rafmacalaba/data-use-mentions-extended huggingface dataset:
_zijt_ is the error term. Like equation (1), this focuses on the variables‘ indirect effects, but on magnitude instead of frequency.

As with equation (1), we consider variants of equations (2)-(4) that include private credit, the Gini coefficient, and quadratic values of income and governance.<sup>5</sup>

# **3. Data**

We compiled an unbalanced panel with observations on the number of people killed in flood events, as well as variables capturing the physical magnitude of floods and the affected population‘s exposure and vulnerability, for 2,194 floods in 108 countries during 1985-2008.

# _3.1 Flood data_

We coded the dependent variable in equation (1), _Fjt_ , as zero if the DFO reported no floods in a country in a given year. Otherwise, we set it equal to the sum of reported events for that year. On average, there was just over one flood per country-year in the sample (Table 3), but the number varied considerably, as the standard deviation was more than twice the mean. More than half (57%) of the observations equaled zero.

Flood deaths recorded in disaster databases, including the DFO‘s, are typically from drowning and severe injuries. Deaths from unsafe or unhealthy conditions following a flood are also a health consequence, but disaster statistics typically include only the deaths

> 5 Some previous studies on disaster fatalities have also included a variable representing the frequency of disasters, typically calculated as the sum of previous events. Keefer et al. (2010) found that earthquake frequency reduces fatalities, and they argued that more frequent earthquakes increase the payoffs to fatality prevention measures. This may be so, but the results presented in this paper refer to models that exclude such a variable because the country fixed effects in those models should capture cross-country differences in flood frequency. As a test of this, we added the cumulative number of floods to the fatality models, and
allow the supervisor to easily aggregate ratings and default experience to back-test the mapping from the rating buckets to the default probabilities.

- The system would ensure a consistent treatment of capital and loan loss reserves. This is of course a vital component of Pillar 2 and Basel Core Principle 8.

- Favor the development of a risk based capacity within the banking system independently from each country decision to officially remain in Basel I or to adopt the different options of Basel II.

• The homogeneity of bank classification schemes would provide the system of an important additional property: individual banks data could be aggregated at a country level generating an important, so far mostly missing, information about the cyclical developments of credit quality. It would also make possible to monitor the effect of structural reforms (legal, regulatory, dissemination of credit information) on the quality of credit and on the cost of credit. Current Basel II arrangements under the IRB preclude such developments and have not considered the important public good element represented by this information externality).

# **5. Conclusions**

In this paper we have discussed a simple methodology for the integrated estimation of expected and unexpected losses for countries that have a source of centralized credit information, such as a credit register, and we have shown how these estimates can provide the basis for a simplified risk based bank solvency regulation that is compatible with Basel II and could be used by countries that are not yet ready to adopt the IRB approach.

19
APPENDIX

# B2. Computing Returns: Data and Assumptions

**_Treatment of partial and missed coupon payments:_** A main challenge to compute total returns on historical sovereign bonds was to collect bond-level data on partial or missed coupon payments during spells of default. We retrieved information on interest servicing during crises from the historical reports of the UK-based Corporation of Foreign Bondholders (CFB) (1876-1944, 1945-1986), the US-based Foreign Bondholders Protective Council (FBPC) (1934-1940, 1945-1950, 1953-1964/67), the Association Belge pour la Défense des Détenteurs de Fonds Publics (1898-1915), and the French Association Nationale des Porteurs Franҫais de Valeurs Mobiliéres (1936-1945, 1948-1974, 1987-1988, 1996). To fill gaps, we also rely on the rich body of investor reports that we gathered for the long-run dataset of prices and restructurings (see Appendix B1 above and Appendix C1 below). Particularly helpful were reprints of (temporary) debt agreements, official announcements, or press releases of the debtor government. We typically extracted the relevant information on interest servicing from text statements such as: “Coupon due May 01, 1932 paid in Jan. 1933 at rate of 60% of the face value of the coupon.”  For most bonds we have exact amounts and dates of payments. In case the date of partial coupon payments is missing we assume that the debtor paid on the due date of the coupon (original deadline). In the case we do not find any indication that coupons are missing, we assume that they are fully paid. After gathering all coupon details, we again calculate accrued interest by equally distributing the (full or partial) payments over the original coupon payment period (eq. 5). For example, in the case of a yearly coupon frequency, we calculate returns by dividing the coupon paid by 12 (equal amounts per month).

