rafmacalaba/data-use-mentions-extended huggingface dataset:
that SBP incurs in offering them is quite substantial.

In light of our results, some policy implications emerge. First, to make the schemes more cost effective, it is important that the SBP reassesses the refinancing rates it offers to commercial banks. Lending at negative real interest rates is costly and distorts the allocation of credit at the aggregate level as Zia (2008) has shown. Second, the schemes could be more impactful if opened to all firms in all sectors in the economy. In particular, it is likely that new firms, or firms that are diversifying into new markets or products, may benefit more from access to export finance. Prioritizing new export ventures when allocating the funds is likely more efficient than continuing to lend to established exporters.

# **References**

- Akg ̈und ̈uz, Y. E., S. H. Kal, and H. Torun (2018): “Do subsidized export loans increase exports?” _The World Economy_ , 41, 2200–2215.

- Amiti, M. and D. E. Weinstein (2011): “Exports and Financial Shocks,” _The Quarterly Journal of Economics_ , 126, 1841–1877.

- Antr`as, P. and C. F. Foley (2015): “Poultry in Motion: A Study of International Trade Finance Practices,” _Journal of Political Economy_ , 123, 853–901.

- Berman, N. and J. H ́ericourt (2010): “Financial factors and the margins of trade: Evidence from cross-country firm-level data,” _Journal of Development Economics_ , 93, 206–217.

- Bernard, A. B., J. B. Jensen, S. J. Redding, and P. K. Schott (2007): “Firms in International Trade,” _Journal of Economic Perspectives_ , 21, 105–130.

- Brun, M., J.-P. Gambetta, and G. Varela (2020): “Slow Rockets
following trade liberalization are disproportionately poor. In developed countries, Kletzer (2004) suggests ‘yes,’ but for developing countries we are far from sure. Enterprise surveys report the responses of firms to trade liberalization, but typically give little information on the characteristics of their employees, while household surveys, which do provide this information, cannot easily be matched to enterprises. The latter do, however, generally suggest that, in many low income countries, very few of the poorest are employees in the formal manufacturing sector.

8
Skoufias, E., Vinha, K., & Beyene, B. M. (2021). Quantifying Vulnerability to Poverty in the DroughtProne Lowlands of Ethiopia. _Policy Research Working Paper_ ; No. 9534. World Bank, Washington, DC. © World Bank. https://openknowledge.worldbank.org/handle/10986/35107 Sulla-Menashe, D., & Friedl, M. A. (2018). _User guide to collection 6 MODIS land cover (MCD12Q1 and MCD12C1) products_ . USGS: Reston, VA, USA, 1, 18.

Socio-Economic Database for Latin America and the Caribbean (2022). <u>https://www.cedlas.econo.unlp.edu.ar/wp/en/estadisticas/sedlac/. CEDLAS and The World Bank.</u> Retrieved March 2022.

Solano-Rodríguez, B., Pye, S., Li, P. H., Ekins, P., Manzano, O., & Vogt-Schilb, A. (2021). Implications of climate targets on oil production and fiscal revenues in Latin America and the Caribbean. _Energy and Climate Change_ , 2, 100037. <u>https://doi.org/10.1016/j.egycc.2021.100037</u> Stampini, M., & Tornarolli, L. (2012). The growth of conditional cash transfers in Latin America and the Caribbean: did they go too far? _IZA Policy Paper_ . No. 49 ThinkHazard! Platform (2022). https://thinkhazard.org/. Global Facility for Disaster Reduction and Recovery (GFDRR Labs). The World Bank. Retrieved March 2022.

UNDP (2022). Social Protection in Times of Uncertainty. _Technical Note: Recalibrating... Getting Back on Track Towards the SDGs_ . XIV Ministerial Forum for Development in Latin America and the Caribbean.

Ward, P. J., Blauhut, V., Bloemendaal, N.,
of sampled households in the EMOP data is 15 households. There are, however, two communes out of the 370 communes surveyed in 2019 with only one household interviewed in each village. These villages are Didieni in the Djidieni arrondissement in the Koulikoro region, and Niantaga in the M’pessoba arrondissement in Sikasso region.

