle Continue 2014|Jan 2014|Dec 2014|$1,348|$536|$758|
|**Cameroon**|Quatrième Enquête Camerounaise Auprès des Ménages 2014|Oct 2014|Dec 2014|$2,238|$968|$1,535|
|**Côte**<br>**d’Ivoire**|Enquête Harmonisée sur les Conditions de Vie des Ménages (EHCVM)<br>- 2018/2019|Sep 2018|Jul 2019|$1,531|$923|$1,242|
|**Eswatini**|Household Budget Survey|Jan 2017|Feb 2018|$1,280|$721|$942|
|**Ethiopia**|Socioeconomic Survey 2015-2016, Wave 3|Sep 2015|Apr 2016|$470|$260|$318|
|**Gabon**|Enquête Gabonaise pour l'Evaluation et le Suivi de la Pauvreté 2017|Jul 2017|Dec 2017|$3,801|$2,571|$3,624|
|**Gambia,**<br>**The**|Integrated Household Survey on Consumption Expenditure and<br>Poverty Level Assessment 2015/16|Apr 2015|Apr 2016|$1,037|$460|$774|
|**Ghana**|Ghana Living Standards Survey|Oct 2016|Oct 2017|$1,605|$899|$1,294|
|**Kenya**|Integrated Household Budget Survey 2015-2016|Sep 2015|Aug 2016|$1,373|$621|
productivity and � supply elasticity.

<u>1 Zt</u> !+� Equation (1) thus de...nes the theoretical market price as p<sup>�</sup> t<sup>=</sup> h At i . Also, to quantify the impact of di¤erent shocks, one can calculate the ...rst-order e¤ect for each of them.

where the right-hand side gives us the sum of the e¤ect of changes in all i 2 ffood,feed,ethanol,exportsg demand fundamentals and production fundamental A: USDA databases have time series for prices, all four demand uses (ethanol, feed, food, and exports), production, and yield per acre. The model uses these to estimate elasticities and identify exogenous shocks. For demand price elasticities, it uses instrumental variables, taking yield per acre shocks as a ...rst-stage instrument for prices. Changes in yield per acre are explain mostly by weather factors. Farmers have almost no control over short run productivity levels. Therefore, it is reasonable to assume that they are exogenous to the production process and are appropriate instruments for prices. Supply elasticities are estimated following Roberts & Shlenker (2013). Estimation results can been seen in Table I.A. Results fall within other literature’s ...ndings<sup>1</sup> . Once elasticities are estimated, given demand, supply and price data, one can identify exogenous components by reversing the isoelastic equation and setting the exogenous component equal to the demand or supply level times prices elevated to inverse elasticity.

Given time series for At; Zt<sup>i;andpt;andestimatedvaluesfor!; �,onecandecomposeprice</sup> changes per year by estimating the di¤erent terms of equation (2). As a result, changes in inventories explain the remaining residual. Results per variable can be seen in Figures II to V.

> 1 The Food and Agriculture Policy
6

|||**Table**|**S. 2 – continue**|**d from previous page**||||
|---|---|---|---|---|---|---|---|
|TUS code|TUS desc.|% Rur. time|% Urb. time|FAO desc.|Factor|Compendium desc.|Factor|
|892|TRAVEL RELATING TO SEARCH OF|0.0001|0.0004|depends on type|.|depends on type|.|
|911|SLEEP AND RELATED ACTIVITIES|0.3766|0.3738|sleeping|1|sleeping|0.9|
|921|EATING AND DRINKING|0.0563|0.0586|eating and drinking|1.5|eating sitting|1.5|
|922|SMOKING, DRINKING ALCOHOL AND|0.0011|0.0005|eating and drinking|1.5|eating sitting|1.5|
|931|PERSONAL HYGIENE AND HEALTH|0.0444|0.0425|Average of washing hands/face|2|grooming|2|
|932|WALKING, EXERCISE MINING, JOG|0.0028|0.0044|Between running and batting/bo|5.5||5|
|941|RECEIVING MEDICAL AND PERSONA|0.0002|0.0003|sitting quietly|1.2|sitting reading|1.3|
|942|RECEIVING MEDICAL AND PERSONA|0.0001|0.0001|sitting quietly|1.2|sitting reading|1.3|
|951|TALKING, GOSSIPING AND QUARRE|0.0486|0.0402|standing average for men and w|1.45|sitting talking on the phone|1.5|
|961|DOING NOTHING, REST AND RELAX|0.0651
_Ease of Entry_ Any factor that affects the ease of entering a new business activity would affect profitability _π_ , and also directly affect _α_ , the ease and speed with which copycats can imitate a discovery. We use the World Bank’s measure of how difficult it is to start a new business, based on the number of procedures required to complete the process. However, these data are only available for January, 2003. Therefore, this measure is only useful to the extent that these barriers have been relatively persistent over the past decade, which we consider reasonable.