**_Accounting for debt restructurings/ haircuts:_** We account for creditor losses due to a debt restructuring or debt write-off. We do
or initiatives that improve the delivery of basic services and facilitate investments in physical and human capital. In contrast, if vulnerability is predominantly risk induced, then implementing a program that addresses the risk may be essential (Skoufias, Vinha, and Beyene 2024). For example, if the risk is caused by wide uninsured income fluctuations, then implementing an insurancebased program may be required to reduce vulnerability.

The analysis described in this paper involved the application of this proposed method to the generation of a poverty and vulnerability map for Senegal. Unlike the previous quotas, which relied on commune poverty rates, the new method is based on a recognition of the dynamic nature of poverty. Nonpoor households experience shocks and may therefore be at risk of falling into poverty. This extension of the 20
measure and the volatility measure are included. In ( _R7_ ), growth and inflation are measured on a quarter-on-quarter basis instead of year-on-year. Specification ( _R8_ ) adds depreciation of the local currency against the U.S. dollar to the set of control variables.

As discussed in Section 3.1, the term “liquidity” can have more than one meaning. Since we are concerned with the availability of funding liquidity to banks, as opposed to the degree of liquidity of a market which is better captured by traditional measures such as the spread between on-the-run and off-the-run securities or the bid-ask spread, the Libor-OIS spread is our preferred measure. However, disentangling a pure liquidity component from a counterparty risk component is not straightforward, since availability of credit depends crucially on credit risk, and more than one approach is worth considering. One alternative measure in the literature has been the spread between Libor and the rate on CDs, since purchasers of CDs do not necessarily face the liquidity constraints that banks do during a financial crisis (Taylor & Williams 2009). Furthermore, since CDs are typically only insured up to a limit, CD rates may rise along with

> 15 We use quarter-on-quarter (QoQ) inflation and growth data to better capture sharp, short-run changes that may be important during a crisis, as well as for consistency with the overall frequency of the dataset. However, QoQ data for inflation may result in extreme outliers, which we ameliorate by taking logarithms. Dropping these cases would potentially bias the results, since we lose valuable information from those observations. In any case, the results reported here remain robust to either artificially limiting the inflation rate in these cases to 1,000 percent, or dropping these observations entirely.

> 16The measure of loan demand is from the Fed’s Senior Loan Officer Survey. The ECB collects comparable data on loan demand faced by European banks, but we use the U.S. measure since U.S. banks lend less in developing countries.

13
smaller data set, which we term the qualitative data set for convenience, supplements the existing measures with qualitative assessments of project characteristics, extracted from primary documents such as Project Appraisal Documents (PADs), Implementation Completion and Results Reports (ICRs) and IEG ICR Reviews (ICRRs). The qualitative data variables include an expert panel assessment of the quality of Project Development Objectives (PDOs) and results frameworks. They also include data on restructurings and a set of contingent indicators such as the number of PDO changes and closing date extensions for those projects that underwent restructuring – i.e. factors that are countable but not counted in existing administrative data. We complement this with a review of the ICRRs from outlier projects – defined either as those with highly satisfactory outcome ratings in low capacity environments (‘positive outliers’) or highly unsatisfactory ratings in high-capacity environments (‘negative outliers’).

