This paper investigates some common determinants of default probability changes ofindividual firms using Standard & Poor's ratings database. We analyze and quantify the re-sponses of hazard rates to changes in various economic variables, namely financial markets,business cycle and credit...

In credit default prediction models, the need to deal with time-varying covariates often arises. For instance, in the context of corporate default prediction a typical approach is to estimate a hazard model by regressing the hazard rate on time-varying covariates like balance sheet or stock...

The time-continuous discrete-state Markov process is a model for rating transitions. One parameter, namely the intensity to migrate to an adjacent rating state, implies an ordinal rating to have an intuitive metric. State-specific intensities generalize the state-stationarity. Observing Markov...

Little empirical evidence provides insight in person-oriented drivers of business survival and success of small business owners. In this paper I perform a duration analysis of business survival amongst young white (selfemployed) small business owners in the U.S. Compulsory exits are...

This paper addresses two issues encountered in the empirical financial distress literature: a-theoretical treatment of leverage and product-market competition as predictors of financial distress hazard; and lack of attention to frailty as a potential source of bias in reported estimates. We...

We estimate the causal impact of restructuring aid granted by the European Commission between 2003 and 2012 on the survival and financial viability of aided firms. Using a comprehensive dataset we find that restructuring aid increases a firm's average survival time by 8 to 15 years and decreases...

We model credit rating histories as continuous-time discrete-state Markov processes. Infrequent monitoring of the debtors' solvency will result in erroneous observations of the rating transition times, and consequently in biased parameter estimates. We develop a score test against such...

Using a local adaptive Forward Intensities Approach (FIA) we investigate multiperiod corporate defaults and other delisting schemes. The proposed approach is fully datadriven and is based on local adaptive estimation and the selection of optimal estimation windows. Time-dependent model...