rafmacalaba/datause-encoder-data huggingface dataset:
_SECURITIES CLEARANCE AND SETTLEMENTSYSTEMS_

|**Risk**|**Risk Management Tools**|
|---|---|
|**_Credit Risk_**|**Monitoring members' creditworthiness:**In addition to admission standards<br>participants have to submit copies of their financial statements and are subject<br>to periodic reviews.|
||Novation: Satisfaction and discharge of existing contractual obligations by<br>means of their replacement by new obligations. In the context of the securities<br>clearance and settlement system the clearing agent sometimes guarantees the<br>delivery and receipt of settlement obligations, becoming the counterparty to<br>each trade. However, novation moves the credit risk to the clearing agent<br>obliging this institution to implement risk management tools to face this<br>exposure.|
||**Clearing Fund:**Contributions from participants to cover losses which might<br>take place during business operation.|
||**Buy ins and Sell outs:**These are settlement assurance procedures that, in<br>case of a settlement failure, allow the buy of securities in the market at the<br>seller (who failed) cost (buys-in) or the sale of securities in the market at the<br>buyer (who failed) cost (sell-outs).|
||Net**debit caps:**A net debit cap is the maximum amount that a participant is<br>permitted to incur in its net debit position to all other participants. It<br>establishes an upper limit to the exposure that any participant can pose to the<br>system. It is normally linked to the liquid resources available for the clearing<br>agent. In order to be effective, transactions that exceed a participant's net<br>debit cap should be rejected.|
||**Bilateral credit limits:**Sometimes clearing agents require each participant to<br>establish a bilateral credit limit with each of the other participants|
||**Collateral:**Clearing organizations require collateral to cover certain<br>exposures. The type of collateral accepted ranges from liquid assets such as<br>cash or government securities to the securities cleared by the arrangement.<br>The concentration of collateral, the legal perfection of the security interests<br>and adequate valuation are issues that have to be carefully considered in order<br>to determine the effectiveness of the collateral. Bankruptcy laws may affect<br>the clearing organization's and its participants collateral interests due to<br>different priorities among creditors and the so called "zero hour" rule or<br>simply different institutions may have different bankruptcy procedures.<br>In the futures/commodity markets margins act sometimes as collateral.<br>Margin is a good faith deposit (of money, securities or other financial<br>instruments) assuring that a future contract will be fulfilled.<br>2 8|

> _28 In the equity markets, margin has another meaning. It is the money deposited with the broker that serves as partial payment when purchasing securities. The money deposited with the broker is the difference between the purchase value of the shares and the collateral value (haircut)._

_16_
# How Household Characteristics Shape Program Access and Asset Accumulation: A Mixed Method Analysis of the Vision 2020 Umurenge Programme in Rwanda

## Justine Gatzinsi

_Rwanda Local Development Administrative Entities Authority_ Renate Hartwig _University of Namur_ Lindsay Mossman, Umutoni Marie Françoise & Isimbi Roberte _FATE Consulting Ltd_ Laura Rawlings* _World Bank_

**JEL-codes** `─` D04, I38, O12 **.**

`─` **Key-words** Gender, Household Context, Rwanda **,** Social Protection, Mixed Method Analysis.

**__________________**

* _Corresponding Author:_ Laura Rawlings, World Bank Group, Washington D.C. Email: lrawlings@worldbank.org.

_Acknowledgements_ : This research has been supported by the World Bank’s Rapid Social Response Trust Fund. The Trust fund is supported by the governments of Norway, the Russian Federation and the United Kingdom. The financial support is greatly acknowledged. The financial support is gratefully acknowledged. We are also grateful to Theresa Betancourt, Hugo Brousset Chaman, Vincent Gahamanyi, Andrew Kettlewell, Carolyn Turk, Briana Wilson and participants in the Kigali-based seminar for valuable comments and suggestions on earlier versions of this research.

