rafmacalaba/data-use-mentions-extended huggingface dataset:
conventional banking (see Anagol et al. 2017). While access to a mobile money account reduces transaction costs, inexperienced customers often require assistance to use their account and do not use the technology in the most cost-effective way. Instead of transferring money from person-to-person using their own account, many inexperienced users require the help of an intermediary and make transfers using agent-to-agent transactions that incur additional fees on both ends of the transaction. Although the practice is officially not permitted by mobile money providers in our setting, it is extremely widespread. In our audit study, we find that agents overcharge consumers in 31% of all transactions. Similarly, inexperienced workers may be unable to use their account without an intermediary and may be prone to disclose passwords and other identifying information to mobile agents or peers to help them access their account, which raises additional consumer protection concerns. One question we ask in this study is

> 12In our population, most workers could not have opened accounts without the assistance of their employers. The firm, for example, provided employment records and identification data directly to the partner financial institutions. Formal account ownership at baseline was rare, and it was not possible to link wage payments to pre-existing accounts.

> 13Mobile money also offers additional features and functionality that traditional bank accounts lack, and that may make mobile money more useful for certain types of transactions such as remittances. In our experiment we use accounts that permit person-to-person transactions, the ability to cash in or out at any registered agent in the nationwide network, the ability to make direct payments, and airtime purchases from mobile providers.

> 14See Suri (2017) for an overview of the literature on mobile money.

7
impact optimal spatial allocations, as do heterogeneous road construction costs and border frictions. The paper navigates this complexity via a graduated approach, starting with small-scale PE investments and gradually progressing towards GE simulations where social planners spend large amounts. This requires different network representations and methods.

To increase the scale of investments to entire roads or collections of segments, I build a detailed representation of the transport network connecting 447 important cities and 52 ports along the fastest routes. My network graph has 1379 nodes and 2344 edges (links), summing to 315K km. I apply a network finding algorithm and find 481 potential new links summing to 104K km. Building them all would raise RE by 7.1%, from 0.68 to 0.72, and MA (denominated in road distance) by 5.5%. The most valuable links increasing RE/MA by more than 0.1% are new trans-Saharan roads through Mauritania, Mali, and Chad and reopening the closed Morocco-Algeria border. Some new roads in Central and Southern Africa would also significantly increase RE/MA. When border frictions are activated, the MA gain drops from 5.5% to 3.9%, with particularly high losses on remote and border-crossing links. The median link yields a 50% lower MA gain under frictions.

According to the World Bank ROCKS database, the median 2-lane highway in Africa costs $ 611K 2015 USD per km. Using a heterogeneous road costs prediction model considering road length, terrain ruggedness, and population density, I estimate the cost of the existing transport network at $ 186B USD’15, and the proposed extension of $ 104K km at $ 56B, yielding an average MA return of $ 1.4/km per $ invested in new links, which drops to _∼_ $ 0.7/km/ $ if frictions are added.

Examining road quality measured by travel speed, I find that upgrading all links to _≥_ 100km/h yields a time-denominated MA gain of 42.
incentives and disincentives correspondingly shape the types of routines used by groups in conflict.

