rafmacalaba/data-use-mentions-extended huggingface dataset:
assessment tool, Survey of Wellbeing via Instant and Frequent Tracking (SWIFT),<sup>5</sup> which makes use of the latest ML techniques to estimate expenditure levels and the incidence of poverty in 10 to 15 simple questions. SWIFT offers two key advantages. First, the poverty estimates are fully consistent with the official poverty estimates of the country. Second, producing poverty estimates traditionally requires one to two hours of interview and more than six months of data processing, but SWIFT needs only five to ten minutes of interview and less than a week of data processing. Both significantly reduce the time and costs needed to produce poverty estimates. This method is woven into a DRM (disaster risk management) questionnaire. With both SWIFT and DRM data, the team can assess direct and indirect impacts of floods and how these are related to poverty. Gaining insights in these areas is crucial for TURP as the project helps the government create an evidence-driven disaster risk management strategy, which promotes better targeting and informs investment decisions in disaster prevention. In addition, the questionnaire also collects information on food security status of the households. The Coping Strategies Index (CPI index) was developed by WFP and CARE International as an indicator of food insecurity. In Dar es Salaam, DRM interviews were completed with the comparative (reduced) CSI. It is composed of 5 questions on food access and coping strategies to deal with limited food access. It produces a score between 0-56, where a higher score means higher food insecurity.

# 2.2.2 Follow-up interviews over the phone

Follow-up interviews with 701 households were carried out in September 2018. After the floods of April 2018, it was decided to implement a follow-up phone interview to assess the impacts on the households included in the original sample. The follow-up interviews were carried out by a call-center in Dar es Salaam from September 3-11, 2018. Among the 730 households for which phone numbers had been obtained in 2017, 419 were reached and agreed to the follow up interview,
5.7 Piloting and traininz Very thorough pilot tests will be needed of the whole organisational set up of the survey. If numerous respondents are used in each household what are the best arrangements for interviewers? What should the sex, age and background of interviewers be? If anthroponetric measurements are to be taken how is the work load to be split between interviewers? Will the mother be involved in the anthropometric measurements? In a health survey typically two interviewers proceed to each household. Particular attention should be paid to how measuring boards and scales are to be transported (if used). Experience from USAID's Demographic and Health Surveys (DHS) is useful here.

Many questions in a health survey are on sensitive topics and interviewers need thorough training to be able to deal constructively with potential problems.

Special procedures are needed in order to obtain blood, faecal, urine samples etc with specially trained staff made available. 5.8 Seasonalitv and fieldwork operations One potential methodological drawback of single-round survevs investigating health is the seasonal concentration of many infectious diseases and of food shortages. This needs to be taken into account in the design of country health studies. Combined with the need to use highly trained interviewers in order to collect reliable and consistent data on health, this suggests that fieldwork operations should follow a sinilar model to that adopted for the LSMS. In other words, a limited number of teams of interviewers should conduct a programme of work evenly spaced out across an entire calendar year. Entry, validation and editing of data should proceed in parallel. Even at the cost of adding somewhat to the expense of fieldwork, efforts should be made to ensure that interviews in each region and stratum, for example urban areas, are also spread across the whole year. However it should be recognised that conducting year-round fieldwork may be impractical in precisely those countries in which seasonal 41
data can serve as a reliable proxy.

As a cross check, in Appendix Figure A1, we compare the website traffic of ChatGPT against its popularity on the internet, as measured by Google Trend index.<sup>2</sup> Semrush’s estimates of ChatGPT’s monthly website visits closely align with the trends observed in the weekly Google Trends data, a rapid rise following the release of GPT 3.5, a subsequent slowdown after mid-2023, and some short-term fluctuations during holiday seasons. The strong correlation between Google Trends data and Semrush’s traffic estimates substantiates the reliability of the website traffic data. We also compared Semrush data with similar data obtained from other sources, the patterns for popular websites with over 1 million sessions per day are also largely consistent.