The project success ratings themselves fall on a six-point scale ranging from 1 (highly unsatisfactory) to 6 (highly satisfactory). For a binary designation of satisfactory project, attaining a cut-off of 4 or more is required (72% of projects in our data were rated as ‘satisfactory’). There is a tendency for IEG to downgrade ratings assigned by project management and, in the case of PPARs, its own reviewers. Of the 1,968 projects for which we have final ICR and ICRR ratings, 628 were downgraded from the ICR and 54 upgraded. Of the 563 projects for which we have PPARs, 159 were downgraded and 54 upgraded. As most downgrades are from satisfactory to moderately satisfactory and from moderately satisfactory to

> 8 This measure is distinct from the staff quality measure in Denizer et al. (2013), who adopt the average outcome of all other observed projects of the TTL as their quality measure. Our quality measure is somewhat more closely related to the one in Limodio (2021), although our measure utilizes additional project-level information in the value-added calculation, and is discussed further in the next section.
that for a ten digit tariff line to belong to the set AMt, it is sufficient for the tariff line in year t to match with one tariff line from any of the three periods in the base period.

The vast majority of tariff lines are matched with a tariff line in at least one of the three years of our base period, but not all tariff lines have a match in the base period. For 2011 (A2011), there are 632 tariff lines that are not an element of AMt. For 2012 there are 347 tariff lines that are not an element of AMt, i.e., they do not match at the ten digit level with any tariff line in any of the three years of our base period.

# **Tariff for Matched Tariff Lines in 2011** .

We need to develop separate procedures for tariff lines h in the set AM2011 and for those not in the set AM2011. First consider those tariff lines in the set AM2011. Using the tariff rate data from the Customs Union, we can follow a procedure based 10
<mark>Direct taxes and social benefits in Serbia are less equalizing than in a few Central and Eastern Europe (CEE) countries where similar analysis has been conducted. Based on the CEQ analysis for other countries</mark><sup>12</sup> <mark>, and disaggregating effects by policy instruments, the equalizing effects of direct taxes and social benefits in Serbia are somewhat stronger than in non-European developing countries, but still considerably smaller than in those CEE economies.</mark> The marginal contribution of all direct transfers in Serbia is to reduce the Gini (when pensions are treated as deferred income) by 0.0139. In Russia, Romania, and Croatia, they reduce inequality by 0.0220.024 points. Direct transfers in Armenia and Albania also have a higher capacity to reduce inequality, with the marginal contribution of 0.019 and 0.17, respectively. <mark>At the same time, the impact of indirect taxes in Serbia on inequality is close to the average of the CEE countries and non-EU developing countries with available CEQ results.</mark> <mark>The equalizing effects of in-kind transfers in Serbia is comparable with the effects in those CEE countries. The effects of health and education spending in Serbia are considerably stronger than in non-European developing countries which may be the result of its free and universal primary and secondary schooling and almost universal healthcare scheme.</mark>

# **Impacts on poverty**

Government intervention through taxes and benefits is associated with an increase in poverty in Serbia, mostly due to indirect taxes. Using household income and standardized international poverty lines of $1.9, $3.2, and $5.5/day (2011 PPP), the results suggest that the poverty rate decreases after direct taxes and social benefits are taken into account but increases upon the imposition of indirect taxes. In other words, social transfers cannot fully offset the burden of taxes on poverty. Table 3 shows that the
the People's War in Nepal. Pluto Press.

- OPHI (2013). Country Brieng: Nepal Multidimensional Poverty Index (MPI) At a Glance. Technical report, Oxford Poverty and Human Development Initiative, University of Oxford, Manseld Road, Oxford OX1 3TB, UK. Avaialble at: http://www.ophi.org.uk/wpcontent/uploads/ Nepal-2013.pdf.

- Palmer, M., Nguyen, C., Mitra, S., Mont, D., and Groce, N. (2016). The long-term impact of war on health. HiCN Working Papers 216, Households in Conict Network.

