rafmacalaba/data-use-mentions-extended huggingface dataset:
for the country’s own exit yield. Appendix C2 provides further details and shows robustness checks when using alternative discount rates. Among other checks, we apply a 10% flat rate to all deals, as well as a “risk-free” lower bound rate, by using the yield on UK or US long-term government bonds at the time of the restructuring.

To make the estimates as comparable as the data permit, we apply the same haircut computation approach across the entire 200-year span. The required simplifying assumptions are discussed in detail in Appendix C. The Appendix also discusses how we deal with the so-called “sinking fund” structure of many historical bonds, bond buyback options, gold and currency clauses, or country-break ups. Moreover, we show results for alternative haircut measures, in particular the face value (nominal reduction) haircuts and for the socalled “market haircut,” which compares the face value of the old debt to the present value of the new debt. In addition, we check the correlation between our haircut estimates and bond prices around the start of default. This is relevant because, as noted above, the corporate debt literature typically uses market prices at the default onset to estimate bond recovery rates. Taken together, we find that the haircut formula and the choice of the discount rate matter, in particular for the estimated means, but the overall picture and the dispersion of haircuts across space and time is similar, irrespective of the method used.

> 25 We have pricing data for only a subset of these defaulted bonds.

12
0.40|0.40|0.40|0.42|

Notes: *** p<0.01, ** p<0.05, * p<0.1. Robust standard errors are clustered at the DHS cluster level. All regresssions employ cluster x month fixed effects. The weights used are person weights adjusted for the national populations. All regressions use all available data on rural households from 5 Southern African countries (Mozambique, Malawi, Tanzania, Zambia and Zimbabwe). All metrics are based on children being measured below -2 standard deviation thresholds. 41.0 percent of the children are stunted, 15.1 percent are underweight, 5.1 percent are wasted, 12.6 percent are stunted and underweight, and 45.2 percent are malnourished based on any of the three metrics.

24
household heads, owning fewer plots are more likely to be measured than other plots. This is a drawback of GPS data that raises concerns about possible biases introduced by relying on observed GPS plot measures alone.

In presence of rates of missingness this high, imputations are often necessary for analysts to be able to work with complete case datasets. Self-reported land areas measures have been shown to be an important predictor of GPS area measure (Kilic et al., 2013). For that reason it is recommended that GPS measures be taken in addition to, not instead of, self-reported ones.

# **_C. The ‘Gold-Standard’: Compass and Rope Measurement_**

Traversing, also known as the compass and rope method, is widely used in farm surveys and is often considered to be the gold standard (FAO, 1982). When properly implemented, traversing returns highly accurate measures that can also provide a benchmark against which to judge the precision of other 10
_ANDR EE_<sup>_ ́_</sup> _SEPTEMBER 28, 2022_ _14_ Table 1—Cross-validation results.

||_Linear_|_Cubist_<br>_Cubistsynth_|
|---|---|---|
|10-fold val|idation||
|R<sup>2</sup>|0.60|0.94<br>0.95|
|RMSE|8.72|3.49<br>3.10|
|MAE|6.16|1.75<br>1.62|
|Highest co|untry obs|ervation held out for testing|
|R<sup>2</sup>|0.57|0.82<br>0.94|
|RMSE|11.02|7.53<br>5.00|
|MAE|7.77|4.23<br>2.44|
|Final year|held out|for testing|
|R<sup>2</sup>|0.64|0.87<br>0.97|
|RMSE|9.84|6.01<br>3.55|
|MAE|5.96|2.67<br>1.98|

_Note:_ Prediction performance estimated for various setups. In all experiments, the model is optimized for R<sup>2</sup> and the associated MAE and RMSE are given. _Source:_ Results have been estimated by the author for this paper.

In the second experiment, the holdout sample consists of the highest severity rate observed in each country. This explicitly validates the models for their ability to anticipate an unprecedented value (outside observed history) and is specifically aimed at assessing each model’s ability to extrapolate. This more closely resembles the intended use of forecasting the global crisis risks post 2019 based on 2015-2019 data. It follows the previous work of Celiku and Kraay
poses challenges for electricity distribution to keep up with heavy demand.<sup>15</sup> Figure A1 in the appendix (panel a) lends support to the idea that electricity prices increased more in provinces with a relatively poor quality of the grid. An inverse proxy for the latter is the province-level average self-generated electricity as a share of total electricity consumed over the entire period 1998-2015.

