rafmacalaba/data-use-mentions-extended huggingface dataset:
br>Note: Numbers reported in the table as of 2007. GSM = global system for mobile communications; Mbps = megabits per second.<br>— = Not available.<br>n.a. = Not applicable.<br>Figure 21. Impressive expansion of the Internet market in Burkina Faso<br>a. Internet service trends b. Benchmarked against West African peers<br>0.8 16 9 160<br>0.7 14 8 140<br>7<br>0.6 12 120<br>6<br>0.5 10 100<br>5<br>0.4 8 80<br>4<br>0.3 6 3 60<br>0.2 4 2 40<br>0.1 2 1 20<br>0.0 0 0 0<br>Internet users (per 100 people)<br>International Internet bandwidth (bits per second per person) Internet users (per 100 people)<br>International Internet bandwidth (bits per second per person)<br>Internet users Internet users<br>basket for internet<br>International internet bandwidth<br>International internet bandwidth / Price<br>1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 Cape Verde Senegal Nigeria Gambia, The Togo Ghana Cote d'Ivoire Guinea-Bissau Benin Mauritania Mali Guinea Burkina Faso Niger<br><!-- End of picture text --> _Source:_ World Bank, including AICD analysis.

32
underlying welfare distribution (see also Narayan et al., 2022). First, they calculate the probabilities for each type of household defined by the household size, education and age of household head, and area of residence from phone surveys to estimate the income loss probabilities for a particular type of household. These probabilities for each type of household from the phone surveys are then mapped to the 2019 household survey available for each country. Second, whereas one can estimate the probabilities of income losses for each type of household, the size of these losses for each household is still not clear. The sizes of these losses are important for understanding the changes in household income in 2020, and thus, understanding the impact of the pandemic on poverty. To get a sense of the size of the losses, Mahler et al. (2022) rely on sectoral – agriculture, industry, and service – growth rates in national accounts. The underlying assumption in their formulation is that the sum of all household losses (calculated using the first step above) are equivalent to the total loss in national accounts. Using this assumption allows

> 8 Countries reporting change in household income report either if they lost, gained, or had no change in income since the start of the pandemic. Countries reporting change in household consumption report if households lost or did not lose consumption since the start of the pandemic. The income aggregate is preferred where available. Table A1 lists countries with the respective welfare measure used.

14
. It is estimated that it can reduce the annual mileage of private passenger cars and motorcycles by 540 million and 16 million vehicle-kilometers respectively. According to the feasibility study conducted by national authorities, the tram line will have an upfront cost of approximately €225 million and annual operation and maintenance costs of €12 million (Ministry of Communication and Works, Public Works Department, 2015). It is estimated that it will serve up to 17.9 million passengers in year 2030, while it will have an annual electricity demand of about 9,130 MWh. According to these assumptions and based on results extracted from OSeMOSYS, in the first three years of its operation (i.e. 2028-2030), the added modal shift enabled by the tram line will result in final energy savings of 87 ktoe (mainly gasoline) and a reduction in GHG emissions of 249 ktons CO2 eq.

The third measure that relates to the transport sector is the scrappage of vehicles, which have a first registration date older than 15 years, and their replacement with battery electric vehicles. For a maximum replacement rate of 200 vehicles per year with a grant of €5,000 per vehicle, this measure will require public funds of €1 million annually. Overall, it is assumed that 400 vehicles will be replaced through this scheme. This will allow short-term annual energy savings amounting to 0.2 ktoe in 2023, leading to a GHG emission reduction of 0.5 ktons CO2 eq in the same year. Given that OSeMOSYS projections about the power generation mix indicate that the carbon intensity of electricity will decrease over time, it is estimated that the annual GHG emission reduction will increase to 0.6 ktons CO2 eq by 2025.