> 5We have tested aggregating the data to the arrondissement level and find similar effects as reported here, though they have less precision because our measures are necessarily less precise at a higher level of aggregation. The EMOP data we use show 46% of the households as urban, which almost exactly matches national statistics on urbanization rates, suggesting that our data are broadly representative of both urban and rural areas.

> 6This implies that our measure of IDP presence and population should be considered as a measure of formally recognized IDPs who are likely receiving services. To the extent that there might be large numbers of IDPs in communes who are not receiving services, our data do not measure them. The available evidence that we can glean from the EMOP survey suggests that the number of people who fit such a category is very small.

15
and 9 means Excellent. We then aggregate these individual (rescaled) grades to obtain an aggregate grade point ranging from 5 to 45, with grades 5 and 45 representing the lowest and highest grades respectively. We also compute the total grade points for STEM (mathematics and science) and non-STEM (social studies, Kinyarwanda, and English) subjects. It is important to emphasize that the grading system was unchanged during the study period, thus ensuring comparability of the grades across years. Nonetheless, for ease of interpretation and to ensure consistency with the test scores of the individual subjects, we standardized the grade points for the aggregate, STEM, and non-STEM subjects. Finally, using the geo-location of all primary schools in the country and data on the location and year of establishment of coffee mills, we spatially match each school to the nearest coffee mill.

## **3.2 DHS Data**

To explore potential mechanisms, we use data from the Demographic and Health Surveys (DHS) to understand the potential mechanisms. The DHS data is a nationally representative survey and covers a wide range of issues including, but not limited to, health, education, and household assets. For the purposes of this study, we focused on anthropometric measures (wasting and underweight) of children under five years, school attendance, and household wealth. The main advantage of the DHS over the other surveys such as the Integrated Household Living Conditions Survey (EICV) is that it is geocoded, allowing us to spatially match survey locations with the coffee mills datasets to determine treated and control households.

## **3.3 Complementary Data**

We complement our analysis with extensive data on coffee intensity at baseline from Guariso and Verpoorten (2018). Coffee intensity is measured as the number of coffee trees per sq km in 1999, compiled from the Rwanda coffee census. We also include data on road density at the municipality level, average annual temperature, total precipitation, and coffee suitability.

# **4 Empirical Strategy
influx of SUTPs has had both positive and negative impacts. It seems on average, the host community has been strong and adaptive, and not negatively impacted. This is not to disregard that real strains do exist in some regions where the SUTP population is very large. Nor do these results undermine findings of displacement effects in the labor market that certain types of workers are experiencing. However, on average nationally, we do not see a systematic decline in the welfare of the host community between 2011 and 2013.

The remainder of the paper is organized as follows. Section 2 outlines the data availability and technical issues. Section 3 discusses descriptive statistics of the foreign-born and host community. Section 4 explores the impact of the foreign-born population on host community welfare.

# **1. DATA AND TECHNICAL ISSUES**

## **_Data Sets_**

Data availability limits which data set can be used to identify the foreign-born population and geographic location while measuring poverty. The Turkish Statistical Institute (TUIK) has been conducting three nationally representative surveys annually since 2005; the Household Income and Consumption Expenditure Survey (HICES), the Survey on Income and Living Conditions (SILC) and the Labor Force Survey (LFS). However the HICES, which is the national survey that is used to measure official poverty,

> 5 UNCHR, 2013pg 13

> 6 UNHCR (22 November 2013), UNHCR (15 September 2014)

> 7 UNHCR (22 March 2013),  Erdogan (2014), pg 14

> 8 This technical issue will be discussed further later in the paper.

4
correlation across all countries in 2014). Figure 2 focuses on Burkina Faso. In 2010, child mortality in Burkina Faso was 97 per thousand live births in the richest wealth quintile but 175 among the poorest quintile; similarly, 93.2 percent of women coming from the richest quintile delivered in a health facility, but only 46.1 percent of those in the poorest quintile did so (Institut National de la Statistique et de la Démographie - INSD/Burkina Faso and ICF International, 2012). In the past decade, Burkina Faso has introduced several reforms that aim at improving financial access to health services for the poor, including the reduction of user fees for obstetric services in 2007, exemption of user fees for the worst off (les indigents) in 2009, ResultsBased Financing, which introduced pro-poor incentives to health care providers in 2014, and generalized free health care for women and children in 2015 ( _la gratuité_ ).<sup>3</sup> Globally, this (considerable) effort to improve health outcomes among the poor has had mixed impact.

