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  1. Article ; Online: Ignoring Spatial and Spatiotemporal Dependence in the Disturbances Can Make Black Swans Appear Grey.

    Pace, R Kelley / Calabrese, Raffaella

    The journal of real estate finance and economics

    2021  Volume 65, Issue 1, Page(s) 1–21

    Abstract: Automated valuation models (AVMs) are widely used by financial institutions to estimate the property value for a residential mortgage. The distribution of pricing errors obtained from AVMs generally show fat tails (Pender 2016; Demiroglu and ... ...

    Abstract Automated valuation models (AVMs) are widely used by financial institutions to estimate the property value for a residential mortgage. The distribution of pricing errors obtained from AVMs generally show fat tails (Pender 2016; Demiroglu and James
    Language English
    Publishing date 2021-03-31
    Publishing country United States
    Document type Journal Article
    ZDB-ID 2018867-5
    ISSN 1573-045X ; 0895-5638
    ISSN (online) 1573-045X
    ISSN 0895-5638
    DOI 10.1007/s11146-021-09836-2
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Article ; Online: Has previous loan rejection scarred firms from applying for loans during Covid-19?

    Cowling, Marc / Liu, Weixi / Calabrese, Raffaella

    Small business economics

    2021  Volume 59, Issue 4, Page(s) 1327–1350

    Abstract: Abstract: The concept of the 'discouraged' borrower is well documented. In this paper, we consider whether smaller firms in the UK who have been previously rejected for bank loans have been scarred by the experience so badly that even in the presence of ...

    Abstract Abstract: The concept of the 'discouraged' borrower is well documented. In this paper, we consider whether smaller firms in the UK who have been previously rejected for bank loans have been scarred by the experience so badly that even in the presence of two exceptionally generous Covid-19 loan guarantee schemes, they still refuse to make an application. Furthermore, we also consider what happens when they do. As banks have either zero or minimal loss exposure, do they still maintain their normal strict lending protocols or do they relax their standards to fulfil the governments' objective of supporting struggling businesses through the crisis? Our findings show that 72% of previously rejected borrowers are reluctant to request loans. We find some evidence that previously scarred firms faced such severe liquidity problems that they relaxed their distrust of banks during the Covid-19 crisis. However, their share of the government-guaranteed loan portfolio was slightly lower suggesting that banks were treating each new loan application on its merits.
    Plain english summary: The Covid-19 crisis hit smaller businesses so hard that even previously rejected borrowers were forced to apply for loans to keep them afloat. Previous loan rejections have not discouraged small businesses in the UK in applying for Covid-19 government-guaranteed loans. Banks have used the loan guarantee schemes to continue to supply loans to small business during the pandemic. Our paper analyses the important phenomenon of borrower scarring and discouragement, when potential debtors are self-excluded from the lending market because they have previous rejections or expect a negative bank response. We consider around 45,000 UK small businesses from 2018 to 2020. On the demand side, we find that the economic shock for small businesses during the pandemic dissipates the scarring effect. Specifically, we find that micro and small businesses had the highest loan demand in the first two quarters of the pandemic (from March 2020). On the supply side, we show that scarred borrowers were not routed onto Covid-19 government-guaranteed loan schemes. These findings show the importance of government-backed lending schemes for small businesses during crisis period.
    Supplementary information: The online version contains supplementary material available at 10.1007/s11187-021-00586-2.
    Language English
    Publishing date 2021-12-18
    Publishing country United States
    Document type Journal Article
    ZDB-ID 1478919-X
    ISSN 1573-0913 ; 0921-898X
    ISSN (online) 1573-0913
    ISSN 0921-898X
    DOI 10.1007/s11187-021-00586-2
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  3. Book ; Online: Joint model for longitudinal and spatio-temporal survival data

    Medina-Olivares, Victor / Lindgren, Finn / Calabrese, Raffaella / Crook, Jonathan

    2023  

    Abstract: In credit risk analysis, survival models with fixed and time-varying covariates are widely used to predict a borrower's time-to-event. When the time-varying drivers are endogenous, modelling jointly the evolution of the survival time and the endogenous ... ...

