rafmacalaba/data-use-mentions-extended huggingface dataset:
One partial exception to the low rate of penetration is Rwanda, where use of most insurance products is very low, but where 80 percent of adults have medical insurance through the government’s _Mutuelle de Santé_ . About half of adults express a need to learn more about both life and asset insurance, suggesting that lack of information is an important barrier to the take-up of other insurance products. Another exception is South Africa, where 46 percent of adults have some sort of funeral insurance coverage, and where penetration of other types of insurance (26 percent) is higher than in lower-income countries as well. The view of insurance here is more positive—three-quarters of those surveyed agree that it is ―important to have insurance just in case‖ of threats such as death, loss of income, funerals, crimes, and so forth.

# **_Business literacy, as indicated by surveys of enterprises, is likely low_**

As discussed in the introduction, improving financial literacy for entrepreneurs may be as important improving the same for consumers in the developing world. FinScope’s household surveys do not contain questions related to business literacy, but they have launched a separate series of surveys of businesses which do contain relevant questions. For instance, according to a survey of businesses in Zambia in 2010, almost 73 percent of MSMEs are prevented from accessing finance because of inadequate business records. The report notes that ―helping MSME owners keep business records, identify more profitable lines of business, develop business plans, and improve general business administration could allow them to increase productivity and make it easier for them to access financial services.‖ Access to finance is also a problem for small businesses relative to larger enterprises, and particularly for the majority of small businesses that are unregistered. On the other hand, the returns to education for enterprise owners are high—one year of additional education apparently boosts labor productivity by 10 percent. The returns to financial literacy education and other forms of capacity building might therefore be high as well.

FinScope conducted
different aspects of firm dynamics, firm-product and firm-destination dynamics, as well as exporter growth patterns, concentration, and diversification in the non-oil exporting sector.

This paper introduces the Database and uncovers four new stylized facts based on the measures contained therein. The distinguishing feature of these stylized facts is that they could not have been uncovered using any other cross-country source of trade data available so far. We also confirm or generalize facts found in the recent trade literature.

The first stylized fact is that more developed and larger economies have a larger export base (number of exporters), larger exporter size, more concentrated export sectors among firms, more diversified exporters (in terms of their portfolio of products and destinations), and lower entry and exit rates, relative to less developed and smaller economies. The survival rates of new exporters are not correlated with the level of development or with the economic size of countries. These patterns are also true for countries with larger export sectors relative to income. This is consistent with more developed and larger economies having more competitive export sectors, with more firms that are globally competitive, and a higher proportion of large firms.

The second stylized fact is that across countries, expansions along the intensive margin – i.e., increases in the average exporter size – contribute more to export growth in the short run than expansions along the extensive margin – i.e., increases in the number of exporters. This evidence supports a trade model with heterogeneous firms along the lines of Melitz (2003), where entrants into export markets tend to be marginal firms that have little impact on total exports.

The third stylized fact is that across countries, entry and exit rates are high and strongly positively correlated with each other. Both entry and exit rates are negatively correlated with survival rates of new exporters, average exporter size, and diversification at the exporter level (in 3
inappropriate in other contexts (such as in the US), it worked well for this study - all of the women who were selected from this sampling frame did in fact engage in sex-for-money.

Though SHCP had been relatively successful in enrolling women into their program, it was possible that women who joined the peer groups were not representative of the average sex worker in the area.<sup>14</sup> To construct as representative a sample as possible, we identified other women who met SHCP’s definition of a sex worker but who were not involved in the peer groups. To do this, the enumerators visited each peer group and asked members to list all the women she knew who fit SHCP’s description of a sex worker, whether they were in a peer group or not. After compiling this list, duplicates were eliminated by the peer group educators. The resulting “universe” of sex workers we identified for our sampling frame from this method thus includes all women in the peer groups as well as all other women identified by any peer group member.

Overall, we identified 1,205 women in this manner. Since the population of Busia Town is only 44,196, and assuming that the age distribution of the population fits that of the 2003 Kenyan Demographic and Health Survey (in which women aged 15-49 make up 21.9 percent of the rural population), we estimate that roughly 12.5 percent of women in Busia earn some income from transactional sex.<sup>15</sup> From this sample frame, we randomly sampled women to participate in the project (stratified by the peer group in which they were identified). Initially, we sampled 248 women. Of these, seven women refused to participate in the project, and another 49 dropped out before data

> 14. However, Robinson and Yeh (2011) show that there is no difference in observable characteristics between those in the peer groups and other women who supply transactional sex.

