rafmacalaba/data-use-mentions-extended huggingface dataset:
and 2015. Only two countries have three waves of the survey (Bulgaria and the Democratic Republic of Congo), approximately half of the countries have two waves (20% of them are African countries), and the rest has only one wave. Although this is not a panel, firms were asked information on sales and employment for the year of the survey and the three previous years, which allowed the construction of annualized growth rates. To assign pollution data to each firm, we use the year of the survey wave and assign the pollution level that corresponds to that same year. For example, the Republic of Yemen has two waves, 2010 and 2013. Then for firms surveyed during the wave 2010, we assign 2010 pollution mean values, and for firms surveyed in 2013, we assign 2013 pollution mean values. In the end, because firms that have GPS location were mostly surveyed after 2010, our sample is reduced to 80 countries with only one wave of the survey (with the exception of the aforementioned example of Yemen that keeps the two waves).

For our estimation, we only use PM 2.5 data. NO2 data are only available until 2011 and georeference information is available starting at 2010, which results in most of the geo-referenced firms with no available NO2 data. In the end, the sample for the second half of our analysis consists of 56,841 firms, distributed in 412 cities, in 79 countries. From these firms, 17.4% are in Africa, 6.2% in East Asia Pacific, 12.3% in Europe and Central Asia, 14.3% in Latin America, 12.6% in the Middle East and North Africa, 21% in South Asia, and 16.2% in high-income countries.

PM 2.5 concentration levels vary widely across our sample (Figure 1). Only 30% of the firms are located in cities where PM 2.5 levels are considered safe by the WHO, i.e
# **_5.2 Improving the enabling environment for financial inclusion_**

Beyond regulatory interventions, some of the barriers to account ownership highlighted by the unbanked require investments in government-enabled infrastructure to help increase financial inclusion. One example is official government-issued identification, which the barriers data discussed above shows is a significant reason why many unbanked adults do not have an account, as it is almost always required to open any type of account, whether with a financial institution or with a mobile money provider. Biometric identification, such as a fingerprint-based identification, can increase account ownership (as seen in India, discussed above), as well as significantly increase loan repayment rates for borrowers with the highest predicted default risk (Giné, et al., 2012).

Identification is not the only documentation barrier people face, however. Within the sample of adults who report documentation as a barrier, for example, almost half do have an ID. Government identification does not always fully satisfy KYC (“know your customer”) requirements defined by a country’s regulator, however. People may also need documentation such as a utility bill with a home address, which may be difficult to produce.

Access to a mobile phone is another example in which expanding infrastructure and access could facilitate broader inclusion. As mentioned in the section on barriers, the second most common reason adults in Sub-Saharan Africa name for not having a mobile money account was the lack of a mobile phone. The Gallup World Poll data on mobile phone ownership finds that in SubSaharan Africa, 44 percent of the 166 million unbanked do not have a mobile phone. Likewise in South Asia, 44 percent of the 432 million unbanked adults in the region do not have a mobile phone. Access to mobile phones could overcome the barriers of physical distance and the high cost of banking fees that unbanked adults say prevent them from accessing financial services. This could be especially beneficial for expanding access for women, who are much less likely than men to own a mobile phone in Sub-Saharan Africa
most renewable technologies analysed in this paper, the impacts of lower oil prices assessed throughout this paper are limited to general statements. Second, it is not easy to identify the most appropriate alternative system to which the DTP plant should be compared. If deployed as a unit contributing to the base load of a power grid, the criterion for comparison would be related to the minimum LRMC and the alternative to the DTP plant may very well be a non-oil based installation, such as a coal-fired or a hydro plant.

11. Nevertheless, it is possible to obtain some insight from a Bank study of the likely costs at various sizes of a generic DTP plant.<sup>5</sup> ' Based largely on Philippine data and at 1983/84 prices, the study calculated generation costs of about 12.1, 8.4 and 6.6e/kWh; base capital costs of 2,100, 1,700 and 1,300 $/kW installed; and plantation areas of 2,000, 6,700 and 31,000 hectares for 3, 10 and 50 MW, respectively. The key assumptions include biomass yield at 10 bone-dry World Bank, 'echnical and Cost Characteristics of Dendrothermal Power Systeme, **Enetgy** DepL Paper No. 31, _5/_ December 1985.
of sons and daughters born before the time span of interest, her education (no education, some primary education, and some secondary or higher education), a dummy variable indicating whether she is currently in a union,<sup>9</sup> a dummy variable indicating whether she has had more than one union, a continuous household wealth index (see Section 4.1), a dummy variable indicating whether she has always lived in the same community, a dummy variable indicating whether the current location is urban, mortality rates of children under five years at the district

> 9 This variable is not included in the estimation of equation (1b), given that widowhood is strongly correlated with being in union.
human capital of girls.

