rafmacalaba/data-use-mentions-extended huggingface dataset:
Before we turn to testing this last hypothesis with a panel survey, we need a better understanding of informality in the CIS-7 and of the relationship between informality and self-employment.

# **Informality**

The question of self-employment and the transition from self-employment to SMEs is closely related to the question of informality. In the Soviet Union, belonging to a recognized category was essential for obtaining any formal right including pension, health insurance, access to schools and others. People outside formal categories were not officially contemplated and the real unemployed or people who had no interest in joining the labor force had to find some form of licit or illicit mean to be recognized as a formal category.

This type of attitude continued during the transition period. Owners of informal or illegal activities would still have the incentives to be registered formally somewhere, usually as self-employed, to keep a pension or a health record alive. Thus, informality is not necessarily expressed in terms of non registered activities but in terms of registered activities or self-employed who in fact conduct most of the business in informal or illegal form. By far, informality in the East (and in the West) occurs in formally registered activities with the known system of 'double accounting'<sup>18</sup> .

Estimates of the informal sector for transition countries are numerous and the methodologies for these estimates variable. Kaufmann and Kaliberda (1996) have pioneered estimates based on electricity consumption, Johnson et Al. (1997) and Lacko (2000) have also followed this approach reaching very large estimates of the informal sectors in transition. Alexeev and Pyle (2003) have been somehow critical of the approach and of the causes that explain the informal sector and Hanousek and Palda (2004) have shown that this approach may be unsound. Schneider and Klinglmair (2004) review these approaches and also propose a different estimation procedure reaching their own figures on estimates of the informal sector in transition and non transition economies.

Tables 4.2 and 4.3 report the various estimates for
4 countries with IRAs than countries with private involvement in the local loop in 2003 while the opposite is true for developed countries. In other words, a country does not seem to need a regulator to attract private operators and a regulator does not guarantee that the government will be open to the private sector in its local loop. Second, it shows that, while on average the introduction of the private sector was simultaneous in developed countries (in 1997), private sector participation briefly preceded the creation of regulatory agencies in developing countries.

# **3. TELECOM PERFORMANCE AND ITS DIMENSIONS**

In this section, we first discuss the dimensions of telecom performance of interest to policymakers. Then we define the performance indicators we have selected in order to analyze the impact of reform policies on sector performance and present basic data for developing and developed countries.

It could be argued that the five main dimensions of telecom performance of interest to policymakers are fiscal costs, access rates, affordability of services, quality of services, and productivity. The main challenge is thus to identify economic indicators that best approximate these dimensions in practice and for which data are available for a large sample. The need for wide coverage essentially rules out the fiscal dimension of the analysis. There is essentially no statistical information on the level of subsidies in the sector before and after reforms. While in many countries, in particular the richest ones, it could be argued that reforms have simply ended any type of public financing in the sector, for many of the poorest, this assumption does not necessarily hold. In the poorest parts of Central America or Sub-Saharan Africa for instance, subsidies are still key sources of financing for connectivity in rural or remote areas.

Access indicators should measure the extent to which people have the right to obtain or take advantage of telecom services—it does not necessarily mean they use the service. Affordability indicators should give a sense of the extent to which telecom services are provided at a reasonable price. Quality indicators should encompass both qualitative and
, with each group being divided based on seasonal precipitation and temperature patterns, based on a raster version of the map available at 0.5° resolution.

- **Crop yield estimates** for Maize, Sorghum, and Rice, from the HarvestChoice Dataverse (Wood-Sichra et al. 2016) capture the estimated yield of various crops (ton/km) at 0.5° resolution.

The full set of satellite indicators used for each country are listed below in Table 2.

