rafmacalaba/datause-encoder-data huggingface dataset:
In this study, we use a variety of data sets. The WHO database<sup>4</sup> provided the COVID-19 data. The low and central values of the VSL for the US are from Robinson et al. (2017b) and Robinson and Hammitt (2016). The GNI and other data were extracted from the World Bank Development Indictors (WDI).

# **3. Results**

# **3.1 Estimates of the COVID-19 mortality costs over time**

**Table 1** shows the historical trend of COVID-19 mortality costs in Côte d'Ivoire. As the income elasticity of the VSL rises over time, regardless of the values of the central US VSL or low US VSL, the VSL for Côte d'Ivoire drops along with mortality costs. The Côte d'Ivoire VSL ( **Panel A of Table 1** ), for example, swings from US$ 734,103.81 to US$ 259,313.96 based on the central US VSL, indicating a drop of 64.68% of the VSL when the income elasticity of the VSL rises from 1 to 1.4. Similarly, for the year 2020, the mortality costs attributable to COVID-19 drop from US$ 98,369,910.86 to US$ 34,748,070.04, indicating a decrease in the mortality costs attributable to the COVID-19 pandemic of 64.68%. With an income elasticity of the VSL of 1, it is interesting to observe that starting in 2021, COVID-19-related mortality costs dropped precipitously, reaching US$ 90,294,768.92 in 2022. Using an income elasticity of the VSL of 1.4 ( **Panel A of Table 1** ), the mortality costs due to the COVID-19 pandemic decreased from US$ 148,586,896.52 (2021) to US$ 31,895,616.53 (2022). This decreasing pattern of mortality costs due to COVID-19 is substantiated when the low US VSL estimates are used ( **Panel B of Table 1** ). With an income elasticity of the VSL of 1, the mortality costs associated with COVID-19 fell beginning in 2021 and reached US$ 42,137,558.83 in 2022.

> 4 Based on data from the WHO database (https://covid19.who.int/data), at the time of writing this paper, the recorded COVID-19 deaths in Côte d'Ivoire were as follows: 134 (2020), 573 (2021), 123 (2022), and 5 (2023). The cumulative total of COVID-19 deaths from 2020 to 2023 is 835. In May 2023, the World Health Organization (WHO) lifted the global health emergency declaration for COVID-19. Furthermore, in 2023, numerous countries discontinued regular tracking and reporting of new COVID infections. As a result, the year 2023 is not included in this study.

5
association between the book value of machinery and equipment in KED and the establishment technology sophistication measures (MOST and MAX) from FAT, which will be explained in the next section.

**Internal validation.** We conduct an additional validation exercise of the technology measures, by studying whether establishments with larger sales, employment and sales per worker are more likely to use top-tier technologies, which are the more sophisticated technologies in each BF and are marked in bold in Appendix A.1. Specifically, we estimate a linear probability model for each business function, where the dependent variable is binary and equal to 1 if the establishment uses one of the technologies classified as top-tier for the business function and 0 otherwise. The model includes a full set of country- and, for the GBFs, 2-digit sector fixed effects. The independent variables are either (log) sales, (log) employment or (log) sales per worker. We find that the coefficients for these variables are positive and significant in a large majority of business functions.<sup>15</sup>

These ex-post checks further reassure us about the soundness of the survey design, the data collection process, and the accuracy of responses.

# **3 Measures of Technology Sophistication**

We next introduce measures of technology at the business function and establishment levels, constructed using information collected by the FAT survey. Before analyzing these measures, we illustrate the granularity of the grid and how these measures can characterize the sophistication of technology used by establishments, with examples from FAT.

## **3.1 Technology Measures**

We denote by _ANUMf,j_ the number of different technologies from the grid used in business function _f_ in establishment _j_ . When more than one technology is used in a business function, we explore whether the technologies used are contiguous in the sophistication ranking of the grid or, instead, there are sophistication gaps in the vector of technologies used. Formally, we define the sophistication gap of establishment _j_ in business function _f_ ( _SGf,j_ ) as a binary variable that takes the value of 1 if the establishment uses technologies with sophistication rank _τ_ and _τ_ + _k_ for _k ≥_ 2 in function _f_ but does not use the technology with sophistication

> 15For sales we find a positive coefficient in 100% of BFs (85% significant at 5% level); for employment 98% are positive (93% significant); and for productivity 80% are positive (52% significant, and never negative and significant).

