Essays on Forecasting Life Expectancy and Fiscal Sustainability

Abstract

This thesis covers three broad objectives. Firstly, we extend an existing popular mortality model to improve forecasts of life expectancy rates. Secondly, we use the improved demographic projections as inputs and show that it is capable of enhancing the performance of term spread in generating forecasts of GDP growth rates. Lastly, as mortality changes directly affect fiscal sustainability, we use the improved demographic projections to examine the fiscal impacts of population ageing in Singapore.

The Lee-Carter (LC) model is a popular model but being a simple model, it assumes homoskedasticity. We value-add to the existing literature by relaxing this assumption. Essay one first extends the classical LC model with GARCH-type structures to allow for volatility clustering in its time-varying component. This allows us to model the presence of conditional volatility in mortality rates. Next, the model is extended with time-varying multivariate GARCH models to account for the presence of conditional correlations between the male and female mortality series. We show that modeling both the presence of conditional volatility and correlations offer the greatest improvements to forecasts of life expectancy at birth and at retirement age.

Term spread has been commonly used to forecast GDP growth rates but evidences of its forecasting ability have been mixed across countries and overtime. There are also signs that its forecasting ability has declined over the years. In essay two, we seek to examine both the relevance of term spread as well as the contributions of mortality indexes in forecasting GDP growth rates. We first use multivariate GARCH models to investigate the evidence of conditional correlations between GDP growth rates, term spreads and mortality indexes, which has not been attempted in the literature. Next, we show that including the use of conditional volatility of male mortality indexes, together with term spreads, helps to improve forecasts of GDP growth rates. This finding supports that the improved demographic forecasts in essay one using LC method extended with multivariate GARCH model has important and useful implications towards macroeconomic forecasting.

Demographic changes produce direct and significant effects on fiscal sustainability and with a rapidly ageing population in Singapore, the demographic shift caused by a shrinking working age group and smaller income tax base is expected to impose increasingly important fiscal implications. In order to derive an accurate assessment of future fiscal burdens brought about by demographic pressures, it is important to have accurate projections of future population changes. Using the methodology of stochastic demographic projections obtained from the LC method extended with time-varying multivariate GARCH model in essay one, we project how the population ageing problem is expected to worsen in Singapore and how it will impact the government fiscal position over the next twenty years. In addition to the case of pure demographic effects, we also included several calibration analysis to account for an increase in immigration figures, an extension of retirement age, an increase in female labor force participation rates, and an increase in labor force productivity rates. The calibration results supports that the rate of decline in the fiscal support ratio under the baseline scenario will be moderated with higher immigrant inflow, extended retirement age, larger female labor force and higher labor force participation rates.