_Table 2: Indicators and sources for auxiliary satellite data_

|Satellite indicator|Sri Lanka|Tanzania|
|---|---|---|
|**Urbanization**|||
|Night-time-lights|VIIRS|VIIRS*|
|Building footprints||Ecopia and Maxar, via Gates<br>Foundation*|
|Built-uparea||Global Urban Footprint*|
|Built-uparea|Global Human Settlement Layer*|Global Human Settlement Layer|
|Population||WorldPop|
|Agglomeration index||Belghith et al (2020) (See<br>Appendix A)|
|Spatial features|Sentinel 2*||

10 The team also calculated spatial features using the Sp.Feas package for Tanzania based on Sentinel 2 imagery, but these were found to be highly colinear with the building footprint data and were therefore discarded.

8
- III. Although the swings of intellectual pendula are not always easy to predict, it seems probable that inequality will remain a major topic of public and academic interest for the foreseeable future, as various major global forces currently contribute to rising gaps both within and between countries. Against a background of much more abundant academic research and public debate on inequality in recent years, I argue that the Bretton Woods institutions can and should remain relevant in this area. Their niche, which is a hugely important one, is “inequality at the bottom”, in contrast to the growing emphasis elsewhere on inequality at the top. A continued focus on poor people, poor countries and, especially, poor people in poor countries, remains much needed and the World Bank and the IMF are well-placed to provide it.  Four specific areas are suggested for this research agenda.

Methodologically, the paper draws on three sources of information. The first is a simple text analysis of the online document and publication repositories maintained by the World Bank and the IMF. The World bank’s _Open Knowledge Repository_ is an electronic library containing all public-access documents produced by Bank staff since around the year 2000, as well as a selection of older documents. It currently contains over 33,000 documents organized in 11 collections. We downloaded and machine-read 16,573 such documents, between July and September 2021. For the IMF, I draw on 48,616 documents published between 1946 and 2021 and downloaded from the IMF eLibrary between July and September 2021. Using a word search algorithm, we searched the full text of all downloaded documents for a series of keywords, including equality; inequality; poverty; equity; and inequity. In this final version of the paper, I make use only of the “equality and inequality” series, to plot five-year moving averages of both the absolute and relative (to all words) usage of the terms.

This broad-brush quantitative analysis is important to ground truth my assessment of changes in the importance of inequality in the textual
) parallel pre-trends; (2) lack of correlation between the IV and key economic observables; and (3) evidence from Ganong and Liebman (2018) that in the pre-recession year of 2006, changes in unemployment rates, a proxy for economic fundamentals, were not contributing to changes in local SNAP participation profiles.<sup>5</sup> We then turn to national retailer scanner data available from 2006-2015 to document the impact of benefit changes on retail prices and sales. As in Leung (2021), we build on Beraja et al. (2019) to construct a wide variety of store-level price indices based on data spanning over 20,000 stores, 2.6 million barcodes, and 50% of US grocery-store sales.<sup>6</sup> We estimate that a 1% increase in benefits per population causes a moderate and persistent

> 4According to USDA (2019), “the degree of the variation in methodologies and therefore SUA amounts is of concern as similarly situated households living a few miles apart could have significantly different benefit amounts.”

> 5This is shown in Panel A of Figure 3 in their paper: the contribution of unemployment-rate growth to participation-rate growth vanishes in 2006.

> 6See Appendix Section D for details about the choice and construction of these indices. Income-group-specific price indices are discussed in Section 5.

2
/leaders in rural and urban areas of Gao, Timbuktu and Kidal in August and September 2015. The objective of the survey was to analyze perceptions and priorities with regard to the Peace Accord, to analyze perceptions of security, to determine access to basic infrastructure and school attendance, to understand nutrition levels, and to measure household asset ownership.

