Dynamics of demographic changes and economic development

Mishra, Tapas
(2006)

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Authors
  • Mishra, Tapas
    author
Supervisors
de la Croix, David
;
Shadman, Fatemeh
Abstract
(en) Demographic changes and economic growth are inextricably linked. However, the complex role of demographic system, specifically its temporal features have not been treated with rigor till recently. This dissertation undertakes such an attempt to explain cross-country growth variations and focuses on longterm growth projections by explicitly treating demographic system in a stochastic shocks framework. We exploit the temporal characteristics of demographic system to shed light on its evolution, study its complex interaction with economic system and analyze the long-run effect on economic growth/development. The dissertation contains four chapters. After outlining the motivation of the thesis and an overview of the chapter scheme in the first chapter, we investigate in Chapter 2 how the effects of demographic components viz., age specific population have changed over the decades. Following the standard practice of assuming 'stationary' features of population growth, we first evaluate and extend the popular empirical economic growth models. We find that decadal changes have brought forth variations in economic growth of developed and developing economies. We argue that accounting for temporal features of the demographic and economic growth system would provide clear insights into persistent growth fluctuations. In Chapter 3 we develop a new mechanism to characterize stochastic nature of demographic shocks in which population series with large temporal dimension is assumed to be governed by certain degree of stochastic shocks. By doing so, the conventional 'stationary' assumption underlying the current theoretical and empirical exploration is relaxed and more dynamic information about the persistence of shocks is accommodated in the economic growth models. To this end, we first provide an analytical framework to show that long-memory shocks in demographic age structure or population might induce long-memory in economic growth. An empirical illustration of both developed and developing countries is carried out to demonstrate that population age structure in these countries are characterized by long-memory. The causality of stochastic demographic shocks' influence and economic growth (and the converse) is also examined. Following the theoretical development and empirical illustration in Chapter 3, in Chapter 4 we propose to forecast total and age-structured population employing fractionally integrated ARMA (in short, ARFIMA) technique. The conventional methods of population forecasting is discussed in this chapter evaluating the advantages and potential weaknesses of these methods. Our approach to population forecasting can be considered as a shift from the conventional 'low, medium, and high' variant and the recently used ARMA projections (assuming stationarity or first difference stationarity of aggregate population) and is a departure from the stochastic population forecast based on Leslie matrix as used in the extant population forecasting literature. In Chapter 5 we incorporate the memory properties of demographic age- distribution to forecast Gross Domestic Product (or National income) of some developed and developing countries. We relax the stationary age-structure and population growth assumption in the model while performing long term income projections. We argue that the growth of total age-structured population need not be stationary and that any degree of stochastic shocks in these series can affect forecasting performance. Given that a long-memory panel method is yet to be comprehensively built for forecasting, we perform forecast of demography-based income in the univariate context assuming a stochastic long-memory process for age-structured population growth. Finally, Chapter 6 summarizes the main findings of the thesis and outlines some possible directions for further research.
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Citations

Mishra, T. (2006). Dynamics of demographic changes and economic development. https://hdl.handle.net/2078.5/72979