While website traffic data is valuable for tracking individuals’ AI usage, it has several limitations. First, individuals’ use of VPNs can obscure the actual geographic origin of traffic. This may bias the usage data for economies with small populations, particularly island territories, though the impact on larger economies is negligible. Second, most of the traffic analytics tools Semrush relies on only work with Google search engine. While traffic estimates from other search engines like Bing, DuckDuckGo, Yandex, and Baidu can be available, the accuracy is less ideal. Results on Baidu is particularly limited, compromising data quality in China. Third, traffic data can inflate user numbers as the same individual with several digital devices could be counted as different users, leading to overestimation of engagement. Fourth, traffic data does not necessarily reflect the depth or quality of engagement with AI tools, what people are using them for, offline AI usage or enterprise-level AI usage. Fifth, as generative AI is increasingly integrated into various new applications, such as search engines or devices like Siri as announced by Apple, the indirect usage of generative AI websites—such as traffic via APIs—cannot be captured by this dataset.

# **3 The Rapid Adoption of Generative AI
at 0.5<sup>◦</sup> resolution and covers the period 1982–2015. The dataset was created by combining agricultural census data, satellite remote sensing and information on crop calendar and crop harvested area. Although the data include only four main crops, thereby partly limiting our analysis, the tradeoff permits us to assemble consistent long panel data. Finally, in some specifications, we exploit data from different sources including type of regime from The Economist Intelligence, broadband internet coverage provided by Collins Bartholomew’s Mobile Coverage Explorer, and other country-level characteristics (i.e., population density, elevation, distance to the 65
. New users do not have a significant effect on the Gini index (which is thus not reported in table 5).

**Table 5. Poverty Impacts, Loss of Ethio Telecom monopoly, New Users**

|_Scenario_|_Poverty indicators_<br>_Headcount_<br>_Poverty gap_|
|---|---|
|Baseline|24.21<br>6.864|
|Increase in new users by 5.2 percentage points|24.13<br>6.836|
|Difference|−0.09<br>−0.028|

_Source:_ Elaboration based on data derived from the WELCOM Stata Tool and the 2015/16 HCES; see CSA 2018. _Note:_ The Gini coefficient is based on consumption rather than income. Gini coefficient results were not significant for new entrants. Due to rounding the difference between the baseline and the increase in new users is not exact.

The increase in uptake is associated with an average relative impact on welfare of 0.28 percent (table 6).<sup>27</sup> New entrants who belong to the richest consumption decile are expected to gain an average of

> 23 These extensive margin estimates have been carried out using the WELCOM mcema module. Please refer to Rodríguez-Castelán et al. 2021.

> 24 See the WELCOM user manual at WELCOM Stata Tool, Global Solutions Group on Markets and Institutions for Poverty Reduction and Shared Prosperity, Poverty and Equity Global Practice, World Bank, Washington, DC, http://dasp.ecn.ulaval.ca/webwel/welcom.html.

> 25 The mcema module allows the user to run six alternative models to estimate expenditures. See the mcema user manual for more information on each methodology.

> 26 Alternatives considered but not used for this simulation involve taking the average at the level of the primary sampling unit, random imputation, linear regression imputation, stochastic regression imputation, and quantile regression imputation. For the purpose of this
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find the set of relevant development indicators, we employ a variable-selection procedure which reduces the number of possible indicators from 42 to about 10. The set of possible development indicators is combined from the FinStats database of Al-Hussainy _et al._ (2010), the Financial Structure database of Beck _et al._ (2000) and various supervisory structure and public governance indicators constructed in Kaufmann _et al._ (2010) and Melecky and Podpiera (2012). By explicitly modelling the variation of the parameters that determine equilibrium credit with our selected set of indicators, we account for the countryspecific level of economic, financial and institutional development and are thus able to more precisely detect excessive credit provision.

We provide empirical evidence to suggest that the credit-to-GDP ratio, which restricts the response of credit to GDP and the GDP deflator to unity, is an inappropriate indicator to determine equilibrium credit. Empirical evidence of this is twofold. We first estimate the aggregate cross-country averages of the income and price elasticities of credit within the MG framework and test the unit elasticity hypothesis. This hypothesis is strongly rejected for the income elasticity of credit, and rejected at the 5% level for the price elasticity of credit. The MG estimate of the price elasticity of credit shows substantial variation and is, in fact, not significantly different from zero. We then inspect the cross-country distribution of the income elasticity of credit and find strong evidence of bi-modality. We use the PMG estimation framework to test for cross-country homogeneity of the income and price elasticities and find that this hypothesis is also strongly rejected by the data.

We show further that the cross-country variation in the elasticities is significantly related to the level of development of the countries in our sample. The main development indicators that explain the variation in equilibrium credit elasticities are: financial depth, access to financial services, use of capital markets, efficiency and funding of domestic banks, central bank independence, the degree of supervisory integration, and the experience of a financial crisis. In addition, countries located in Europe and Central
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al. 2020). The associated disruption to crisis health planning in trading partners makes net importers of medical products particularly vulnerable (Baldwin and Evenett, 2020).

