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The purpose of this paper is to address the issues of correlated events and individual heterogeneity in multiple best management practices (BMPs) adoption.

The authors used survey data collected from broiler producers in Louisiana, USA. The authors estimated several duration models that either considered event dependence or heterogeneity or both.

Results from the conditional frailty model indicated that large farms adopt BMPs earlier, farmers who have been in broiler farming profession for a long time are late to adopt BMPs and more informed farmers, through contact with extension agents and education, are early adopters of BMPs.

The limitation of this study is that the authors did not validate the robustness of the conditional frailty model using a more rigorous approach, such as empirical simulation method.

Many farmers do not adopt a new technology immediately after it becomes available. Duration models help to understand why farmers wait and how long they wait before adopting a new technology. In case of correlated events, where farmers adopt more than one technology, it is important to know the driving factors behind multiple technologies adoption. The findings from this study should help to properly target farmers to increase the adoption rate of a desired BMP.

This is the first study in agriculture technology adoption literature that uses a conditional frailty model to understand why farmers wait to adopt a new technology. This study also addresses both dependence in BMP adoption and heterogeneity in farmers’ quality that impact technology adoption.

Survival (default) data are frequently encountered in financial (especially credit risk), medical, educational, and other fields, where the “default” can be interpreted as the failure to fulfill debt payments of a specific company or the death of a patient in a medical study or the inability to pass some educational tests.

This paper introduces the basic ideas of Cox's original proportional model for the hazard rates and extends the model within a general framework of statistical data mining procedures. By employing regularization, basis expansion, boosting, bagging, Markov chain Monte Carlo (MCMC) and many other tools, we effectively calibrate a large and flexible class of proportional hazard models.

The proposed methods have important applications in the setting of credit risk. For example, the model for the default correlation through regularization can be used to price credit basket products, and the frailty factor models can explain the contagion effects in the defaults of multiple firms in the credit market.

This paper aims to provide an overview, a classification of existing research groups for correlated default models using a reduced-form method and an identification of future research opportunities in the field.

A systematic literature review is used for the identification, selection, evaluation and synthesis of relevant literature using keywords regarding the reduced-form default models in the Web of Science database. The authors also add articles from cross-referencing and expert recommendations to the literature. HistCite^™ program is used to generate a citation map of the literature.

The results show that reduced-form correlated default risk models are developing towards modelling credit risk with both observable and unobservable variables. The frailty correlated default model at the firm level is still a potential research field.

This is the first paper systematically reviewing the research on reduced-form models of default timing.

The purpose of this study is to employ a duration-based approach to model the inter-arrival times of bank failures in the US banking system for the period of 1934-2014, in line with the suggestions of Focardi and Fabozzi (2005), who used a similar model for explaining contagion in credit portfolios.

Conditional duration models that allow duration between bank failures to depend linearly or nonlinearly on its past history are estimated and evaluated.

The authors find evidence of strong persistence along with nonmonotonic hazard rates, which imply a financial contagion pattern, according to which a high frequency of bank failures generates turbulence, which shortly after leads to additional fails, whereas prolonged periods without abnormal events signify the absence of contagious dependence, which increases the relative periods between bank failure appearance. Further, the authors obtain statistically significant results when they allow duration to depend linearly on past information variables that capture systemic bank crisis factors along with stock and bond market effects.

The originality of this study consists in proposing a new time series approach for the prediction of bank probability of default by incorporating a default-risk contagion mechanism. As contagious bank failures are a key topic in macroprudential supervision, this study could be of value for supervisory authorities in setting pro-active actions and tightening regulatory measures.

This article examines the impact of different policy instruments on livestock farmers' willingness to recycle manure. The results shed light on the optimal policy combination.

A game theoretical framework is constructed to illustrate farmers' optimal strategies under different policies. Theoretical results are empirically tested by survey data from beef cattle farmers in Central China.

Empirical results show that penalties work better than subsidies if each type of policy is implemented separately. The authors also find a positive interaction between subsidy and penalty policies, suggesting that a combination of subsidy and penalty policies produces the best outcome in incentivizing livestock farmers to recycle manure. Furthermore, planting and breeding simultaneously have the strongest effect on increasing livestock farmers' willingness to recycle manure, suggesting that the combination of planting and breeding can be an optimal strategy for manure management.