# _4.2 Countervailing versus Autarchic Power_

As suggested by a long line of anthropological research associated with Geertz and Horowitz, our ethnographies of local level conflict show that power is as much about generating shared meanings in a particular context of social and cultural norms and institutions than it is anything else. Lacking influence involves a vicious cycle: those unable to purposefully navigate in shared worlds of meaning-making are precisely those who lack the opportunities for the kinds of conjecture, refutation, inquiry, and criticism, which might result in greater influence. Said differently, marginalization is about lacking both the capability and the occasions on which to engage in productive conflict. With this debt, marginalized actors struggle to “get recognized” in these contexts and tend to oscillate between intense “loyalty” to core cultural values and “exit” from them, often manifest in violent protest or total apathy (Hirschman 1970, Appadurai 2004). Finding the middle ground amidst these two extremes typically involves negotiating meta-rules, intermediaries, and approaches to interest formation and defense, all of which make the prospect of finding resolutions to conflict more palpable.<sup>65</sup> But even adaptive conflict management routines—within or outside of KDP processes—are insufficient to reach the poorest of the poor. The most troubled need the most help to develop the countervailing power to challenge dominant norms of communication. Here, small experiments suggest that such efforts need to speak in deeply symbolic cultural and social languages to become actions of resistance. A small KDP pilot program that targets widows in four provinces provides a good example. Run by an NGO, the program helps organize widows by organizing them to the point that they can collectively rejoin group decision-making.<sup>66</sup> A major tool it uses is training in documentary photography, which some participants have used to express a range of sensations and impressions of village life. Such targeted attempts are in many ways the missing
At the time, less than half the steps considered necessary for fully effective reform had been taken in the countries studied. But reforms have progressed significantly since then, as the forthcoming update of the scorecard is expected to show.

Updated indicators are available for nearly 20 low-income countries (table 8). All but one have a new electricity law, and all but three have or will soon have an independent regulator. Progress on commercialization and restructuring is less uniform. Even more disparate is the presence of the private sector—except perhaps in the form of independent power producers.

A recent survey of urban water issues found that 65 percent of the developing countries had achieved separation between operator and government, yet only 17 percent had a functioning regulatory body (World Bank 2002) in place. Still, a growing number of countries were using more appropriate policies, governance, and management arrangements. But the challenge remains formidable, especially in low-income countries. Out of a maximum score of 7.0, low-income countries averaged 1.8, compared with 3.1 for lower-middle-income countries, and 3.9 for upper-middle-income countries. These findings show that despite progress in the past decade, most countries have a long way to go in establishing an environment that will stimulate increased investment.

A similar recent survey for the transport sector conducted for a sample of 20 low-income high potential developing countries shows that 70.6% of these countries are reforming the port sector, 68.4% the airport sector, and 55% the railways sector (Ouedraogo (2004)). The survey points out that the selected developing countries tend to encourage private sector investment in the port, airport and railway sectors but that competition level has 22
high. This pattern is visualized in figure 2, where expenditure brackets are plotted against the share of the number of transactions and value of transactions.

_Figure 2 Typical Expenditure Transaction Profile_ <!-- Start of picture text --> 40%<br>35.08%<br>34.38%<br>35%<br>30%<br>27.71%<br>24.45%<br>25%<br>20%<br>16.14% 16.04%<br>15% 13.88%<br>10.58%<br>10%<br>6.98%<br>5.38%<br>5%<br>2.74%<br>1.95%<br>0.00% 0.01% 0.02% 0.05% 0.74% 0.80% 1.09% 0.86% 0.57% 0.30% 0.19% 0.08%<br>0%<br>Expenditure Brackets (in US$ Equivalent)<br>Share of transactions Share of amount processed through the FMIS<br>Source: Authors.<br>Share of transactions and amounts processed thru FMIS<br><!-- End of picture text --> The transaction profile data was obtained for Pakistan and Cambodia and was plotted against this template. This has subsequently been used to determine the granularity of the transactions. The granularity of the transactions allows for an assessment of whether the system is being used for retail transaction processing or just for drawing out advances from treasury which are then processed off-line (and not through the system). Therefore, it can be used to see whether there is a wider control problem with the payment approval process in a country.

10
|
|N|85674|34590|87824|

Note: + p<0.10 * p<0.05 ** p<0.01 *** p<0.001 We observe that the number of advertisements has gone down in all three models, corroborating the expected decrease. The rates for advertisement are regulated and revised by the Department of Films and Publication, Government of Bangladesh depending on the circulation of respective newspaper. Based on the survey of Procuring Entity Officials, the average cost of an advertisement for a tender was approximately Tk. 25,200 (approximately US$ 295). It has been assumed that the advertisement costs have increased commensurate with inflation. Based on these figures the cost savings were between Tk. 266 crore (US$ 31 million, as per model 1a) and Tk. 210 crore (US$ 24 million as per model 1b) for about 69,000 tenders.

