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Mortality forecasting in a post-COVID world

Last week I presented at the Longevity 18 conference.  My topic was on robustifying stochastic mortality models when the calibrating data contain outliers, such as caused by the COVID-19 pandemic.  A copy of the presentation can be downloaded here, which is based on a paper to be presented at an IFoA sessional meeting in N

Written by: Stephen RichardsTags: mortality projections, coronavirus, outliers

Robust mortality forecasting for 2D age-period models

The covid-19 pandemic caused mortality shocks in many countries, and these shocks severely impact the standard forecasting models used by actuaries.  I previously showed how to robustify time-series models with a univariate index (Lee-Carter, APC) and those with a multivariate index (Cairns-Blake-Dowd, Ta

Written by: Stephen RichardsTags: outliers, coronavirus, forecasting, mortality projections

From magical thinking to statistical thinking

The Institute and Faculty of Actuaries in the UK has recently added mortality projection to its syllabus, so this year I have been teaching the subject for the first time to students at Heriot-Watt University.
Written by: Angus MacdonaldTags: mortality projections, deterministic models

All about the base(line)

When we first developed a technique for putting longevity trend risk into a 1-in-200 framework consistent with Solvency II, we sought to accommodate model risk by supporting a wide range of stochastic projection models.
Written by: Gavin RitchieTags: VaR, smoothing, mortality projections

Mortality by the book

Our book, Modelling Mortality with Actuarial Applications, will appear in Spring 2018.  I wrote the second of the three parts, where I describe the modelling and forecasting of aggregate mortality data, such as provided by the Office for National Statistics, the Human Mortality Database or indeed by any insurer whose own data is suitable.
Written by: Iain CurrieTags: GLM, mortality projections, R language

Reviewing forecasts

When making projections and forecasts, it can be instructive to compare them with what actually happened. In December 2002 the CMI published projections of mortality improvements that incorporated the so-called "cohort effect" (CMIB, 2002). These projections were in use by life offices and pension schemes in the United Kingdom from 2003 onwards.
Written by: Stephen RichardsTags: cohort effect, mortality projections, mortality improvements

Picking a winner

So what will the winner of the battle of the UK General Election be able to tell us about projection modelling? I'm not talking about the parties who will gain a share of power after May 7th, but which of the polling organisations will most closely forecast the results.
Written by: Ross AinslieTags: mortality projections, model risk

Simulating the Future

This blog has two aims: first, to describe how we go about simulation in the Projections Toolkit; second, to emphasize the important role a model has in determining the width of the confidence interval of the forecast.

Written by: Iain CurrieTags: simulation, mortality projections

Demography's dark matter: measuring cohort effects

My last blog generated quite a bit of interest so I thought I'd write again on cohorts. It's easy to (a) demonstrate the existence of a cohort effect and to (b) fit models with cohort terms, but not so easy to (c) interpret or forecast the fitted cohort coefficients. In this blog I'll fit the following three models:

Written by: Iain CurrieTags: cohort effect, APC, mortality projections

Forecasting with cohorts for a mature closed portfolio

At a previous seminar I discussed forecasting with the age-period-cohort (APC) model:

$$ \log \mu_{i,j} = \alpha_i + \kappa_j + \gamma_{j-i}$$

Written by: Iain CurrieTags: APC, mortality projections, cohort effect