Calibrating Credit Risk Dynamics in Private Infrastructure Debt

Blanc-Brude, Frédéric; Hasan, Majid; Whittaker, Timothy

doi:10.3905/jfi.2018.27.4.054

Cited by 10 publications

(8 citation statements)

References 13 publications

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“…There are two broad dichotomous groups of private companies, which can undertake PPP infrastructural projects. These are those who are effective and have the capability to lower costs and manage risks and on the other hand, those who cannot (Blanc-Brude, 2013). The dilemma of government is to determine which of the firms should be given the contract to undertake the work.…”

Section: Data Analysis and Discussionmentioning

confidence: 99%

“…Because of the long-term scope of PPP projects, accurate information on the existing, future and indirect costs of the works are obscured – this elevates the tendency for experiencing moral hazard and adverse (Blanc-Brude, 2013; Loben, 2009).…”

Section: Agency Theory and Pppsmentioning

confidence: 99%

“…When the risks and liability of cost overruns are not borne by the party constructing, low incentive to control costs is created (Blanc-Brude, 2013). The behaviour of the agent influences the incentive to control costs.…”

Section: Agency Theory and Pppsmentioning

confidence: 99%

“…The behaviour of the agent influences the incentive to control costs. However, the challenge of retrieving information about agents and the risks associated with long-term contracts can also present an obstacle to overcoming cost control problems (Blanc-Brude, 2013).…”

Section: Agency Theory and Pppsmentioning

confidence: 99%

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An empirical examination of moral hazards and adverse selection on PPP projects

Owusu‐Manu

Edwards

Kukah

et al. 2018

JEDT

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Purpose-Failures of Public-Private-Partnership (PPP) projects are often ascribed to the agency problem, which arise under conditions of inadequate and asymmetric information when a principal (the client) hires an agent (the contractor). This paper aims to identify the causes and effects of moral hazard and adverse selection on PPP construction projects using a synthesis of extant literature (to determine key variables) and analysis of survey questionnaire data collected. Design/Methodology/Approach-Mean score ranking was used to rank the causes and effects of moral hazard and adverse selection problems in PPP construction projects. One sample t-test was conducted to establish the relative significance of these variables. Findings-Effort dimensions (which are not verifiable), low transfer of risk, lack of accurate information about project conditions, wrong party chosen to execute project and renegotiation of contracts were the most significant causes of moral hazard and adverse selection problems in PPP construction projects. In addition, reduction of competition, high transaction costs, consequences on profitability of project, siphoning of funds and negative implications on enforceability of contract were the most significant effects of moral hazard and adverse selection problems in PPP construction projects. Originality/Value-Research findings provide guidance to construction stakeholders in the PPP sector on the different causes and effects of adverse selection and moral hazard. This pioneering study is the first to conduct an empirical assessment of the causes and effects of moral hazard and adverse selection of PPP construction projects in a developing country. Practical Implications-Application of these findings will help to mitigate moral hazard and adverse selection problems occurring when undertaking PPP construction projects.

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Section: Data Analysis and Discussionmentioning

confidence: 99%

Section: Agency Theory and Pppsmentioning

confidence: 99%

Section: Agency Theory and Pppsmentioning

confidence: 99%

Section: Agency Theory and Pppsmentioning

confidence: 99%

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An empirical examination of moral hazards and adverse selection on PPP projects

Owusu‐Manu

Edwards

Kukah

et al. 2018

JEDT

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“…donde, DP es la probabilidad de incumplimiento, LGD es la pérdida dado el incumplimiento y EAD la exposición al incumplimiento. Cabe resaltar que gran parte de los desarrollos teóricos se han enfocado en la estimación del primer componente, es decir, la DP, en este campo los modelos estructurales han ofrecido una ventaja considerable (ver Freydefornt, 2001;Aragones, Blanco & Iniesta, 2009;Blanck-Brude & Hasan, 2016;Blanc-Brude, Hasan & Whittaker, 2018). Sin embargo, los demás componentes de estimación de la EL, pueden tener limitaciones que son importantes y merecen una atención especial.…”

Section: Riesgo De Crédito Y Modelos Estructurales De Estimaciónunclassified

Probabilidad de incumplimiento en inversiones de infraestructura: análisis a partir de modelos estructurales de riesgo de crédito

Quimbayo

2020

RMCE

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Este trabajo tiene como objetivo estimar las probabilidades de incumplimiento en proyectos de infraestructura. Para ello, se analiza la exposición que tienen los prestamistas frente a un estado de incumplimiento. Esta aplicación se realiza al asumir dinámica propia del ratio de cobertura del servicio de la deuda (DSCR) y el perfil de pago determinado por el flujo de efectivo disponible del proyecto, donde estos se modelan estocásticamente siguiendo los mismos supuestos de la teoría de valoración de opciones desarrollado por Black y Scholes (1973) y Merton (1973). De esta forma, mediante la adaptación de modelos estructurales desarrollados para activos ilíquidos, como extensión de los modelos de riesgo de crédito de Merton (1974) y KMV de Moody’s, se analizan los componentes de probabilidad, exposición y pérdidas de los prestamistas en escenarios de incumplimiento.

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Future outlook and challenges

Li¹,

Wei²

2023

Time-Dependent Reliability Theory and Its Applications

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Calibrating Credit Risk Dynamics in Private Infrastructure Debt

Cited by 10 publications

References 13 publications

An empirical examination of moral hazards and adverse selection on PPP projects

An empirical examination of moral hazards and adverse selection on PPP projects

Probabilidad de incumplimiento en inversiones de infraestructura: análisis a partir de modelos estructurales de riesgo de crédito

Future outlook and challenges

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