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**Table 13. Presence of Ombusman as oversight tool by Income Level**

||Do countries h|ave an Ombu|dsman?<br>||
|---|---|---|---|---|
|Incomelevel|no|yes|Total|% yes|
|Low|11|14|25|56|
|Middle|5|25|30|83.3|
|High|5|16|21|76.2|
|Total|21|55|76||

# <u>Oversight Tools and Level of Democracy</u>

The purpose of this section is to investigate the relationship between the level of democracy and the number of oversight tools that are available to the legislature. Before we can do so, however, we need to discuss how our ‘democracy’ variable is operationalized.

The Freedom House computes an annual index of freedom for all the countries in the world; this index is regarded by many social scientists as a proxy index of democracy; known as Gastil index, it is computed in the following way. The Freedom House assigns to each country a political rights score and a civil liberties score. Both scores are 7-point scales. The index of freedom is estimated by adding a country’s political rights score to that country’s civil liberties score and by dividing their sum by 2. This means that the Gastil index of freedom is also a seven point scale. So, for example, if the fictional country of Abbaba has a score of 3 for its political rights and of 4 for its civil liberties, then Abbaba’s democratic score is (3+4)/2 that is 3.5. Countries that score from 1 to 2.5 points on this scale are considered democratic; countries scoring from 3 to 5.5 are quasi17
input into our calculations, we estimate the persistence of 61 commodity prices using around a century of data taken from Jacks (2013) and find wide variation in the persistence of shocks across commodities, with many being highly persistent (though still stationary).<sup>8</sup>

> 7 For example, Cashin et al. (2000) argue that highly persistent commodity price shocks will undermine commodity price stabilization schemes, but they make this argument descriptively. 8 The long sample is important to reduce the well-known attenuation bias on the estimation of persistence in short samples. Appendix Table 2 lists the estimated persistence of 61 individual commodity prices.

7
availability, labor regulation, tax rate burdens, land acquisition. The subscript c for these variables indicate that it is based on city-level average rather than a firm’s answer.

Overdraft Facilityc Trade Creditc Inf Competititonc Outagec Webc Security Costc Capacity Agglomerationc City share of firms with overdraft facility. Based on WBES calculation.

City average of the proportion of total annual sales of goods and services that are paid for after delivery. Based on WBES calculation.

City share of firms who say that they directly compete with informal firms. It is a measure of the importance of the informal sector and its competition with the formal sector. Based on WBES calculation.

City share of firms that experienced a power outage in the survey year. Based on WBES.

City share of firms that answer that they use websites to conduct business.

City average of the share of a firm’s sales paid for security. Based on WBES.

The share of firms whose number of employees exceeding 50, as a proxy of capacity agglomeration. Computed based on sample firms.

**Table 2. Summary Statistics**

||N|mean|sd|p10|p25|p50|p75|p90|
|---|---|---|---|---|---|---|---|---|
|L-growth|97669|0.041|0.143|-0.084|0.000|0.007|0.096|0.179|
|L-growth for high-growth firms|5,412|0.370|0.197|0.170|0.230|0.321|0.454|0.627|
|L-growth for non-high-growth firms|92,257|0.022|0.113|-0.096|0.000|0.000|0.074|0.135|
|LP-growth|70068|-0.026|0.
average by both CEEC-8 and the EU15 are management of ports, IT infrastructure and customs. They are respectively 26 percentage points and 16 percentage points for the latter two below the average for CEEC-8.

> 14 WMO’s indicators rely on three sources—Global Competitiveness Report, World Competitiveness Yearbook, and a dataset compiled in Kaufmann, Kraay and Zoido-Lobaton (1999).  Each indicator is constructed as a simple average of two inputs as described in the appendix.<sup>14</sup>
Stone, Clay and Glass Produc|ts8,857|29,754|29.77|5,980|15,365|38.92|
|Metal products|23,949|48,913|48.96<br>|17,706<br>|31,176|56.79|
|Electrical<br>Machinery|9,557|21,552|44.34|5,873|15,437|38.04|
|Machinery and Transport|||||||
|Equipment|19,423|95,749|20.29|9,046|44,231|20.45|
|Other|2.494|14,107|17.68|1,643|8,109|20.27|
|Total|157,488|447,104|35.22|103,779<br>|257,012|40.38|

- a) indirect taxes and subsidies are deducted (see table 2.3).

