A nonsmooth, nonconvex model of optimal growth
نویسندگان
چکیده
This paper analyzes the nature of economic dynamics in a one-sector optimal growth model in which the technology is generally nonconvex, nondifferentiable, and discontinuous. The model also allows for irreversible investment and unbounded growth. We develop various tools to overcome the technical difficulties posed by the generality of the model. We provide sufficient conditions for optimal paths to be bounded, to converge to zero, to be bounded away from zero, and to grow unboundedly. We also show that under certain conditions, if the discount factor is close to one, any optimal path from a given initial capital stock converges to a small neighborhood of the golden rule capital stock, at which sustainable consumption is maximized. If it is maximized at infinity, then as the discount factor approaches one, any optimal path either grows unboundedly or converges to an arbitrarily large capital stock.
منابع مشابه
Benson's algorithm for nonconvex multiobjective problems via nonsmooth Wolfe duality
In this paper, we propose an algorithm to obtain an approximation set of the (weakly) nondominated points of nonsmooth multiobjective optimization problems with equality and inequality constraints. We use an extension of the Wolfe duality to construct the separating hyperplane in Benson's outer algorithm for multiobjective programming problems with subdifferentiable functions. We also fo...
متن کاملOptimal Control of Nonconvex Discrete and Differential Inclusions
Optimization problems for discrete and diierential inclusions have many important applications and generalize both standard and nonstandard models in optimal control for open-loop and closed-loop control systems. In this paper we consider optimal control problems for dynamic systems governed by such inclusions with general endpoint constraints. We provide a variational analysis of diierential i...
متن کاملAn efficient one-layer recurrent neural network for solving a class of nonsmooth optimization problems
Constrained optimization problems have a wide range of applications in science, economics, and engineering. In this paper, a neural network model is proposed to solve a class of nonsmooth constrained optimization problems with a nonsmooth convex objective function subject to nonlinear inequality and affine equality constraints. It is a one-layer non-penalty recurrent neural network based on the...
متن کاملA Class of Nonconvex Nonsmooth Approximate Potential Functions for Nonconvex Nonsmooth Image Restoration
Nonconvex nonsmooth potential functions have superior restoration performance for the images with neat boundaries. However, several difficulties emerge from the numerical computation. Thus the graduated nonconvex (GNC) method is suggested to deal with these problems. To improve the performance of the GNC method further, a class of nonconvex nonsmooth approximate potential functions have been co...
متن کاملExistence of Solutions for Nonconvex and Nonsmooth Vector Optimization Problems
We consider the weakly efficient solution for a class of nonconvex and nonsmooth vector optimization problems in Banach spaces. We show the equivalence between the nonconvex and nonsmooth vector optimization problem and the vector variational-like inequality involving set-valued mappings. We prove some existence results concerned with the weakly efficient solution for the nonconvex and nonsmoot...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید
ثبت ناماگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید
ورودعنوان ژورنال:
- J. Economic Theory
دوره 132 شماره
صفحات -
تاریخ انتشار 2007