Moreover, researchers have noted that simply expanding resources for health care may widen these disparities. Gwatkin (2005) warns that because expanded health services typically reach wealthier groups before disadvantaged ones, poor people are unlikely to be the main beneficiaries of efforts to accelerate progress towards the health Millennium Development Goals (MDG) by providing additional resources to the health sector. Analyzing nationally representative surveys in 64 developing countries over the 1990-2011 period, Wagstaff, Bredenkamp and Buisman (2014), establish that the poorest 40 percent have made faster progress than the richest 60 percent on MDG

> 3 A recent study on the reduction and exemption of user fees showed that the majority of public sector health workers were unaware or at least did not understand these directives, and this contributed to weak implementation and adherence to the policy changes (Ridde et al., 2018).
- **_Jain irrigation systems, Jalgaon, India_** : adapted existing drip irrigation systems specifically to meet the needs of smallholder farmers, and works closely with customers to teach  ̳precision farming‘ (which optimizes the balance between fertilizers, pesticides, water and energy to increase output); and uses dance and song to explain the benefits of drip irrigation to farmers who can‘t read

Source: World Economic Forum (2011). WEF and the Boston Consulting Group partnered to review more than 1,000 emerging market-based companies with annual sales ranging from $25 million to $5 billion, coupled with interviews of almost 200 business executives, to identify 16 showcase companies in light of sustainability, innovation and scalability criteria.

Enterprise surveys are another potential source of systematic information on the extent and breadth of such local green innovations. However, most national industrial census efforts and complementary internationally-comparable enterprise surveys have not yet systematically been collecting information on green product, process, organizational and marketing innovations.

# **3 FOSTERING INNOVATION – POLICIES FOR PROMOTING FRONTIER AND CATCH-UP INNOVATIONS AND FOR DEVELOPING ABSORPTIVE CAPACITY**

As with all other technologies, market failures in the creation, dissemination and absorption of knowledge by firms provide a rationale for public policies addressing the development and commercialization of green technologies. In addition, green technologies are also characterized by environmental externalities. The combination of knowledge and environmental market failures require combined policy responses and 12
- **Labor legislation:  M** any countries have enacted laws that prohibit racial discrimination in the labor market.  However, little is know about adequacy, enforcement  and effectiveness of this legislation.

# **References:**

- Addison, J. and  J. L. Grosso. (1996). "Job Security Provisions and Employment: Revised Estimates." Industrial Relations. 35(4).

- Addison, J. and P. Teixeira. (2001). "The Economics of Employment Protection." IZA Discussion Paper No. 381. Institute for the Study of Labor, Bonn, Germany.

- Addison, J. T., P. Teixeira, and J. L. Grosso. (2000). "The Effect of Dismissals Protection on Employment: More on a Vexed Theme." _Southern Economic Journal_ 67(1): 105-122.

- Akerlof, G. and R. Kranton (2000). “Economics and Identity” _Quarterly Journal of Economics_ 115(3):  715-53.

- Arbache, J. S.. (2002). "Unions and the Labor Market in Brazil". Background paper for the Brazil Jobs Report. The World Bank and Instituto de Pesquisa Econômica Aplicada.

- Arias, O. and W. Sosa. (2004). "Subjective poverty in Bolivia: a binary quantile regression approach, 2003." Work in process. World Bank, Washington, D.C.

- Arias, O., Yamada, G. and L. Tejerina (2004). “Education, Family Background and Racial Earnings Inequality in Brazil.” International Journal of Manpower, Vol. 25, No. 314.

- Barrera, F. and L. Higuera. (2004). “Characterization of Training in Colombia Household and Firms surveys”, Background study for a World Bank study “Colombia Lifelong Learning”, Bogota, Colombia.

- Batra, G. (2001). “Skills Upgrading and Competitiveness in Developing Countries
Paravisini, D., V. Rappoport, P. Schnabl, and D. Wolfenzon (2015): “Dissecting the Effect of Credit Supply on Trade: Evidence from Matched Credit-Export Data,” _Review of Economic Studies_ , 82, 333–359.