- b) includes 3,831.7 million pesos (excl. indirect taxes and subsidies) for petroleum refining, which are not shown in the census Resumen General but taken from Sistema de Cuentas Nacionales de Mexico.

- **c)** the footwear industry (2,675.9 million cruzeiros) was reallocated from wearing

- apparel to footwear and leather.

Source: Mexican gross value added in national currencies calculated from Resumen General (see table 2.3 which does not exclude bank costs). Brazilian gross value added in national currencies calculated from Censo Industrial (see table 2.1 which does not exclude bank costs). Bank costs derived from the same sources (for calculation see chapter II). PPPs from table 4.9.
# _Better Educated Labor Force_

Before looking at how the rise in educational attainment translated into higher skills of the labor force, it is useful to have a brief look at the types of workers in the labor market. The Labor Force Survey (LFS) shows that between three-quarters to four-fifths of the population aged 15 to 59 years were employed in 2004 (Figure 23.A). Unemployment never rose above 5 percent and was just over 1 percent in August 2004. The rest are those not in the labor force due to household duties, old age, seasonality, studying, or other reasons. Labor force participation dropped by about five percent due to the early 1990s, principally due to more and longer school attendance and in spite of a decline of seasonal work.

With economic development, more people leave family work, primarily in agriculture, to take up wage employment. Indeed, the share of wage workers among the employed in February increased by about one half. The rise in wage employment also led to a decline in the August harvest season effects. Nevertheless, still more than half of all jobs were non-wage in 2004. Further, among wage workers, only about half received monthly wages in 2004. While almost 99 percent of the monthly wage workers are covered by the 1998 Labor Protection Act or are public sector workers, only 70 percent of other wage workers, and six percent of non-wage workers, belong to these categories. Remarkably, the share of monthly wage workers among wage workers is unchanged compared to the early 1990s, and about 10 percent lower than prior to the crisis in 1996. Due to the continued rise in wage employment, the share of workers on monthly payroll in total employment increased up to 1996 and stagnated since.

As to be expected, the increase in enrolment rates since the early 1990s led to a more qualified labor force. The education attainment of the labor force improved steadily since the early 1990s. The labor force with more than primary education doubled since 1991 to reach close to 40
well-above average for a diverse set of industries from textiles, wearing apparel and leather, wood and wood products to chemicals, basic metals and fabricated metal products. The largest numbers of new products are introduced in the basic metals and fabricated metal products and machinery and equipment industries. Most product innovators are multi-product plants. For innovating plants overall, their new products generally account for less than 50% of revenues and they tend to add to the plants‟ existing product scope in most industries.

To provide a richer characterization of product innovation and assess the role that risk plays for the innovation-survival link we construct a variety of measures which interact both the dummy and

> plant-year observations have less than 10 employees. Of those 939 plant-year observations, in most cases plants remain in the ENIA survey reporting less than 10 employees for multiple years. Hence, we are confident that plant exit from the ENIA sample does indicate real failure. Nevertheless, we conduct an econometric exercise focusing on plants with more than 15 employees in Section 4.2.

> 10 The INE collects information on which plants in the ENIA survey are part of a multi-plant firm, i.e., a firm with at least two plants responding to the survey. The information was kindly provided to the authors for the purposes of this research project. During the 1997-2003 sample period on average 8.3% of firms are multi-plant firms. In the rest of the paper we will be particularly careful to denote single-unit establishments which are the object of ENIA‟s survey as „plants‟ and refer to „firms‟ only when this corresponds to units with multiple plants.

> 11 See Navarro (2012) and Fernandes and Paunov (2009) for details on the products data. Due to a change in product classification from ISIC Rev. 2 to ISIC Rev. 3 classification in 2001, we omit that year in the econometric analysis.

5