Optimal Growth Problem Research Articles

Analyzing a Maximum Principle for Finite Horizon State Constrained Problems via Parametric Examples. Part 2: Problems with Bilateral State Constraints

In this article, a maximum principle for finite horizon state-constrained problems is analyzed via parametric examples. These parametric examples resemble typical optimal growth problems in mathematical economics. Since the maximum principle is only a necessary condition for local optimal processes, a large amount of additional investigations are needed to obtain a comprehensive synthesis of finitely many processes suspected for being local minimizers. Our analysis not only helps to understand the principle in depth, but also serves as a sample of applying it to meaningful prototypes of optimal economic growth models. Problems with unilateral state constraints have been studied in Part 1 of the article. Problems with bilateral state constraints are addressed in this Part 2.

Optimal Processes in a Parametric Optimal Economic Growth Model

A parametric finite horizon optimal economic growth problem is solved by using the maximum principle for optimal control problems with state constraints in the book by R. Vinter [Optimal Control, Birkhäuser, Boston, 2000; Theorem 9.3.1]. From the obtained results it follows that if the total factor productivity is relatively small, then the expansion of the production facility does not lead to a higher total consumption satisfaction of the society.

On discrete time infinite horizon optimal growth problem

Optimal growth problem is an important optimization problem in the theory of economic dynamics. This paper provides an overview of the main approaches used in the existing literature in solving infinite horizon discrete time optimal growth problem and includes very recent developments.

Some Facts about the Ramsey Model

In modeling the dynamics of capital, the Ramsey equation coupled with the Cobb–Douglas production function is reduced to a linear differential equation by means of the Bernoulli substitution. This equation is used in the optimal growth problem with logarithmic preferences. The study deals with solving the corresponding infinite horizon optimal control problem. We consider a vector field of the Hamiltonian system in the Pontryagin maximum principle, taking into account control constraints. We prove the existence of two alternative steady states, depending on the constraints. This result enriches our understanding of the model analysis in the optimal control framework.

Application of optimal control and stabilization to an infinite time horizon problem under constraints

In modeling the dynamics of capital, the Ramsey equation coupled with the Cobb-Douglas production function is reduced to a linear differential equation by means of the Bernoulli substitution. This equation is used in the optimal growth problem with logarithmic preferences. We consider a vector field of the Hamiltonian system in the Pontryagin maximum principle, taking into account control constraints. We prove the existence of two alternative steady states, depending on the constraints. A proposed algorithm for constructing growth trajectories combines methods of open-loop control and closed-loop stabilizing control. Results are supported by modeling examples.

Bernoulli substitution in the Ramsey model: Optimal trajectories under control constraints

We consider a neoclassical (economic) growth model. A nonlinear Ramsey equation, modeling capital dynamics, in the case of Cobb-Douglas production function is reduced to the linear differential equation via a Bernoulli substitution. This considerably facilitates the search for a solution to the optimal growth problem with logarithmic preferences. The study deals with solving the corresponding infinite horizon optimal control problem. We consider a vector field of the Hamiltonian system in the Pontryagin maximum principle, taking into account control constraints. We prove the existence of two alternative steady states, depending on the constraints. A proposed algorithm for constructing growth trajectories combines methods of open-loop control and closed-loop regulatory control. For some levels of constraints and initial conditions, a closed-form solution is obtained. We also demonstrate the impact of technological change on the economic equilibrium dynamics. Results are supported by computer calculations.

Optimal Growth with Resource Exhaustibility and Pollution Externality

This paper investigates a problem of optimal growth with resource exhaustibility and pollution externality, based on a unified framework that explicitly considers augmentable man-made capital, exhaustible resource reserves, and accumulative environmental pollutants as three stock variables for optimal control analysis. Characterizations of the social optimum show that for any given man-made capital and resource reserves, resource extraction flows generated in optimal growth with both resource exhaustibility and pollution externality are smaller than those with only resource exhaustibility, and taking account of pollution externality resulting from resource extraction reduces the growth rate of consumption if man-made capital and natural resources are complements in final goods production. Existence, uniqueness and comparative statics of the steady state are analyzed. Conditions for transitional dynamics stability of optimal growth with resource exhaustibility and pollution externality are established. Expositions are made on whether allocations in a market equilibrium are consistent with the social optimum outcomes.