# _The Financial System_

There have been many studies linking financial system development and economic growth (e.g. Beck, Levine and Loayza 2000). However, beyond these economy-wide effects, the financial system directly affects the profitability of discoveries because the cost of financing directly affects the costs of both experimentation and imitation. To consider this relationship, we introduce 1995 private sector credit as a percentage of GDP. As one of the areas singled out by Hausmann and Rodrik (2003b) when considering methods to overcome market failures for economic discovery in El Salvador is through government support of high-risk finance, the relationship between discovery activity and the financial system is even more interesting.

# _Results_

The estimation results using the HS 4-digit and HS 6-digit data are shown in Table 7<sup>9</sup> . This same estimation was performed on the 4-digit and 6-digit data pooled by industry to give

> 9 Most of the explanatory variables of interest are not available for earlier time periods, therefore we will not use the SITC data in this section. Note that to this point, the SITC data have not behaved differently from the HS data.

32
As a proxy for ...nancing needs of agri-food products, a measure of sanitary risk is computed at the 8-digit level of the HS classi...cation (Jaud et al., 2009a). The Sanitary Risk Index (SRI) re‡ects the propensity of products to fail health and safety controls on the European Union (EU) market. Thus, it captures the need for investments to comply with the EU food safety requirements. Several studies in the standard and trade literature suggest high costs of compliance, both variable and ...xed, for ...rms exporting high-value food products (Garcia-Martinez and Poole, 2006; Maskus et al., 2005). Our proxy captures the need for ...nancing associated with exporting to stringent developed countries market. Since our focus is on African ...rms’ability to sustain in the export markets, capturing the di¤erentiated e¤ect of ...nancial development requires an export based measure rather than production based measure.

The paper contributes to three strands of literature. First, it contributes to a literature on credit constraints and patterns of trade. This rapidly growing line of research highlights the role of ...nance for credit constrained ...rms to fund both short term and longer term needs. A number of papers have provided evidence on the positive e¤ect of the supply of external ...nance to ...rms on trade performances (Manova, 2008; Beck, 2003; Svaleryd and Vlachos 2005; Berman and Hericourt forth, Bugamelli et al. 2008; Görg and Spaliara 2009). More recently, several papers have looked into the e¤ects of liquidity shortages following banking crisis on the performances of ...rms already engaged in exporting (Amiti and Weinstein, 2010; Bricogne et al., 2010). Crucially, the negative e¤ects of credit constraints vary with the industry dependence on external ...nance (Rajan and Zingales, 1998
)|(8.0)|(9.7)|(8.6)|(8.0)|(5.9)|(6.0)|(6.4)|(5.8)|(6.7)|(6.6)|(5.7)|(4.9)|(4.3)|(3.9)|(3.7)|(3.6)|(3.6)|(3.6)|(3.6)|
|22|Other goods-producing|18.6|18.2|18.3|17.8|17.3|17.7|17.5|17.3|17.3|14.5|14.2|14.6|13.7|12.8|12.1|11.1|10.7|10.7|10.7|10.7|
||sectors|(16.0)|(13.0)|(14.2)|(10.5)|(8.4)|(8.3)|(8.1)|(7.8)|(7.8)|(8.3)|(8.)|(8.3)|(7.5)|(6.9)|(6.4)|(6.2)|(6.1)|(6.1)|(6.1)|(6.1)|

Note: Table reports average applied MFN rates by industries of the Russian input-output table. The standard deviation is reported in parentheses. Mapping from 10 digit codes to industries of the Russian input-output table is based on the Rosstat classification.

