The Application of Time Series Analysis in Economic Growth

Dear Colleagues,

Time series models and their applications to economic growth have experienced paradigmatic shifts in attention in the past four decades since Dickey and Fuller (1970s). A transition from a knife-edge testing for nonstationarity in time series data using a unit root mechanism to the one with a flexible framework, the fractional integration method, has infused active interests from academics and policy makers alike. Applied to the context of economic growth (at regional or cross-country levels), those varied testing methods underline important implications for policy (endogenous and exogenous). A stream of research that began with, for instance, Jones (1995) and Lau (1999, 2008) opened the door for a more rigorous testing of growth models using flexible framework. However, while the I(0)-I(1) framework has found meteoric rise in applications in economic growth context, especially with respect to the method’s ability to identify exogenous and endogenous growth mechanisms, use of fractional integration (and more generally, long-memory) methods in identifying such growth apparatus are still in infancy. Admittedly, given that fractional time series methods can accommodate greater dynamics with regard to the nature of shock convergence to a steady-state, one would naturally expect some approximations of exogenous, semi-endogenous or endogenous growth models to be identified by a rigorous applications of such a method. In the face of a clear dearth of literature, this Special Issue aims to contribute to the extant growth literature by providing either a theoretical apparatus or rigorous empirical findings which combine ‘long-memory methods’ with ‘exogenous/endogenous’ growth models.

Reference

Jones, C.I. (1995), `Time Series Tests of Endogenous Growth Models’ the Quarterly Journal of Economics, Vol. 110, No. 2 (May, 1995), pp. 495-525.

Lau, S-H Paul (1999) "I(0) in, integration and cointegration out: Time series properties of endogenous growth models", Journal of Econometrics, Vol. 93, November 1999, pp.1-24.

Lau, S-H Paul (2008) Using an error-correction model to test whether endogenous long-run growth exists", Journal of Economic Dynamics and Control, Vol. 32, No. 2, 2008, pp.648-676.

As an academic community, we are perennially standing at a crossroads and are constantly challenged to advance something new, that can—by and large —approximate reality. It is no doubt that development of time series models and our ability to test economic growth (both exogenous and endogenous) have not gone hand in hand.

The largely unsynchronized nature of integration, thanks to the slow-paced development of computational methods in the past two decades, have shown us some sparks of exciting development, but pegged back for some unknown reasons, to demonstrate the power of long-memory models in identification of growth mechanisms. What is a policy-relevant exercise is that ‘such an identification has enormous implication for predicting the growth architecture of nations and outline schemes of their adaptability to shocks of varied length and magnitudes’. In this Special Issue, I am inviting both theoretical and empirical papers which demonstrate new developments in the application of long-memory methods in testing economic growth, model convergence patterns using a path-dependence structure, and provide a robust identification tool for exogenous or endogenous economic growth mechanisms.

Prof. Dr. Tapas Mishra
Guest Editor

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• long-memory
• exogenous growth
• endogenous growth
• convergence in growth
• fractional integration and cointegration
• fractional error correction mechanism
• cross-country and cross-regional