rafmacalaba/data-use-mentions-extended huggingface dataset:
# **3.1 The Data Set**

The data set we use is the World-Bank-NBS Survey on 120 Chinese cities of 12,000 firms between 2002 and 2004. In the data, all provinces in China are covered except Tibet.<sup>4</sup> For each province, the capital city is selected, and if the province is not too small (by China‟s standard), other cities are also selected. Typically, provinces with high total GDP are allowed to survey more cities. In each province, top cities (as measured by either total GDP or total industrial output) are selected. For all but four cities, we sample 100 firms; for the four mega cities (Beijing, Tianjin, Shanghai, and Chongqing), we sample 200 firms. Thus, we have 12,400 sample firms in total. See Table A1 for a complete list of provinces and cities. All firms are from manufacturing. For each city, the top 10 manufacturing industries in terms of sales revenue are drawn. For each industry, all firms in the sample universe are divided into large, middle and small firms, each accounting for 1/3 of total industry revenue. Then from each of three types of firms, an equal number of firms are drawn. Firms are required to have a minimum of 10 employees. The distribution of our sample industries is displayed in Table A.2.

The survey has three main parts. The first part was sent to the senior managers of a firm, covering topics related to basic firm characteristics, bottlenecks to firms' growth, relationship with clients and suppliers, labor, infrastructure, trade, finance, corporate governance and relationship with the government. The second part was sent to the accounts and personnel officers, concerning topics on ownership composition, financial statements and labor statistics. The last part is answered at the city level, covering basic characteristics of the city that a firm is located.

> 4 Tibet is not selected because there
Positive impact of digital infrastructure on the development of SSA, by comparing data from 177 countries between 1990 and 2019.

Calderon and Cantu (2020) 1990-2019 Global The relationship between ICT adoption and firm productivity has been widely studied in the literature, mainly suggesting positive effects. Cardona et al. (2013) summarize the empirical literature on ICT adoption and productivity by classifying the literature between methodology used, aggregation level, and type of ICT. The authors conclude that most of the studies find positive and statistically significant effects of ICT adoption on productivity. They also note the methodological differences apparent in the empirical literature, as well as the impact of estimating effects at different levels of aggregation (such as country-level versus firm-level). Additionally, Cardona et al. (2013) find stronger productivity effects of ICT at the macroeconomic levels (country and continents) than at the firmlevel. Welsum (2007) adds that measured total factor productivity (TFP) should rise in sectors using ICT, but it is possible that this occurs more rapidly in already highly productive and technological sectors. At the same time, Basu et al. (2003) suggest that the adoption of ICT may be associated with a decrease in total factor productivity (TFP), which could be attributed to the learning curve involved in the adoption of these technologies and the accompanying organizational changes. Similarly, Schweikl and Obermaier (2019) review 86 empirical studies at the firm level and claim that this productivity paradox could be explained by adjustment delays, measurement issues, mismanagement, and unrealistic expectations on the ICT productivity effects.

The productivity effects of ICT are even more challenging to generalize at the sector level, especially between manufacturing and service firms. Bertschek et al. (2013) find that there is no causal effect of fixed broadband internet adoption and productivity using data from a sample of German manufacturing and services firms between 2001 and 2003. The identification strategy relies on an instrumental variable approach considering that, by that time, only 60 percent of the firms had adopted broadband internet
# **7 Impact on firm performances**

We first examine the extent to which formalization resulted in any of the key purported benefits of formalization, and then turn to examining impacts on the main outcomes of profitability, sales growth, and employment.

# **7.1 Impact on intermediate outcomes**

Table 6 examines whether formalizing is leading firms to be more likely to access banks, improve accounting and other business practices, be less harassed for taxes, or access new customers. It does this through estimation of equations (3) and (4) using our two rounds of follow-up surveys. The top of the table presents the yearly intent-to-treat impacts of the different interventions, while the bottom of the table presents the impact of formalization for those who respond to treatment.