Optimal growth with investment enhancing labor

We study a non-convex optimal growth problem with investment enhancing labor. We prove that there exists an optimal growth path, that all optimal paths are interior and we provide a condition under which at least one of them is monotonic. We also study the existence and uniqueness of the steady state. We show in particular that a rise in the efficiency of the investment enhancing labor does not necessarily lead to an increase in the steady state value of this labor. Furthermore we provide a complete study of the dynamics of the optimal solution in the special case of a logarithmic utility function and a Cobb–Douglas production function.

Export dynamics as an optimal growth problem in the network of global economy.

We analyze export data aggregated at world global level of 219 classes of products over a period of 39 years. Our main goal is to set up a dynamical model to identify and quantify plausible mechanisms by which the evolutions of the various exports affect each other. This is pursued through a stochastic differential description, partly inspired by approaches used in population dynamics or directed polymers in random media. We outline a complex network of transfer rates which describes how resources are shifted between different product classes, and determines how casual favorable conditions for one export can spread to the other ones. A calibration procedure allows to fit four free model-parameters such that the dynamical evolution becomes consistent with the average growth, the fluctuations, and the ranking of the export values observed in real data. Growth crucially depends on the balance between maintaining and shifting resources to different exports, like in an explore-exploit problem. Remarkably, the calibrated parameters warrant a close-to-maximum growth rate under the transient conditions realized in the period covered by data, implying an optimal self organization of the global export. According to the model, major structural changes in the global economy take tens of years.

Ruling Out Multiplicity of Smooth Equilibria in Dynamic Games: A Hyperbolic Discounting Example

The literature that conducts numerical analysis of equilibrium in models with hyperbolic (quasi-geometric) discounting reports difficulties in achieving convergence. Surprisingly, numerical methods fail to converge even in a simple, deterministic optimal growth problem that has a well-behaved, smooth closed-form solution. We argue that the reason for nonconvergence is that the generalized Euler equation has a continuum of smooth solutions, each of which is characterized by a different integration constant. We propose two types of restrictions that can rule out the multiplicity: boundary conditions and shape restrictions on equilibrium policy functions. With these additional restrictions, the studied numerical methods deliver a unique smooth solution for both the deterministic and stochastic problems in a wide range of the model’s parameters.

Problem of optimal endogenous growth with exhaustible resources and possibility of a technological jump

In 2013, S. Aseev, K. Besov, and S. Kaniovski (“The problem of optimal endogenous growth with exhaustible resources revisited,” Dyn. Model. Econometr. Econ. Finance 14, 3–30) considered the problem of optimal dynamic allocation of economic resources in an endogenous growth model in which both production and research sectors require an exhaustible resource as an input. The problem is formulated as an infinite-horizon optimal control problem with an integral constraint imposed on the control. A full mathematical study of the problem was carried out, and it was shown that the optimal growth is not sustainable under the most natural assumptions about the parameters of the model. In the present paper we extend the model by introducing an additional possibility of “random” transition (jump) to a qualitatively new technological trajectory (to an essentially unlimited backstop resource). As an objective functional to be maximized, we consider the expected value of the sum of the objective functional in the original problem on the time interval before the jump and an evaluation of the state of the model at the moment of the jump. The resulting problem also reduces to an infinite-horizon optimal control problem, and we prove an existence theorem for it and write down an appropriate version of the Pontryagin maximum principle. Then we characterize the optimal transitional dynamics and compare the results with those for the original problem (without a jump).

Dynamic optimal capital growth of diversified investment

We investigate the problem of dynamic optimal capital growth of diversified investment. A general framework that the trader maximize the expected log utility of long-term growth rate of initial wealth was developed. We show that the trader's fortune will exceed any fixed bound when the fraction is chosen less than critical value. But, if the fraction is larger than that value, ruin is almost sure. In order to maximize wealth, we should choose the optimal fraction at each trade. Empirical results with real financial data show the feasible allocation. The larger the fraction and hence the larger the chance of falling below the desired wealth growth path.