A similar level of geographic heterogeneity applies also to fuel prices. As fuels need to be transported mainly by trucks, but also by sea vessels, the price of fuel is extremely sensitive to disruptions to the transportation network, roads in particular. Events such as the closure of a road, disruption in naval shipment or technical failure of a supplier’s transportation equipment add substantial randomness to the propagation of nationally mandated prices energy prices.<sup>16</sup> The provinces with lower transport infrastructure density are expected to suffer more significantly from such negative shocks given the paucity of viable alternative routes. Panel (b) of Figure A1 provides suggestive confirmation of this hypothesis by showing a negative correlation between changes in fuel prices and the period-average kilometers of highway per square kilometer of the province area.

The empirical analysis will rely on such geographic variation of electricity and fuel prices over time to extract the exogenous local component of price changes over time.

> 15This is also consistent with the 2009 World Bank Enterprise data, which shows that high shares of firms in West Java experienced power outages relatively to northern Sumatra.

> 16In some cases, variation is induced by policy. For instance, frequent shortages have prompted authorities to approve higher tariffs in remote areas to unlock local small-scale supply from independent utilities (IEA, 2014). In an attempt to address these large price differences, in 2016 the Government of Indonesia has started the implementation of a “One-price Fuel Policy” program, which however falls beyond the period of our analysis.

8
The most well known examples of using ‘edutainment’ for gender-based violence prevention are Sexto Sentido, carried out by Puntos de Encuentro in Nicaragua, and Soul City, carried out by the Institute for Health and Development Community in South Africa and eight other Sub-Saharan countries in Africa. Both have used prime time television soap operas, radio programs, school-based work, and other media to address violence against women, gender, sexuality and rights. Some research suggests that Sexto Sentido has had a positive impact (Abaunza, 2002; UNFPA, 2002; Berliner, 2002), but little quantitative evidence of effectiveness has been published or disseminated. However, an ambitious qualitative and quantitative evaluation is underway involving a three-year panel/cohort study among more than 4500 young respondents and at least three rounds of data collection--in 2003, 2004, and 2005 (Guedes, 2004). This study will measure the program’s success in changing attitudes and behavior around gender, stigma, HIV/AIDS and gender-based violence. Soul City has already conducted extensive population-based impact studies of Series 4, which addressed gender-based violence for the first time in 1999 (Scheepers, 2001; Scheepers and Cristophides, 2001; Soul City, 2001; UNFPA, 2002; Singhal et al., 2004). That research found that the series reached 82% of the population in South Africa and had a positive impact on both awareness and knowledge about violence against women. The impact on attitudes appeared to be mixed. Certain attitudes about violence improved slightly (such as whether violence is a private affair), but some stayed the same or deteriorated. For example, there were no changes in the levels of those who believed that men have the right to beat their wives, or in the belief that such beatings are socially acceptable. The evaluation focused on intermediate outcomes such as knowledge, attitudes, and intentions, but not on how these related to outcomes such as levels of actual violence. The program measured a greater impact on HIV/AIDS attitudes and behaviors
ECNFT-Q03|2002, 2008, 2011,<br>2017, 2021|ADM 1|ADM 2|
|Ecuador|ENEMDU|2008, 2011, 2017,<br>2022|ADM 1|ADM 2|
|El Salvador|EHPM|2002, 2008, 2011,<br>2017,2022|ADM 1|ADM 2|
|Guatemala|ENCOVI|2011, 2014|ADM 1|ADM 1|
|Honduras|EPHPM|2008, 2011, 2017,<br>2019|ADM 1|ADM 2|
|Mexico|ENIGH, ENIGHNS|2002, 2008, 2010,<br>2016, 2022|ADM 1|ADM 2|
|Panama|EH|2002, 2008, 2011,<br>2017, 2021|ADM 1|ADM 1|
|Paraguay|EPH|2002, 2008, 2011,<br>2017, 2022|ADM 1|ADM 1|
|Peru|ENAHO|2002, 2008, 2011,<br>2017,2021|ADM 1|ADM 3|
|Uruguay|ECH, ECH-S2|2002, 2008, 2011,<br>2017,2021|ADM 1|ADM 1|

Note: Province or state level imputation is indicated with ADM 1, district imputation is indicated with ADM 2, and lower-unit levels are indicated with ADM 3.