To overcome that, we also use household surveys to estimate changes at the individual level. The research design for this approach follows for the most part the same identification strategies and assumptions as the school-level analysis. However, the richness of information of the household-level data, as compared to school censuses, allows the analysis to take advantage

> 16  It was not possible to also use matching techniques with the pool of cross-sectional data available. The only common level of aggregation between baseline data —that would be used to predict program participation and construct the propensity score for each household— and follow up data was the district. This implies that matching is only possible at the district level and the province has only 34 districts.

> 17 These samples are restricted to girls who finished primary school (having at least five years of schooling). Additional econometric exercises also show that the GSP program did not have indirect effects on either enrollment in grades 4 and 5 or completion of primary school.

12
intake for richer households (75<sup>th</sup> quantile) is over three times as large as that for poorer households.

These adjustments in caloric intake link directly to concessions in dietary quality. Households at the bottom of the dietary diversity distribution must make larger reductions in the diversity of their diets to maintain energy levels, relative to those at the top of the distribution. The richer households (75<sup>th</sup> quantile) make larger percentage reductions in the quantity (calories) of food consumed than in the quality (dietary diversity) of food consumed.

These findings are consistent with the literature on the impact of high food prices on nutritional outcomes. For example, Klotz _et al._ (2008) argue that during times of economic crisis and when households cannot increase the amount that they spend on food, they are forced to cut back on expensive, micronutrient-rich foods to maintain their consumption of core staples. Therefore economic shocks will lead to micronutrient deficiencies before weight loss. Jensen and Miller (2008) similarly find that in the face of food price inflation, poor urban households in China substitute toward cheaper foods.

These findings are also consistent with past studies related to the impact of economics shocks on nutrition. Diagana _et al._ (1999) find decreases in levels of dietary diversity and changes in food consumption patterns after the 1994 devaluation of the CFA franc using data from West Africa. Martin-Prevel _et al._ (2000) find reductions in maternal and nutritional status following the same currency devaluation. And Block _et al._ (2004) find declines in maternal and child nutritional status following drought and financial crisis in Indonesia in 1997-98. See Ruel _et al._ (2010) for a more detailed review of the literature on the effects of economic crises on household wellbeing.

# _Policy-relevant thresholds_

In terms of the value of food consumption and caloric intake, the marginal effects estimated at the policy-relevant cutoff by UQR are smaller than those estimated by OLS, implying
# **3.1 Horizontal redistribution across age groups**

The generational dimension of the tax and transfer system has been receiving much attention in many European countries’ public debate. As growth has slowed down following the financial crisis and the prevalence of precarious employment increased in many countries, income levels of younger generations have frequently taken a hit. At the same time, the income levels of older generations have been much more stable (Bussolo et. al, 2018). Hence, it is of high relevance to investigate how the tax and transfer systems perform across age groups and how they evolved over the past years. Figure 5 contrasts developments of tax systems across age groups, showing the average income tax and contribution rate by age groups in a selection of countries that representing the different trends around Europe.

# **Figure 5. Different age-tax profiles across Europe: Average tax and social contribution rate by age group, 2014**

_Source:_ Authors’ calculations based on EUROMOD H1.0+. _Note:_ the light blue line indicates the average tax and social contributions rate, calculated as a share of gross income, for 2007. The navy solid line indicates the same variable for 2014. The blue dashed line indicates the counterfactual rate in 2014 had the tax and transfer system been the same as that of 2007.

13
strong test of RD theory: if the theory is right then we should find a negative conditional effect on _SWL_ of our measure of the economic welfare of friends and neighbors.

However, this identifying assumption puts too much onus on our particular theoretical model. We can reasonably expect that the longer-term security provided by friends and neighbors would enhance one’s satisfaction with life independently of current economic welfare. (That would also be the case if wealth gains to friends and neighbors facilitate investments in local public goods that take time to increase economic welfare.) So RD effects may still be present even if we find a non-negative effect of comparison-group welfare controlling for owneconomic welfare; the more robust conclusion one can draw is that RD may exist but is not dominant over the positive external effect.

Table 1 provides descriptive statistics (including for the control variables we will use in our regressions later); we also give an urban-rural breakdown. Note that on average, people tend to think that they are worse off economically than their friends and neighbors. Also note that in all dimensions (objective and subjective) living standards are higher in urban areas.

