scholarly journals Limiting too-big-to-fail: market reactions to policy announcements and actions

2021 ◽  
Author(s):  
Mario Bellia ◽  
Sara Maccaferri ◽  
Sebastian Schich
Keyword(s):  
Risk Premia ◽  
Bank Debt ◽  
Too Big To Fail ◽  
Subordinated Debt ◽  
Public Authorities ◽  
Market Reactions ◽  
European Banks ◽  
Market Perceptions ◽  
Using Data ◽  
Made In

AbstractBanks considered too-big-to-fail (TBTF) tend to benefit from funding cost advantages as their debt is considered implicitly guaranteed by public authorities, even if the latter have undertaken substantial effort to limit TBTF. This paper focuses on the changes in related market perceptions in response to bank regulatory and resolution reform announcements as well as actual failure resolution actions. It analyses how premia on risky bank debt have reacted to such events, using data for senior and subordinated debt CDS quotes for 45 European banks from January 2007 to May 2020. The empirical results are consistent with progress being made in reducing the value of implicit bank debt guarantees, especially on subordinated bank liabilities. Some earlier bank failure resolution actions appeared to significantly raise risk premia, although more recent failure resolution cases either had no effect on risk premia or moved them in the opposite direction. Several of these events consisted of no-action, that is, in particular, they did not entail any bail-in. As opposed to resolution actions, the reactions of risk premia to policy and regulatory announcements are more difficult to explain and no clear pattern seems to be emerging, confirming the view that action speaks louder than words.

scholarly journals Cleaning up Third World Debt Without Getting Taken to the Cleaners

1990 ◽  
Vol 4 (1) ◽  
pp. 31-42 ◽  
Author(s):  
Jeremy Bulow ◽  
Kenneth Rogoff
Keyword(s):  
Third World ◽  
Debt Crisis ◽  
Population Control ◽  
Development Aid ◽  
Bank Debt ◽  
International Debt ◽  
Regulatory Changes ◽  
Loan Guarantees ◽  
Third World Debt ◽  
Made In

Should taxpayers of wealthy countries finance a leveraged buyout of third world debt? The case for establishing an international debt discount facility rests on the belief that the overhang of foreign commercial bank debt is stifling growth in the Highly Indebted Countries, and that coordination problems among private sector banks are blocking efficiency-enhancing debt reduction schemes. Thus there is scope for a multilateral government agency to step in, buy up the debts, and pass on the efficiency gains to struggling debtors. Our contention is that a debt discount facility would in fact be a black hole for aid funds, and would yield only minimal efficiency benefits. Our assessment of the debt crisis suggests a very different approach. Development aid should be divorced from debt negotiations and instead should be tied to countries' performance in areas such as environmental policy, drug interdiction, and population control. Future aid allocations should not be disguised as loan guarantees, and the massive bond obligations of existing multilateral lenders ought to be placed on the books. Finally, we recommend reversing a number of legal and regulatory changes made in the 1970s that served to encourage the loans in the first place.

scholarly journals Data-Driven Approach for Predicting and Explaining the Risk of Long-Term Unemployment

2020 ◽  
Vol 214 ◽  
pp. 01023
Author(s):  
Linan (Frank) Zhao
Keyword(s):  
Machine Learning ◽  
Age Groups ◽  
Learning Models ◽  
Public Authorities ◽  
Ensemble Machine Learning ◽  
European Public ◽  
Data Driven Approach ◽  
Using Data ◽  
Machine Learning Models

Long-term unemployment has significant societal impact and is of particular concerns for policymakers with regard to economic growth and public finances. This paper constructs advanced ensemble machine learning models to predict citizens’ risks of becoming long-term unemployed using data collected from European public authorities for employment service. The proposed model achieves 81.2% accuracy on identifying citizens with high risks of long-term unemployment. This paper also examines how to dissect black-box machine learning models by offering explanations at both a local and global level using SHAP, a state-of-the-art model-agnostic approach to explain factors that contribute to long-term unemployment. Lastly, this paper addresses an under-explored question when applying machine learning in the public domain, that is, the inherent bias in model predictions. The results show that popular models such as gradient boosted trees may produce unfair predictions against senior age groups and immigrants. Overall, this paper sheds light on the recent increasing shift for governments to adopt machine learning models to profile and prioritize employment resources to reduce the detrimental effects of long-term unemployment and improve public welfare.

scholarly journals Gestation at completion of prenatal questionnaires in ALSPAC

2020 ◽  
Vol 5 ◽  
pp. 100
Author(s):  
Yasmin Iles-Caven ◽  
Kate Northstone ◽  
Jean Golding
Keyword(s):  
Data Collection ◽  
Pregnant Women ◽  
First Trimester ◽  
Environmental Data ◽  
Parents And Children ◽  
Using Data ◽  
Time Critical ◽  
Avon Longitudinal Study ◽  
In Pregnancy ◽  
Made In