Implementation of a carbon tax on fuels for sectors that do not fall within the EU ETS can be considered as an ambitious but useful measure to promote early action towards an energy transition aligned with the Paris Agreement goals. This envisioned tax is assumed to be implemented gradually and reach €120 per ton of CO2
_Average monthly wage (USD, PPP)_ is the average monthly wage received by the individual during that 12-month period. If the student worked at least one month, average wage is equal to total wages divided by the number of months he worked (i.e., it is equal to her average monthly wage conditional on working). If she did not work at all, average wage is zero. Purchasing power parity (PPP) adjustment of wages was done using the 2019 (Ecuador) or 2017 (Brazil) PPP conversion factor.

# **Other variables based on individual-level administrative data**

_Student administrative variables (PCA score)_ consist of an index created for Brazil and Ecuador through a Principal Component Approach with the goal of reducing the dimensionality of the student characteristics included in estimation. The index includes the following student characteristics: age, gender, mother’s education level (less than primary, primary, high school, higher education, unknown), whether the student has children (Ecuador), and socioeconomic status index (Ecuador).

_Peer administrative variables (PCA score)_ follows the same logic, but for peers’ (average) characteristics. The variables included in the calculation of the index were average characteristics at the student’s cohort level, which is defined as all students (excluding the student herself) who entered (for Brazil) or graduate in (for Ecuador) the same program in the same year. Thus, the calculation of the index includes peers’ average age, percentage of peers who are women, percentage of peers with each level of mother’s education, percentage of peers with children (Ecuador), and peers’ average socioeconomic index (Ecuador).

# **Outcomes from survey data**

_Dropout rate_ is the percentage of students that dropped out among those who were supposed to graduate the academic year before the survey.

_Extra time to graduate (ETG)_ is the average percentage of additional time that students take to graduate relative
# **5 Conclusion**

As most exporters are also importers of intermediate goods and other inputs required in the production process, trade costs that constrain the capacity of firms to import are also likely to affect their export dynamics, especially in the context of rising GVCs. Using trade flows, Customs transactions and firmlevel data, several studies have so far provided evidence on how the reduction of import barriers can shape export performance and diversification patterns. This paper contributes to this literature by quantifying a new source of trade costs based on a novel measure of uncertainty in import clearance times and by exploring its impact on manufacturing firms’ export entry, exit and survival decisions. Using the PPML estimator on a sample of 48 developing countries over 2006-2014, we find that supply chain unreliability due to uncertainty in import clearance times impacts neither the entry nor the exit rate but translates into lower survival rates for entrants, reducing the number of firms that continue to serve the foreign market beyond their first year of entry. This effect grows larger over time with the accumulation of reputational costs to input-importing exporters and is mainly driven by South-North trade, possibly reflecting the time-sensitivity of importers in developed countries that tend to rely more heavily on lean supply-chain strategies. Results also reveal sectoral heterogeneity in the impact of import uncertainty, as well as the mediating role of sunk costs of entry in foreign markets that are found to attenuate the negative effect of uncertainty on export survival rates as firms delay exiting the export market. Most importantly, our measure of uncertainty displays a distinctive effect on export performance, as neither the mean nor the median time to import impacts survival.

Our findings suggest that developing countries seeking to promote the survival of newly-exporting firms in foreign markets should consider undertaking policies targeted at reducing the uncertainty these firms face when importing their production inputs. Predictability in border clearance times is key to a smooth running of the supply chain, allowing firms to deliver on time to time-sensitive foreign customers. Notwithstanding the contribution of firm-specific factors such as limited financial liquidity or willingness to
strategies for reducing these costs, and highlighting sources of information for comparing costs and learning about new remittance products. This included explaining the fixed fee and exchange rate commission components of the cost and illustrating how much they vary across different providers, showing how the transaction costs fall with the amount sent so that bundling smaller transactions into one large transaction saves costs, and providing information about the _sendmoneypacific_ website for comparing costs and about the new Westpac direct debit card as a new product.

The remittance material was then adapted for the East Asian and Sri Lankan populations. Since _sendmoneypacific_ doesn’t cover remittance transactions for these remittance corridors, both groups were given instructions and shown how to get rates and the expected amount received on the Western Union website, plus ANZ Bank online and _fxcompared.com_ for the Sri Lankans, and _MoneyBookers_ for the East Asians in New Zealand.

