rafmacalaba/datause-encoder-data huggingface dataset:
higher human capital, better institutions or better policies. This paper examines the effect of aid on economic institutions and finds no robust evidence of either a positive or negative relationship between aid and economic institutions.

Studies of the relationship between aid and growth find that much of aid does not translate one for one into higher public investment and the effect varies tremendously between countries (World Bank, 1998). The typical aid dollar finances 29 cents of public investment. Even more noteworthy, studies have found that the share of GDP devoted to public capital spending does not have a relationship to economic growth. This is because how spending translates into public capital depends on the efficiency of government expenditures and the relationship between budgeted and realized expenditures. For example, infrastructure services have been shown to be important for growth (Serven and Calderon, 2004) but it is harder to show that infrastructure expenditures are important (Hulten, 1996 and World Bank, 1998).

Even if aid does not affect investment and thus growth directly, aid could affect growth (indirectly) through its impact on policies or institutions (or even skills/human capital). Some of these changes could be productivity enhancing (or reducing) and could add value even if funding public capital does not (see World Bank, 1998). For example, donors often attempt to strengthen legal systems and property rights. There are countless projects funded that aim to reform the judiciary and numerous laws adopted as a result of donor intervention, for example: bankruptcy, accounting, disclosure, company, collateral, and land registration laws. It has been argued that many countries underwent rapid economic liberalization (or deregulation, which is equivalent to a particular form of institutional reform) because of pressures from the donor community. This “Washington Consensus”, though geared towards what was believed to be an improvement in policies and institutions was often blamed for much of the vicissitudes of Russia and Latin America in the 1990s. Explanations for the less than positive results have varied between an underestimation of the time needed to implement institutional change or the too rapid pace of 3
<!-- Start of picture text --> (A) Increase in the number of issuers (B) Number of first-time issuers<br>500 300<br>450<br>400 250<br>350 57% 200<br>300<br>250 150 94%<br>200<br>150 + 16% 100<br>100 43% 50<br>50 84%<br>0 0<br>2006-2008 2009-2012 2009-2012<br><!-- End of picture text --> Sources: Brazil CVM, Boletim Anbima January 2012, and World Bank calculations.
important improvements that countries can and should make in taxing such products as tobacco and alcohol. Unfortunately, even when, as in the recent Philippine reform, an adjustment mechanism is included in the law it is often unrelated to the rate of price inflation. The uniform annual adjustment of 4% established in the Philippines is definitely better than nothing, but in some cases it may be too much and in others too little: it is most unlikely ever to be just right.

The importance of good administration has long been as obvious to those concerned with tax policy in developing countries as has its absence. Initially, the effective administration of high‐rate excise taxes depended on establishing an adequate system to control the physical commodity. Producers and sellers of excise products were registered and their premises policed so that no goods were shipped without paying tax, just as import duties are typically paid at the point of importation before the product is released from border control. Another type of physical control, useful only for specific taxes, was to apply a seal over the cork (or a strip seal or ‘stamp’ over the cap or around the package) to signify that the tax had been paid. Such systems are not cheap to administer and frequently resulted in both corruption and evasion. Increasingly, however, excise taxes, like other taxes, are administered primarily through control of accounting records, supplemented by such technological aids as ‘digital stamps.’<sup>12</sup> These recent developments may be useful in many cases. However, the main lesson from experience is that when excise taxes are increased not only should their structure be kept as simple as possible to make administration manageable but that in many cases the basic excise tax administration may also need strengthening if the revenue (and health) objectives of such increases are to be achieved.

# **Is Earmarking a Good Idea?**

The dual objectives of ‘sin’ taxes are in a sense inherently contradictory: one target, increased revenue, is more likely to be achieved if the consumption of the taxed products increases while the other, improved health outcomes, requires that consumption be reduced. Those who support increasing excise taxes on alcohol and tobacco taxes on health grounds often argue that the proceeds of such taxes should be earmarked to finance health expenditures ‐‐ especially for the poor, who are usually most impacted by such taxes ‐‐ or perhaps such other health‐focused activities such as anti‐tobacco education and advertising. While many countries with high excises do not earmark the revenues from these taxes,

> 12 Digital stamping encrypts information on a stamp or even directly on a container and permits authorities to authenticate and verify the embedded information in the field with simple handheld instruments.