25
levels (as measured by the Gini index). It is notable, however, that a slight uptick has been found in the periods 2012 and 2013–15, with the Gini index being 30.8.<sup>4</sup> The Government of Egypt (GoE) has introduced several flagship economic reforms aimed at correcting macroeconomic imbalances, addressing foreign exchange shortages, and improving the competitiveness of the economy. The package of reforms includes the devaluation of the Egyptian pound in March 2016, the adoption of a floating exchange rate in November 2016, and the implementation of the Civil Service Law. The government has also implemented a fiscal consolidation program, the highlights of which are the streamlining of energy subsidies and the adoption of a value-added tax (VAT) rate to replace the already existing goods and services tax (GST). On the business environment side, an industrial licensing law and a new investment law have been passed, and new insolvency and company laws are currently under discussion in the parliament. These reforms are aimed at improving the business environment to encourage private sector–led growth.

The reforms have had a positive effect on the fiscal accounts and external accounts. On the fiscal accounts side, Egypt’s overall deficit decreased in FY17 to 10.9 percent of GDP (preliminary figures) compared to 12.5 percent of GDP a year earlier. Similarly, the primary deficit decreased to 1.8 percent of GDP in

> 3 Official rates follow an adjusted cost‐of‐basic‐needs approach, producing household‐specific poverty lines based on the caloric requirements of the household members and region‐specific cost per calorie and Engel regressions. The average national poverty line is LE 5,788 per person per year and is equivalent to about US$4 per day in 2011 purchasing power parity (PPP). As a comparison, poverty rates based on the international poverty line of US$1.90/day at 2011 PPP was 1.35 percent.

> 4 Estimate refers
,830|26%|2.4%|
|Areas offormal development<br>|170<br>|197<br>|26<br>|16%<br>|1.5%<br>|
|Densitiesinformalareas|171|187|15.9|9%6|0.9%||

[1] 2001 and 2011 census data corresponding to current AMC boundaries

[2] built up area as measured on Google Earth imagery dated Oct 2000 and jan 2001 for the year 2001 and May and Nov 2010 for 2011

[3] Slum areas measured on Google Erath imagery dated as above. Were included slums that have no apparent planned street structures and settlements with streets narrower than about 3 meters

[4] Average densities in slums extrapolated from a detailed topographical and social survey in 15 slums done by SEWA-MHT in 2001 and 2011
Policy Research Working Paper 9861

# **Abstract**

This paper examines the relationship between urban agglomeration and firm innovation using a recently developed dataset that consistently measures city boundaries across Asia together with geo-referenced firm-level data. It finds that the spatial distribution of innovation by firms is highly concentrated within countries. Further, firms in larger cities have substantially higher propensities to introduce product and process innovations and undertake R&D activities, a result that holds for subgroups of countries and even when the largest cities are excluded from the analysis. Finally, the presence of high quality universities and highly ranked engineering departments in cities is positively associated with firm innovation, lending support to the idea that the accumulation of human capital locally is a key channel through which urban agglomeration affects innovation.

This paper is has been accepted for publication in _the World Bank Economic Review_ . 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://www.worldbank.org/prwp. The authors may be contacted atlimingchen@adb.org, rhasan@adb.org, and yijiang@adb.org.

_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
Grogan (2011) and Grogan and Sadanand (2009) provide careful analyses of the impacts of electrification on fertility in Colombia and Guatemala, arguing in both cases that it does reduce the number of children born. In Colombia, electrification reduced birth propensity (in the year prior to the 1993 census) by 6%, mostly among women who already had at least two children. 45 In Guatemala, women who were under 30 at the time electricity was installed in their communities have 28% fewer children than women who were older when electricity arrived, controlling for spatial and temporal covariates.<sup>46</sup> In Bhutan, ADB (2010) finds that 0.04 fewer children had been born within 3 years of the survey in households in communities with electricity.<sup>47</sup> While each of these studies is limited by available data, and together they only cover three developing countries, together they do strongly suggest the possibility that rural electrification has a causal impact on fertility.

