We assess whether climate transition risk is priced in Europe's equity market by analysing relative equity returns of high versus low CO2-emitting firms. We use a panel data set covering firm-specific carbon emissions of 1,555 European companies over the period 2005-2019. We add to the existing...

We calculate the social cost of carbon (SCC) under stochastic climate volatility resulting from uncertainty about future climate risk regimes where weather extremes are becoming more frequent and intense. Using a stochastic dynamic integrated climate-economy model where representative agents are...

This paper examines the asymmetric impact of economic policy uncertainty (EPU) and oil price uncertainty (OPU) on inflation by using a Nonlinear ARDL (NARDL) model, which is compared to a benchmark linear ARDL one. Using monthly data from the 1990s until August 2022 for a number of developed and...

This paper uses the endogenous regime switching model with dynamic feedback and interactions developed by Chang et al. (2023) to estimate global food price mean and volatility indicators, the latter measuring uncertainty and risk in the global food market. Both are then included in structural...

This paper examines the impact of transition and physical climate risk on stock markets using, for the first time in this context, the annual CCPI index calculated by Germanwatch as well as its components (in addition to a wide range of other indices) for 48 countries from 2007 to 2023....

We develop a multivariate unobserved components model to extract business cycle and financial cycle indicators from a panel of economic and financial time series of four large developed economies. Our model is flexible and allows for the inclusion of cycle components in different selections of...

We propose a novel multivariate GARCH model that incorporates realized measures for the variance matrix of returns. The key novelty is the joint formulation of a multivariate dynamic model for outer-products of returns, realized variances and realized covariances. The updating of the variance...

This paper discusses identification, specification, estimation and forecasting for a general class of periodic unobserved components time series models with stochastic trend, seasonal and cycle components. Convenient state space formulations are introduced for exact maximum likelihood...

We model panel data of crime careers of juveniles from a Dutch Judicial Juvenile Institution. The data are decomposed into a systematic and an individual-specific component, of which the systematic component reflects the general time-varying conditions including the criminological climate....

We present new results for the likelihood-based analysis of the dynamic factor model that possibly includes intercepts and explanatory variables. The latent factors are modelled by stochastic processes. The idiosyncratic disturbances are specified as autoregressive processes with mutually...