> 15.
information. As a result, the farmers have been able to cut trader margins by half and increase their revenue (Vaitla et al. 2015c).

When governments make their data available in a machine-readable format, the possible uses of the data expand, and correspondingly, so do their value. A recent policy evaluation looked at the impact of a Senegalese law reducing the length of pre-trials on the quality of decisions. The law was implemented to increase court efficiency, which has been shown to matter for economic development. One could fear that such an efficiency reform would deteriorate the quality of the judgments. Through a laborious effort of digitalizing case-level data from the court, the impact evaluation found this not to be the case and that firms benefitted from the faster process times, suggesting that the reform indeed worked as intended (Kondylis and Stein 2018). In this way, making data machine-readable could assure that past policy changes were appropriate.

Because of these benefits, the signaling value of being a country that makes data widely available can help countries reduce their sovereign bond spreads, decrease their external debt burden, and foster growth. If African countries could raise their level of data transparency to the level of the top quartile of upper middle-income countries, the region as a whole would save 4.87 basis points in sovereign bond spreads and decrease their external debt by more than 400 million dollars (Kubato and Zeufack 2020). Another study finds that <mark>data transparency has a positive and sizable effect on real gross domestic product per capita (Islam and Lederman 2020)</mark> . These findings and the examples above reveal that collecting and disseminating data should not be viewed as a drain on public finances.

# **Understandability**

Data accessibility is often not enough to ensure that data are used by governments or individuals when the data are difficult to understand or there is a lack of skills to understand how to use the data. One example where data only attained its value when it was understood properly relates to
pay their bills and deliver quality products on the prospect of future business. Trust is built on a history of successful, repeat transactions. The RPED surveys show, for example, that firms generally deal with a single supplier of a particular input on a regular basis (even when they have a choice among sources of supply) and the average length of relationship exceeds seven years (Bigsten et al. 2000a). But, as many economic activities require dealing with different partners at different times and cooperation is more easily sustained in relationships if sanctions for opportunistic behavior come not just from the business partner who has been cheated but also from other firms in the business community, business and community networks are formed to govern transactions.<sup>5</sup> Selfgovernance in such networks works by sharing information on non-delivery, late payment, and default via a multilateral reputation mechanism, supported by a framework of credible commitment, enforcement, and coordination.

At early stages of industrialization incentives based on repeated interactions work well. The fact that it is difficult to locate alternative business partners in the SSA environment, because there are few firms, because market information is inadequate, and because transportation costs are high, persuades firms to make efforts to maintain their existing relationships. They recognize that they are locked in to some extent with existing business partners because of high search and screening costs. This provides incentives to behave cooperatively – i.e. reduces incentives for opportunism (Kranton 1996; Ramey and Watson 2001). As a consequence, such self-enforcing relational contracts are shown in the RPED surveys to be one of the standard ways for manufacturers, suppliers and clients to do business in the region. A large majority of African manufactures describe their relationships with suppliers and clients as simple long-term business acquaintances (Bigsten et al. 2000a).

But the SSA business environment also has features that work to undermine and weaken repeated-game incentives for cooperative behavior. Self-enforcing transactions, governed through repeated interaction, depend on expectations about the future (Axelrod 1984;
The relation involves average, not marginal productivity of capital, because natural disasters do not destroy the least productive assets first, but affect random sectors and random portions of the existing capital (Hallegatte and Vogt‐Schilb 2016). Note that if the productivity of the affected capital was equal to the marginal productivity of capital, that is ��� , then the loss of consumption would simply be equal to the loss of capital (and would thus be independent of the reconstruction duration).

Then, to estimate the welfare impact of a macroeconomic loss in consumption, it is necessary to account for the distributional impacts of the disaster, that is whether it impacts poor or nonpoor people, and for the ability of the population to cope with the shock. Our framework is flexible regarding the definitions of “poor” and “non‐poor.”<sup>3</sup> In particular, one can decide to focus on extreme poverty by defining the poor following national or international poverty lines; through a Multidimensional Poverty Index; using a given fraction of the population (e.g., the bottom 20 or 40% of the income distribution); or using a broader definition of poor people that is relevant for disaster analysis (e.g., the population with no access to financial instruments, or the population that is “vulnerable” to falling back into poverty<sup>4</sup> ). In what follows, we define the poor as the people in the bottom 20% of the consumption distribution. All the calculations that are proposed in this section are nonetheless possible in a more complex framework with more than two categories.