Two potentially important sources of positive external effects for poor people from better-off households are private transfers and employment, in the form of _ganyu_ (as noted in the Introduction). Figure 1 shows how the total value of gifts given and gifts received (in cash and with imputed values for in-kind) vary with log consumption per person. (These are locallysmoothed scatter plots.) Gifts given (as a proportion of consumption) tend to rise with consumption, though with a sign of a U-shaped relationship in rural areas. Gifts received tend to fall in rural areas, but with signs of a u-shaped relationship in rural areas. Note that recorded receipts greatly exceed the value of gifts given (Table 1); this appears to be common in survey 23
, retail and services industries. Third, we drop firms with less than 10 employees. This removes some of the cross-country variance regarding reporting requirements for small firms, and removes suspicious listings which may be holding companies rather than active firms. Finally, we drop firms with more than 5000 employees to trim outliers.<sup>17</sup> We relax these assumptions in robustness checks in Section V.C. to show that none of them drive our main results.

The unique attribute of the BvD dataset for our purposes is that it provides ownership and management information at the firm-level, compiled from the accounts data from official sources. Importantly, BvD harmonizes job title descriptions across countries to define managers as “individuals actively working for/in the company on a daily basis, who deal with current affairs on an executive point of view, but who do not necessarily sit at the table of the board of directors”. This emphasis on defining managers as part of the active workforce of a company, rather than board members or directors for example, is crucial since it maps directly to the notion of management used in our model. Moreover, BvD manually matches country-

> 14We thank Daniela Scur for helping us link the firms in our dataset with those in the WMS.

> 15For example, in some countries only the city is reported which is much finer than the geography available in other datasets. By querying the list of cities in Google Maps, we retrieve the generic address for the city that includes the full list of regional identifiers (e.g. country, state, municipality and city).

> 16

> 17

10
many economies dominated by the informal sector. It also presents an unavoidable challenge for policy as formal registration is likely to be a first step before firms can start integrating in GVCs.

By construction, our data will miss a limited volume of cross-border economic activity by smaller firms that goes unreported. This is especially prevalent in agricultural products, but also in manufacturing there likely is a trail of smaller, informal firms that make small sales in neighboring countries.

# **4. Results**

Our empirical results are organized around eight important messages that we want to highlight. We summarize them at the end, but in the following sub-sections we first discuss the supporting evidence in detail.

## **4.1 Few firms are globally engaged**

We first document the absolute number of firms that export as well as its increase and the growth in absolute export volumes. For this analysis, we use an export threshold of 10,000 USD per year. We exclude smaller exporters for two reasons. First, the customs data also includes trade flows for individuals and firms that export idiosyncratic (often personal) items without really being in that line of business. There is no way to differentiate them from firms that would are indeed producing the items, but are simply not (yet) successful at exporting. Second, we cannot be certain that the registered firms in our dataset represent an exhaustive 8
Departures from the hypothesis of integration persist for all products but tur arhar and moong, once controlling for the considered determinants. This points to unobserved factors that matter for integration. For the cases of tur arhar and moong, we cannot reject the hypothesis that the law of one price holds after controlling for transport costs. From the estimates in Table 20 we device a statistical test for the law of one price. The null hypothesis is that the law of one price holds. Therefore, after controlling for the determinants, we expect the fixed effects plus the constant term to be statistically equal to zero. We report the test statistics in Table 22. We test all commodities together and each commodity individually. We adjust the individual using the Bonferroni method that corrects for the fact that when testing individual hypothesis there is a random probability of rejection because of the number of tests. When testing all the commodities together we reject the hypothesis of the law of one price holding for every good. When testing this hypothesis by commodity, we find that, for tur arhar and moong, price deviations are equal to zero once controlled for transport costs.

## _The role of consumers’ preferences and local production_

For a subset of the sample we measure local production and consumption preferences **.** We rely on household surveys and local production statistics to test for the role of consumption and production on the deviations from the law of one price. Because data on consumption and production patterns are not available across all district/states and commodities, these variables are included in an alternative specification (reported in the last two columns in Table 20).

Consumer preferences play an important role in retail markets. The marginal effect of increasing the consumption share of a given commodity by 1 percentage point is correlated with a reduction of deviations from the law of one price of 1.7 percentage points. The production variable is not statistically significant, and it is not retained in the final model.

Commodities for which there is strong demand have lower deviations
subsidy increases as supply elasticity increases, and (v) demand elasticities influence the subsidy for large importers and exporters.