15
_-9._ with qi - _Gi_ + Xi(Pix-Px) + Si(ftP-Ps) and Vit W v* it + (Xit-Xi)(Pixapx) **+** (Sit-Si)(pis-ps) When equation (5) is substituted into (1), the fixed-effect estimation equation can be rederived in substantially the same form as in (2).

(6) Yit -Mi + _XitB_ + Sit7 + nit with ai - ai + qig - - b **+** pxg 7 - C + p8g 6 nit * it + pit These matrices can be stacked as in preparation of equation (3) to allow fixed-effect estimation of ai, jO and 7.7 ai will thus capture all three components of country-specific economic performance outlined above. The gist of the method can be presented in Figure 1. Suppose that the economic performance measure of interest is the current account/GNP ratio (C), and that Countries A and B have observed (negative) ratios of CA and CB, respectively, in this period. The two countries have observed terms-oftrade in that period of TA and TB, respectively, and otherwise face an identical external environment. CA is less than CB, so that<sup>an initial</sup> examination of the evidence suggests that B has a more successful externalaccount performance than A. However, there is a normal relationship observed historically between the terms of trade for a country and its current account: as the term of trade improve (T rises) so also will the current account.8 This normal relationship is illustrated in Figure 1 by the slope of the line C(T).
**<u>Figure 9: Domestic Debt Level and Structure in 2007 and 2011.</u>**

<!-- Start of picture text --> Domestic debt (as % of GDP) Implicit interest rate<br>0 5 10 15 20 25 0 .05 .1 .15 .2 .25<br>Domestic Debt (as % of GDP) in 2011 Implicit interest rate in 2011<br>Maturity structure non-Central Bank holders<br>0 .2 .4 .6 .8 1 0 .2 .4 .6 .8 1<br>Long term debt (as % of Domestic Debt) in 2011 non-Central Bank holders (as % of Domestic Debt) in 2011<br>.25<br>25<br>20 .2<br>15 .15<br>10 .1<br>5 Implicit interest rate in 2007 .05<br>Domestic Debt (as % of GDP) in 2007<br>0 0<br>1 1<br>.8 .8<br>.6 .6<br>.4 .4<br>.2 .2<br>Long term debt (as % of Domestic Debt) in 2007 0 0<br>non-Central Bank holders (as % of Domestic Debt) in 2007<br><!-- End of picture text --> _Source: our elaboration on the LIC domestic public debt dataset._

# **5. Conclusions**

Several low-income countries are now taking advantage of lower debt burdens, thanks to the debt relief programs of the late 1990s and early 2000s. Since then, they started relying on a growing basis on internal financing. The change in the composition of financing sources, related also to decreasing foreign aid and increasing foreign direct investment and remittances, could have several implications for debt sustainability and for the scaling-up of public investment and poverty-reduction expenditures. In theory, domestic debt could bring several benefits to LICs, but it could also crowd out private investment and thus hinder the growth process. However, the existing empirical evidence on the balance of costs and benefits of domestic borrowing in LICs is quite scant.

One of the main limitations that institutions and researchers face when dealing with the macroeconomic effects of government financing in LICs is poor data quality. In particular, data on domestic debt in LICs have been so far quite heterogeneous in terms of definitions and coverage. This paper introduces a new data set on the stock and structure of domestic debt in 40 LICs over the period 1971-2011. With respect to the existing data sets, this one puts together information on domestic debt in a way that ensures comparability across countries (definition of do21
careful interpretation in light of sample coverage, the CHIP data provide a reasonable approximation of the situation in much of China.