_Disclaimer:_ The findings, interpretations and conclusions expressed in this paper, as well as, any errors or omissions are entirely those of the authors.
# **Table 1: Summary Statistics**

||K|MS|SL|MS|
|---|---|---|---|---|
||**Mean**|**Std. dev**|**Mean**|**Std. dev**|
|Percent Male|71.1||50.6||
|Age|43.1|12.5|41.8|11.2|
|Years of schooling|10.4|2.4|9.3|2.9|
|Percent Married|85.6||81.3||
|Age of business in years|6.0|7.0|10.8|10.6|
|Usual hours per week working in business|77.2|18.9|56.6|19.3|
|Percent that doesn't keep business records|85.6||73.3||
|Percent registered with the D.S. office|30.6||7.9||
|Percent registered with the Pradeshya Saba|60.0||12.1||
|Percent registered with the Provincial Govt.|1.7||3.7||
|Percent registered with the Central Govt|1.7||0.8||
|Percent registered with the Business Chamber|0.0||0.6||
|Percent unregistered with any entity|18.9||76.6||
|Percent in retail trade|100.0||49.6||
|Percent in manufacturing|0.0||50.4||
|_Baseline values_|||||
|Market value of inventories|24493|18000|12308|16982|
|Value of non-land capital stock owned|13154|13720|27447|28414|
|Total reported revenues - retail|28007|25028|15389|17612|
|Total reported revenues - manufacturing|||7541|10550|
|Total reported profits - retail|5201|4302|4020|3266|
|Total reported profits - manufacturing|||3390|3890|
|Percent not paying taxes (baseline)|92.8||96.1||
|**Sample Size**|**174**||**619**||

# Note:

Baseline is July 2005 for KMS, March 2005 for SLMS.

24
Table A3.3: INSTITUTIONAL COST,S OF TEACHER TRAINING INSTITUTES l l

||CAFOP/ENI|I<br>ENS|IPNETP|
|---|---|---|---|
|||1'000 CFAF--||
|Personnel Expenses||||
|-<br>Permanent Ivorian Staff<br>-<br>Salaries<br>-<br>Housing Allowance|1,390,524<br>1D56,863|790,000<br>94,800|341,000<br>40,920|
|-<br>Temporary Staff|1.i7,050|19,500|43,400|
|-<br>Technical Assistants<br>-<br>Cooperative Contracts)<br>-<br>Local Contracts<br>)|1,221,688|885,802<br>128,713|405,548|
|Subtotal|2,936,125|1,918,815|830,868|
|Operating Expenses|731,510|311,200|169,750|
|Scholarships||||
|-<br>Regular Students<br>- Teachers on Leave|94,200<br>_|1,563,700<br>650,955|147,350<br>_|
|Total Recurrent Costs|3,7151,835|4,444,670|1,147,968|
|(Enrollment)|(1,570)|(2,100)|(265)|
|Recurrent Cost per Student|2,396.073|2,116.509|4,331.955|
|Amortization of Buildings and||||
|Equipment (per Student)|765.695|677.283|350.955|
|Total Cost per Student|3,161.768|2,793.792|4,682.910|
Some authors have analyzed tax structures in low-income countries with weak tax mobilization. They have concluded that the weaknesses were a conseqiuence of the fact that the formal sector of the economy represented a relatively small share of employment and business activities. Therefore, the effect of reforms associated with those taxes levied on personal or corporate income have had quite limited impact on government revenues (Tanzi, 1987, 2000; Gemmel and Morrissey, 2003). Given the limited public administration tools in many developing countries, the empirical evidence suggests that perhaps the best policies are through introduction of indirect taxation mechanisms to finance necessary government expenditures (Heady, 2004, Bird and Zolt, 2005). As “in many developing countries, the effects of even the most progressive income tax on distributional outcomes are likely to be small compared to the effects of taxes on consumption...” (Bird and Zolt, 2005).

The general equilibrium analysis of tax systems has added interesting dimensions missing in studies with partial equilibrium models. These complex interdependencies are included in the analysis of public policies and its linkage to economic output. See, for example, Thissen, M. (1998), Devarajan and Hossein (1998), and Ke-young Chu et al. (2000). Additionally, the social accounting matrices (SAM) used in the CGE studies have become more user-friendly for programming. See Keuning et al. (1988), Robinson (1989), Round (2003), Ahmed, V. and O’Donoque, C. (2007).