This study is based on firsthand survey data and provides new evidence on the effectiveness of alternative environmental policies on manure recycling.

We propose a generic algorithm for numerically accurate likelihood evaluation of a broad class of spatial models characterized by a high-dimensional latent Gaussian process and non-Gaussian response variables. The class of models under consideration includes specifications for discrete choices, event counts and limited-dependent variables (truncation, censoring, and sample selection) among others. Our algorithm relies upon a novel implementation of efficient importance sampling (EIS) specifically designed to exploit typical sparsity of high-dimensional spatial precision (or covariance) matrices. It is numerically very accurate and computationally feasible even for very high-dimensional latent processes. Thus, maximum likelihood (ML) estimation of high-dimensional non-Gaussian spatial models, hitherto considered to be computationally prohibitive, becomes feasible. We illustrate our approach with ML estimation of a spatial probit for US presidential voting decisions and spatial count data models (Poisson and Negbin) for firm location choices.

The administration of social assistance benefits is devolved to local agencies in Belgium, which raises questions about how much variation in spell lengths of benefit receipt is associated with differences across agencies. We address this issue by analysing the monthly hazard of benefit exit using administrative record data for 14,270 individuals in 574 welfare agencies. Our random-effects model allows for differences in both the observed and unobserved characteristics of beneficiaries and of local agencies. There are large differences in median benefit duration for individuals serviced by different welfare agencies: the range is from two months to more than 24 months. We find strong associations between beneficiary characteristics (sex, age, foreign nationality, citizenship acquisition, work history and being a student) and spell length. The estimates show higher odds of exiting social assistance receipt in bigger municipalities and in agencies which provide more generous supplementary assistance, and also strong evidence of shorter episodes in agencies where active labour market programme participation rates are higher.

The purpose of this paper is to examine the effect employed friends have on the probability of exiting unemployment of an unemployed worker according to his/her educational (skill) level.

In common with studies on unemployment duration, this paper uses a discrete-time hazard model.

The paper finds that the conditional probability of finding work is between 24 and 34 per cent higher per period for each additional employed friend for job seekers with intermediate skills.

These results are of interest since they suggest that the reach of national employment agencies could extend beyond individuals in direct contact with first-line employment support bureaus.

Because of the lack of appropriate longitudinal information, the majority of empirical studies in the area assess the influence of social networks on employment status using proxy measures of social interactions. The current study contributes to the very limited empirical literature of the influence of social networks on job attainment using direct measures of social structures.

There is a long period from completing studies to finding a permanent or temporary (but at least satisfactory) job in all European countries, especially in Mediterranean countries, including Italy. This paper aims to study the determinants of this duration and measure them, for the first time in a systematic way, in the case of Italy.

This paper provides several measures of duration, including education level and other criteria. Furthermore, it attempts to identify the main determinants of the long Italian transition, both at a macroeconomic and an individual level. It tests for omitted heterogeneity of those who are stuck at this important crossroads in their life within the context of parametric survival models.

The average duration of the school-to-work transition for young people aged 18–34 years was 2.88 years (or 34.56 months) in 2017. A shorter duration was found for the highly educated; they found a job on average 46 months earlier than those with compulsory education. At a macroeconomic level, the duration over the years 2004–2017 was inversely related to spending in the labour market policy and in education, gross domestic product growth and the degree of trade union density; however, it was directly related to the proportion of temporary contracts. At the individual level, being a woman, a migrant or living in a densely populated area in the South are the risk factors for remaining stuck in the transition. After correcting for omitted heterogeneity, there is clear evidence of positive duration dependence.

Positive duration dependence suggests that focusing on education and labour policy, rather than labour flexibility, is the best way to smooth the transition.

This study develops our understanding of the Italian school-to-work transition regime by providing new and detailed evidence of its duration and by studying its determinants.

We study the implications of ownership and its induced incentives on firm survival on the stock market for young and high‐tech firms. Using a unique data set of all 341 firms listed on the Neuer Markt, the German equivalent of the NASDAQ, our results differ from studies on more traditional firms. Ownership by CEOs has no influence on firm survival when introducing measurements of human capital and intellectual property rights. This confirms assumptions that firms in the knowledge based industries differ in their governance structure from traditional firms.