The Generalized Neoclassical Growth Model

IGIER Working Paper No. 231

32 Pages Posted: 4 Jun 2003

See all articles by Marco Maffezzoli

Marco Maffezzoli

Bocconi University - Department of Economics

Alejandro Cunat

London School of Economics & Political Science (LSE) - Department of Economics; Bocconi University - IGIER - Innocenzo Gasparini Institute for Economic Research; Centre for Economic Policy Research (CEPR)

Date Written: February 2003

Abstract

We construct and numerically solve a dynamic Heckscher-Ohlin model which, depending on the distribution of production factors in the world and parameter values, allows for worldwide factor price equalization or complete specialization. We explore the dynamics of the model under different parameter values, and relate our theoretical results to the empirical literature that studies the determinants of countries' income per capita growth and levels. In general, the model is capable of generating predictions in accordance with the most important findings in the empirical growth literature. At the same time, it avoids some of the most serious problems of the (autarkic) neoclassical growth model.

Keywords: International Trade, Hechscher-Ohlin, Economic Growth, Convergence, Simulation

JEL Classification: F1, F4, O4

Suggested Citation

Maffezzoli, Marco and Cunat, Alejandro, The Generalized Neoclassical Growth Model (February 2003). IGIER Working Paper No. 231, Available at SSRN: https://ssrn.com/abstract=390940 or http://dx.doi.org/10.2139/ssrn.390940

Marco Maffezzoli (Contact Author)

Bocconi University - Department of Economics ( email )

Via Gobbi 5
Milan, 20136
Italy

Alejandro Cunat

London School of Economics & Political Science (LSE) - Department of Economics ( email )

Houghton Street
London WC2A 2AE
United Kingdom
+44 20 7955 6961 (Phone)

Bocconi University - IGIER - Innocenzo Gasparini Institute for Economic Research ( email )

Via Roentgen 1
Milan, 20136
Italy

Centre for Economic Policy Research (CEPR)

London
United Kingdom

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Downloads
171
Abstract Views
1,178
Rank
333,424
PlumX Metrics