Initially we had planned that the financial literacy training would focus just on remittances, but inspection of the baseline survey data from the Pacific Island group indicated that very few of the participants had credit cards, and a lack of awareness of this credit channel was corroborated by qualitative discussions with participants. For the Pacific Island group only, we therefore expanded the material covered in the financial literacy training to also include comparisons of sources of credit, especially in terms of their annual percentage rate of interest. The teaching material was based on examples of advertisements for payday lenders and other short term finance companies that used prominent sports stars to target Pacific Islanders (e.g. Figure 1a). The participants were taught how to calculate credit interest rates so that they could compare the annual cost of a payday or short-term loan or hire purchase with the cost of obtaining the same funds either as a cash advance or a purchase with a credit card.

The randomly chosen survey respondents were then invited to the financial literacy training sessions, which were held at multiple times and venues to ensure the maximum participation from those who were invited. These were typically held at churches, community centers,
, Zettelmeyer & Hollar (2008), and Daude et al. (2010).

Argentina introduced export duties after the 2002 crisis to capitalize on the devaluation of the currency among other considerations. This source of taxation was typically used in the past as an emergency source of funding during a balance of payment crisis. The sharp devaluation of the peso in early 2002 and its potential impact on domestic prices was an opportunity to establish an export tax on all products, with heterogeneous tax rates: higher for the main agri-food export products and oil, and lower for processed products such as heavy manufactures. **Figure 20** shows the evolution of export duties as a share of the GDP, discriminating between those arising from commodities and non-commodities sources. As observed, the increase of global commodities prices during the 2000s contributed to raising tax revenues from this source. Notably, the 2008 peak of export duties, contributing to fiscal revenue with almost 3 percent of GDP, matches the first boom peak in the so-called commodities super-cycle.

To understand the impact of export duties on public accounts, long-term prices of commodities are considered. We follow Marcel et al. (2001) and Zettelmeyer & Hollar (2008) assuming a unitary elasticity price of the exports and adjusting the revenues applying the long-term price of the exports considered.

prominently in developing countries. It is also worth considering that in unstable economies like the Argentinian, the concept of potential output that points to the use of the full capacity of production factors loses some clarity (Alberola & Montero, 2006). 23 Real GDP series for Argentina is constructed based on ONP 2004, Ferreres, and current INDEC data.
gap, as it could be the case that use of oDesk by ethnic Indians across countries is uncorrelated with the general Indian-ethnicity populations of countries. Rauch and Trindade (2002), for example, relate trade flows to the distribution of the ethnic Chinese population across countries, rather than the greater likelihood that two observed traders are Chinese.

Table 10 closes this gap using empirical models similar to the gravity framework from the trade literature. The dependent variable in Columns 1-7 is the share of contracts originating from a country on oDesk that are outsourced to India. We focus on shares of contracts, rather than contract volumes, as the adoption of oDesk across countries as a platform for e-commerce is still underway and somewhat idiosyncratic to date. Shares allow us to consider the choice of India for outsourcing independent of this overall penetration of oDesk.

The core regressor is taken from the World Bank’s Bilateral Migration and Remittances 2010 database. This database builds upon the initial work of Ratha and Shaw (2007) to provide estimates of migrant stocks by country. We form the Indian diaspora share of each country’s population by dividing these stocks by the population levels of the country. We complement this diaspora measure with distances to India calculated using the great circle method, population and GDP per capita levels taken from the United Nations, and telephone lines per capita in 2007 taken from World Development Indicators. We also calculate a control variable of the overall fit of the country’s outsourcing needs with the typical worker in India.<sup>20</sup> Column 1 presents our base estimation. We have 92 observations, and we weight by the log number of worldwide contracts formed on oDesk. The first row shows the connection of oDesk outsourcing to the diaspora population share, which is quite strong. A 1% increase in the Indian diaspora share of a country is associated with a 1% increase in the share of oDesk contracts outsourced to India. The country-level placement of oDesk contracts in India systematically followed the pre-existing levels of Indian
_Environmental standards_ are our final category. Here we look at the stock of _ISO 14000_ certifications per capita and the number of _UNEP_ conventions signed, complemented with the Food and Agriculture Organization’s data on _pesticide_ use per 1000, WDI data on the share of _renewables_ in electricity production and _water_ withdrawals relative to internal resources, and WHO data on _air pollution_ measured as particulate matter with diameter of 2.5 μm or less in urban areas.

