Survival analysis is a popular research tool in medicine and demography. It has been used for many years to study the duration of socio-economic phenomena. The aim of this article is to evaluate the relationship between the coefficients of the proportional hazards model (PH) and the accelerated...

This paper uses survival analysis as a tool to assess credit risk in loan portfolios within the framework of the Basel Internal Ratings-Based (IRB) approach. By modeling the time to default using survival functions, the methodology allows for the estimation of default probabilities and the...

This article estimates the impact of a policy change on an event probability in a difference-in-differences hazard model using four estimators. We examine the error distributions of the estimators via a simulation experiment with twelve different scenarios. In four simulation scenarios when all...

This paper delves into the intricate dynamics of the likelihood of merger and acquisition (M&A) completion in China and scrutinizes the influence of global and domestic economic conditions through survival analysis. By utilizing data from 3227 domestic M&A transactions from 1998 to 2024, this...

Predictions of the individual unemployment duration will allow to distribute target support while searching for a job more effectively. The paper uses survival models to predict the unemployment duration based on data from Russian employment centers in 2017-2021. The dataset includes...

Survival models have become popular for credit risk estimation. Most current credit risk survival models use an underlying linear model. This is beneficial in terms of interpretability but is restrictive for real-life applications since it cannot discover hidden nonlinearities and interactions...

The age at which women become mothers for the first time is ever increasing in many industrialized countries. Therefore, fertility determinants that might deteriorate with age, such as health, and their effect on reproductive patterns, should be given more attention. We explore the effect of the...

In econometrics, Autoregressive Conditional Duration (ACD) models use high-frequency economic or financial duration data, which mostly exhibit irregular time intervals. The ACD model is widely used to examine the duration of transaction volume and duration of price variations in stock markets....

Survival analysis or duration modelling is a widely applied statistical method for estimating the expected time until a specific event of interest occurs. In recent decades, this method has garnered significant attention within the field of social sciences, particularly in economic-based...

Sanctions are a recurrent issue on the international scene that has gained relevance in recent decades. This article intends to approach this matter in an innovative way by analyzing the relative importance of sanctions' types and objectives, besides target countries' characteristics, on...

One of the key decisions in execution strategies is the choice between a passive (liquidity providing) or an aggressive (liquidity taking) order to execute a trade in a limit order book (LOB). Essential to this choice is the fill probability of a passive limit order placed in the LOB. This paper...

A vast majority of Loss Given Default (LGD) models are currently in use. Over all the years since the new Capital Accord was published in June 2004, there has been increasing interest in the modelling of the LGD parameter on the part of both academics and practitioners. The main purpose of this...

This paper investigates duration dynamics in Borsa ̇Istanbul (BIST) stock exchange via Autoregressive Conditional Duration (ACD) model applied on time observed between consecutive trades. Investigation of a suitable error term specification reveals that Weibull ACD (WACD) model is the most...

IPO information disclosures such as the strategic uses of IPO proceeds and the time frame to utilize them have the potential to signal the listing companies’ post-IPO survival. We examine the role of the IPO proceeds on 423 companies’ survival in the Malaysian market from 2000 to 2014. Using...

In biomedical research, challenges to working with multiple events are often observed while dealing with time-to-event data. Studies on prolonged survival duration are prone to having numerous possibilities. In studies on prolonged survival, patients might die of other causes. Sometimes in the...

Current demographic changes require greater participation of people aged 50 or older in the labour market. Previous research shows that the chances of returning to employment decrease with the length of the unemployment period. In the case of older people who have not reached the statutory...

Analyzing survival (life-testing) data and drawing inferences about them is a part of engineering and health sciences. So far, various statistical tools, e.g., survival (reliability) function (s f ), probability density function (pd f ), and hazard rate function (HR) were available among...

Many panel data methods, while allowing for general dependence between covariates and time-invariant agent-specific heterogeneity, place strong a priori restrictions on feedback: how past outcomes, covariates, and heterogeneity map into future covariate levels. Ruling out feedback entirely, as...

We give a thorough analytic characterization of a large class of sticky-price models where the firm’s price setting behavior is described by a generalized hazard function. Such a function provides a tractable description of the firm’s price setting behavior and allows for a vast variety of...

This paper explores the effect of financial development on the duration of economic recoveries, considering a sample of 414 economic recoveries observed in 67 countries during the period 1989-2019. We define the duration of economic recovery, as the time it takes the economy to return to its...

The goal of this paper is to provide a framework for understanding the appropriate time horizons for certain asset classes by quantifying their specific duration. We then use that duration framework to apply an asset-liability matching methodology across all time horizons with the goal of...

This paper proposes a causal decomposition framework for settings in which an initial regime randomization influences the timing of a treatment duration. The initial randomization and treatment affect in turn a duration outcome of interest. Our empirical application considers the survival of...

Customer relationship management and marketing analytics have become critical for nonlife insurers operating in highly competitive markets. As it is easier to develop an existing customer than to acquire a new one, cross-selling and retention are key activities. In this research, we focus on...

This paper proposes a causal decomposition framework for settings in which an initial regime randomization influences the timing of a treatment duration. The initial randomization and treatment affect in turn a duration outcome of interest. Our empirical application considers the survival of...

The Reserve Bank of India has put 11 public sector banks under prompt corrective action and is planning to put three more where public sector banks constitute 68.9% of the total asset of the Indian banking industry based on 2018 figures; this raises a genuine concern for the financial health of...