# 2.2. Distribution of asset and consumption losses

The distribution of losses from a disaster depends on poverty, assets used, affected individuals and capital, and consumption losses, as each section of the framework below describes.

## 2.2.1. Income categories

In each country, there are � individuals, partitioned in ��
empirically—the removal of licenses requirements, the removal of technical requirements, and the reduction of fees and charges for administrative procedures.

Overall, 70 (35) of 1,874 districts, 22 (18) of 196 provinces, and 3 (2) of 25 states in Peru eliminated at least one regulatory barrier in 2014 (2013). Among these, eliminating operating license requirements was the most common regulatory change (Table 2). The extent to which different municipalities eliminated regulatory barriers to competition in 2013 and 2014 is illustrated in the map of Peru in Figure 2. It shows substantial variety in the reform municipalities. Notably, the map reveals significant differences between both years with several municipalities eliminating regulatory barriers to market entry and competition only in one of the two years.

Several establishments benefitted from more than one eliminated regulatory barrier within a year because the responsible district and the higher tier province municipality both eliminated barriers that are inconsistent with national law. On average, establishments located in reform district or province municipalities benefitted from 4.5 eliminated barriers in 2013 and 5.4 in 2014. In 2013, illegal licenses requirements were the most common type— establishments in licensereform municipalities benefitted on average from 4.1 eliminated illegal license requirements; establishments in technical- and fee-reform municipalities benefitted on average from the elimination of 1.9 and 1.02 such barriers, respectively. In 2014, the removal of regulatory barriers was more evenly distributed among these types. Establishments in license-, technical- and feereform municipalities benefitted on average from the elimination of 2.5, 4.1, and 1.6 such barriers, respectively. The fact that many establishments benefitted from more than one eliminated barrier allows us to also estimate the impact of the intensity of municipal reforms.

# **4.3 Matched census-reform data set**

We match the data on regulatory changes across the 1,800 municipalities in Peru in 2013 and 2014 with establishment census panel data from 2008-15, using the 6-digit location codes providing
co-financing requirement is around 20%, local governments will need to contribute about 0.5 percent of GDP for projects to utilize the structural funds.

The question that Hungary should resolve in the inter-government finance thus has several levels. First the central government needs to reconsider incentives, particularly with respect to the mechanism of budgetary transfers to local governments. Second, the central government needs to improve the mechanism for allocating investment funds to local governments. Third, the central government needs to improve its monitoring of financial management (including asset management) of local governments. And finally, after these steps are completed, the central government should reconsider how to regulate the access of local governments to the financial markets and possibly increase the local government borrowing cap. While any obligations of local governments increase the fiscal risk vis-a-vis the central government, too low a cap on local government borrowing may produce sub-optimal results as well, particularly in during the EU accession process.

## **THE HEALTH FINANCING LIABILITY**

# **An open-ended state guarantee**

As many other European countries, Hungary provides an unlimited state guarantee that all citizens have access to adequate health care. The central government explicitly guarantees that health services are provided even if revenues of the health fund fall behind the planned anount.1<sup>7</sup> Data in table 3.6 indicate that in every year since 1992 actual expenditures and the deficit have been above budgeted levels. The guarantee, however, generates moral hazard in the health system, reduces incentives toward costreduction and efficiency, and is a source of persistent financial imbalance in the health system.

This problem arises particularly because the shift from tax-based to health insurance-based financing has not been completed, the mechanism for health investment decisions is not transparent, and many structural problems in the health system remain unresolved. Moreover, health care cost is expected to increase rapidly with the political pressure to apply state-of-the-art technology and new medications, and, similarly to pensions, with population aging in the next fifty years.
**<u>Figure 5: Market Map of the Kenya VC/PE Industry</u>**

<!-- Start of picture text --> 100-500MM<br><!-- End of picture text -->

# _Source: Primary Research_

# **F. Business Environment: Doing Business and Global Rankings**

Despite a thriving ecosystem of entrepreneurs and a private sector-led economy, Kenya has made a relatively mediocre showing in global investment climate rankings. Specifically, as shown in Table 12 below, the country has consistently ranked in the bottom half of both the World Bank’s Doing Business Report and the Heritage Foundation’s Economic Freedom Index. It has also ranked in the bottom quartile of Transparency International’s Corruption Perception Index.