- Reis, J. G. and D. Taglioni (2013): “Determinants of export growth at the extensive and intensive margins : evidence from product and firm-level data for Pakistan,” Policy Research Working Paper Series 6341, The World Bank.

- Rho, Y. and J. Rodrigue (2016): “Firm-Level Investment And Export Dynamics,” _International Economic Review_ , 57, 271–304.

- Ria ̃no, A. (2011): “Exports, Investment and Firm-level Sales Volatility,” _Review of World Economics (Weltwirtschaftliches Archiv)_ , 147, 643–663.

- Van Biesebroeck, J., J. Konings, and C. Volpe Martincus (2016): “Did export promotion help firms weather the crisis?” _Economic Policy_ , 31, 653–702.

- Van Biesebroeck, J., E. Yu, and S. Chen (2015): “The impact of trade promotion services on Canadian exporter performance,” _Canadian Journal of Economics_ , 48, 1481– 1512.

29
:_AICD calculatio<br>FAO (2005); and Keer-|ns based on data from<br>MISC ( http://www.keer|Yoshino and others<br> -misc.com)|(2009); UNJLC and|

what is observed in other parts of Africa. Another coastal gateway available is Mombasa, Kenya, through Uganda. Cultural and geographic considerations aside, trading via Mombasa is the most economically viable option for South Sudan.

South Sudan might also rely on Lamu, Kenya, which is north of Mombasa, as a gateway to ship oil to overseas destinations in the future. An important consideration for South Sudan is the significant port congestion problems that currently plague both Port Sudan and Mombasa. As they significantly exceed their handling thresholds, both ports are facing extended dwell times and delays (though such challenges are more acute in Port Sudan than in Mombasa). As South Sudan becomes better integrated with East Africa, it is recommended that it rely more on Lamu and Mombasa, particularly considering the inefficiencies to be encountered at Port Sudan.

# **High costs**

Freight tariffs in South Sudan are as high as $0.20 per tonne-kilometer (tonne-km)—twice those found in Sudan and four times those in South Africa, the continent’s best performer (table 2). These costs are a direct economic consequence of South Sudan’s poor surface transport infrastructure and place a significant cost burden on transport users and suppliers. The average transport tariff between Juba and Kampala is $0.18 per tonne-km, or three times the average tariff paid to transport goods from Mombasa to Kampala (approximately $0.06 per tonne-km). Consequently, the overall cost of transporting goods over 980 km between Mombasa and Kampala is $115, and barely covers half the cost of transporting goods between Juba and Kampala, a distance of 630 km (Yoshino 2010).

Poor transport infrastructure forces trucks to carry small loads and face much longer travel times.
World Bank, 2020a). Moreover, as the extent of automation to produce the same food product varies widely across countries, we would expect for the same product larger reduction in supplies in countries with less automation.

To account for the heterogenous impact of Covid-19 on food supply across countries and products, we rely on data at the country-product level on the share of low-skill workers in the total value added in exports (Auguiar et al., 2019). We assume that the initial shock in supply proportionally increases with the weight of low-skill labor in total value added in exports. In our baseline scenario, we use information from Chinese food exports in January and February 2020 to define the potential upper bound for the decrease 3
and, then, intervention in the FOREX market, _Int2_ , is computed as the average of the monthly change in the ratio of reserves to broad money, _R2_ , Note that _Int2_ is positive whenever reserve accumulation exceeds the increase in monetary aggregates —thus, implying a strong degree of intervention in the foreign exchange market.

We also consider trade and financial openness as determinants of RER misalignments. _Trade openness_ is proxied as the ratio of real value of exports and imports (that is, total trade) to real GDP, and the data is obtained from the World Bank’s World Development Indicators (WDI). Measuring _financial openness_ involves data on foreign assets and liabilities from Lane and Milesi-Ferretti (2001, 2007). We construct the ratio of foreign liabilities as a percentage of GDP (which include stocks of liabilities in portfolio equity, foreign direct investment, debt and financial derivatives) and, for robustness purposes, the ratio of foreign assets and liabilities to GDP. We also assess the role played by the composition of capital flows in affecting the ability of the government to sustain RER undervaluations. Hence, we decompose our measure of financial openness into equity- and loan-related foreign liabilities. While the former includes the foreign liability position in foreign direct investment and portfolio equity, the latter includes only the debt liability position ( _i.e._ portfolio debt and other investments). The same calculation is performed for the ratio of foreign assets and liabilities to GDP.

