Measuring Convergence Using Dynamic Equilibrium Models: Evidence from Chinese Provinces

30 Pages Posted: 31 May 2012

See all articles by Lei Pan

Lei Pan

Wageningen University and Research (WUR) - Development Economics Group

Olaf Posch

Universität Hamburg, Department of Economics; CREATES

Michel van der Wel

Erasmus University Rotterdam

Date Written: May 30, 2012

Abstract

We propose a model to study economic convergence in the tradition of neoclassical growth theory. We employ a novel stochastic set-up of the Solow (1956) model with shocks to both capital and labor. Our novel approach identifies the speed of convergence directly from estimating the parameters which determine equilibrium dynamics. The inference on the structural parameters is done using a maximum-likelihood approach. We estimate our model using growth and population data for China's provinces from 1980 to 2009. We report heterogeneity in the speed of convergence both across provinces and time. The Eastern provinces show a higher tendency of convergence, while there is no evidence of convergence for the Central and Western provinces. We find empirical evidence that the speed of convergence decreases over time for most provinces.

Keywords: Economic convergence, Dynamic stochastic equilibrium models, Solow model, Structural estimation

JEL Classification: C13, E32, O40

Suggested Citation

Pan, Lei and Posch, Olaf and van der Wel, Michel, Measuring Convergence Using Dynamic Equilibrium Models: Evidence from Chinese Provinces (May 30, 2012). Available at SSRN: https://ssrn.com/abstract=2071055 or http://dx.doi.org/10.2139/ssrn.2071055

Lei Pan (Contact Author)

Wageningen University and Research (WUR) - Development Economics Group ( email )

Hollandseweg 1
WAGENINGEN, 6706 KN
Netherlands

Olaf Posch

Universität Hamburg, Department of Economics ( email )

Von-Melle-Park 5
Hamburg, 20146
Germany

CREATES

School of Economics and Management
Building 1322, Bartholins Alle 10
DK-8000 Aarhus C
Denmark

Michel Van der Wel

Erasmus University Rotterdam ( email )

Burg. Oudlaan 50
Rotterdam, NL 3062 PA
Netherlands

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