Computational general equilibrium tools have been used in studies of the fiscal system of Pakistan by both domestic and international economists (Shah and Walley (1991), Feltenstein and Cyan, (2013), Feltenstein et al. (2014)). Studies of tariffs, with application to Pakistan, have led to the general notion of reducing tariffs. See, for example, Kemal M. A. et al. (2001), Martinez-Vazquez J. (2006), and Guilherme and Taglioni (2013). Some recent studies have 5
treatment. These individuals’ application details were then submitted into ISKUR’s Management Information System (MIS).

The MIS system then stratified applicants for each course by gender and whether or not they were aged less than 25. Within these strata, the MIS then randomly allocated trainees at the individual level into one of three groups: a treatment group who were selected for training, a control group who were not, and a waitlisted group who the training provider could select into the training if there were drop-outs. Since training providers are paid on the basis of number actually trained, if individuals assigned to treatment drop out of training, providers look to quickly fill in the empty spots. In Card et al. (2011)’s evaluation in the Dominican Republic, this led to one-third of the control group being offered treatment, with this selection typically nonrandom. The inclusion of a waitlist was done to prevent this from occurring. Thus if a course had capacity for 50 trainees, and 120 were deemed eligible, 50 would be randomly assigned to treatment, 50 to control, and 20 to a waitlist.<sup>10</sup> If individuals from the treatment group dropped out before one-tenth of the training course had been completed, providers could draw replacements as they liked from the waitlist. If they exhausted the first waitlist, then they drew from a second waitlist of individuals who had just missed the cut of being in the top group of applicants. At no time were trainees or prospective trainees informed of the evaluation. We do not use the waitlist in our study, since their selection into training is non-random.

The final evaluation sample consists of 5,902 applicants, of which 3,001 were allocated to treatment and 2,901 to control. There are 173 individuals who applied to more than one course. These individuals were still randomly selected into treatment or control, but have a higher probability of selection since they participate in more than one course lottery. Our estimation strategy accounts for this.

# **3.4 Compliance with Treatment**

As is common with many training programs, not all those accepted into the course took up the training. Twenty-three percent of the individuals assigned to treatment chose either to not take training or had dropped by the second day of the course, despite it being typically only two to three weeks between the interviews for a course and its start date. There was relatively little

> 10 If between 1.8 and 2.2 times the course capacity applied, then proportionally smaller groups were chosen. For example, if 100 people applied for a course with capacity 50, then 50 individuals would be allocated to the training (of which 40 would be designated the treatment group for surveying and measurement purposes), 40 would be allocated to control, and 10 to the waitlist.

8
# **1. Introduction**

The COVID-19 pandemic has caused a sharp reduction of economic activity, which negatively affected the revenues, liquidity and potentially solvency of many firms. In response to this crisis, the European Central Bank announced the Pandemic Emergency Purchase Program (PEPP) on March 18, 2020. The PEPP earmarks €750 billion for the purchase of government and private debt securities until the end of 2020 without a preset allocation rule.<sup>1</sup> PEPP-eligible private debt instruments are investment-grade, issued by non-bank corporations located in the euro zone, and dominated in euros.<sup>2</sup> The <mark>combined monetary and fiscal policy response to the COVID-19 crisis around the world, including corporate QE, appears to have led to a quick overall recovery of equity prices.</mark> <mark>This paper uses an event study methodology to investigate which European firms benefited more from the PEPP as evidenced by a more positive share price response and a greater decline in the CDS spread, signaling lower expected credit losses on a firm’s debts. We find a more positive abnormal stock return for investment-grade firms, consistent with the PEPP targeting investment-grade debt securities. At the same time, the CDS spread of investment-grade firms declined relatively more after the PEPP announcement, suggesting improved expectations of solvency for such firms.</mark> <mark>The benefits of the PEPP, however, extend beyond strictly PEPP-eligible firms. In particular, European firms with a non-investment grade rating also experienced a more positive abnormal stock (relative to firms without a credit rating) as evidence of a spillover of the PEPP to credit</mark>

> 1 The Federal Reserve <mark>announced the establishment of two new facilities to acquire corporate bonds in the primary and secondary market on March 23, 2020. T</mark> hese are the <mark>Primary Market Corporate Credit Facility (PMCCF) and the Secondary Market Corporate Credit Facility (SMCCF).</mark>

> 2 In addition, remaining maturity has to be at least 6 months in the case of bonds, and at least 28 days for commercial paper.