Empirical evidence about agricultural protection using the framework of Anderson (1992), Anderson and Hayami (1986), and Swinnen (1994) is plentiful. Two studies that employ cross-country agricultural protection data are summarized here, leaving discussion of U.S. studies for the following section. Olper (1998) employs a reduced form econometric model to explain the structure of Common Agricultural Policy (CAP) transfers in eight countries in the European Union. He considers effective and nominal protection rates in these eight countries annually over 1975-1989. The explanatory variables are (loosely) motivated by (i) the pressure group model of Becker (1983, 1985) and Olson (1965), (ii) extensions of the model of voter-politician interactions by de Gorter and Tsur (1991) and Swinnen (1994) and de Gorter and Swinnen (1994), and (iii) the model of altruism by Bullock (1994). Olper’s panel regression estimates yield three findings. First, agricultural protection increases under adverse market conditions for the farming industry supporting the counter-cyclical hypotheses of Bullock. Second, countries with comparative disadvantage in agriculture enjoy greater protection in agriculture supporting the view that Stolper-Samuelson effects motivate losers from liberalization to organize politically. Third, a high budget share for food consumption reduces protection perhaps indicating government’s concern for welfare losses from protection. In sum, both, special interests as well as government concern for welfare determine the structure of CAP transfers.

Honma (1993) empirically investigates whether Japan’s agricultural protection is determined according to the Anderson-Hayami (1986) framework of endogenous protection. The dependent variable in his regression is a nominal protection coefficient (NPC) measured as the ratio of the value of agricultural output in domestic prices to its value in border prices. Its log represents a rate of difference between the output valued in domestic and border prices. Using panel data on 14 industrial countries between 1955-1987 Honma
because privacy protections tend to help build trust in digital transactions. The former variable’s effect is ambiguous, at least in the short run. On the one hand, such laws require that digital signatures have equal recognition under the law as properly signed paper contracts. On the other hand, such regulations require authentication procedures to ensure that parties involved in a transaction are real, which can deter the use of digital payments in contexts where authentication comes at the expense of privacy rights.<sup>14</sup> Finally, _Capabilitiesi2019_ is included to control for human capabilities that are positively linked to DFS usage as reflected in educational attainment. In the regressions below, we rely on mean years of schooling among adults aged 25 or older from the UNDP’s Human Development Index to proxy for this factor, because of its wide country coverage. Again, results are qualitatively similar when the schooling variable is replaced by the full HDI or the World Bank Human Capital Index.

Equation 2 adds to equation 1 the share of the of the population that made or received a digital payment in 2017 ( _DigPayi,2017_ ), which is from the penultimate version of the Global Findex dataset. It is included to control for the level of digital payment usage in a country prior to the pandemic.<sup>15</sup> Recall that our estimation approach for uncovering causal relationships is rooted in the assumption that the COVID-19 shock was unanticipated, and that its effects on digital participation depended on pre-existing conditions. For this reason, the explanatory variables are measured in 2019 to the extent possible. By controlling for the level of digital payment usage just prior to COVID-19 (and the trend in payment usage prior to that), equation 2 fully controls for developments in payment usage to that point. For these reasons, the coefficients for the remaining

> 14 For additional details on the construction of these indexes, see World Bank (2021, Chapter 6).

> 15 Note that the Findex data were not collected in 2018
Figure 3. Percent of firms expected to give gifts in meetings with tax officials**

<!-- Start of picture text --> 45 41<br>40 33.7<br>35 29.1<br>30<br>2520 15.3 14.6 17.4 18.9 17.9 17.9 13<br>15 10.8 10.9<br>10 7.7 7.3 8.3 6.5<br>5 1.2 0 2 0.4 3.1 0.8<br>0<br><!-- End of picture text --> Source: World Bank. Enterprise Surveys Taxes are paid by a minority of firms in South Asia that have to contend with relatively high corporate tax rates and poor tax administration. Most firms do not pay any taxes (due to informality and availability of legal exemptions) or reduce their tax liabilities through various schemes. This regime results in a

> 51 Ibid

> 52 This is well documented in the First Report of the Tax Administration Reform Commission in India. Interviews with tax experts working in South Asia suggest that the problem of disproportionate pressure on good taxpayers due to revenue targets is common throughout the region.

> 53 Apparel Export Promotion Council, India. 2013. Agenda Note for Consideration of Inter‐ministerial Workshop on Apparel Sector.

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8|
|Europe, Middle East & North Africa|250|12.7|165|4.8|293|4.5|1,035|6.8|
|Sub-Saharan Africa|78|3.9|68|2.0|94|1.5|341|2.2|
|**Memo:**|||||||||
|BRICS 5 countries|72|3.7|203|5.8|482|7.5|2481|16.3|
|OPEC 12 members|280|14.2|174|5.0|311|4.8|1,077|7.1|

Source: Based on UN COMTRADE database.