- b. Tender Preparation Costs – The shift to electronic tendering has meant a number of costs pertaining to tender preparation are no longer incurred. There were significant printing costs, transportation costs, postal costs that are being saved due to the shift. The savings per tender is estimated on the basis of responses of the PE official’s survey. The averages are calculated by organization as the number of tenders vary significantly by organization (with LGED the majority of tenders in consideration), and the tender preparation cost vary in a statistically significant way across organizations. As the PE officials were asked the average tender preparation cost over a time period, the tender preparation costs have not been adjusted for inflation. The total tender preparation cost savings was estimated to be Tk. 53.5 crore (US$ 6.3 million).

72
# **3.3 Analysis of Bilateral Sectoral Trade**

We now refine our estimation approach by considering a gravity equation of bilateral trade, which allows us to simultaneously consider exporter and importer effects using a detailed panel of bilateral trade data. We define our treatment groups analogously to the definition in subsection 3.1, but now differentiate between exporter and importer effects in a unified framework. The estimating equation here is given as _TRijst_ is the dollar value of (unidirectional) exports from country _i_ to country _j_ in sector _s_ in year _t_ . As before, we account for size effects by including the GDP of the exporter and importer, allowing for these effects to vary between the various sectors. Whereas in the earlier analysis of aggregate trade – estimated separately for exports versus imports – there was only a single _IPA_ variable to consider, here we delineate the effect depending on whether a country is the exporter ( _IPAit_ ) or the importer ( _IPAjt_ ) in a particular trading relationship. Analogous controls for TRIPS compliance are included again, as in the earlier version.

Our regime of fixed effects remains largely unchanged relative to that in equation (1). We include exporter- and importer-specific income-group-sector-year fixed effects ( _λ_ ( _i_ ) _gst_ and _λ_ ( _j_ ) _gst_ ) and linear time trends ( _λjt_ and _λjt_ ), and in addition, we include the dyadic fixed effect _λij_ to account for long-run bilateral determinants of trade costs (such as distance, shared border, and common language), accounting for the gravity-based nature of the estimation. These country-pair effects also control for time-invariant exporter- and importer-specific factors, because they are 25
Treasury Bond Yield|(0.0569)<br>-0.384***|(0.0571)<br>-0.382***|(0.0572)<br>-0.381***|(0.0560)<br>-0.288***|(0.0558)<br>-0.293***|(0.0574)<br>-0.359***|
|||(0.0823)|(0.0825)|(0.0822)|(0.0827)|(0.0827)|(0.0835)|
||ICRG Index|-1.926***|-1.983***|-1.921***|2.566|19.35***|0.211|
|||(0.391)|(0.395)|(0.391)|(2.113)|(6.657)|(2.843)|
||Methodology Assessment|0.103|||4.143**|||
|||(0.0983)|||(2.055)|||
||Periodicity and Timeliness Assessment||0.0663|||19.10***||
||||(0.267)|||(6.335)||
||Data Source Assessment|||0.123|||1.784|
|||||(0.0993)|||(2.582)|
||Methodology x ICRG||||-1.093**<br>|||
||||||(0.495)|||
||Periodicity and timeliness x ICRG||||
middle class larger relative to Kharas (2010), who focuses on the consumer market. As a result, we have not made an assumption about whether increasing returns are deferentially available in the investment or consumption sector. More generally, GDP is preferred to income based on household surveys given the risk of top-coding, and the fact that we are interested in the middle and top of the distribution, especially in low and lower-middle income countries (Deaton, 2005; Ravallion, 2003). The use of national accounts in place of average income is most controversial when studying the lower tail of the income distribution (Pinkovskiy and Sala-i-Martin, 2014).

