When all financial assets have risky returns, the mean-variance portfolio model is potentially subject to two types of bliss points. One bliss point arises when a von Neumann-Morgenstern utility function displays negative marginal utility for sufficiently large end-of-period wealth, such as in...

We benchmark seven global optimization algorithms by comparing their performance on challenging multidimensional test functions as well as a method of simulated moments estimation of a panel data model of earnings dynamics. Five of the algorithms are taken from the popular NLopt open-source...

We calculate the socially optimal level of illiquidity in an economy populated by households with taste shocks and present bias (Amador, Werning, and Angeletos 2006). The government chooses mandatory contributions to respective spending/savings accounts, each with a different pre-retirement...

Should the generosity of unemployment benefits and the progressivity of income taxes depend on the presence of business cycles? This paper proposes a tractable model where there is a role for social insurance against uninsurable shocks to income and unemployment, as well as inefficient business...

We implement a dynamic programming algorithm on a computational grid consisting of loosely coupled processors, possibly including clusters and individual workstations. The grid changes dynamically during the computation, as processors enter and leave the pool of workstations. The algorithm is...

A new algorithm for the group minimization problem (GP) is proposed. The algorithm can be broadly described as follows. A suitable relaxation of(GP) is defined, in which any feasible point satisfies the group equation but may have negative components. The feasible points of the relaxation are...

This paper introduces a method for solving numerical dynamic stochastic optimization problems that avoids rootfinding operations. The idea is applicable to many microeconomic and macroeconomic problems, including life cycle, buffer-stock, and stochastic growth problems. Software is provided

Rules often are complex in order to distinguish different types of behavior that may have different consequences. Greater complexity thus allows better control of behavior. But individuals may need to incur costs ex ante to determine how more complex rules apply to their contemplated conduct....

This paper formulates a model of retirement behavior based on the solution to a stochastic dynamic programming problem. The workers objective is to maximize expected discounted utility over his remaining lifetime. At each time period the worker chooses how much to consume and whether to work...

A nonlinear programming formulation is introduced to solve infinite horizon dynamic programming problems. This extends the linear approach to dynamic programming by using ideas from approximation theory to avoid inefficient discretization. Our numerical results show that this nonlinear...