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Development Economics and Structuralist Macroeconomics

Development Economics and Structuralist Macroeconomics

Essays in Honor of Lance Taylor

Edited by Amitava Krishna Dutt

Lance Taylor is widely considered to be one of the pre-eminent development economists in the world and is known for his work on development planning, macroeconomics of development, stabilization policy, and the global economy. He has also been the major force behind structuralist economics, which is seen by many to be a major alternative to orthodox development economics and policy prescriptions. The essays in this volume, written by well-known scholars in their own right, make contributions to each of these areas while honoring the contributions made by Lance Taylor.

Chapter 2: Modeling economic growth with GAMS

P. Ruben Mercado, Lihui Lin and David A. Kendrick

Subjects: development studies, development economics, economics and finance, development economics


P. Ruben Mercado, Lihui Lin and David A. Kendrick The theoretical and computational modeling of economic growth has experienced a significant comeback in recent years, particularly in the form of optimal growth models. Qualitative properties of simple one-sector models of optimal growth have been known for a long time, and closed form solutions can be obtained for particular models with simple objective functions and dynamic constraints. However, computational methods become a necessity as soon as we move from simple models to more complex specifications.1 These methods are very useful not only to obtain solutions and simulations of empirically specified models, but also to explore the behavior of complex theoretical models.2 Our goal in this chapter is to introduce some strategies to implement optimal growth models in GAMS (General Algebraic Modeling System).3 We begin with a simple Ramsey-type model and later present a more complex dynamic multisector model originally developed by David Kendrick and Lance Taylor (Kendrick and Taylor, 1969 and 1970). The last one is particularly interesting since it is a four-sector model with a nonlinear objective function, non-linear constant elasticity of substitution (CES) production functions, and non-linear absorptive capacity functions. It was an early effort to show the feasibility of solving multisector nonlinear optimization models with the use of computational methods. At that time, its solution required the most powerful computers available at MIT. Today, it can easily be implemented in a personal computer and it provides, among other things, a good training ground...

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