We solve a portfolio choice problem that includes mortality-contingent claims and labor income under general HARA preferences. Our contribution beyond existing literature is to (i) focus on the covariance between shocks to human capital and financial capital, to (ii) model the utility of a family with basic needs and (iii) include life insurance and pension annuity claims in one unified life-cycle model. Our solution employs a “similarity reduction” mapping which reduces the two-dimensional HJB equation into one dimension. This allows for the implementation of a quick numerical scheme. And, when shocks to human capital and financial capital are perfectly correlated, a closed-form expression is obtained as a special case.

We determine the optimal lifecycle purchasing strategy for deferred income annuities (DIAs)—which are distinct from single-premium income annuities (SPIAs)—for an individual who wishes to maximize the expected utility of his/her annuity income at a fixed time in the future. In contrast to the vast portfolio-choice literature for SPIAs, we focus on the stochasticity of the DIA’s payout yield and address concerns that rates are currently “too low” to justify irreversible annuitization. We assume a mean-reverting model for payout yields and show that a risk-neutral consumer who wishes to maximize his/her expected retirement income should wait until yields reach a threshold—which lies above historical averages—and then purchase the DIA in one lump sum. In contrast, a risk-averse consumer who is concerned the payout yield will remain below average for an extended period and worries about losing mortality credits while waiting, should employ a barrier purchasing strategy, as in the portfolio choice problem under transaction costs. We illustrate how this insight is applied in the context of annuitization. In fact, the optimal behavior of a risk-averse consumer resembles an asymmetric dollar-cost averaging strategy, with a portion of the DIA-budget spent even while payout rates are below historical averages. As part of our analysis we offer an easy-to-use asymptotic approximation for the optimal purchasing strategy (threshold) and provide some numerical examples to illustrate the concept.