19
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<!-- Start of picture text --> 52<br>o 50<br>o<br>e<br>5<br>=<br>Bo<br>6°<br>= 33<br>&o<br>s N ¥v &Rw<br>s &<br>Ye2 w§<br><!-- End of picture text -->
|**1 INTRODUCTION ............................................................................................. 3**|
|---|
|**2 SERVICES TRADE POLICY DATA ..................................................................... 3**|
|Scope and organization of the database .................................................................... 3|
|Relationship to other databases ............................................................................... 7|
|**3 MEASURING SERVICES TRADE POLICY RESTRICTIVENESS ............................ 8**|
|Basic principles ...................................................................................................... 9|
|Scoring ............................................................................................................... 10|
|Aggregation ........................................................................................................ 13|
|Decomposition of changes in STRI scores in 2008-11 vs 2016 ................................... 18|
|Other considerations ............................................................................................ 21|
|**4 DATA PRESENTATION IN I-TIP SERVICES .................................................... 21**|
|Services Trade Policy Database .............................................................................. 22|
|Presentation of policy information on the screen ...................................................... 24|
|Description of Excel and CSV downloads of policy information.................................... 25|
|Presentation of the STRI results on the screen ......................................................... 25|
|Description of Excel and CSV downloads of the results of the selection for the STRI ..... 26|
|Description of the file "All World Bank STRI data (including 2008-11)" ........................ 26|
|**5 CONCLUDING REMARKS ............................................................................... 27**|
|**REFERENCES ..................................................................................................... 29**|
|**ANNEX 1 CLASSIFICATION OF MEASURES......................................................... 30**|
|**ANNEX 2: LIST OF ECONOMIES COVERED, SOURCE AND GROUPS ..................... 45**|
|**ANNEX 3 SUMMARY OF THE COVERAGE OF SECTORS AND MODES .................... 47**|
|**ANNEX 4 SECTOR DEFINITIONS USED IN THE QUESTIONNAIRE ....................... 48**|
|**ANNEX 5 SCORING OF MEASURES ..................................................................... 52**|
|**ANNEX 6 SECTORAL AND MODAL WEIGHTS ...................................................... 63**|
|**ANNEX 7 LIST OF LAW FIRMS THAT CONTRIBUTED TO FILLING**|
|**QUESTIONNAIRES ............................................................................................. 64**|

2
<!-- Start of picture text --> Overall :<br>2016 :<br>2014 7<br>2 1 0 1 2 3<br>Estimate<br><!-- End of picture text --> <!-- Start of picture text --> Overall "<br>2016 :<br>2014 7<br>1.00 0.75 0.50 0.25 0.00 0.25 0.50 0.75 1.00<br>Estimate<br><!-- End of picture text --> <!-- Start of picture text --> Overall '<br>2016 '<br>2014 '<br>1.00 0.75 0.50 0.25 0.00 0.25 0.50 0.75 1.00<br>Estimate<br><!-- End of picture text -->
analytical capacity, informing the public debate, and influencing the development community are in the range of 0.23 and 0.26.<sup>12</sup>

**Figure 3: Objectives of Policy Reports**

<!-- Start of picture text --> 60% 55%<br>49%<br>50%<br>40%<br>31% 31% 32% 30%<br>30%<br>20%<br>10%<br>0%<br>Inform Lending Inform Build client Inform/stimulate Influence No Development<br>government analytical public debate development Objective<br>policy capacity community<br>Source: Business Warehouse.<br>Note: Policy reports can have multiple objectives.<br><!-- End of picture text -->

**Increased focus on the quality of knowledge services and its impact has led to a three-pronged approach towards measuring quality:** i) self-assessment, ii) systematic collection of client feedback, and iii) IEG performance reviews.

**i) Self-assessments are provided by the TTL of the report** . After completing a policy report, the TTL is required to evaluate in the system whether the report has met its pre-specified objectives.<sup>13</sup> The Sector Manager and Country Director later validate and endorse this assessment.  Table 1 below shows that TTLs assess their work favorably on average.  Almost half of all policy reports that had the objective of informing lending were considered to have fully met this objective,<sup>14</sup> while more than a quarter of policy reports that sought to influence the development community had the highest assessment score. Informing and stimulating the public debate was the highest rated objective. About 46 percent of policy reports with this objective had fully met it according to the self-assessment.

12 Recent Independent Evaluation Group (IEG) studies show that only 23 percent of knowledge services included indicators that tracked the achievement of the policy reports outcome, and that those knowledge services that had tracking mechanisms performed better in terms of meeting the specified objectives (World Bank, 2013d). 13 The development objectives mentioned earlier are measured using a scale ranging from 1 to 0. A score of 1 indicates that the objective was fully met; a score of 0.75 or above indicates that it was largely met; a score of 0.5 or above indicates that it was partially met; and a score of 0 indicates that the objective was clearly not met.

14Many are ESWs are undertaken with the objective of providing the analytical basis for future lending operations. This indicator is such likely to capture management foresight and political risks (for example, a planned lending operation may go ahead because of a change in government) rather than the quality of the ESW.