2
World Bank (2020), **Women and Trade: The Role of Trade in Promoting Gender Equality** , World Bank, Washington DC.

World Bank. 2022. Women, Business and the Law 2022. Washington, DC: World Bank. doi:10.1596/978-1-4648-1817-2. License: Creative Commons Attribution CC BY 3.0 IGO <mark>Zhang, Jian, Jin, Songqing, Li, Tao and Wang, Haigang, (2021), Gender discrimination in China: Experimental evidence from the job market for college graduates,</mark> _<mark>Journal of Comparative Economics</mark>_ <mark>, 49, issue 3, p. 819-835.</mark> <mark>Zveglich, Joseph and Rodgers, Yana, (2003), The Impact of Protective Measures for Female Workers,</mark> _<mark>Journal of Labor Economics</mark>_ <mark>, 21, issue 3, p. 533-556.</mark> 47
trigonometric specification (which is also preferred by the BIC criterion). Figure 4 plots the two seasonal functions together with the 95% confidence range for the dummy variable estimates. The trigonometric seasonal functions (which omit the large December effect given the inclusion of the December dummy) are again much shallower than the visual pattern suggested by the dummy variable seasonal factors. In this case, both the trigonometric seasonality function and the zero axis lie entirely within the 95% dummy variable confidence intervals. The estimated seasonal gap based on the trigonometric specification is 2.7 percent.

Three conclusions emerge. First, the _F_ tests reject the hypothesis of no seasonality in caloric intake. This is true of both sets of pooled OLS estimates and of the FE trigonometric estimates. Second, on average, across Tanzania, seasonality in food consumption appears limited. Third, notwithstanding these insights and the large cross‐section dimension of the dataset, measuring consumption seasonality from only three cross‐sections of data remains ambitious and indicative at best. It also does not tell us whether the observed seasonality in food consumption is due to seasonality in staple prices, which the paper now probes further by estimating the elasticity of calorie consumption to staple prices.

The focus in estimating the elasticity of calorie consumption to staple prices is on the effect of the concurrent price of maize and rice, the two principal staple foods. In particular, an average staple food price _p_<sup>_av_</sup> is constructed as the logarithmic average of the deflated maize and rice prices in the district of each reporting household using regionally differentiated expenditure weights, distinguishing across districts and between urban and rural households.<sup>20</sup> The Tanzanian maize and rice price series contain gaps, which we interpolate using estimates of equation (4).<sup>21</sup>

> Overall, our FE estimates are effectively based on approximately one third of the number of observations used in the pooled OLS estimates implying a substantial loss in efficiency.

> 20  Price data are not reported for the Pwani region which forms the hinterland to Dar es Salaam. We use Dar es Salaam prices for Pwani households.

> 21 The procedure for estimating seasonal gaps is robust against the presence of missing values avoiding the need for interpolation at that stage. However, in constructing the average staples prices we have the choice between dropping missing observations and interpolating. In the latter case, we can interpolate using estimates of equations (4). The results are qualitatively similar and in what follows we report the results using interpolated prices. We use equation (4) to construct interpolated prices for region _r_ over a gap of _k_ months as

19
all women in NFHS-2 and NFHS-3, we construct a cumulative measure of the number of surviving children. This is accomplished by summing over all births up to that point conditional on the child being alive or reported as having died after October 1994.

For women interviewed prior, i.e. all women in NFHS-1, we approximate this measure. First, we observe that all interviews for NFHS-1 in Haryana took place at the end of the NFHS itself, in 1993. We therefore estimate the cumulative number of surviving children by taking total surviving children as of 1993 and adding one if the woman reports a current pregnancy. This measure is an imperfect but best-possible approximation, enabling us to reasonably exclude women whose fertility is complete. Possible sources of mismeasurement that we cannot account for are child mortality in this period or new pregnancies between the relatively short time frame of 1993 and February 1994.