In addition to this baseline survey, the World Bank was sponsoring a mobile phone survey among IDPs in Bamako, returnees in Gao, Kidal and Timbuktu town and refugees in camps in Niger and Mauritania. This survey interviewed 500 respondents on a monthly basis. In the August 2015 round of this survey, questions about perceptions and priorities with regard to the Peace Accord were included. This paper also makes use of a subset of the responses obtained from that survey, particularly those from refugees in Niger (n=80) and Mauritania (n=100) as these sub-populations who live outside Mali’s borders are important stakeholders in the peace process whose opinions risk being ignored.<sup>15</sup> To select a household in a village or neighborhood for the baseline survey, random selection was used: the enumerator divided the locality into two parts and selected five

> 15 For a more elaborate description of this mobile phone survey, see: Etang Ndip, A., J. Hoogeveen and J. Lendorfer (2016). Socioeconomic Impact of the Crisis in Mali on Displaced People. _Journal of Refugee Studies._

7
Taken together, our results suggest that promoting cooperation between spouses may have larger, statistically significant and positive impacts on household welfare outcomes compared to boosting wives’ empowerment, as proxied by the share of female controlled income in disjoint income. Recalling the predictions of the theoretical model, we expect relatively larger gains from intrahousehold cooperation versus wives’ empowerment where both spouses receive relatively high utility from household public goods, and where current norms limit the ability of husbands to exercise control over their wives’ incomes.

Interestingly, Njuki et al. (2013) investigate women’s empowerment in rural areas of 6 countries, and report findings that help put our findings into a broader context. The authors estimate that rural Malawian women are more empowered than their counterparts in the other five countries included in the study, both in terms of an overall empowerment index as well as most of the index subcomponents. Even though only 23 percent of the sampled rural Malawian women are considered fully empowered, 72 percent reported being self-confident; 53 percent reported having held a leadership position; and strikingly, 64 percent reported having either sole or joint control over household income and expenditures. Additionally, only 6.8 percent of the sample reported that they supported the statement: “there are times when a woman deserves to be hit.” This evidence suggests that the prevailing social norms and customs in Malawi could support women’s income generation and limit husbands’ ability to control that income.

Returning to the theoretical model, our results are also consistent with outcomes that arise when relaxing model assumptions. For instance, we assume that the wife suffers greater labor costs as her ability to control labor income is reduced. If this is not the case, then her labor supply would only be weakly increasing, as captured in the model of Heath and Tan (2016). Additionally, allowing for the husband to choose his labor supply could lead to insignificant impacts on total labor income, to the extent that husbands reduce their labor in response to increase in their wives
model. Despite similar aggregate effects, the relative importance of wage discrimination and gender norms reverses in a model with talent shocks, which aligns with the findings from Hsieh et al. (2019) and is further discussed in Section 7.2. Third, we show that nonhomothetic preferences _amplify_ the effects of declining gender barriers on aggregate and sectoral outcomes because falling barriers make economies richer, shifting consumption and labor demand away from agriculture and toward manufacturing and services. Lastly, we perform a robustness check that accounts for gender-specific comparative advantage across occupation-sector pairs, which we quantify from a benchmark economy – the – United States in 2015 which we assume to have no wage discrimination, following Lee (2024). After adjusting for these estimated gender productivity differences in all country-years, changes in gender barriers remain relevant, accounting for 21% of observed growth in GDP per capita, compared to 28% in the baseline.

**Related Literature.** A large literature documents gender disparities in the labor market, but only a few recent studies provide cross-country comparisons and examine the macroeconomic implications of gender roles. Cuberes and Teignier (2014), Albanesi et al. (2023), and Olivetti et al. (2024) provide excellent reviews. Several papers study the link between gender roles and structural transformation in the United States, including Ngai and Petrongolo (2017), Ngai et al. (2024), Moro et al. (2017), and Rendall (2018). Across countries, Gottlieb et al. (2023), Bridgman et al. (2018) and Bick et al. (2022) use rich time-use surveys to examine the implications of gender differences in hours worked. Our – quantitative approach which measures gender barriers as wedges and quantifies their – importance for aggregate outcomes aligns most closely with Hsieh et al. (2019), Lee (2024), and Chiplunkar and Goldberg (2024). Hsieh et al. (2019) study the aggregate implications of talent misallocation due to gender and racial
# 2.3 Description of the KUR borrowers

