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A Further Look into the Demography-based GDP Forecasting Method

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  • Tapas K. Mishra

Abstract

Demography-based income forecasting has recently gained enormous popu- larity. Malmberg and Lindh (ML, 2005) in an important contribution forecast global income by incorporating demographic age information where the vari- ables were assumed to be stationary. Drawing on the insights from recent theoretical and empirical advances, in this paper we re-examine the stationary assumption and argue in favour of a more flexible framework where ’stationar- ity’ is a limiting condition of the stochastic demographic behavior. Based on Mishra and Urbain (2005) where we showed that the age-specific population display varied long-term and short-term dynamics, we invest this idea in the present paper for long-term projections of per capita income (till 2050) of a set of developed and developing countries and the World income. We find that GDP forecast that corroborates demographic information have higher forecasts than without demographic information - a result consistent with ML, but we find that embedding ’memory’ features of demographic variables lead to higher forecast that ML. The relevance of stochastic shocks in GDP forecasting is drawn in this paper and implications of these forecast in the presence of fluc- tuating age-shares in those countries are discussed.

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Paper provided by Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg in its series Working Papers of BETA with number 2006-17.

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Date of creation: 2006
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Handle: RePEc:ulp:sbbeta:2006-17

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Keywords: Global income forecasting; Long memory; Demographic components; Economic growth.;

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