The CHIP dataset contains detailed information on household incomes, consumption, composition and demographics, and many other (but not all) variables collected by the NBS as part of its annual rural household survey. Additional variables were collected using an independent questionnaire designed by the CHIP and RUMiC project participants. The CHIP dataset also contains matching community‐level data gathered through a village survey. The availability of rich information at the individual, household and village levels provides a unique resource for our analysis.

The CHIP datasets also contain information on household participation in the dibao and wubao programs. Participation is self‐reported. In our analyses we treat households that indicated participation in either the dibao or wubao programs as dibao households and their members as dibao participants because the distinction between the two programs is not always clear at the local level and because during the time frame of our analysis the wubao program was to some extent being absorbed by the dibao program (World Bank Social Protection Group 2010).

Table 2 shows the number of dibao (including wubao) households and individuals in the CHIP datasets. The numbers of dibao households and individuals increase markedly over the three years, reflecting the expansion of the program during this time frame. The numbers of dibao households and individuals are adequate for analysis at the national level, but with disaggregation the numbers quickly become too small. Consequently, our analysis is carried out primarily at the national level.

In order to evaluate the dibao program’s targeting performance and poverty impacts, we need to estimate the “ex ante” or counterfactual level of income that households would have had in the absence of the dibao transfers. Here we estimate ex ante income as equal to reported or “ex post” income minus the amount of dibao transfers received by the household. This approach assumes that receiving a dibao transfer does not change household behavior. It is widely recognized in the literature on cash transfers that households that receive transfers are likely to alter their behavior, for example, by reducing effort to earn income. If this is the case for rural dibao recipient households, our estimates of ex ante income will understate the true 10
- (ii) The **business registration process in the Commercial Court Registry was highly discretionary** and in many respects not consistent with good international practice. Even judges in the same court required different documents. As one lawyer says, “ _I had to file the same form to the same court in 15 different ways depending on what judge handled my registration_ ” (Jersild and Skopljak, 2007).

- (iii) **Businesses needed to visit several government offices** to start operating their business (business registry, tax authority, statistics bureau, pension and health insurance) and _ex ante_ inspections were mandatory for all activities, whether low or high risk.

- (iv) **The minimum capital requirement for LLC’s was significant –** approximately €5,000.

- (v) The **registries lacked accuracy, accessibility and transparency** . The registries were paper based and one had to prove legal interest to be allowed access to any information contained therein.

- (vi) **There was no exchange of data between the stakeholder institutions** that in turn increased the burden on businesses that had to re-submit the same information to several agencies.

- (vii) Business **entities were issued (at least) 4 identification numbers** used for different purposes, including the statistical number, the tax number, the business registration number and the social security registration number.

During the mid-2000s, Serbia underwent major structural reforms driven by the need for a substantial transformation of the socialist into a market economy legal system, with the objective to create a favorable business environment and increase private investment, business start-ups, job creation, and incentives for efficiency among both private and state-owned enterprises. Within this broader context, business entry was so burdensome, that it was an obvious candidate for major reform.

The reform started with the Cabinet adopting principles of reform, based on which the legal and institutional framework were designed and implemented. A Business Registration Law and Companies Act were enacted in late 2004, and a new administrative agency was established to take over business registration from the courts and municipalities- the Serbian Business Registers Agency (SBRA). The SBRA started operating on January 1, 2005 as a newly established administrative, self-sustainable agency with an electronic and central business register for the 5
<!-- Start of picture text --> oe 5 ies w/ . © Cos : ~<br>f i Vg t TMs al i, *<br>~ y L v ale fi<br>aa Wa - y F | ¥<br>Cluster: [71 Mii2 L_IN/A pe : L<br>1BRO 48188 | :<br>JUNE 2024<br><!-- End of picture text -->
language at later stages of development (Mustard 2006: 33). Many studies (cited in Mustard 2006: 37) have shown that children with poor verbal skill development during their first three years of life do poorly in language and literacy in school.