Despite the facilitation of access to bank accounts in treatments 2 and 3, and the creation by banks of a special account for _entreprenants_ , column 1 shows no significant impact of formalizing on whether the business has a bank account. 25 percent of the control group had accounts, suggesting that in practice the requirement to be formal was not always binding, and that those who signed up for the accounts through our intervention were substituting from accounts they would have opened anyway. Treatment group 2 is 5 percentage points more likely to have received a loan in the second year, but there are no other significant impacts on loan usage. As a result, the overall instrumented impact of formalizing on loan receipt is positive, but not statistically significant.

Columns 3 and 4 do show significant impacts of formalizing on the likelihood of attending business training in the past year (67 percentage points), with this impact coming from treatments 2 and 3 who were offered this service. Formalized firms are more likely to be doing any form of accounting (15 percentage points), but this did not translate into improved overall business practices.<sup>15</sup> One possible explanation is that there was some crowding out effects, and better accounting practices were
# **Figure 8:  Comparing naïve and floor area adjusted population densities (FAPD) across 400 global cities**

Figure a. Population density and city income, 2015. (population per km2 of built-up area, log scale) <!-- Start of picture text --> 150000<br>100000<br>Mumbai<br>50000<br>Kinshasa Karachi Hong Kong<br>Dhaka<br>Lagos Beijing<br>10000 Shanghai<br>Tokyo<br>London<br>5000<br>2000 Dallas<br>City income in 2015, log scale<br>Density (population per sq. km of built-up), log scale<br>500 1000 5000 10000 40000<br><!-- End of picture text --> Figure b. Floor Area Adjusted Population Density (FAPD) and city income, 2015 (population per km2 of floor space, log scale) <!-- Start of picture text --> 150000<br>100000<br>30000<br>Kinshasa<br>Karachi<br>Mumbai<br>10000 Dhaka<br>Lagos LondonHong Kong<br>5000<br>Tokyo<br>ShanghaiBeijing<br>2000<br>City income in 2015, log scale<br>Density (population per sq. km of floor space), log scale<br>500 1000 5000 10000 20000 40000<br><!-- End of picture text --> Source: Analysis based on DLR WSF 3D data set The FAPD in Figure 8b is a reasonable indicator of livability. Hong Kong’s FAPD is in line with that of a highincome city like London or Tokyo. FAPDs for low-income cities such as Kinshasa and Mumbai are also lower than their naïve population densities, with the correction making more of a difference for specific neighborhoods that have taller structures. While the FAPD makes intuitive sense, more work is needed to get better estimates of building heights
greater economic security. In the end, she shares her learnings with other women in her village and uses her own economic success to support her children’s schooling and her husband’s business as well. A subsequent moderated discussion prompted members of the community to articulate how Amina’s story, and women’s micro-entrepreneurship more broadly, may align with their goals and values. It also prompted the audience to set collective aspirations for the next generation and to identify coordinated behaviors that would advance those aspirations (Lewin, 1952). This event was conducted with the approval of the village chief. Village elders, religious leaders, and economic leaders were also invited as community members who would likely have influence over women successfully becoming micro-entrepreneurs. Program beneficiaries were also encouraged to invite their husbands, family members, and friends, i.e., people who could provide them instrumental and socioemotional support.

The 1-week life skills training was conducted in groups of approximately 20 women who came together to learn skills like goal setting and planning, decision-making, problem-solving, interpersonal communication, and leadership. In addition to teaching practical skills, these training sessions were intended to build women’s sense of self-worth, confidence, and both independent and interdependent agency. Women were also prompted to identify their values and their strengths as well as discuss their roles in and contributions to their families and communities. The same film from the community sensitization was used in several training sessions to role model the exercise of different life skills and link these skills to community values and contributions. The pedagogy of these trainings was grounded in participatory, problem-centered, personalized learning.