8
|**Rainfall**<br>0.000|0.033|
|---|---|
|**Relative Humidity**<br>0.024|0.017|
|**Temperature**<br>0.007|0.053|
|**Wind Speed**<br>0.008|0.007|
|**Workday**<br>-0.020|0.029|
|**Summer**<br>-0.104|0.116|
|**Winter**<br>-0.155|0.118|
|**Diwali**<br>-0.018|0.151|
|**Observations**<br>22229||
|Source: Authors' analysis based on data described in the text.||
|The dependent variable is an indicator of whether PM2.5 observa|tion is missing,|
|(=1 if missing and =0 otherwise). The explanatory variables are t|he same as|
|in Table 4, except that we drop all discontinuity dummies and the|time|
|polynomial, and include an indicator for whether CO measure is<br>and =0 otherwise) and also include season fixed effects. Std. Erro|high (=1 if high<br>rs are clustered|
|at one week. * indicates significantly different from zero at 10 pe|rcent level, **|
|at 5 percent level, and *** at 1 percent level.||

|**Table S1.8 A**|**nnual Profits of the Delhi Metro**|**Rail Corporation Ltd.**|
|---|---|---|
||**From Traffic Operations**|**From All Operations**|
||Real Terms in 2004-05 price|s (in million rupees)|
|2004-05|70.0|-7612.6|
|2005-06|285.0|8177.1|
|2006-07|843.4|2119.0|

68
our sample. In both cases, however, we show that the coverage remains satisfactory.

There is a risk of underestimating the share of overall industry output covered in FactSet since about only one-fifth of U.S. entities in our FactSet sample have information on sales data available. Aggregating over their sales, thus, may lead to under-representing the actual share of U.S. output observed. In spite of this bias, the coverage is very high. In 2021, the revenue from U.S. agribusinesses with available sales data totaled approximately $4,000 billion—representing about 75%-85% of the total U.S. industry output as per BEA data (see Figure A.14). This share decreases slightly to about 70%-75% when considering only those agribusinesses that are actively reporting in the relationship data each year.

There is also a possibility of overestimating the sales data in our sample compared to the BEA benchmark, as some companies in our sample may report revenues from diverse business segments not directly related to agribusiness.<sup>12</sup> To address this, we adjust for sales from activities two a broad that ex- non-agribusiness using approaches: approach cludes sectors like mining, construction, and services, and a narrow approach that also excludes non-agribusiness manufacturing and trade sales. The broad approach shows a slight reduction in the share of U.S. output represented in our sample, while the narrow approach suggests a coverage ratio of just under 70% for all U.S. agribusinesses with sales data, dropping to around 65% for the subset of actively covered firms.<sup>13</sup> In conclusion, the above considerations suggest that the FactSet coverage of U.S. agribusinesses is satisfactory, with monitored firms constituting a significant portion of the overall U.S. agribusiness output. This detailed approximation helps frame the scope and scale of our investigation into the agribusiness sector and suggests that our dataset captures a

> 12As entities in our sample are classified based on their primary NAICS code, part of their reported sales might stem from revenues accrued in other business segments. Depending on the BEA’s methodology of classifying output from multi-product establishments, this might lead to an overestimation of the sales data reported in our sample relative to the BEA benchmark.

> 13Additional differences and thus under- or overestimation relative to the BEA benchmark can arise from the treatment of cross-border sales depending on the BEA methodology and potentially consolidated reporting for revenues accrued by foreign subsidiaries of the U.S. agribusinesses in our FactSet sample.