Both stunting and poverty are associated with declines in years of schooling. In Brazil, lowincome, stunted children receive more than four fewer years of schooling on average and, once they become adults, earn an estimated 30 percent less income than the average worker (Grantham-McGregor and others 2007).<sup>6</sup> Thomas and Strauss (1997) show almost a 20 percent reduction in returns to schooling among self-employed males in Brazil when height is added to the wage function.

Studies of adult literacy in the United States under the U.S. Department of Education National Education Assessment Program have shown that children with the lowest physical and mental health also perform at the bottom of the distribution in standardized tests. Figure 5, from Grantham-McGregor and others (2007), shows the cognitive deficits resulting from being in the lowest wealth quintile in the first three years of life. On the basis of income, the standard deviations in cognitive and schooling deficits of children ( _z_ scores) in the poorest 20 percent of households are significant. The five countries featured represent three continents and both lowand middle-income groups, suggesting that culture and location are less important than biology in determining these deficits.

**Figure 5. Cognitive or Schooling Deficits Associated with Moderate Stunting in Children Less Than Three Years from Six Longitudinal Studies**

<!-- Start of picture text --> 0.5<br>Z scores<br>0.1 Philippines S Africa Indonesia Brazil Peru Jamaica<br>-0.3<br>-0.7<br>-1.1<br>-1.5<br><!-- End of picture text --> _Source_ : Grantham-McGregor and others 2007.

6. Stunted children with limited cognitive skills are more likely to drop out and to learn less when they do stay in school (Grantham-McGregor and others 2007).

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ratios, and the subscript _i_ refers to countries. The existence of credit constraints implies β _1_ > 0, while the alleviating role of financial sector development implies β _2_ < 0. As regression (27) poses similar problems in terms of the different biases identified in section 2 for cross-country growth regressions, most studies use the dynamic panel techniques suggested by Arrellano and Bond (1991) and Arrellano and Bover (1995) to control for these biases. Using data for 5,000 firms across 36 countries, Love (2003) shows that financial development reduces firms' dependence on cash holdings for investment, while Laeven (2003) shows, for a sample of 400 firms across 13 countries, that financial liberalization helped reduce small firms' financing dependence on internal cash, while it adversely affected large firms' financing possibilities. The effect of financial development and liberalization is also economically significant. Love (2003) shows that firms’ financing constraints – as measured by the cost of capital – in countries with low levels of financial development are twice as high as in countries with average levels of financial development, while Laeven (2003) shows that financial liberalization had a significant economic effect on firms’ financing constraints, reducing small firms’ constraints by 80%.

# **6.2. Household-level approaches**

While the availability of financial information for listed companies and survey data for non-listed companies has resulted in a rapid expansion of firm-level studies, the lack of comparable data for households has impeded similar research for the effect of access to finance on household welfare until recently. As in the case of aggregate and firm-level studies, the identification problem prevents inference from cross-sectional household surveys with data on welfare and access to finance variables. A final and very recent technique therefore uses controlled experiments with households and/or microentrepreneurs, whose financing constraints are randomly alleviated and who are then compared to a control group whose constraints were not alleviated. The challenges of these studies are less in estimation techniques than in the proper identification of treatment and control groups and of the experimental treatment itself. In the following, we will discuss three examples.

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repeated cross-section and panel samples of firms covering 32 EMDEs before and after Basel III implementation, with only some countries exposed to the treatment (Basel III implementation) and others not. To gauge the effect of Basel III on SME financing, we employed the difference-indifferences method and used a regression setup to control for confounding factors and address possible sample selection issues. To tighten the identification, we also formed a panel of matched firm-bank data to isolate the supply-side factors of the SME finance market more accurately.

Overall, our results indicate that Basel III implementation had a moderately negative effect on SME assess to finance in EMDEs. Differentiating across the intensity of financial inclusion, SMEs that were initially on the fringes of financial inclusion could have been affected more adversely than SMEs already using bank credit. Firms accessing credit prior to Basel III implementation may have been less negatively affected, but also the effect could have been insignificant. This finding dovetails with practitioners’ view that once SMEs have an established relationship with a bank, they typically do not face problems in renewing credit—that is, in the absence of large shocks to SME performance or financial stability (Campello, Graham, and Harvey 2010).