According to administrative data, attendance rates of beneficiaries at the community sensitization events was 89.3%. Attendance rates of beneficiaries in the life skills trainings was 93.8%, and 85% completed at least five of six sessions offered. According to administrative data collected in a subset of villages, the entire sensitization lasted approximately 1.5 hours on average, approximately 250 people attended the
Assessing the effectiveness of the Indonesian second population project remains difficult, as can be illustrated with a few examples. No specific target was mentioned in the appraisal report for the family planning and population training centers ... Some indication as to the type of training to be provided as well as output would have enabled a more objective assessment ... In the absence of baseline information or utilization data, the PCR could only comment that "the availability of project vehicles is reported to have greatly improved the provision of services in outlying rural areas." [PCR paragraph 3.05.] It is impossible to objectively evaluate such an assessment ... The bottom-line is that unless specific targets are set during preparation, population projects will remain difficult to evaluate. [pp. 16-17.] Some of the factors responsible for neglect of project evaluation are: lack of evaluation design and targets at the project formulation stage,<sup>3 4</sup>

# 4-. Supervisorv Coefficients

PHND projects have historically required more supervision than projects in-somewhat similar departments (see Table V-2). There is a downward trend in the coefficients, but, as we have indicated elsewhere, it is our impression that the nature of the tesk is likely to keep the need for supervisory visits relatively hiah.

# 5. Summary

In sum, project supervision is strong in terms of routine tasks, problem solving and removing bottlenecks in implementation. However, it remains inadequate in terms of strategic and innovative inputs, project evaluation, follow-up on suggested actions, inter-donor coordination, and in-depth analysis of program-client interface. The population projects may continue to require more supervision than other projects, due to rapid expansion of activities in Africa, complexity of inter34Even the PPARs and POCRs do not have uniform indicators to allow cross-project comparisons. Our examination of all the PPARs/PCRs showed that information on the ranking of projects by intensity and frequency of problems, types of problems, and institutional performance was not uniformly available for all the completed projects.

61
define _g’_ ( _g’=_ low-educated self-employed, high-educated self-employed, unpaid family worker, employer, low-educated employee, and high-educated employee).<sup>37</sup> The spatial distribution of each employment type across the five cities is provide in Annex 2.

We redefine _Ubc_ and _Xbc_ with _bairro_ -specific variables derived from publicly available geospatial data and Census data. The vector _Ubc_ has six elements: population density, night light density (luminosity), average electrification, cell phone tower count, proportion urban, and building density. The spatial distribution of each urban variable across the five cities is provided in Annex 2. The vector _Xbc_ is a vector of durable goods that are used to proxy _bairro_ poverty, namely the share of the _bairro’s_ population that owns each of the following: radio, landline phone, laptop, iron, electric stove, refrigerator, and car. The term _Ic_ is now the city fixed effect. We use robust standard errors.

# **4. The Structure of Urban African Labor Markets**

> 36 <mark>The 10 percent cutoff follows Grimm et al. (2012).</mark>

> 37 <mark>The Mozambique 2017 Census does not provide information on social insurance or firm registries. Instead, drawing from Fields (2015), we use education level as a proxy for formal and informal.</mark>

13
world commodity prices, a current account deficit, and an overvalued real exchange rate. The country had a much more successful adjustment, however, and embarked on a decade of rapid growth.

As recounted in Demery and Demery (1992), Malaysia had high levels of economic growth and rapid rates of growth of manufacturing exports between 1968 and 1984, but was a major natural resources exporter as well. Key commodity exporus included tin, rubber, petroleum, natural gas, and palm oil. Commodity and oil prices boomed in 1979 and 1980, and the government expanded spending. These prices started decl ining significantly in 1981. The terms of trade reversals cost the country real income amounting to seven percent of GDP in 1981 and three percent in 1982. However, expecting the reversals to be temporary, the government maintained its fiscal expansion, relying on foreign borrowing to finance growing government deficits. The large inflows of debt finance, combined with government spending tilted towards the nontradables sectors, resulted in an appreciation of the real exchange rate.

