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CMI Afternoon Seminar: Grouped functional time series forecasting method for multiple sub-populations

The HBS builiding
Dates:29 May 2018
Times:15:00 - 16:30
What is it:Seminar
Organiser:School of Social Sciences
Who is it for:University staff, Adults, Alumni, Current University students, General public
Speaker:Associate Professor Han Lin Shang
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  • By School of Social Sciences

Associate Professor Han Lin Shang, Associate Professor of Statistics, Australian National University

Abstract: Age-specific mortality rates are often disaggregated by different attributes, such as sex, state, ethnic group, education and socioeconomic status. Forecasting age-specific mortality rates at the national and sub-national levels play a vital role in developing social policy and pricing annuity. However, the independent mortality forecasts at the sub-national levels may not add up to the forecasts at the national level. Further, the independent forecasts may not utilize correlation among sub-populations to improve forecast accuracy. To address these two issues, we modify and extend the grouped univariate functional time series to grouped multivariate functional time series forecasting. For quantifying forecast uncertainty, we utilize a nonparametric bootstrap method to reconcile interval forecasts. Using the regional age-specific mortality rates in Japan obtained from the Japanese Mortality Database (2018), we investigate the one-step-ahead to 15- step-ahead forecast accuracy among the independent and grouped univariate and multivariate functional time series forecasting methods. The grouped multivariate functional time series forecasting methods are not only shown to be useful for reconciling forecasts of age-specific mortality rates at national and sub-national levels, but they also use multivariate functional principal component regression to jointly model sub-populations and enjoy potentially improved forecast accuracy averaged over different disaggregation factors. The improved forecast accuracy of mortality rates is of great interest to the insurance and pension industries for estimating annuity prices, in particular at the level of population sub-groups, defined by critical factors such as sex, region, and socioeconomic grouping.

Tea/coffee and cakes from 2.45.

Join us for this event, which is part of the CMI Afternoon Seminar Series. All welcome. No registration necessary.

The Cathie Marsh Institute for Social Research (CMI) provides a focal point at The University of Manchester for the application of quantitative methods in interdisciplinary social science research in order to generate a world class research environment.

Speaker

Associate Professor Han Lin Shang

Role: Associate Professor of Statistics

Organisation: Australian National University

  • https://researchers.anu.edu.au/researchers/shang-h

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CMI Seminar Room, 2.07
Humanities Bridgeford Street
Manchester

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Dr Sarah King-Hele

0161 275 0279

sarah.king-hele@manchester.ac.uk

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