Katja Hanewald

Explaining Mortality Dynamics: The Role of Macroeconomic Fluctuations and Cause of Death Trends

Abstract Using data for six OECD countries over the period 1950–2006, this paper studies the impact of macroeconomic fluctuations and cause of death trends on mortality dynamics in the Lee-Carter mortality forecasting model. The key results of this study are the following: (1) Periods can be identified in which the Lee-Carter mortality index kt correlates significantly with macroeconomic fluctuations. (2) A few causes of death such as diseases of the circulatory system, influenza and pneumonia, and diabetes mellitus account for a large fraction of the variations in the Lee-Carter mortality index kt . (3) Most cause-specific mortality rates show pronounced trends over the last few decades. These trends change the composition of deaths and alter how total mortality reacts to external factors such as macroeconomic fluctuations.

Stochastic Mortality, Macroeconomic Risks, and Life Insurer Solvency

Motivated by a recent demographic study establishing a link between macroeconomic fluctuations and the mortality index kt in the Lee-Carter model, we assess the impact of macroeconomic fluctuations on the solvency of a life insurance company. Liabilities in our stochastic simulation framework are driven by a GDP-linked variant of the Lee-Carter mortality model. Furthermore, interest rates and stock prices react to changes in GDP, which itself is modeled as a stochastic process. Our results show that insolvency probabilities are significantly higher when the reaction of mortality rates to changes in GDP is incorporated.

Developing Equity Release Markets: Risk Analysis for Reverse Mortgages and Home Reversions

Equity release products are sorely needed in an aging population with high levels of home ownership. There has been a growing literature analyzing risk components and capital adequacy of reverse mortgages in recent years. However, little research has been done on the risk analysis of other equity release products, such as home reversion contracts. This is partly due to the dominance of reverse mortgage products in equity release markets worldwide. In this article we compare cash flows and risk profiles from the providers perspective for reverse mortgage and home reversion contracts. An at-home/in long-term care split termination model is employed to calculate termination rates, and a vector autoregressive (VAR) model is used to depict the joint dynamics of economic variables including interest rates, house prices, and rental yields. We derive stochastic discount factors from the no arbitrage condition and price the no negative equity guarantee in reverse mortgages and the lease for life agreement in the home reversion plan accordingly. We compare expected payoffs and assess riskiness of these two equity release products via commonly used risk measures: Value-at-Risk (VaR) and Conditional Value-at-Risk (CVaR).

Stochastic mortality, subjective survival expectations, and individual saving behavior

Theoretical studies suggest that unexpected changes in future mortality and survival probabilities (stochastic mortality) are important determinants of individuals’ decisions about consumption, saving, asset allocation, and retirement timing. Using data on subjective survival expectations elicited in the Survey of Health, Ageing and Retirement in Europe (SHARE) and corresponding life table data from the Human Mortality Database (HMD), we find evidence of respondents’ awareness of stochastic mortality. We also find that respondents’ saving behavior is influenced by stochastic mortality perceptions.

Risk Management and Payout Design of Reverse Mortgages

We analyze the risk and profitability of reverse mortgages with lump-sum or income stream payments from the lenders perspective. Reverse mortgage cash flows and loan balances are modeled in a multi-period stochastic framework that allows for house price risk, interest rate risk and risk of delayed loan termination. A VAR model is used to simulate economic scenarios and to derive stochastic discount factors for pricing the no negative equity guarantee embedded in reverse mortgage contracts. Our results show that lump-sum reverse mortgages are more profitable and require less risk-based capital than income stream reverse mortgages, which explains why this product design dominates in most markets. The loan-to-value ratio, the borrowers age, mortality improvements and the lenders financing structure are shown to be important drivers of the profitability and riskiness of reverse mortgages, but changes in these parameters do not change the main conclusions.

Postcode-Level House Price Models for Banking and Insurance Applications†

This article develops and compares residential property price models required for banking and insurance applications including pricing, risk management and portfolio management. Our study is based on postcode‐level house prices for Sydney over the period 01–1979 to 03–2011. The estimation results of single‐factor panel data models show that the market‐wide house price index explains between 42 per cent and 44 per cent of the longitudinal and cross‐sectional variation in postcode‐level house price growth rates. Macroeconomic and financial variables, as well as geographic and sociodemographic postcode characteristics are confirmed as important factors for pricing and risk management of products exposed to house price risk.

Portfolio Choice in Retirement - What is the Optimal Home Equity Release Product?

We study the optimal product choice of home equity release products from the homeowner’s perspective in the presence of longevity, long-term care, house price, and interest rate risk. The individual can choose to buy annuities, long-term care insurance, and release home equity using reverse mortgages or home reversion plans. The individual enjoys utility gains from having access to either one of the two equity release products. Higher utility gains are found for the reverse mortgage as its product features allow for higher lump-sum payouts. When given a timing choice, the individual chooses to unlock home equity early in retirement. These key results emerge consistently across a range of cases with different parameter values. The availability of a government-provided LTCI does not change the use of equity release products significantly, but does change the demand for annuities.

Risk Analysis for Reverse Mortgages with Different Payout Designs

Abstract We analyze the risk and profitability of reverse mortgages with lump-sum or income stream payments from the lender’s perspective. Reverse mortgage cash flows and loan balances are modeled in a multi-period stochastic framework that allows for house price risk, interest rate risk and risk of delayed loan termination. A vector autoregressive (VAR) model is used to simulate economic scenarios and to derive stochastic discount factors for pricing the no negative equity guarantee embedded in reverse mortgage contracts. Our results show that lump-sum reverse mortgages are more profitable and require less risk-based capital than income stream reverse mortgages, which explains why this product design dominates in most markets. The loan-to-value ratio, the borrower’s age, mortality improvements and the lender’s financing structure are shown to be important drivers of the profitability and riskiness of reverse mortgages, but changes in these parameters do not change the main conclusions.

Risk Management in Retirement – What is the Optimal Home Equity Release Product?

We study the optimal product choice of home equity release products from the homeowner’s perspective in the presence of longevity, long-term care, house price, and interest rate risk. The individual can choose to buy annuities, long-term care insurance, and release home equity using reverse mortgages or home reversion plans. The individual enjoys utility gains from having access to either one of the two equity release products. Higher utility gains are found for the reverse mortgage as its product features allow for higher lump-sum payouts. When given a timing choice, the individual chooses to unlock home equity early in retirement. These key results emerge consistently across a range of cases with different parameter values. The availability of a government-provided LTCI does not change the use of equity release products significantly, but does change the demand for annuities.

Disaggregated House Price Indices

This paper estimates and compares methods of constructing disaggregated house price indices from existing house price models using individual sales data for Sydney. Nine alternative house price models are selected to cover the most frequently used methods in the literature: the mean model, median models (standard and stratified), hedonic models (restricted and unrestricted hedonic), repeat-sales models (age-adjusted and Case-Shiller weighted), and a hybrid of the hedonic and repeat-sales model. The unrestricted hedonic model and the hybrid model have an advantage over the other seven models in that they do not require stratification of the data for estimating disaggregated indices. Both models employ the whole sample to estimate implicit prices of house characteristics that are used to construct disaggregated house price indices. These two models eliminate variability arising from small sample sizes and provide more efficient estimates of house price heterogeneity. In addition, house characteristics that are important drivers of the variability of individual house prices are identified in the two models. Disaggregated indices constructed from these two models provide more accurate comparisons with an aggregate house price index. We quantify the extent to which disaggregated house prices indices have significantly more variability than, and differing trends from, the aggregate index.