Starting in 1984, the Malaysian government embarked on an adjustment program. It cut government spending to reduce the deficit.<sup>36</sup> To restore external competitiveness and profitability in tradables, it depreciated the nominal exchange rate and reduced external borrowing. Combined with lower domestic inflation, these policies led to a real depreciation between 1985 and 1987 ofjust under 30 percent.

The change in the real exchange rate, along with the other adjustment policies, had several beneficial effects. The current account returned to surplus in 1986 and 1987 and resources started to move back to the tradables sectors.'<sup>7</sup> The adjustment also restored growth. According to World Bank data (World Bank, 1999), aggregate real GDP growth averaged 8.3 percent annually from 1987 to 1991, well above the rates before the adjustment.'<sup>8</sup> And for the whole decade 1987 to 1996 aggregate real growth averaged 8.5 percent.
we control for the various country-level factors (column 6). The implication here is that changes in macro-level factors most likely explain the downward trend. The remaining country and firm-level variables do not show any significant relationship with overall corruption.

> 6 We also experimented with including controls for country size proxied by (log of) total population and the quality of democracy as measured by the Polity2 variable from the Polity database. Adding these controls to the final specification above caused the estimated coefficient value of _Time Tax_ to decline slightly from 0.030 (column 6, Table 2) to 0.028 (not shown) and it remained significant at the 5 percent level.

19
interviews in the case of the gender paper, and a close anthropological reading of folklore narratives in the Folklore paper) into conversation with other kinds of more conventional quantitative data, and thereby enrich our understanding of important phenomena. The degree of reflexivity is even more acute in two projects that are underway that are conducting open-ended interviews at scale and then analyzing using them ML and NLP.

The first study, which I am involved with, piggybacks on an ongoing panel survey of Rohingya refugees and their Bangladeshi hosts in Cox’s Bazaar in Bangladesh. We have been conducting 30-minute openended interviews with 2,000 respondents equally divided between hosts and refugees covering three domains – aspirations, well-being and “belongingness” to understand how the hosts perceive the refugees and vice versa. In the first paper out of this project we develop a method to extend a sub-sample of 400 human coded interviews to a much larger sample of documents using NLP (Ashwin et al 2022), thus attempt to circumvent the small sample bias associated with qualitative analysis. We apply the method to study parental aspirations for children, bringing in ideas from philosophy and anthropology to distinguish between “aspirations" ( a process of reversing a “core value" that results in a “change in the self") and “ambition" (“a specic goal that can be fully grasped in advance of achieving it"), and to include the concept of the “capacity to aspire" which is a cultural and cognitive resource that allows people to navigate their way to a better future. We find that there are interesting and policy-relevant differences between general and educational ambitions, and secular and religious aspirations. We also find that while poorer and less educated parents (more prevalent among the Rohingya refugees) say that budget constraints limit their ability to help their children achieve their hopes and aspirations for them, refugees are more able to express clearly articulated navigational capacity than hosts which we think may due to the selection and learning effects associated with surviving violence and finding their way to the refugee
**Figure 8. Rule complexity affects performance in Albania**

<!-- Start of picture text --> 10<br>9 Wocal-budget<br>con rl hr * central inst-budget<br>8<br>personnel<br>cZ7 ginlbdet<br>ional- * local-personnel<br>4; 6 *-persucntral inst-<br>i 4 -judca-<br>3 - personnel<br>2-<br>1<br>0<br>0 1 2 3 4 5<br>complexity of rules<br><!-- End of picture text --> In Figure 8 the horizontal axis shows the perception of officials of the complexity of budget management and personnel management rules in their respective administration (local governments, central institutions, regional administrations, judicial bodies and the control branch). The vertical axis shows the perception of these same officials on the enforceability of these rules. Both complexity and enforceability of rules have been ranked on a scale 0 to 10 with 0 being the worst possible, and 10 being the best possible.<sup>5</sup>

# _7.2 Step 2 - encourage contestation in interpretation_

The country reports also provide a summary of the descriptive data, presented in a format that facilitates comparisons between countries. In parallel, appropriately anonymized survey data is being placed on Internet sites. Open discussion fora are being facilitated to encourage policy makers, academics and other commentators to test alternative interpretations of the findings, to contest possible interpretations and to suggest locally appropriate reform interventions.