To construct the aggregate household characteristics, we use the SEDLAC household survey data at province/state level. We generate the following household aggregate characteristics: the proportion (ZZ), of households engaged in agriculture in the state, the state's employment rate, the state's unemployment rate, the share of self-employed and entrepreneurs in the state, the share of the 11
where _pk_ is the percentage of total pixels in each location with color _k_ , with _k_ equal to 0 for green, 1 for orange, 2 for red, and 3 for dark red, respectively. To obtain the daily congestion index, we compute the index for every hour and take the average over 24 hours. By construction, the figure varies between 0 and 300, where 0 indicates a free-flow traffic condition and 300 a highly congested condition. We interpret the traffic congestion index (TCI) as a measure of aggregate delay from free-flow speed.<sup>6</sup> We use and construct the daily congestion index over the period from March 20, 2019 to May 19, 2020 for several major cities with varying degrees of Covid-19 lockdowns. These include Paris and New York City, subject to strict lockdown measures starting on March 17 and March 20, 2020, respectively. We also include Bogotá and New Delhi, both of which started to enforce strict Covid-19 lockdown policies on March 25, 2020. We use the traffic conditions in Hong Kong SAR, China, a city that did not implement any Covid-19 lockdown measure, as our main control series for modeling the counterfactual scenarios for Bogotá, New Delhi, New York City, and Paris. Alternatively, in addition to using the TCI of Hong Kong SAR, we also use the TCI from cities such as Cairo, Sofia, Stockholm, and Tokyo that opted for relatively softer lockdown measures. Finally, we enrich our control index time series with information on traffic congestion city-level precipitation and temperature from Menne et al. (2012a,b). In what follows, we focus on core cities only. The methodology is, of course, replicable to measures of congestion at the greater metropolitan area level.

> 6 Dasgupta et al. (2020) use the same underlying information from Google Maps to calculate the average speed within a city. Their approach, however, requires estimating a city-specific correspondence between speeds and colors and assuming that the correspondence is stable
Another important issue covered by the 2011–12 Bank Regulation and Supervision Survey pertains to the definition and the limits on related party exposures. About 95 percent of respondents state that their countries include as “related parties” significant controlling shareholders and board of directors along with the relatives and business interests of these two parties. In general, EMDEs have slightly stricter regulations and guidelines governing related parties. Note that what appears to be a drop in the median of the limit of related party exposure as a percentage of a bank's regulatory capital from 100 percent in 2005 to 25 percent in 2010 is in large part driven by differences in the sample of countries that responded to both surveys. If we focus on the “matched” sample, this change disappears.

**Table A6. Bank Governance:** **<u>Selected Responses</u>**

||**ALL**|**ADV**|**EMDEs**|
|---|---|---|---|
|**A. Authority Over Appointments**|**% Yes**|**% Yes**|**% Yes**|
|Does the supervisor exercise approval authority with respect to the appointment of<br>Board directors?|85|91|83|
|Does the supervisor exercise approval authority with respect to the appointment of<br>Senior bank management?|79|80|78|
|**B.**<br>**Remuneration or Compensation**|**% Yes**|**% Yes**|**% Yes**|
|Is the remuneration or compensation of Board directors evaluated as part of the<br>supervisory process to ensure that theydo not lead to excessive risk-taking?|59|74|53|
|Is the remuneration or compensation of Senior bank management evaluated as part<br>of the supervisory process
merged with the relevant cycle’s CN files. The House and Senate files were separated for each cycle. Congressional committee and sub-committee assignments for each Congress were obtained from Congressional Quarterly (1991-1999).

