Mortality is different across countries, states and regions. Several empirical research works however reveal that mortality trends exhibit a common pattern and show similar structures across populations. The key element in analyzing mortality rate is a time-varying indicator curve. Our main...

This paper explores and develops alternative statistical representations and estimation approaches for dynamic mortality models. The framework we adopt is to reinterpret popular mortality models such as the Lee-Carter class of models in a general state-space modelling methodology, which allows...

This article discusses Windle and Carvalho's (2014) state-space model for observations and latent variables in the space of positive symmetric matrices. The present discussion focuses on the model specification and on the contribution to the positive-value time series literature. I apply the...

We present a detailed methodological study of the application of the modified profile likelihood method for the calibration of nonlinear financial models characterised by a large number of parameters. We apply the general approach to the Log-Periodic Power Law Singularity (LPPLS) model of...

Functional time series and high-dimensional scalar predictors frequently arise ina wide range of modern economic and business applications, which require statisticalmodels that can simultaneously handle the temporal and causal dependence that areprevalent in large sets of mixed-type data. We...

This paper studies the SEIRD epidemic model for COVID-19. First, I show that the model is poorly identified from the observed number of deaths and confirmed cases. There are many sets of parameters that are observationally equivalent in the short run but lead to markedly different long run...

Statistical methods that shrink parameters towards zero can produce lower predictive variance than does maximum likelihood. This paper discusses an approach to doing this for age-period-cohort models, and applies it to fitting opioid mortality rates with a generalization of the Lee-Carter model...

This note examines general variance-covariance structures for the specific effects and the overall error term in a two-way error component (EC) model. So far panel data literature has considered these general structures in a one-way model and followed the approach of a Cholesky-type...

We review the literature on robust Bayesian analysis as a tool for global sensitivity analysis and for statistical decision-making under ambiguity. We discuss the methods proposed in the literature, including the different ways of constructing the set of priors that are the key input of the...

We provide a methodology for testing a polynomial model hypothesis by extending the approach and results of Baek, Cho, and Phillips (2015; Journal of Econometrics; BCP) that tests for neglected nonlinearity using power transforms of regressors against arbitrary nonlinearity. We examine and...