Value function iteration is one of the standard tools for the solution of the Ramsey model. We compare six different ways of value function iteration with regard to speed and precision. We find that value function iteration with cubic spline interpolation between grid points dominates the other methods in most cases. For the initialization of the value function over a fine grid, modified policy function iteration over a coarse grid and subsequent linear interpolation between the grid points provides a very efficient way to reduce computational time.
value function iteration policy function iteration Howard's algorithm acceleration cubic interpolation stochastic Ramsey model