For children, birth date criteria and the construction of the individual siblingcomposition-based criteria is relatively straightforward. For each child we construct sibling histories and sum up the number of siblings alive at the time of birth. To be eligible, the number of live siblings at birth must be less than or equal to 2.

For completeness, we note that one secondary source, the MODE, 2004 evaluation report, suggests that the eligibility criteria for OBC children appears different than for SC children, based on a later birth date of January 1996. However, this discrepancy is inconsistent with all other primary and secondary sources, and cannot be independently verified. We do not therefore take this into account in our main analysis, but in the robustness checks, we show that our results are unaffected even under this alternative criterion.

# **3.3 Graphical Illustration**

To make the identification strategy more concrete, we graph the share of children alive at 36 months, showing the sample means for each survey wave by gender and eligibility in Figure 1, below. At “baseline”, the initial survival likelihood of eligible and non-eligible boys is higher than for girls in each category. Moreover, non-eligible children as a whole are more likely to survive. Girls eligible for the ABAD program are the worst off.

Since only eligible girls were likely to have received the program in 1994, we examine program effects by comparing the gap between eligible/non-eligible boys to the gap between eligible/non-eligible girls over time. While the survival rates of both eligible and non-eligible boys remains steady over time, girls’ survival to 36 months increases across both groups. This result suggests a common trend underlying the treatment of girls outside of the ABAD program. In addition, however, the gap between eligible and noneligible girls narrows over time while the gap for eligible and non-eligible boys shows no change. As a result, mean survival for eligible girls in 2006 is statistically indistinguishable from mean survival for non-eligible children overall, while the eligible boys still trail behind.

9
NL-2/2-1-88

- 25 -

(3) Now the budget deficit equation in steady state is given by D * (w - ir)h which indicates that the seigniorage wh is used to finance the fiscal deficit and the interest on reserves. Then using (2), we may write which shows that a given D determines x but not w. The latter will vary inversely with a (if v > ir) and directly with ire The following example brings out some important conclusions. First, a given budget deficit is consistent with many inflation rates. Second, a zero budget deficit is consistent with any inflation level if ir = r. Thus, if the central bank returns the entire seigniorage to the public in the form of interest on bank reserves (which implies w = id) then inflation is indeterminate.l/ In view of the latter indeterminateness one may ask why is it that the Sargent-type school of rational expectations puts so much weight on eliminating D as an immediate cure for inflation. The answer would probably be that when D - 0 the "natural" solution for x -0 is x = ir = v = 0 rather than ir = > 0 . This can be rationalized by the presumption that since D = 0 "there is no reason" for agents to expect v > 0.

1/ When we take account of currency the indeterminateness of v with D = 0 requires, in addition, that the central bank returns to the public the amount of the inflation tax on currency. The latter component will be small when inflation is high, since real currency holdings will fall relative to interest bearing deposits.
# Shared Prosperity

## Links to Growth, Inequality and Inequality of Opportunity

Ambar Narayan<sup>*</sup> Jaime Saavedra-Chanduvi<sup>*</sup> Sailesh Tiwari JEL Classification Codes: O10, D63 Key words: Growth; inequality; poverty; inequality of opportunity; shared prosperity Sector Board: Poverty Reduction (POV)

> * Corresponding authors: anarayan@worldbank.org; jsaavedra@worldbank.org. The World Bank Group (Mail Stop: MC4-415), 1818 H Street NW, Washington DC 20433, USA. The authors would like to thank Maya Sherpa and Hiroki Uematsu for research assistance and empirics; Tara Vishwanath, Luis Felipe Lopez-Calva and Pedro Olinto for useful comments; and Gabriel Demombynes and Espen Beer Prydz for the income growth calculations for United States.  The provisional database on shared prosperity, which the paper draws upon, is the product of joint work by a Technical Working Group for measuring Shared Prosperity, comprising of economists from DEC, PREM and the Regional vice-Presidencies. The findings, interpretations, and conclusions are entirely those of the authors. They do not necessarily represent the view of the World Bank Group, its Executive Directors, or the countries they represent.