    Abstract In credit risk analysis, survival models with fixed and time-varying covariates are widely used to predict a borrower's time-to-event. When the time-varying drivers are endogenous, modelling jointly the evolution of the survival time and the endogenous covariates is the most appropriate approach, also known as the joint model for longitudinal and survival data. In addition to the temporal component, credit risk models can be enhanced when including borrowers' geographical information by considering spatial clustering and its variation over time. We propose the Spatio-Temporal Joint Model (STJM) to capture spatial and temporal effects and their interaction. This Bayesian hierarchical joint model reckons the survival effect of unobserved heterogeneity among borrowers located in the same region at a particular time. To estimate the STJM model for large datasets, we consider the Integrated Nested Laplace Approximation (INLA) methodology. We apply the STJM to predict the time to full prepayment on a large dataset of 57,258 US mortgage borrowers with more than 2.5 million observations. Empirical results indicate that including spatial effects consistently improves the performance of the joint model. However, the gains are less definitive when we additionally include spatio-temporal interactions.
    Keywords Quantitative Finance - Risk Management ; Computer Science - Computational Engineering ; Finance ; and Science ; Computer Science - Machine Learning ; Statistics - Machine Learning
    Subject code 330
    Publishing date 2023-11-07
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  4. Article ; Online: Modeling Antimicrobial Prescriptions in Scotland: A Spatiotemporal Clustering Approach.

    Gieschen, Antonia / Ansell, Jake / Calabrese, Raffaella / Martin-Barragan, Belen

    Risk analysis : an official publication of the Society for Risk Analysis

    2021  Volume 42, Issue 4, Page(s) 830–853

    Abstract: In 2016, the British government acknowledged the importance of reducing antimicrobial prescriptions to avoid the long-term harmful effects of overprescription. Prescription needs are highly dependent on the factors that have a spatiotemporal component, ... ...

    Abstract In 2016, the British government acknowledged the importance of reducing antimicrobial prescriptions to avoid the long-term harmful effects of overprescription. Prescription needs are highly dependent on the factors that have a spatiotemporal component, such as bacterial outbreaks and urban densities. In this context, density-based clustering algorithms are flexible tools to analyze data by searching for group structures and therefore identifying peer groups of GPs with similar behavior. The case of Scotland presents an additional challenge due to the diversity of population densities under the area of study. We propose here a spatiotemporal clustering approach for modeling the behavior of antimicrobial prescriptions in Scotland. Particularly, we consider the density-based spatial clustering of applications with noise algorithm (DBSCAN) due to its ability to include both spatial and temporal data. We extend this approach into two directions. For the temporal analysis, we use dynamic time warping to measure the dissimilarity between time series while taking into account effects such as seasonality. For the spatial component, we propose a new way of weighting spatial distances with continuous weights derived from a Kernel density estimation-based process. This makes our approach suitable for cases with different local densities, which presents a well-known challenge for the original DBSCAN. We apply our approach to antibiotic prescription data in Scotland, demonstrating how the findings can be used to compare antimicrobial prescription behavior within a group of similar peers and detect regions of extreme behaviors.
    MeSH term(s) Algorithms ; Anti-Bacterial Agents/therapeutic use ; Anti-Infective Agents ; Cluster Analysis ; Prescriptions
    Chemical Substances Anti-Bacterial Agents ; Anti-Infective Agents
    Language English
    Publishing date 2021-07-22
    Publishing country United States
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 778660-8
    ISSN 1539-6924 ; 0272-4332
    ISSN (online) 1539-6924
    ISSN 0272-4332
    DOI 10.1111/risa.13795
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    In stock of ZB MED Cologne/Königswinter

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  5. Article: Downturn loss given default