One channel for the negative effect of Basel III could arise because of banks shifting toward more unsecured (presumably short-term) lending and, on secured lending, banks requiring much more collateral from SMEs. Financial crises curtailed the progress in easing SME access to finance across the board. In contrast, SMEs in countries with better contract enforcement saw their access to finance ease significantly more.

In addition, we examined whether young and small firms suffered disproportionally more and whether initially less capitalized and less liquid banking systems enhanced the moderately negative effects of Basel III. However, we found little support for heterogeneity in the effects of Basel III across these firm and bank characteristics. Further, we failed to find evidence that the moderately negative effect of Basel III on SME financing would be less negative in countries transitioning to Basel III from Basel 2.5 versus Basel II.

Our findings have important policy implications. According to our results, well-capitalized and provisioned banking systems could be more successful in improving SME access to finance and, 38
_Table 1: Structure of Enrollment and Public Expenditure on Education_

||_1980_|_1985_|_1993_|
|---|---|---|---|
|Gross enrollment ratio (percentage)||||
|Primary|148.0|126.0|104.0|
|Secondary|32.0|39.0|48.0|
|Higher|1.1|1.6|2.0|
|Public expenditure on education||||
|As a percentage of GNP||||
|Primary|0.95|0.79|0.75|
|Secondary|1.00|0.79|0.74|
|Higher|_0.55_|0.58|_0.51_|
|As a percentage of public expenditure||||
|Primary|3.4|3.6|4.7|
|Secondary|3.6|3.5|4.3|
|Higher|1.9|2.8|3.1|
|As a percentage of education expenditure||||
|Primary|38|36|40|
|Secondary|40|36|39|
|Higher|22|27|21|
|Percentage of cumulative public spending<br>received by best educated decile a/||29|27|

# a/ Staff estimates

_Source:_ State Education Commission and SSB.

A single summary indicator of structural equity is provided by the share of cumulative public expenditure received by the best educated decile in a generation. Overall, 10 percent get 27 percent of cohort resources and 90 percent receives the balance, reflecting an egalitarian distribution of public subsidy in education. This is also well below the regional Asian average of 39 percent. Normally, the best educated decile in developing countries receives more than its population share of the cumulative public expenditure on education. The cutoff at 10 percent is an arbitrary one, but it
<!-- Start of picture text --> Figure 10A: Poverty Rate, Alternative Scenarios in 2030 Figure 10B: Poverty Headcount, Alternative Scenarios in 2030<br>90 x r ) 60M e@<br>80 x * *<br>70 ® 3 50M<br>60 e@ ®@ e % Lao<br># 3 @<br>cc 50 e g<br>= e@ e@ 3 e@<br>ag 4030 * e * @ ra2ov2 30m e e x<br>e e 9g @ 20m<br>20 @ x 3<br>10M bad x 8 r )<br>10 @ 4 @ e 8 é $ 3 8<br>0-@ @ om -@ @<br>2 3 ¢§ @ €$ = — @ ¢€ 8 2 3 ¢§ @ € = £—€ #8 € 8<br>8s g €% # & s = gs 8 s g@ =% 2% 8s gs = g 4<br>< : s E <= : s ” E<br>=) E © 2 FS x) E 8 2 FS<br>< a 2 < gs 8<br><!-- End of picture text --> Poverty rates in 2030 for the Base Case and Fully Integrated scenarios. Initial (2010) poverty rate shown as an "X". Countries with ten highest headcounts shown. Source: International Futures v7.0 Year Scenario %* 2010 ll Base Case @ 2030 @ Growth and Shared Prosperity ff Improved Institutions and Security Extended Poverty rates in 2030 for the Base Case and Fully Integrated scenarios. Initial (2010) poverty rate shown as an "X". Countries with ten highest headcounts shown. Source: International Futures v7.0 Year Scenario %* 2010 i Base Case @ 2030 i Growth and Shared Prosperity Improved Institutions and Security Extended