# **4. Results**

## **4.1. Overall Results**

Focusing first on GVC integration, table 1 shows the results for the full sample of 61 OECD countries covering the years 1995, 2000, 2005, and 2008–11 (columns 1 and 2) and those for the full sample of 40 WIOD countries covering the period 1995–2011 (columns 3 and 4).<sup>8</sup> The production factors labor and capital significantly increase domestic value added. The same applies to both our trade-related variables foreign value added for domestic processing ( _FVADP_ ) and—most importantly—our two GVC measures of backward ( _FVAX_ ) and forward links ( _DVAR_ ). In other words, GVC integration helps increase a country’s domestic value added and thus fosters economic upgrading

**Table 1. Overall impact of GVC participation on economic upgrading**

|VARIABLES|(1)<br>_DVA_|(2)<br>_DVA_|(3)<br>_DVA_|(4)<br>_DVA_|
|---|---|---|---|---|
||**OECD**||**WIOD**||
|_FVAX_|0.0685***||0.0428***||
||(0.0091)||(0.0129)||
|_FVADP_|0.252***|0.232***|0.
.100***|17.078***|1.698|
||(5.800)|(1.466)|(1.139)|(2.305)|(2.550)|(7.090)|
|Observations|43|42|40|44|44|35|
|R-squared|0.060|0.002|0.113|0.073|0.053|0.311|

Source: Own calculations using data from Fitch (up to third quarter 2020), and IMF Financial Soundness Indicators available at https://data.imf.org/?sk=51B096FA-2CD2-40C2-8D09-0699CC1764DA.

Note: Data on the selected core FSI indicators is as per the third quarter of 2020. Robust standard errors appear in parentheses.

Figure 3 provides information on the relevance of considering bank profits as a first absorbing buffer for increases in loan provisioning. Overall, the two approaches provide a similar assessment as denoted by the large pairwise correlation coefficient between the two indicators (0.953).

# **Figure 3: Testing for the inclusion of profits in the computation of the Distance from Break Point (CDBP)**

<!-- Start of picture text --> Upper middle income Lower middle income Low income<br>45<br>40<br>35<br>30<br>25<br>20<br>15<br>10<br>5<br>0<br>0 20 40 60<br>Consolidated Distance to Break Point (CDBP) including profits (in percentage points)<br>(in percentage points)<br>Consolidated Distance to Break Point (CDBP)<br><!-- End of picture text --> Source: Own calculations using data from Fitch (up to third quarter 2020).

Note: The figures report the percentage point increase in the non-performing loan ratio at the
income and financial depth also suggests that there is likely to be room for policy interventions to increase financial inclusion.

# SELF-REPORTED BARRIERS

The Global Findex survey, by asking more than 70,000 adults without a formal account why they do not have one, provides insights into where policy makers might begin to make inroads in improving financial inclusion.

Non-account-holders reporting barrier as a reason for not having an account (%) <!-- Start of picture text --> Religious reasons 5<br>Lack of trust 13<br>Lack of necessary documentation 18<br>Too far away 20<br>Family member already has account 23<br>Too expensive 25<br>Not enough money 30<br><!-- End of picture text --> _Note:_ Respondents could choose more than one reason. The data for “not enough money” refer to the percentage of adults who reported only this reason. _Source:_ Demirguc-Kunt and Klapper 2012.