# _7.3 Step 3 - challenge prior assumptions_

The country reports then examine any prior assumptions or topical reforms already under consideration in the light of the available data. These prior assumptions have been derived from country dialogue with government officials and business and civil society representatives. They tend to fall into two categories. Some are assertions of facts (e.g. most civil servants would rather work in the private sector
percent to 23 percent.

# Use of Digitalized Accounts Is Also Rising

Account ownership is key to financial inclusion. But secure and convenient ways to use accounts are essential if users are to reap the full benefits of account ownership. The Global Findex database also sheds light on whether and how people use their accounts for payments.

## _Digital Payments_

Globally, 52 percent of adults (more than three‐quarters of account owners) reported having made or received at least one digital payment using their account the previous year. In high‐income economies, the share of account owners using their accounts for digital payments was 97 percent. In the euro area the share of adults who made or received digital payments increased from 87 percent in 2014 to 92 percent in 2017, and the share making digital payments increased from 92 percent to 97 percent. In developing ECA economies, the share of adults making or receiving digital payments rose from 46 percent to 60 percent between 2014 and 2017, suggesting that the share of account owners doing so increased from 80 percent to 92 percent.

ECA countries with significant growth in the use digital payments include Belarus, Bosnia and Herzegovina, Bulgaria, Croatia, Georgia, Kazakhstan, the Republic of North Macedonia, Montenegro, Russia, Turkey, and Ukraine (figure 6). Several countries witnessed an increase of more than 15 percentage points in the share of adults using digital payments during 2014–17. Uzbekistan, where fewer people used digital payments in 2017 than in 2014, seems to be an outlier (table 3).

13
household surveys (from the I2D2 database) and micro‐simulation techniques (Olivieri et al. 2014; Bussolo et al. 2008; Bourguignon, Ferreira, and Lustig 2005) and is performed in a framework inspired from robust decision‐making techniques, in which all uncertain parameters are varied systematically to the full range of possible outcomes. We combine assumptions on future demographic changes (How will fertility change over time? How will education levels change?); structural changes (How fast will developing countries grow their manufacturing sector? How will the economies shift to more services?); productivity and economic growth (How fast will productivity grow in each economic sector?); and policies (What will be the level of pensions? How much redistribution will occur?). The range of possible futures of these parameters is determined based on historical evidence, and on the socioeconomic scenarios currently developed for the analysis of climate change, the Shared Socio‐Economic Pathways (SSPs) (Kriegler et al., n.d.; O’Neill et al. 2013). These sets of assumptions are used to generate hundreds of scenarios for the future socioeconomic development of Vietnam.

Then, we select two representative scenarios, one optimistic and one pessimistic in terms of poverty reduction and changes in inequality. Finally, we introduce quantified estimates of the impacts of climate change on agriculture incomes and food prices, on natural hazards, and on malaria, diarrhea and stunting into these two scenarios. Here again the impacts of climate change are uncertain. We thus consider again two cases, one high impact and one low impact, and investigate the potential impact of unmitigated climate change on the number of poor people living in extreme poverty in 2030 in the four cases (optimistic and pessimistic regarding socioeconomic trends, and optimistic and pessimistic regarding climate change impacts).

The results are unequivocal: the impact of climate change on poverty is conditioned by overall development progress. In particular, the impacts of climate change are lower in scenarios with high structural