Solving Consumption and Portfolio Choice Problems: The State Variable Decomposition Method

We develop a new solution method for a broad class of discrete-time dynamic portfolio choice problems. The method efficiently approximates conditional expectations of the value function by using (i) a decomposition of the state variables into a component observable by the investor and a stochastic deviation; and (ii) a Taylor expansion of the value function. We illustrate the accuracy of the method in handling several realistic features of portfolio choice problems such as intermediate consumption, multiple assets, multiple state variables, portfolio constraints, non-time-separable preferences, and nonredundant endogenous state variables. We finally use the method to solve a realistic large-scale life-cycle portfolio choice and consumption problem with predictable expected returns and recursive preferences.