Globally, the most frequently cited reason for not having a formal account is lack of enough money to use one (figure 1.13). This is the response given by 65 percent of adults without a formal account, with 30 percent citing this as the only reason (multiple responses were permitted).<sup>13</sup> This segment of the population is less likely to be bankable.

On average, respondents chose 1.7 responses, including most commonly the lack of enough money to use an account along with a second barrier. The next most commonly cited reasons for not having an account are that banks or accounts are too expensive and that another family member already has one, a response identifying indirect users. Each of these is cited by about a quarter of adults without an account. The other reasons reported (in order of importance) are banks being too far away, lack of the necessary documentation, lack of trust in banks, and religious reasons.

Examining these self-reported barriers by region
presence in the first three months following the earthquake—161 from a single village. The popular notion of LeT’s heavy involvement in relief work following the earthquake is not supported by our data.

There are other highly reputed international and local charitable organizations under the umbrella of Islamic charity such as the international organization Islamic Relief that had a significant presence in the data (7 percent of the households in the census) and should not be lumped together with the militant organizations.

# <u>Trust</u>

We first note (Figure 4), perhaps surprisingly, that trust in locals in the earthquake zone, on average, is lower than in foreigners—only 25 percent of respondents say that “people in your village” can be trusted compared to 45 percent for general foreigners. The local trust numbers are almost exactly in line with the results of the World Values Survey. The most interesting variation comes within the earthquake zone as we move closer to the fault-line. In line with our earlier data showing the gradient of foreign presence and distance to the fault-line, the foreign trust variables also increase dramatically as we move closer to the fault-line. Trust in foreigners increases to 60 percent as we move to the immediate vicinity of the fault-line compared to 45 percent 20 kilometers away, and 30 percent 40 Kms away (at which point, trust in locals is _higher_ than trust in foreigners). In sharp contrast, _there is almost no relationship between_ local trust variables and distance to the fault-line. We attribute the increase in foreign trust as we move closer to the fault-line to the increase in foreign aid and presence of aid workers: The fact that local trust does not change with distance to the fault-line points to the fact that the increase in foreign trust is not a general disaster effect on attitudes but something that can be attributed to aid itself. Finally, the low absolute level of local trust is both a sign of the fragmentation and 23
reallocation effects of FDI on market composition (Alfaro, 2016), but FDI’s effects on social development are largely ignored. In this paper, we investigate how FDI inflow affects an important aspect of social changes, female entrepreneurship, in the world, along with the interaction between FDI inflow and various economic barriers for female entrepreneurship, and of female empowerment. Female employment and leadership have important ramifications for development of poor countries. More work and leadership opportunities for women would raise the return to women’s time and human capital investment, induce women to emphasize the quality of children at the expense of the quantity of children (Becker and Lewis 1973; Galor 2005), reduce fertility rates and facilitate the critical transition from the Malthusian regime to the modern growth regime (Galor and Weil 2000; Galor 2005).

In this paper, we study whether and how FDI affects female entrepreneurship, and how the FDI effects interact with gender-specific barriers and empowerment. We mainly use the World Bank Enterprise Survey data, and supplement it with complementary indicators of barriers to female entrepreneurship and women’s empowerment. We allow the FDI effects to have two components: the country-level FDI level, and the countryindustry level FDI (i.e., country-specific measure of FDI intensity in an industry, intraindustry FDI for short). The overall FDI effect captures the comprehensive effect of FDI across all industries, and the intra-industry FDI allows for within-industry spillover and/or “crowding out” effects. We define female entrepreneurship by a firm having both women participation in firm ownership _and_ a female being the top manager of the firm, capturing both ownership and control by women for the firm (Atrido and Hallward-Dreimeier, 2011). By this measure, female entrepreneurship varies from zero in some countries to close to 40 percent in Mongolia.

FDI might affect female entrepreneurship via several channels. Via FDI, there can be social norms transmitted from investing countries to host countries. There can be knowledge spillover, both across and within industries, spurred by the