Most KUR borrowers are micro entrepreneurs: 97 percent have fewer than five full-time salaried workers and only 44 percent have any paid workers. They operate in a diverse range of sectors of activity, with the most common ones including trade (42 percent of borrowers), crop and animal production (22 percent of borrowers), and manufacturing (14 percent of borrowers). On average, businesses have been in operation for seven years; however, there is considerable variation, with some firms that were established shortly before receiving their loan and others that have been in operation for over 30 years. According to novel data collection for this study described in Section 2.4, the average firm had profits of 3.6 million IDR (US$ 240) in the month preceding the survey (December 2020), and the median firm had profits of 1.5 million IDR (US$ 100).

Although most KUR borrowers have some form of formal documentation for their businesses, most have limited financial management practices, and many do not use bank accounts for their businesses. Eightyfive (85) percent of KUR borrowers have some form of formal documentation for their businesses. Most commonly, businesses only have the Business Certificate (SKU) or the Certificate of Business Domicile (SKDU), which is issued by local authorities and recognizes that the business exists and operates in the locality. Nevertheless, fewer than half of KUR borrowers separate their business and personal finances, and only 28 percent have any written business records. Less than a quarter of firms record every purchase, can easily determine how much cash they have on hand, or can use their records to prove to a loan officer that they would have sufficient funds to repay a loan. Despite limited financial record-keeping, three-quarters of borrowers can calculate the costs of the products and services they offer.

KUR borrowers range in age from the late teens to the elderly, with an average entrepreneur age of 40 years old. Thirty-seven percent
**A Gender Employment Gap Index (GEGI): A Simple Measure of the Economic Gains from Closing Gender Employment Gaps, with an Application to the Pacific Islands**

Steven Pennings<sup>1</sup> World Bank, DECMG

> 1 Email: spennings@worldbank.org and steven.pennings@gmail.com

A spreadsheet with the Gender Employment Gap Index (GEGI) for each country (and background data used in its construction) are available for download [link] or at the author’s website: https://sites.google.com/site/stevenpennings/ JEL: J16, 040, E24. Keywords: gender, employment, female labor force participation, economic growth.

The views expressed here are those of the author and are not necessarily those of the World Bank, its executive directors or the countries they represent. This paper was commissioned under the Pacific Gender Equality Program and guided by Helle Buchhave, Giorgia Demarchi and Dimitria Gavalyugova. I thank Kathleen Beegle, Helle Buchhave, Giorgia Demarchi, Federico Fiuratti, Anna Fruttero, Dimitria Gavalyugova, Aart Kraay and Sergio Schmukler for helpful comments on this paper; Dimitria Gavalyugova for help with employment data for the Pacific Islands; Young Kim for sharing her estimates of the effects of gender employment gaps on growth; Federico Fiuratti for research assistance and Kathleen Beegle and Michael Weber for discussions and data on better employment.
Brazil, is when fierce competition for contracts take place and bidders that do not have the capability of placing bids with bots claim that they do not see their bids through among the high frequency of bids placed by bots. In addition, government agencies and the public now question the wisdom of a random closing to reverse auctions: a great deal of processes are closed at the heat of the bidding or within very few seconds, sparking concerns that the random closing might be cutting short bidding that would otherwise lower prices for the government.

Some governments in Brazil have started taking action against high-frequency bids. For instance, the government of the State of São Paulo will automatically extend the time allowed for submission of bids if one is received within three minutes prior to closing. The state also requires new bids to lower the bidder’s previous bid by a minimum amount, usually 0.5% of the previous price – this is to counter bids that lower the price by cents, just enough to get ahead of the competition.