11
# **Foreword**

_Until the global financial crisis of 2007-09, the global economy was adding an estimated 150 million new consumers of financial services each year. Rates of increase have since slowed but growth continues apace. Most new consumers are in developing countries, where consumer protection and financial literacy are still in their infancy. Particularly in countries that have moved from central planning to market economies, empowering consumers has become a prerequisite for efficient and transparent financial markets and a necessary base to ensure that new consumers have the requisite confidence in the formal financial system. In addition, technological innovation and increased competition for financial services worldwide have created a wide array of financial services available to consumers—all with new risks and rewards. Particularly over the last year, the global financial crisis has highlighted the need for strong consumer protection and financial literacy. As a result, government authorities worldwide are looking at practical and effective ways of improving consumer protection in financial services and promoting financial literacy._ _Consumer protection ensures that consumers receive information ex ante that will allow them to make informed decisions, are not subject to unfair and deceptive practices, have access to recourse mechanisms to resolve disputes when transactions go awry, and are able to maintain privacy of their personal information. Financial literacy initiatives give consumers the knowledge, skills and confidence to understand the information they receive and evaluate the risks and rewards inherent in each type of financial service and product. We are pleased to provide this Working Paper on Consumer Protection and Financial Literacy: Lessons from Nine Country Studies. This Working Paper is being published by the Finance and Private Sector Department of the Europe and Central Asia Region of the World Bank in order to stimulate discussion on what needs to be done to improve consumer protection and financial literacy worldwide. Comments and feedback would be appreciated and should be sent to Sue Rutledge (srutledge@worldbank.org)._ ii
<mark>Energy Poverty Advisory Hub (2023). N</mark> ational Indicators: "Uncovering New Possibilities Expanded - - Knowledge" https://energy <u>poverty.ec.europa.eu/system/files/2023 10/EPAH2023_2nd%20Indicators%20Report_Final_0.pdf</u> <mark>EU Energy Poverty Observatory (EPOV) (2019). Case Study: French National Energy Poverty Observatory (ONPE). Link:</mark> <u><mark>https://energy-poverty.ec.europa.eu/system/files/202110/epov_case_study_france.pdf</mark></u> <mark>European Commission (2023). Energy poverty in the EU. Link:</mark> <u><mark>https://energy.ec.europa.eu/topics/markets-and-consumers/energy-consumer-rights/energy-</mark></u> <mark>-</mark> <u><mark>poverty eu_en</mark></u> European Commission (2023b). Smart grids and meters. Link: Smart grids and meters (europa.eu) European Union (2016). Energy Poverty Handbook. Link: https://bpie.eu/wpcontent/uploads/2016/11/energypovertyhandbook-online.pdf Fehrer, D., and Krarti, M. (2018). Spatial distribution of building energy use in the United States through satellite imagery of the earth at night, Building and Environment, Volume 142, Pages 252-264, ISSN 0360-1323, https://doi.org/10.1016/j.buildenv.2018.06.033.

Fergus, P., & Chalmers, C. (2021). Energy sobriety: a behaviour measurement indicator for fuel poverty using aggregated load readings from smart meters. In Towards Energy Smart Homes: Algorithms, Technologies, and Applications (pp. 21-47). Cham: Springer International Publishing.

Frei et al. (2021). Front. Built Environ., 10 February 2021 Sec. Sustainable Design and Construction Volume 6 - 2020 | https://doi.org/10.3389/fbuil.2020.609877

Freund, C. L., & Wallich, C. I. (1996). The welfare effects of raising household energy prices in Poland. The Energy Journal, 17(1).

Goldblatt, R., Hanson, G., Heilmann, K., & Khandelwal, A. (2016). What's the matter with nightlights? Using Landsat imagery to improve nightlight-based measures of local economic activity with an application to India (pp. 1–18).González-Eguino, M. (2015). Energy poverty: An overview. Renewable and Sustainable Energy Reviews, 47, 377-385. https://doi.org/10.1016/j.rser.2015.03.013 <mark>Gouveia et al. (2022). Energy Poverty. National Indicators. Insights for a more effective measuring. Link:</mark> <u><mark>https://energy-poverty.ec.europa.eu/system/files/202301/EPAH_Energy%20Poverty%20National%20Indicators%20Report_0.pdf</mark></u> <mark>Government of the UK. English Housing Survey. Link:</mark> <u><mark>https://www.gov.uk/government/collections/english-housing-survey</mark></u> Halkos, G. E., & Gkampoura, E. C. (2021). Coping with energy poverty: Measurements, drivers, impacts, and solutions. Energies, 14(10), 2807.

Herrero, S. T., & Bouzarovski, S. (2014). Energy transitions and regional inequalities in energy poverty trends: Exploring the EU energy divide.

Herrero, S. T. (2017). Energy poverty indicators: A critical review of methods. Indoor and Built Environment, 26(7), 1018-1031.

<mark>Hills, J. (2011). Fuel poverty: the problem and its measurement. Interim report of fuel poverty. URL</mark> <u><mark>http://sticerd.lse.ac.uk/dps/case/cr/CASEreport69.pdf</mark></u> 36
deviation of expenditure, percentage of food stamp recipients, share of male headed household and share of poor people.<sup>19</sup>

# _D. Result and Discussion_

First, a simple cross sectional study gives an evidence of a negative impact of remittances on the labor market participation. In 2002, the correlation of remittance and labor market participation at the individual level is -0.036.<sup>20</sup> The result suggests that any individual who receives remittances from abroad is 3.6% less likely to participate in the labor market. The estimates for correlation coefficient are robust across years, and the sign of the coefficient never changes.

However, the weekly hours worked of employed people are not significantly correlated with remittance as seen in the scatter plot of individual level remittance and weekly working hours (Figure 2). There are some mass points around 40, 50 and 60 hours, and the working hours for most workers are fixed at 40, 50 or 60 hours per week regardless of the level remittance income. It suggests that the remittance income is strongly correlated with the labor market participation decision, but not with how many hours the employees would work.

> 19 Poor people are identified by national poverty line defined by PIOJ. See World Bank (2006c). 20 The result is significant at 5% confidence level.

12