> 44 Gonzalez-Eiras and Rossi (2007) use difference in difference estimates, with controls for GDP, unemployment, income inequality, public spending, political party, water privatization; and year and province fixed effects.  Their results are not robust to dropping provinces with high rates of missing values, or to standard errors clustered by province.  They therefore call for caution in drawing policy conclusions from their results.

> 45 Grogan (2011) instruments electrification of a village with historical education levels in the municipal capital (argued to be exogenous because most migration is rural to urban, and argued to reduce the cost of electrification by increasing development and hence the number of grid connections) and gradient interacted with education.  Gradient along with numerous other municipal, household, and individual characteristics are included as controls.

> 46 Grogan and Sadanand (2009) regress the number of children born on age at the time electricity was installed in the community, controlling for current age, age when improved water and sanitation introduced to community
- -46

The highest cost overruns broken down by project component were for generation projects, wlth an average 28% overrun (for projects approved In 1967-78). X detailed study of hydro projects approved In the 1970s showed far higLer cost verruns of 40% for hydro components compared to 18% for non-hydro. Transmission and distribution projects Incurred lower overruns of 16% and 11%, respectively, but these estimates are not reliable because the quality and extent of technical Information available from both Bank reports and utilities do not permit sound conclusions to be drawn about costs. This situation Is due In part to the large number and diversity of technical specifications, small-size of equipment, and frequent force account activities Involved In transmission and distribution projects, all of which make It difficult to monitor project performance.

One might expect to find a high correlation between the amount of cost and project Implementation overruns, given that delays can result In cost Increases. However, there appears to be little correlation. This lack of correlation between Increased costs and project delays can be partly explained by the fact that delays In project start-up need not affect project costs. Also, projects may be reduced In size so as to avoid total cost overruns.

# Disbursements

Taking disbursements from the time of Board approval to the date of the final disbursement, the average perlod for a loan to be disbursed was 69 months compared to an average Implementation period of 66 months. Most loans were disbursed over 5-8 years. Two thirds of the loans were disbursed over six or more years and 10% were disbursed over nine or more years; only 3.5% were disbursed within three years, as shown In Table 1.

- 4/ Geological Complicatlons and Cost Overruns - A Survey of Bankfinanced Hydroelectric Projects, Energy Department Note No. 61, July 1985.
.596|0.613|

_Notes_ : The regressions are OLS estimations of equation (3) for the period 1999-2005. In columns (1) to (4) the dependent variable is the logarithm of the number of exported products to country _j_ by firm _f_ in year _t_ , and in columns (5) to (8) the dependent variable is the logarithm of the export sales in country _j_ by firm _f_ in year _t_ . Fixed effects by firm, country and year and a constant are included in all specifications. Tariff _fjt_ is the tariff measure faced by firm _f_ when exporting to country _j_ in year _t_ . Using HS6 product level tariff data from TRAINS, we construct the firm level tariff by taking the average of tariff over the basket of all the HS6 products exported by firm _f_ in the initial year (1999) to country _j_ . This basket is kept fixed over the period. Country level control variables definitions are reported in table 4. _∗∗∗, ∗∗,_ and _∗_ indicate significance at the 1, 5 and 10 percent levels respectively.

# _Alternative country samples_

In the previous regressions, the sample of Asian countries selected as a group of comparison included countries that are homogeneous in terms of trade integration and geographical proximity, but they differ in terms of economic development. Since the export patterns of French firms might differ according to the income level of the destination country, in this section we carry out two additional sensitivity tests.

We first restrict the sample to LDC Asian economies and exclude the high-income Asian countries like Korea, Japan and Singapore. Table 8 reports these results. The previous findings are robust to the countries selected as a group of comparison. When we compare the results in columns (2) and (3), on the one hand, and columns (5) and (6), on the other, the effect of Chinese tariff liberalization relative to 29