Enrolling a cohort in pregnancy can be methodologically difficult in terms of structuring data collection. For example, some exposures of interest may be time-critical while other (often retrospective) data can be collected at any point during pregnancy.  The Avon Longitudinal Study of Parents and Children (ALSPAC) is a prime example of a cohort where certain data were collected at specific time points and others at variable times depending on the gestation at contact.  ALSPAC aimed to enrol as many pregnant women as possible in a geographically defined area with an expected date of delivery between April 1991 and December 1992. The ideal was to enrol women as early in pregnancy as possible, and to collect information, when possible, at two fixed gestational periods (18 and 32 weeks). A variety of methods were used to enrol participants.   Approximately 80% of eligible women resident in the study area were enrolled. Gestation at enrolment ranged from 4-41 (median = 14) weeks of pregnancy. Given this variation in gestation we describe the various decisions that were made in regard to the timing of questionnaires to ensure that appropriate data were obtained from the pregnant women.  45% of women provided data during the first trimester, this is less than ideal but reflects the fact that many women do not acknowledge their pregnancy until the first trimester is safely completed. Data collection from women at specific gestations (18 and 32 weeks) was much more successful (80-85%). Unfortunately, it was difficult to obtain environmental data during the first trimester. Given the time critical nature of exposures during this trimester, researchers must take the gestational age at which environmental data was collected into account. This is particularly important for data collected using the questionnaire named ‘Your Environment’ (using data known as the A files).

scholarly journals EVALUASI PELAPORAN KAMSELTIBCAR LANTAS DALAM MENDUKUNG PELAPORAN DEKADE AKSI KESELAMATAN JALAN

2019 ◽  
Vol 2 (1) ◽  
pp. 1
Author(s):  
Nunung Nuring Hayati ◽  
Ni Nyoman Suartini ◽  
Achmad Wicaksono ◽  
Ike Fibriani ◽  
Mirtha Firmansyah ◽  
...  
Keyword(s):  
Data Mining ◽  
Road Safety ◽  
Road Transport ◽  
Public Knowledge ◽  
Traffic Law ◽  
Using Data ◽  
Two Parameters ◽  
Self Protection ◽  
The Relationship ◽  
Made In

Kamsebtibcar Lantas or secure, safety, orderliness, and fluency of traffic are made in support of road safety actions reporting on traffic due to the lack of public knowledge about the importance of using self-protection tools that have been determined in traffic law number 22 of 2009 concerning traffic and road transport. By using this program, you can find out the relationship between the factors that cause accidents. From those collected from various regions in East Java, taken from 2016 to 2018. The data obtained can be processed using data mining techniques. This technique works by using a pattern that is a reference for decision making. By using the Fp-Growth algorithm that works with the data tree system to find out the patterns of reporting activities that are happening, this pattern is determined by two parameters, namely support (support value) and confidence (certainty value). With this system, it can help the parties concerned to improve facilities in various Kamseltibcar Lantas reporting activities. Kamsebtibcar lantas atau keamanan, keselamatan, ketertiban, dan kelancaran lalu lintas dibuat dalampedalam mendukung pelaporan aksi keselamatan jalan pada lalu lintas yang dikarenakan minimnya pengetahuan masyarakat tentang pentingnya penggunaan alat perlindungan diri yang telah ditentukan pada undang-undang nomor 22 tahun 2009 tentang lalu lintas dan angkutan jalan. Dengan menggunakan program ini dapat mengetahui hubungan antara faktor-faktor penyebab kecelakaan. Data yang dikumpulkan dari berbagai daerah yang ada di wilayah Jawa Timur diambil pada tahun 2016 sampai dengan 2018. Data yang telah didapat dapat diolah menggunakan teknik data mining. Teknik ini berfungsi dengan menggunakan pola yang menjadi acuan untuk penentuan keputusan. Dengan menggunakan algoritma Fp-Growth yang bekerja dengan sistem data tree untuk mengetahui pola kegiatan pelaporan kamsebticar lalu lintas yang sedang terjadi, pola ini ditentukan dengan dua parameter, yaitu support (nilai penunjang) dan confidence (nilai kepastian). Dengan sistem ini dapat membantu pihak yang berkaitan untuk meningkatkan fasilitas dalam berbagai kegiatan pelaporan Kamseltibcar Lantas.

scholarly journals Density Variations during Solidification of Grey Cast Iron

2018 ◽  
Vol 925 ◽  
pp. 155-162 ◽  
Author(s):  
Kristina Hellström ◽  
Péter Svidró ◽  
Lucian Vasile Diaconu ◽  
Attila Diószegi
Keyword(s):  
Complex Geometry ◽  
Control Volume ◽  
Solidification Process ◽  
Simulation Software ◽  
Volume Changes ◽  
Silicon Alloys ◽  
Know How ◽  
Grey Cast ◽  
Using Data ◽  
Made In

As part of moving towards a sustainable production of diesel engines for heavy vehicle applications, the ability to predict casting defects has become ever so important. In order to model the solidification process for cast components correctly, it is of essence to know how the material will actually behave. To produce sound castings, often of complex geometry, the industry relies on various simulation software for the prediction and avoidance of defects. Thermophysical properties, such as density, play an important part in these simulations.Previous measurements of how the volume of liquid grey iron changes with temperature has been made with a conventional dilatometer. Measurements have also been made in the austenitic range, then on iron-carbon-silicon alloys with a carbon content lower than 1.5 wt%. Based on these measurements the density variations during solidification were calculated. The scope for this paper is to model the volume changes during solidification with the control volume finite difference method, using data from the density measurements.