**International market size** The third variable is a measure of relative international market size, according to legally-binding provisions to international trade agreements. We define each country’s global market by summing up the populations and incomes of all other countries, with weights corresponding to the number of legally enforceable provisions of multilateral agreements between the country and all others. Table 2 lists the 32 legal provisions in our data set, and shows that they fall into two broad groups, which together make up the legal architecture of the international economy.<sup>9</sup>

This measure has three main advantages for our analysis. First, it allows us to measure directly the effect of international integration treaties, participation in which is a policy choice for the government. Other analyses of trade liberalization (Sachs and Warner, 1995; Wacziarg and Welch, 2008; Easterly, 2019) have typically focused on a mixture of policy decisions (e.g., liberalizing state monopolies in exporting sectors), and trade outcomes (e.g., abnormally low shares of trade to GDP). By focusing specifically on the policy decision to integrate economically through trade agreements, we ensure our counterfactuals are tied to policies actually within government’s control. Second, because we calculate market size in terms of GDP and population, these measures allow us to estimate directly the relative value
entrepreneur faces to start a business, from a legal perspective as well as in practice. The index of bankruptcy regulation should reflect the speed and efficiency of the bankruptcy process; in particular how well the justice system establishes priorities for creditors and enforces compensation. With the labor market regulation index, we want to measure how difficult it is for a firm to adjust its labor force. The measure should also include information about the wage setting system of the country, and the power of organized labor. The index of fiscal burden aims at measuring the burden to firms imposed by taxation and fiscal spending, an element that determines in many cases a firm’s choice of location. With the trade regulation index we look at how much countries protect domestic producers; specifically we are interested in measuring the cost for the entire economy of protecting a selected group of producers. The financial markets regulation index should capture how easy a firm’s access to capital markets is. For instance, special credit conditions for some industries, or interest rate controls can reduce the availability of credit to more deserving firms and distort incentives for investment. Finally, the contract enforcement index is a general measure of how easily firms can turn to the justice system to resolve legal disputes.

# **Measuring regulation**

We use six data sources for the construction of our indices: Doing Business (The World Bank Group), Index of Economic Freedom (The Heritage Foundation), Economic Freedom of the World (The Fraser Institute), Labor Market Indicators Database (M. Rama and R. Artecona, 2000), The Corporate Tax Rates Survey (KPMG), and International Country Risk Guide (The PRS Group). These sources cover the largest number of countries and areas under regulation, and their measures use a clear methodology and are straightforward. Except for the Labor Market Indicators Database, all sources are public. Our sample covers 76 countries.<sup>8</sup> In most cases, data are based on surveys conducted in
Russian scientific community, it is acknowledged that the opportunity costs to be a scientist are high as other occupations, such as finance or real state are more profitable and carry a higher social status. Moreover, survey data shows that, at least at the beginning of 2000s, about 40% of researchers had R&D as a part time job (Yegorov, 2009).

Nevertheless, the rate of engineers (and scientists to a smaller degree) graduating from Russian universities is very high. The share of engineers among new university degrees in Russia (27.3 percent) is lower only than in Korea (Figure 8). Ukraine, Mexico, Japan, the United Kingdom, and the United States all had lower rates than Russia. By contrast, the equivalent figure for science degrees (5.8 percent) was lower than most comparators, at roughly half the share in Mexico and less than half the share in the United Kingdom.