The basic premise underlying the analysis that follows is that attributes of public procurement regulation may influence incentives to use trade policy and decisions to requisition existing stocks and prohibit exports in crises. The idea is that specific attributes of procurement regimes may facilitate or constrain the ability of agencies to rapidly procure needed supplies of medical products in an emergency. PP practices that are designed to control corruption, ensure accountability through due process, transparency, nondiscrimination, and competitive bidding may constrain the ability to respond rapidly. Conversely, PP regimes that are efficient in the sense of allocating contracts more rapidly may be more conducive to addressing an emergency and attenuate incentives to resort to trade restrictions. We do not have strong priors on whether the relationship will be positive or negative but treat this as an empirical question.

Several dimensions of PP policy may be salient in influencing the likelihood that trade policy is used. For example, “buy national” prescriptions reflecting industrial development objectives may be accompanied by restrictive import policies to support domestic production. In circumstances where domestic production capacity is too small to satisfy a crisis-induced increase in demand, a policy bias towards domestic sourcing may be associated with a temporary reduction of removal of import restrictions. The higher the initial import barriers the greater the scope for liberalization. In short, differences in the attributes of PP regimes may be associated with differences in trade policy responses to a global pandemic.

In our analysis of PP regimes we are limited by the availability of indicators that characterize salient attributes of PP regimes.<sup>8</sup> One relevant feature of procurement systems on which comparable information is reported on a cross-country basis is the time taken to complete procurement processes. The World Bank Doing Business Contracting with the Government indicator measures the time <mark>of awarding a specific public contract to a domestically-owned medium-sized limited liability company based on the indicator’s
1<br>1 3 .7<br>0 2 .65 .9<br>2 4 .8 1.2<br>1.5<br>3.5 .75 1.1<br>treeloss 1 slope drought 1<br>3 sd_temp30_yr .7<br>.5 .9<br>2.5<br>0 .65 .8<br><!-- End of picture text --> Notes: Binned scatterplots show the non‐parametric relationship between consumption and environmental risks. X‐axis shows percentiles of natural logarithm of per‐capita expenditure in 2014. Y‐axis indicates level of environmental risks.

_Source: Authors’ calculation based on data from Brauer et al, 2015, Hansen et al., 2013, Vu et al., 2014b, Harmonized World Soil Database, Climate Research Unit, Bangalore et al., 2016, Winsemius et al., 2015, and VHLSS 2014._ 12
and complete an online application process. Along with the general call for firms to apply, PTP specifically reached out to a list of firms that had exported at least once in the past five years to see if they were interested in applying. The closing date for applications was March 23, 2018 (see timeline in Appendix A).

# **2.2 Random Assignment and Firm Characteristics**

A total of 200 firms met the eligibility conditions for the program after applying. These 200 firms were then randomly assigned to two groups of 100 each on April 11, 2018. The application form data were used to stratify firms by size (small, medium, or large), and whether or not the firms had exported at all in the last 3 years. An additional two strata were added: one stratum of 19 export outlier firms (defined in terms of having export values, the number of destinations exported to, or the number of different products exported above the 95th percentile in the self-reported export data on the application form), and one stratum of 1 firm that was missing firm size information. We then formed

> 3This is a pseudonym, which we use at the request of PTP.

6
Moving from disposable income to consumable income further reduces the Gini coefficient to 0.464 (Figure 2), which is indicative of a remarkable finding: the net effect of adding indirect subsidies and subtracting indirect taxes to/from disposable income is surprisingly equalizing. As Figure 4.B shows, this is not only due to the positive marginal contribution of indirect subsidies to the inequality reduction, but also because indirect taxes have a slightly positive effect despite their regressivity, as indicated by a Kakwani index of -0.03. The latter result is referred in the literature as the Lambert’s Conundrum (Lambert, 2001), which states that “ _If taxes are regressive in relation to the original income but progressive with respect to the less unequally distributed post-transfers (and subsidies) income, regressive taxes exert an equalizing effect over and above the effect of progressive transfers_ ” (Enami, Lustig, and Aranda, 2017).<sup>24</sup> As noted, indirect taxes in Chile are regressive with respect to market income plus pensions (the original income), but they are progressive with respect to disposable income (the less unequally distributed post-transfers income), as indicated by a Kakwani index of 0.09. Indirect taxes, therefore, exert an equalizing effect over and above the effect of progressive direct taxes and direct transfers. This finding evidences that the redistributive impact of fiscal interventions must be assessed by considering the whole system and not as isolated tools, which in turn could lead to misleading policy conclusions.<sup>25</sup> Overall, when taking consumable income as the end concept, only social contributions and the subsidy to gas exhibit, respectively, a negative and neutral effect on inequality, whereas both direct taxes and transfers account for the largest positive marginal contributions (Figure 4.B). The overall equalizing effect of taxes and direct transfers is unambiguous as the Lorenz curve for consumable income lies completely above the Lorenz curve for market income plus pensions (Figure 5).
measured by per capita GDP.<sup>17</sup> To what extent we pick up development related effects related to bilateral trade with the Park and Ginarte index remains open to discussion.

