Forecasting Mortality Indexes Allowing for Economic Growth Dependence
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Objectives: In this study, we introduce a new forecasting methodology for future mortality rate to capture the long-run dynamics between mortality rates and economic variables, including real gross domestic product (GDP) and real GDP per capita. Methods: Using mortality data for South Korean males and females, we show the presence of long-run equilibrium relationships between macroeconomic variables and mortality rates, by implementing the Johansen cointegration methodology. Then their dynamics is modeled by using vector error correction models (VECMs). Results: The VECM forecasts show the significant impact of including economic variables on forecasting future mortality, compared with the forecasts obtained by a model with no economic factors, i.e., a random walk with drift. Conclusions: Our framework provides a methodology to model the dynamics of mortality rate in consideration of economic variables.
Abstract
Objectives: In this study, we introduce a new forecasting methodology for future mortality rate to capture the long-run dynamics between mortality rates and economic variables, including real gross domestic product (GDP) and real GDP per capita. Methods: Using mortality data for South Korean males and females, we show the presence of long-run equilibrium relationships between macroeconomic variables and mortality rates, by implementing the Johansen cointegration methodology. Then their dynamics is modeled by using vector error correction models (VECMs). Results: The VECM forecasts show the significant impact of including economic variables on forecasting future mortality, compared with the forecasts obtained by a model with no economic factors, i.e., a random walk with drift. Conclusions: Our framework provides a methodology to model the dynamics of mortality rate in consideration of economic variables.
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