_Liability dollarization_ is measured as the ratio of foreign liabilities of the financial sector to money. The data is taken from the IFS —more specifically, lines 26C and 34 for foreign liabilities of the financial sector and broad money, respectively. Although this is not a direct measure of the extent to which a country’s balance sheet present currency mismatches in assets and liabilities, there is a wide availability across countries and over time which is attractive for panel data analysis. For robustness 11
the EU (25 percent of 8.9 percent), and importers will save 2.3 cents less on each dollar of import costs from non-EU countries (25 percent of 9.1 percent).

We summarize these calculations in the table below.

# **Summary of Estimates of the impact of a Deep and Comprehensive Free Trade Agreement with the European Union on Armenian Border Costs**

||percentage o<br>and import re|f export<br>venues|
|---|---|---|
|Border costs of trade in 2007||10.4|
|Border costs of exportingin 2010||8.9|
|Border costs of importingin 2010||9.1|
|**Reduction in exporting border costs for EU trade**||**2.5**|
|**Reduction in exporting border costs for non-EU trade**||**2.2**|
|**Reduction in importing border costs for EU trade**||**2.5**|
|**Reduction in importing border costs for non-EU trade**<br>**Source: Authors' calculations based on sources describe**|**d above.**|**2.3**|

> 34 Maliszewska _et al_ ., (2008) assume that a deep and comprehensive free trade agreement between Armenia and the EU would reduce Armenian border costs of exporting to the EU by 50 percent.

98
283–305. https://doi.org/10.1016/j.ress.2018.03.015.

- Mukherjee, Sayanti, Roshanak Nateghi, and Makarand Hastak. “Data on Major Power Outage Events in the Continental U.S.” Data in Brief 19 (August 2018): 2079–83. https://doi.org/10.1016/j.dib.2018.06.067.

- Mukhi, Neha, Debabrata Chattopadhyay, Benjamin Hobbs, and Evangelia Spyrou. 2017. “Building Climate Resilience into Power System Planning : The Case of Bangladesh.” ACS23320. The World Bank. http://documents.worldbank.org/curated/en/296731513710765160/Building- <u>climate-resilience-into-power-system-planning-the-case-of-Bangladesh.</u>

- New York Power Authority, Puerto Rico Power Authority, Puerto Rico Energy Commission, Consolidated Edison, Company of New York, Inc., Edison International, Electric Power Research Institute, et al. 2017. “Build Back Better: Reimagining and Strengthening the Power Grid of Puerto Rico.”

- https://www.governor.ny.gov/sites/governor.ny.gov/files/atoms/files/PRERWG_Report_PR_Grid _Resiliency_Report.pdf.

NDRRMC. 2014. “Y It Happened: Learning from Typhoon Yolanda.” NOAA. 2011. “State of the Climate: Drought for June 2011.” July 2011.

<u>https://www.ncdc.noaa.gov/sotc/drought/201106#national-overview.</u>

- Ouyang, Min, Leonardo Dueñas-Osorio, and Xing Min. 2012. “A Three-Stage Resilience Analysis Framework for Urban Infrastructure Systems.” Structural Safety 36–37 (May): 23–31. https://doi.org/10.1016/j.strusafe.2011.12.004.

- PG&E. 2018. “PG&E 2018 Final Per Unit Cost Guide.” California ISO
_e_<sup>_∗_</sup> _ch,r_<sup>isgeneratedas:</sup> For an area _c_ that is sampled in the survey, the generated non-sample vector _yc,r_<sup>_∗_is then augmented</sup> by the survey data _yc,s_ . Therefore, the final vector for the whole census in area _c_ is _yc_<sup>_∗_= (</sup><sup>_y_</sup> _c,s_<sup>_T, y_</sup> _c,r_<sup>_∗T_)</sup><sup>_T_,</sup> which is made up of the generated out-of-sample welfares and the survey ones.

3. The previous step yields a census vector of welfare _yc_<sup>_∗_, simulated using the fitted model parameters.</sup> This census vector is then used to calculate the indicator for each area _c_ = 1 _, . . . , C_ , as where _f_ ( _·_ ) can be any indicator function such as the FGT poverty indicators.

7