Mapping from PACs to SIC-based agricultural-related sector makes use of the concordance by Beaulieu and Magee (2002).<sup>10</sup> In general the mapping is many-PACs-tomany-SIC-codes. For many-to-one maps, the contributions were simply aggregated for each SIC code. For one-to-many maps, political contributions from each PAC were fractionally assigned equally to each SIC code into which the PAC mapped. To check the consistency of the PAC data, they were compared with the data on the opensecrets.com website. Our data are very comparable in the aggregate, as well as those sectors for which opensecrets.com does report data.

_B. PAC Spending Across Agriculture-Related Sectors_ Figure 2 shows the breakdown of PAC contributions by 2-digit SIC agriculture-related sectors in the 1991-92 election cycle (first bar) and the 1999-2000 cycle (second bar). The striking feature here is that the contributions have held fairly steady over the ten-year period. It appears that the same PACs have contributed fairly predictable amounts of money over this period. Rather than use the 2-digit descriptions, subsequent figures break down farm PACs by seven products—wheat, dairy, sugar, vegetables and fruits, cotton, ranch and other. Figure 3 depicts the total contribution by agriculture-related sectors for each of the five election cycles between 1991 and 2000. In order to compare farm PAC contributions with other agricultural related sectors, Figure 3 also shows contributions by PACs in the following major sectors: Farm Equipment, Agricultural Services, Crop Processing Services, Distribution, Forestry/Nursery, and Food Manufactures.

Farm PACs contributed between $5.5 mn. and $7 mn. during each of those five election cycles. Among farm products the most politically active were sugar PACs, dairy PACs and ranch PACs. Together these three PACS accounted for about 75% of total farm PAC contributions<sup>
- 42 -

# A. Quick Fixes

The yield of the urban property tax is the combined product of a sequence of four factors: the completeness of the fiscal cadastre, the level and accuracy of valuations, the tax rate and exemption schedule, and the efficiency of collections. Efforts to reform a deteriorated property tax system often start at the beginning with a new fiscal cadastre. Unless equal effort is devoted to improving collection efficiency and increasint tax rates, much of the effort devoted to fiscal cadastre is wasted however. Newly discovered, or newly revalued properties yield no revenue if collections are not enforced. They yield twice as much revenue if the tax rate is doubled.

This suggests, as a general rule, that the search for targets of reform should begin at the end of the taxation process--at collection--and work backward. This results not only in more efficient use of effort but a considerably earlier increase in revenues.

Collection efficiency is a good first target. Sorting payment records to identify major delinquents, combined with conspicuous enforcement of penalties, can produce a major one-time increase in collections on arrears. Introduction of financial- reporting systems for collections, and sustained commitment to enforcement can result in a sustained increase in collection efficiency. An increase in tax rate will increase liabi'ities in the next tax ycar, and is a good second target for reform.

These solutions, in effect, increase collections from properties already on the tax rolls increasing liabilities in proportion to existing valuations. Where the fiscal cadastre is reasonably complete, and the valuations still valid in relative terms, these
workers that participated in training and the distribution of the hours spent in training in 2003 in manufacturing firms. We combine this estimate of hours in training with wage data to estimate the wage and salary cost of employee time in formal training. Because these surveys were conducted only in the industrial sector, we do not have estimates for training expenditures for services. Therefore, when comparing our aggregate estimate of training investment to that from other countries, it is important to keep in mind that ours is an

> 16 As one would expect, this method suggests that business R&D in social sciences and humanities is insignificant.

14
9 the impacts of agricultural domestic and trade policies, distinguishing them from the impacts of other merchandise trade policies. A second distinction is that we examine inequality as well as poverty. Third, we focus on the effects of current policies, i.e. of full (not partial) global liberalization, whereas the Hertel and Winters study focuses mainly on the multilateral partial reform proposals that were on the table as of 2005. The country case studies examine not just multilateral trade reform but also unilateral reforms that individual developing countries might implement. The effects of unilateral action are compared with what full liberalization abroad would generate, so as to be able to assess the relative importance domestically for each nation of own-country policies as distinct from those of other countries (over which the country has influence only indirectly via trade negotiations).