Advances in Fish Tagging and Marking Technology

2012 ◽  
Keyword(s):  
Atlantic Salmon ◽  
Salmo Salar ◽  
Release Time ◽  
Tag Identification ◽  
Penobscot River ◽  
Salmon Population ◽  
Declining Populations ◽  
Simple Change ◽  
Using Data ◽  
Made In

<i>Abstract</i>.—Atlantic salmon <i>Salmo salar </i>smolts are stocked in the Penobscot River, Maine to supplement declining populations. Since 2000, approximately 550,000 hatchery smolts are annually released into the river, of which 32% of these (175,000) were marked with visual implant elastomer (VIE) tags indicating release time and location. Our study found that tag colors of adult returns were often misread due to confusion between green and yellow marks and between red and pink marks. Using data collected on mark readings in a controlled hatchery environment, we corrected for tag identification errors made in the field, thereby allowing adjustments to be made in the marked returns to accurately assess the number of returns from multiple stocking groups. When adult returns from multiple stocking groups were compared, significant differences were detected between stocking groups, including a three-fold difference between two of the stocking groups. Hence, a simple change in smolt stocking locations and times may be of value in the recovery of the Penobscot River salmon population.

scholarly journals Are Banks’ Below Par Own Debt Repurchases a Cause for Prudential Concern?

2018 ◽  
Vol 35 (3) ◽  
pp. 501-529
Author(s):  
Martien Lubberink ◽  
Annelies Renders
Keyword(s):  
Fair Value ◽  
Alternative Methods ◽  
Basel Iii ◽  
Regulatory Capital ◽  
Liability Management ◽  
Tier 1 ◽  
Capital Ratios ◽  
European Banks ◽  
Using Data ◽  
Tier 1 Capital

In the lead-up to the implementation of Basel III, European banks repurchased debt securities that traded below par. Banks engaged in these Liability Management Exercises (LMEs) to realize a fair value gain that prudential rules exclude from regulatory capital calculations. The LMEs enabled banks to augment Core Tier 1 capital, given that alternative methods to increase capital ratios were not feasible in practice. Using data of 720 European LMEs conducted between April 2009 and December 2013, we show that poorly capitalized banks repurchased securities and lost about €9.1bn in premiums to compensate their holders. Banks also repurchased the most loss-absorbing securities, for which they paid the highest premiums. These premiums increase with leverage and in times of stress. Hence debt repurchases are a cause for prudential concern.

scholarly journals The Space Distribution of Planetary Nebulae

1968 ◽  
Vol 34 ◽  
pp. 44-50 ◽  
Author(s):  
J.H. Cahn
Keyword(s):  
Computer Program ◽  
White Dwarf ◽  
Local Density ◽  
Planetary Nebulae ◽  
Interstellar Extinction ◽  
Space Distribution ◽  
Using Data ◽  
Dust Distribution ◽  
Made In

A punched-card catalogue of planetary nebulae has been prepared, using data extracted from all existing catalogues. A computer program calculates distances and radii using the method of Shklovsky, in which all nebulae are assumed to have the same ionized mass, and allowance for interstellar extinction is made assuming a continuous galactic-dust distribution. The assumption made in Shklovsky's method, that the nebulae are optically thin, is considered to be satisfied if the calculated radii lie within a certain well-defined interval. The reddening constants obtained are in satisfactory statistical agreement with constants determined by other methods. The local density of planetary nebulae is in agreement with estimates of local white-dwarf densities.

Does Audit Fee Homogeneity Exist? Premiums and Discounts Attributable to Individual Partners

2011 ◽  
Vol 30 (4) ◽  
pp. 249-272 ◽  
Author(s):  
Stuart D. Taylor
Keyword(s):  
Audit Quality ◽  
Audit Fees ◽  
Data Availability ◽  
Audit Market ◽  
Homogeneity Assumption ◽  
Audit Firms ◽  
Audit Fee ◽  
Using Data ◽  
The Individual ◽  
Made In

SUMMARY This paper investigates the implied assumption, made in many audit fee determination studies, that, within a given audit firm, all partners produce a statistically identical level of audit quality and earn a statistically identical level of audit fees. This is referred to as the “homogeneity assumption.” However, this is contradicted by the individual auditor behavioral literature, which shows that different individual auditor characteristics can have an impact on audit quality. Given the fact that audit partners differ in their quality, this paper hypothesizes that different audit partners will be able to earn differing levels of fees. This hypothesis is tested by estimating an audit fee model using data from 822 Australian publicly listed companies for the year 2005. Australia is an ideal audit market for this research, as the disclosure of the name of the audit engagement partner in the audit report is mandatory. The empirical results indicate that individual audit partners earn individual audit fee premiums (or discounts) that are not explainable by the audit firms of which they are members. Data Availability: All data have been extracted from publicly available sources.

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