For high technology trade in Tables 4 and 5 the evolving pattern is different. For both exports and imports, the Park and Ginarte index has a significantly negative impact on the probability that countries trade with each other. The impact of IPRs on positive trade flows, in turn, is slightly negative but not statistically significant. This result is somewhat surprising. If IPRs influence trade flows, we would expect this influence to be most visible for trade in knowledge-intensive goods. Several explanations can be brought forward. First, strong market power effects in the case of high technology goods may offset positive market expansion effects caused by stronger IPRs regimes. Second, stronger IPRs regimes may cause high technology firms to serve foreign markets by FDI, in-part substituting for trade flows. Third, it may be that the Park and Ginarte index does not correctly capture the IPRs effect (see below for a discussion) or that development related effects interplay with stronger IPRs protection. Fourth, our high technology aggregate may include many knowledge-intensive goods which are insensitive to the destination country's IPRs regime; for these goods other than legal means may be more important in appropriating investment in R&D (e.g., first mover advantage or rapid movement down the learning curve). Finally, we omitted important explanatory variables in our gravity equation such as tariff and non-tariff trade barriers; this type of specification error may bias our estimated results.

# **V. Comparisons to related studies**

There are several related studies which also try to estimate the effects of intellectual property rights on bilateral trade flows. 1<sup>8</sup> Maskus and Konan (1994) also use a gravity model to estimate the effect of IPRs protection on bilateral trade. They regress the index developed by Rapp and Rozek (1990) along with several
23

# **_Securities markets are relatively more important at higher income levels._**

The Global Financial Development Database allows for examining the relative size of financial institutions and financial markets around the world. The issue of financial structure – usually approximated by the relative size of bank credit and stock market capitalization – has been an important topic in the policy debate.

In a recent paper, which uses data that are part of the Global Financial Development Database, Demirgüç-Kunt, Feyen, and Levine (2012) examine the issue of financial structure empirically and find that as economies develop, use of services provided by securities markets increases relative to those provided by banks. In other words, as income increases, the marginal increase in economic activity associated with an increase in bank development falls, while the marginal increase in economic activity associated with an increase in securities market development rises. This work highlights the potential economic development costs of policy and institutional impediments to the evolution of the financial system.

The existing research and policy work does not provide enough guidance to justify targeting a particular financial structure for a particular country. However, if market or bank development is too skewed compared to what one could expect given their level of economic development, the above research findings provide a reason to dig deeper: one would need to find out if taxes, regulations, legal impediments or other distortions are leading to excessive reliance on banks or markets. Facilitating a shift from a bank-centric system to a more market-based system through a policy is never an easy task. Actively intervening to ―develop‖ markets is likely to be problematic. Interventions should be more along the lines of enabling environment and reducing impediments. Even in systems with relatively strong role of the state in the economy, shifts in financial sector structure do not occur overnight. China (Box 1.3) is a case in point: despite policy intentions and reforms aimed at promoting non-bank financial institutions and markets, the financial system remains very much dominated by large banks, and in some ways have
|3%|4%|16%|15%|
|5|3%|4%|21%|9%|
|6|3%|3%|22%|13%|
|7|2%|2%|3%|10%|
|8|1%|1%|7%|7%|
|9|2%|2%|11%|16%|
|10|1%|1%|8%|15%|

Source: Authors based on AECM survey; Eurostat.

Figure 3 –Sectoral transition risk scores for highest ranking 15 sectors, based on GHG emissions and total CGS exposures (NACE 2 sample, 2020) 12