John Stachurski

Learn More
This paper considers a neoclassical optimal growth problem where the shock that perturbs the economy in each time period is potentially unbounded on the state space. Sufficient conditions for existence, uniqueness and stability of equilibria are derived in terms of the primitives of the model using recent techniques from the field of perturbed dynamical(More)
This paper proposes and implements a method to predict the evolution of the crosscountry income distribution using a stochastic parameterization of the Azariadis– Drazen (1990) nonconvex growth model. We estimate the dynamic structure of that model from data in the Penn World Tables, and define inductively all future distributions as a norm-convergent(More)
The paper considers random economic systems generating nonlinear time series on the positive half-ray R+. Using Lyapunov techniques, new conditions for existence, uniqueness and stability of stationary equilibria are obtained. The conditions generalize earlier results from the mathematical literature, and extend to models outside the scope of existing(More)
The paper proposes an Euler equation technique for analyzing the stability of differentiable stochastic programs. The main innovation is to use marginal reward directly as a Foster–Lyapunov function. This allows us to extend known stability results for stochastic optimal growth models, both weakening hypotheses and strengthening conclusions. JEL(More)
This paper studies fitted value iteration for continuous state numerical dynamic programming using nonexpansive function approximators. A number of approximation schemes are discussed. The main contribution is to provide error bounds for approximate optimal policies generated by the value iteration algorithm. Journal of Economic Literature Classifications:(More)
The date of receipt and acceptance will be inserted by the editor Summary. This note studies conditions under which sequences of state variables generated by discrete-time stochastic optimal accumulation models have law of large numbers and central limit properties. Productivity shocks with unbounded support are considered. Instead of restrictions on the(More)
This paper studies the convergence properties of a Monte Carlo algorithm for computing distributions of state variables when the underlying model is a Markov chain with absolutely continuous transition probabilities. We show that the L1 error of the estimator always converges to zero with probability one. In addition, rates of convergence are established(More)
The paper gives conditions under which stationary distributions of Markov models depend continuously on the parameters. It extends a well-known parametric continuity theorem for compact state space to the unbounded setting of standard econometrics and time series analysis. Applications to several theoretical and estimation problems are outlined.
We study a two-country version of Matsuyama’s (Econometrica, 72, p. 853–84, 2004) world economy model. As in Matsuyama’s model, symmetry-breaking can be observed, and symmetry-breaking generates endogenously determined levels of inequality. In addition, we show that when the countries differ in population size, their interaction through credit markets may(More)