Kenya's ranking in Transparency International’s Corruption Perception Index is worthy of note because it highlights the kinds of environmental challenges facing enterprises in Kenya. Widespread corruption can act as a leach on an economy and the companies within it, and SMEs lack the resources and networks to navigate the ecosystem of graft unscathed. Fund managers in Kenya actively screen for corrupt practices when conducting due diligence since irregularities exert both seen and unseen costs on businesses. Given that a meaningful part of the value-add of private equity firms is their focus on corporate governance, anything that detracts from these efforts can negatively impact the value of an investee company. Moreover, problems at investee companies can impair the operations and damage the reputation of the private equity firms that are shareholders, either minority or majority, in these businesses.

21
fraction of manufacturing and public employment in the district. The latter in particular permits us to test for complementarities between individual and district characteristics.

We use four rounds of the NSS data – namely data from the “thick” rounds conducted in 1999-00, 2004-05, 2009-10 and 2010-11.<sup>1</sup> Since there has been a significant change in the number of districts during this period, we aggregate district boundaries corresponding to those in 1991.

# **2.2 Micro-Enterprise Survey**

We consider the survey on unincorporated non-agricultural enterprises to gauge the problems faced by micro-enterprises. This is a rich dataset covering enterprises which are not registered – under either the Factories Act of 1948, or the Companies Act of 1956 the two premier law statutes which govern corporate entities in India. The enterprises by definition thus operate in the informal sector. The operation of these enterprises are of particular interest as a third of the rural non-farm labor force during the period of our study report being “self-employed” (engaged in proprietorship), while a fourth report being employed as “casual workers”. This suggests that informal small and micro-enterprises are accounting for a substantial fraction of the rural non-farm employment observed in the data.

The micro-enterprise survey is also conducted by the NSS and covers all states and districts in India, accounting for over 50 million establishments, providing employment to 100 million individuals. The survey includes data on key measures of enterprise performance such as operating expenses, raw materials, fixed capital, workers, wage payments, revenues and gross-value addition. Qualitative measures of enterprise performance such as whether the establishment is expanding, shrinking or a recent entrant, in addition to outstanding credit (and its source) are also provided. Finally, the survey enquires enterprise owners regarding select problems faced by the enterprise. Our study exploits these qualitative questions to analyze how problems faced by enterprises affects enterprise performance, conditional on key enterprise parameters such as capital and labor.

# **2.3 Consumer Pyramids**

The last NSS
tionnaire from Falk et al. (2022), along with a question on how much do the subjects in our sample trust the Colombian government. Additionally, we inquired about the adolescents’ social networks by asking about their number of friends of each nationality and whether they have felt discriminated in school. While these outcomes were not the primary focus of the VenReps Kids survey, they collectively provide a general assessment of social cohesion, a crucial aspect in understanding the overall well-being of children and adolescents.

We measure the average differences in altruism between Venezuelan and Colombian adolescents following the estimation of equation 1. Table 8 presents the results for altruism, trust, discrimination and social ties in panels A, B and C respectively. As in the previous tables, the first column for each outcome reports the results of the estimates of equation 1 without controls, and the second and third columns report the results of the estimation with all controls and the propensity score matching respectively. As for altruism, we see that Venezuelan adolescents are on to donate 17% more of their average willing imaginary money endowment to a good cause relative to Colombian adolescents. As for trust, the results are mixed when analyzing the trust items separately. On average, Venezuelan adolescents tend to be more benevolent towards an injustice, are more likely to think that people have good intentions and have higher trust in the Colombian government. However, they are less willing to return a favor (although not significantly more) and trust less in Colombian unknown people. Moreover, Venezuelan adolescents have felt more discriminated in school and tend to have less friends. The findings suggest that forced migration may have negative impacts on the accumulation of social capital due to barriers in social norms that hinder social integration. Adolescent migrants face challenges in building connections with the host community given their weakened social ties and the presence of exclusionary attitudes.

All in all, our analysis suggests that there are meaningful physical and cognitive devel40