MENA aggregate cycle and world conjuncture: Episodes of volatility and symmetry, and an ADL cointegration test

Garfa, Kamel (2011): MENA aggregate cycle and world conjuncture: Episodes of volatility and symmetry, and an ADL cointegration test.

Abstract

This paper studies the cyclical fluctuations of the Middle East and North Africa countries in interaction with world conjuncture. The purpose is to evaluate in which measure the volatility and the symmetry of these countries had been modified quite particularly after their external integration. We adopt what we qualify as the aggregate cycle of MENA countries in orders to exanimate his evolution towards the G7, the European and the Anglo-Saxon business cycles over 1970-2010 periods. The filter of Hodrick-Prescott is applied in order to decompose the real GDP of the MENA and the most industrialized countries into trend and cyclical components. These last ones will be used to answer the composed questions on various temporal horizons, contemporary, the short term, and the long term. Two approaches will be used: A static one, based on properties of variability, co-variation and correlation, and a dynamic one, based on the study of the long term relations through an Autoregressive Distributed Model and the study of short term dynamics through an Error Correction Model.

• Item Type: MPRA Paper
• Language: English
• Keywords: Aggregate cycles; Synchronization; Fluctuations; Economic conjuncture; Co-integration; Autoregressive Distributed Model; Vectors Errors Correction Model.
• Subjects: F - International Economics > F1 - Trade > F15 - Economic Integration; F - International Economics > F4 - Macroeconomic Aspects of International Trade and Finance > F42 - International Policy Coordination and Transmission

References

Agustin, D & Ken, H (2003): « The business cycle in the G-7 economies», International Journal of Forecasting, 19, 685-700.

Artis, M.J, Zenon G.K and Denise R.O (1997): «Business Cycles for G7 and European Countries, » Journal of Business 70, 1997, pp. 249 – 279.

Chan, Tze-Haw & Lau, Evan (2007): « Business cycles and the synchronization process: a bounds testing approach », Munich Personal RePEc Archive, n° 2053, November.

Engel & Granger (1987): «Co-integration and Error Correction: Representation, Estimation, and Testing », Econometrica, vol. 55, issue 2, pages 251-76

IMF (2007): « Decoupling the train? Spillovers and cycles in the global economy », World Economic Outlook, p 121-160, April.

Inklaara. R, Jong-A-Pina. R & de Haan. J (2008): « Trade and business cycle synchronization in OECD countries—A re-examination », European Economic Review 52 646–666

Johansen, S & Juselius, K (1990): «Maximum likelihood estimation and inference on co-integration with application to the demand for money», Oxford Bulletin of Economics and Statistics, 52.

Luke Keele and Suzanna De Boef (2004): "Not Just for Cointegration: Error Correction Models with Stationary Data", Department of Polytricks and International Relations, Nuffield College and Oxford University;

Monfort, A, Renne, J.P, Ruëffer, R & Vitale, G (2004): «Is economic activity in the G7 synchronised? Common shocks vs. spillover effects », CEPR Discussion Paper, n° 4119

Pesaran, M. H, & Shin, Y (1996): «An autoregressive distributed lag modelling approach to cointegration analysis », Cambridge: Department of Applied Economics, Cambridge University.

Pesaran, M. H., Y. Shin, & R. Smith (2000): « Structural analysis of vector error correction models with exogenous I(1) variables », Journal of Econometrics 97, 293-343

Pesaran, M. H., Y. Shin, & R. Smith (2001): « Bounds Testing Approaches to the Analysis of Level Relationships », Journal of Applied Econometrics, 16(3), 289-326.

Pesaran, M.H., Shin, Y. & Smith, R.J. (1996): « Testing for the Existence of a Long Run Relationship», DAE Working Paper, No. 9622, Department of Applied Economics. Cambridge University.

Stock, J.H & Watson, M (2003): «Has the Business Cycle Changed? Evidence and Explanations », August, NBER.

Uwe Hassler and JÄurgen Wolters (2006): "Autoregressive Distributed Lag Models and Cointegration", Allgemeines Statistisches Archiv, Volume 90, N°1 / March.