Simulated annealing algorithm for optimal capital growth

We investigate the problem of dynamic optimal capital growth of a portfolio. A general framework that one strives to maximize the expected logarithm utility of long term growth rate was developed. Exact optimization algorithms run into difficulties in this framework and this motivates the investigation of applying simulated annealing optimized algorithm to optimize the capital growth of a given portfolio. Empirical results with real financial data indicate that the approach is inspiring for capital growth portfolio.

Solving Dynamic Programming Problems on a Computational Grid

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 implemented using the Master-Worker library running on the HTCondor grid computing platform. We implement value function iteration for several large dynamic programming problems of two kinds: optimal growth problems and dynamic portfolio problems. We present examples that solve in hours on HTCondor but would take weeks if executed on a single workstation. The use of HTCondor can increase a researcher's computational productivity by at least two orders of magnitude.

Stochastic optimal growth with risky labor supply

Production takes time, and labor supply and profit maximization decisions that relate to current production are typically made before all shocks affecting that production have been realized. In this paper we re-examine the problem of stochastic optimal growth with aggregate risk where the timing of the model conforms to this information structure. We provide a set of conditions under which the economy has a unique, nontrivial and stable stationary distribution. In addition, we verify key optimality properties in the presence of unbounded shocks and rewards, and provide the sample path laws necessary for consistent estimation and simulation.

Extension Of Pontryagin Maximum Principle And Its Economical Applications

First, an extension of Pontryagin Maximum Principle in Infinite-Horizon, which was presented by Aseev and Kryazhimiskii, is explained. Since this method is applicable in optimal economical growth problems, for the first time several problems such as consumption and investment are solved. Moreover, for implementing Aseev and Kryazhimiskii 's method on Iranian economy, Luis Serven model is introduced. Then it is calibrated on Iranian economy during the years 1385-1415. By applying the described method, the optimal consumption and investment for maximizing the social welfare are demonstrated. Also the sensitivity analysis is discussed.

Optimal R&D subsidies in a model with physical capital, human capital and varieties

In this paper, we analyze the social planner solution of an endogenous growth model with physical capital, human capital and R&D. The model incorporates three sources of inefficiency: monopolistic competition in the intermediate-goods sector, duplication externalities and spillovers in R&D. A complete stability analysis for the optimal growth problem of this model is provided. We characterize the optimal policy that can decentralize the optimal solution and find that the path of the optimal R&D subsidy can be non-monotonic.

Solution to nonlinear MHDS arising from optimal growth problems

In this paper we propose a method for solving in closed form a general class of nonlinear modified Hamiltonian dynamic systems (MHDS). This method is used to analyze the intertemporal optimization problem from endogenous growth theory, especially the cases with two controls and one state variable. We use the exact solutions to study both uniqueness and indeterminacy of the optimal path when the dynamic system has not a well-defined isolated steady state. With this approach we avoid the linearization process, as well as the reduction of dimension technique usually applied when the dynamic system offers a continuum of steady states or no steady state at all.

Computation of Equilibria in OLG Models with Many Heterogeneous Households

This paper develops a decomposition algorithm by which a market economy with many households may be solved through the computation of equilibria for a sequence of representative agent economies. The paper examines local and global convergence properties of the sequential recalibration (SR) algorithm. The SR algorithm is then demonstrated to efficiently solve Auerbach–Kotlikoff OLG models with a large number of heterogeneous households. We approximate equilibria in OLG models by solving a sequence of related Ramsey optimal growth problems. This approach can provide improvements in both efficiency and robustness as compared with integrated complementarity-based solution methods.

Computation of Equilibria in OLG Models with Many Heterogeneous Households

This paper develops a decomposition algorithm by which a market economy with many households may be solved through the computation of equilibria for a sequence of representative agent economies. The paper examines local and global convergence properties of the sequential recalibration (SR) algorithm. SR is then demonstrated to efficiently solve Auerbach-Kotlikoff OLG models with a large number of heterogeneous households. We approximate equilibria in OLG models by solving a sequence of related Ramsey optimal growth problems. This approach can provide improvements in both efficiency and robustness as compared with simultaneous solution methods.