There is evidence of a brain drain from Russia to the West, with a large share of science and engineering graduates studying abroad and not returning. Russia had the eighth-largest number

**Figure 8: Share of all new university degrees awarded in science or engineering, 2007**

<!-- Start of picture text --> Korea<br>Finland<br>Russia.<br>Mexico<br>Ukraine<br>Czech...<br>Engineering<br>UK<br>Turkey Science<br>Japan<br>Romania<br>U.S.<br>Brazil<br>0 10 20 30 40<br>%<br><!-- End of picture text --> <!-- Start of picture text --> Source: UNESCO.<br><!-- End of picture text --> of science and engineering graduates receiving PhDs in the United States in 2002 (Table 6). By 2007, less than one-fourth of those graduates
To exclude such firms from the sample, we use the question implemented in both rounds of the COV-ES in El Salvador, asking firms to state why the firms did not receive any support. The question included the following response categories: (i) not aware (21% as of R2), (ii) not eligible (26%), (iii) no need for support (only available as a separate category in R2, 28%), (iv) applied but did not receive it (8%), (v) too difficult to apply (8%), (vi) did not expect to get it (only available as a separate category in R2, 1%), and (vii) other (with the ability to specify given in R2, 6%).<sup>9</sup> We use this variable to exclude the firms that respond with category (i), (ii), (iii), or (iv), i.e., the firms that are either not aware, or not eligible, or in no need of support, or have been rejected to receive the support. These categories cover the majority of the control group, so the restricted sample is much smaller. However, we think this restriction alleviates the concerns about the negative selection bias, at least to some extent.

The question on the reason behind not receiving government support was not implemented in either round of the COV-ES in Georgia. In the absence of other alternatives, to supplement the analysis of the Georgia data performed on the full sample, we restrict the sample using the question about the government support itself. Recall that whether the firm received any government support has three response categories: Yes, No but expect to receive it in the next three months, and No. As an alternative control group, we use only the firms that did not yet receive the government support but expect it in the next three months. While this category may
positive correlation observed in Nakivale as regression coefficients remain very stable when going from a regression without controls to a regression with a full set of control variables and household fixed effects (Altonji et al. 2005; Oster 2019). But omitted variable bias is possible in Kampala, as the inclusion of household fixed effects leads to insignificant results. Most importantly, reverse causality could bias regression coefficients in all contexts. And mismeasurement problems could lead to attenuation bias.

In Table 2, we use an IV approach to address endogeneity issues. The structure of Table 2 is similar to Table 1 with respect to samples and control variables. We consider two instruments: 1) the proportion of refugees living in respondents’ EA (Columns 1, 4, and 7), and 2) the average interaction index among other household members and neighbours

> 15With respect to the types of interaction, we find that sharing meals is somewhat more strongly associated with positive perceptions than simply having conversations or business exchanges, whether measured by number of meals/conversations/exchanges or through binary indicators of having participated in any of these exchanges. As the differences are small, and including the separate measures might induce multicollinearity, we keep the focus of this analysis to the overall interaction index.

> 16We explored whether this intra-cluster correlation in perceptions is notable also at higher geographical levels than neighbourhoods. When considering the opinions of peers in the six research sites or the three countries, there is no longer any correlation between the individuals’ and peers’ opinions. As such, individual opinions seem to be strongly influenced by the immediate and local networks, and less so by the wider society.

20
of the results while Section 5 replicates the analysis in another market, Senegal. Section 6 discusses the implications of the findings and some limitations. Section 7 concludes.

# **2. Context and Data**

FINCA DRC is a subsidiary of FINCA international, an MFI operating in 23 countries worldwide which pursues women’s financial inclusion as part of its mission. FINCA DRC launched branchless banking in 2011 in an effort to expand outreach. FINCA’s network has grown rapidly from 322 agents in 2014 (Gutin, 2015) to over 1,200 agents by April 2018, the end of our period of study.

The data we obtained from FINCA DRC are comprised of 1,124,331 transactions performed by 104,237 customers through 1,250 agents linked to 21 FINCA branches. Transactions were performed over a period of one year, between May 2017 and April 2018. The transaction-level data contain the value of each

> 3 Barriers that impede women’s participation in DFS include limited access to phones and internet connectivity, lack of information and assets, limited participation in the salaried labor force and lower socio-economic status (Chamboko et al., 2018).

4