The national CGE models are able on their own to estimate the effects of unilateral reform of agricultural or all merchandise trade-distorting policies. For the national modeler to estimate the effects of other countries’ policies, however, requires input from a global model. The World Bank’s LINKAGE model is chosen here for that purpose. It too is calibrated to 2004, based on Version 7 of the GTAP global protection database (Narayanan and Walmsley 2008) apart from the replacing of its applied agricultural tariffs for developing countries with the more comprehensive set of national price distortion estimates from Valenzuela and Anderson (2008).

There are various ways of transmitting the results derived from a global CGE model such as LINKAGE to a single-country CGE model. Like Hertel and Winters (2006), we adopt the approach developed by Horridge and Zhai (2006). For imports, Horridge and Zhai propose the use of border price changes from the global model’s simulation of rest-of-world liberalization (that is, without the focus developing country). For the focus developing country’s exports, the shift in its export demand curve following liberalization in the rest of the world is given in percentage changes by x=(1/σ)
Locoh, T., and M. P. Thiriat. 1995. “Divorce et remariage des femmes en Afrique de l’Ouest. Le cas du Togo.” _Population_ 50 (1): 61–93.

Madhavan, S. 2002. “Best of Friends and Worst of Enemies: Competition and Collaboration in Polygyny.” _Ethnology_ 41 (1): 69–84.

Madhavan, S., and C. H. Bledsoe. 2001. “The Compound as a Locus of Fertility Management: The Case of The Gambia.” _Culture, Health & Sexuality_ 3 (4): 451–68.

Papps, K. L. 2006. “The Effects of Divorce Risk on the Labour Supply of Married Couples.” IZA Discussion paper 2395, Bonn.

Royston, P., and M. K. B. Parmar. 2002. “Flexible Parametric Proportional-Hazards and Proportional-Odds Models for Censored Survival Data, with Application to Prognostic Modelling and Estimation of Treatment Effects.” _Statistics in Medicine_ 21 (15): 2175–97.

Tertilt, M. 2005. “Polygyny, Fertility, and Savings.” _Journal of Political Economy_ 113 (6): 1341–71.

Udry, C. 1996. “Gender, Agricultural Production, and the Theory of the Household.” _Journal of Political Economy,_ 104 (5): 1010–46.

24
# _6.3 Implementation_

The index implementation could be organized as a series of interviews with IT management in the organization. Different questionnaires could be administered to personnel responsible for the acquisition, operation, and disposal of the organization’s IT infrastructure. An aggregate GGIT index and sub-indexes are then derived from these survey data and supporting documentation. These indexes could be compared with those of other government organizations, and the areas of improvement might be identified based on such comparisons. While the primary purpose of the GGIT index is to indicate areas of improvement, the GGIT methodology could also be used as a guide for improvements in IT processes to achieve environmentally sustainable ICT in each organization.

In addition to cross-sectional comparisons, the GGIT index could be used for monitoring the progress of an organization in improving the environmental sustainability of its IT departments. Year-to-year relative improvements in the aggregate index and its sub-components could be indicative of whether the organization is committed to the green IT agenda.

The GGIT index must be periodically reviewed and updated. ICT technology is progressing, rapidly becoming more efficient and environmentally friendly. It is essential to renew the methodology and the underlying indicators for the index to remain relevant. At the same time, the index should try preserving inter-temporal comparability. One approach to achieve such comparability is to maintain two indexes, the updated and the new index, for some time, allowing monitoring of the progress of government organizations towards the environmental sustainability of their IT departments.

# **7. Conclusions**

In this paper, we propose a new Green Government IT index to assess the environmentally responsible use of computers and other ICT resources by the IT departments of government institutions and other organizations. Our theoretical and empirical methodology relies on the established literature on index construction and draws on the models for evaluating the environmental sustainability of ICT. The paper discusses the conceptual and mathematical foundation behind the new index and defines a set of verifiable, comparable, and transparent indicators for index construction. The flexibility of our methodological framework allows for 17