Forecasting the Convergence State of per Capital Income in Vietnam

DOI: 10.4236/ajor.2013.36047   PDF   HTML     3,665 Downloads   5,688 Views   Citations

Abstract

Convergence problem of an economic variable represents an underlying forecast of neoclassical economic growth model. This paper aims to analyze the convergence of provincial per capita GDP stability in Vietnam over the period of 1991-2007. This can be done by two approaches including bias data-based regression method for testing convergence and Markov chain model for describing features of long-term tendency of per capita income in Vietnam growth in provinces. The regression method results in the signs of convergence. To apply Markov process, we divide total pattern into 5 per capita income classes. Result estimated from the Markov chain model shows the poor convergence.

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N. Minh and P. Khanh, "Forecasting the Convergence State of per Capital Income in Vietnam," American Journal of Operations Research, Vol. 3 No. 6, 2013, pp. 487-496. doi: 10.4236/ajor.2013.36047.

Conflicts of Interest

The authors declare no conflicts of interest.

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