Given the central importance of auction length, we investigate what would happen if the random closing rule was replaced by another rule? Would government agencies get lower prices under different scenarios? This paper will present both a conceptual framework and novel empirical evidence to answer these questions. We used data on all electronic reverse auctions done by the Federal Government of Brazil during 2015-2017 which encompassed over 112 million bids for 7 million purchased items.

Our research revealed that longer random phases resulted in lower prices, but the effect tapers off at the tail end of the 30-minute period. Thus, it seems that closing the auction randomly does not produce optimal prices, especially when closing within seconds. Unsurprisingly, we found that the size of the discount had a material effect on prices; more specifically, larger discounts within the last three minutes of the random phase resulted in lower prices. In addition, the size of the discounts mattered more for the final auction price than the frequency of discounts. This appears to indicate that
trend GDP.<sup>17</sup> The subsidy peaks in 2029Q1 at $1400 per toe, which amounts to a sizable bill of 0.62% of GDP. As emissions decrease, the revenues from the fuel tax and the carbon tax decline. To continue meeting the public debt target, renewable subsidies are phased out gradually until 2037. During the renewable energy boom, carbon taxes can be temporarily lowered as the renewable subsidies sufficiently reduce emissions to stay on target.

Note that there is considerable parameter uncertainty regarding the size of the renewable subsidy and the duration of the boom. At the peak, the 90% HDI ranges from $300 to $2800 per toe. Regarding phase-out time, the 90% HDI ranges from 2032 to 2042. Given strict public debt and low-skilled consumption targets, the uncertainty about the macroeconomic effects of the policy mix considered translates into uncertainty about how much public funds there will be available for renewable subsidies.

At the posterior mean, revenues will be insufficient to sustain a constant debt-trend GDP ratio, even without subsidies, by 2037. This is the beginning of the phase of the _final push_ . The carbon tax increases from $90 in 2037 to $175 in 2053. The carbon tax required to stay on the path to net zero is subject to only moderate parameter uncertainty. For instance, the

> 15We define stranded capital assets as the private capital stock which F-firms do not wish to hold any longer. Stranded assets are valued at replacement costs.

> 16In the Monte Carlo simulation of the 90% HDI, we fix the start date of the renewable subsidy to 2027Q1 and hold the public debt-trend GDP ratio constant at whatever value it has in that period.

> 17To ensure a smooth transition, the subsidies are phased in already in 2026Q2.

20
**Figure 9: Reduction in poverty from first-order effects of road improvement.**

<!-- Start of picture text --> 700,000<br>600,000<br>500,000<br>400,000<br>300,000<br>200,000<br>100,000<br>0<br>CE Juba ‐ Juba ‐ Juba ‐ Juba ‐ Juba ‐ Both All<br>Rumbek Wau Aweil Bor Malakal roads roads<br>Scenario A Scenario B<br>Reduction in Poverty<br><!-- End of picture text --> _Note: Scenarios A uses a lower bound estimate for the elasticity of reduction in the price gap relative to road improvement (-3.22) while scenario B uses the upper bound (-6.61)._ As visualized in Figure 9, upgrading the roads only in Central Equatoria would reduce poverty by 71,000 to 142,000 people, depending on the scenario. Adding Rumbek, Wau and Aweil to the upgraded road network could reduce the number of poor people by up to 438,000. A second road from Juba to Malakal could reduce poverty by up to 262,000 people. Both roads together have the potential to lift 558,000 people out of poverty. Finally, upgrading roads in all states would remove another 93,000 people from poverty. Reducing poverty by a 651,000 people translates into a reduction of the poverty rate by 8.9 percentage points, from 51.7 to 42.8 percent using the 2009 poverty estimate.

Second-order effects are likely to be even more substantial, although we are unable to estimate them with the data at hand. Several second-order effects would further contribute to an improvement of consumption for households. The reduction in prices would also increase trade volumes exacerbating price reductions and increasing consumption and production. This type of extensive margin of the gains from connecting markets is likely to be of a