    Calabrese, Raffaella

    European journal of operational research : EJOR Vol. 237, No. 1 , p. 271-277

    mixture distribution estimation

    2014  Volume 237, Issue 1, Page(s) 271–277

    Author's details Raffaella Calabrese
    Keywords Downturn LGD ; Mixture model ; EM algorithm ; Mixed random variable
    Language English
    Size graph. Darst.
    Publisher Elsevier
    Publishing place Amsterdam ; Boston, Mass ; London ; New York, NY ; Oxford ; Paris ; Philadelphia ; San Diego ; St. Louis
    Document type Article
    ZDB-ID 243003-4
    ISSN 0377-2217
    Database ECONomics Information System

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  6. Article: Estimating binary spatial autoregressive models for rare events

    Calabrese, Raffaella / Elkink, Johan A

    Spatial econometrics: qualitative and limited dependent variables , p. 145-166

    2017  , Page(s) 145–166

    Author's details Raffaella Calabrese and Johan A. Elkink
    Keywords Räumliche Statistik ; Probit-Modell ; Ausreißer
    Language English
    Publisher Emerald
    Publishing place Bingley
    Document type Article
    ISBN 978-1-78560-986-2 ; 1-78560-986-6
    Database ECONomics Information System

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    Inter-library loan at ZB MED

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  7. Book ; Online: Uniform correlation structure and convex stochastic ordering in the pólya urn scheme

    Calabrese, Raffaella

    (Working paper series / UCD Centre for Economic Research ; 2012/16)

    2012  

    Author's details Raffaella Calabrese
    Series title Working paper series / UCD Centre for Economic Research ; 2012/16
    Keywords pólya urn ; convex stochastic ordering ; uniform correlation
    Language English
    Size Online-Ressource (PDF-Datei: 10 S., 262,06 KB)
    Publisher UCD Centre for Economic Research
    Publishing place Dublin
    Document type Book ; Online
    Note IMD-Felder maschinell generiert
    Database ECONomics Information System

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  8. Book ; Online: Improving classifier performance assessment of credit scoring models

    Calabrese, Raffaella

    (Working paper series / UCD Centre for Economic Research ; 2012/04)

    2012  

    Author's details Raffaella Calabrese
    Series title Working paper series / UCD Centre for Economic Research ; 2012/04
    Keywords Misclassification Error Loss (MEL) ; Receiver Operating Characteristics (ROC) curve ; Area Under the Curve (AUC) ; Kreditrisiko ; Prognoseverfahren ; Monte-Carlo-Simulation ; Theorie
    Language English
    Size Online-Ressource (PDF-Datei: 22 S., 387,90 KB), graph. Darst.
    Publisher UCD Centre for Economic Research
    Publishing place Dublin
    Document type Book ; Online
    Note IMD-Felder maschinell generiert
    Database ECONomics Information System

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  9. Book ; Online: Regression model for proportions with probability masses at zero and one

    Calabrese, Raffaella

    (Working paper series / UCD Centre for Economic Research ; 2012/09)

    2012  

    Author's details Raffaella Calabrese
    Series title Working paper series / UCD Centre for Economic Research ; 2012/09
    Keywords proportions ; mixed random variable ; beta regression ; skewness ; heteroscedasticity
    Language English
    Size Online-Ressource (PDF-Datei: 13 S., 146,68 KB), graph. Darst.
    Publisher UCD Centre for Economic Research
    Publishing place Dublin
    Document type Book ; Online
    Note IMD-Felder maschinell generiert
    Database ECONomics Information System

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  10. Book ; Online: Modelling downturn loss given default

    Calabrese, Raffaella

    (Geary Institute working papers ; 2012/26)

    2012  

    Author's details Raffaella Calabrese
    Series title Geary Institute working papers ; 2012/26
    Keywords Downturn LGD ; Mixed random variable ; Mixture ; Beta density
    Language English
    Size Online-Ressource (12 S.), graph. Darst.
    Publisher UCD Geary Institute
    Publishing place Dublin
    Document type Book ; Online
    Note IMD-Felder maschinell generiert
    Database ECONomics Information System

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    Inter-library loan at ZB MED

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