Challenges in the Era of Globalization - iaabd

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Proceedings of the 12th Annual Conference © 2011 IAABD (Pons-Novell 2003; Calvo 2005; and Broner, Gelos, and Reinhart 2006). On the other hand, country specific transmission depends on country-specific financial and trade relations, structural uniqueness, and policies and may account for disparities in effects of global crisis on nations. Methodology Model Estimation Technique In this study, we employ time series econometric techniques to ascertain the impact of the global financial crisis on the Nigerian capital market. Specifically, we use pairwise correlation and the Generalized Method of Moments (GMM) estimator to establish the relationship between the Nigerian Stock Exchange (NSE) and the stock exchanges of 5 major developed economies of USA (DOW and NYSE), UK (FTSE), Canada (S&PTSX), France (CAC) and Germany (DAX). The GMM estimator is a robust estimator to the extent that a lot of popular estimators in econometrics are regarded as special cases of GMM. The OLSE, for instance is regarded as a GMM estimator in which the independent variables are individually not correlated with the residual. For the GMM, we write the moment condition as an orthogonality condition between the parameters and a set of instrumental variables. To ensure that the GMM estimator is identified, we have the same number of instrumental variables as the parameters to be estimated. Thus, we use the lagged values of the series NSEt-1, DOW t-1, FTSE t-1, NYSE t-1, S&PTSX t-1, CAC t-1, DAX t-1 as instruments. Each series consists of 970 observations of the daily closing prices from January 1 st January 2006 to 15th March 2010. Model Specification Towards achieving the objectives of this paper and using the GMM estimator, we posit a multivariate model of the following form: NSE= α0 + β1DOW + β2FTSE + β3NYSE + β4S&PTSX + β5CAC + β6DAX + εi (1) where: NSE is the all share index of the Nigerian stock exchange while DOW, NYSE, FTSE, S&PTSX, CAC, DAX are Dow (Dow Jones Index) and NYSE (New York Stock Exchange Index) represents the capital market of USA. FTSE, S&PTSXM, CAC and DAX are the all share indices of England, Canada, France and Germany. α0 and βi are the parameters to be estimated, and εi is the error term. We expect “a priori”, β > 0. Instrument list: NSEt-1, DOW t-1, FTSE t-1, NYSE t-1, S&PTSX t-1, CAC t-1, DAX t-1. Research Findings We first examine the graphical representation of the time series data employed in this study. Fig 1 below shows that all the series, namely: NSE, DOW, NYSE, FTSE, S&PTSX, CAC, DAX fluctuate in the same manner, indicative of positive correlation. 380
70000 60000 50000 40000 30000 20000 10000 11000 10000 9000 8000 7000 6000 5000 4000 9000 8000 7000 6000 5000 4000 3000 N S E 100 200 300 400 500 600 700 800 900 N Y SE 100 200 300 400 500 600 700 800 900 DAX 100 200 300 400 500 600 700 800 900 Fig 1: NSE, DOW JONES, FTSE, NYSE, S&P TSX, CAC, DAX 5000 4500 4000 3500 3000 2500 2000 16000 15000 14000 13000 12000 11000 10000 9000 8000 7000 DOW 100 200 300 400 500 600 700 800 900 S&P TSX 100 200 300 400 500 600 700 800 900 Challenges in the Era of Globalization Edited by Emmanuel Obuah Table 1 below presents pairwise correlation matrix to describe the relationship existing between NSE and stock markets of 5 (five) of the 7 most industrialized and developed nations of the world (the G7) for the period December 2005 to 15th March 2010. The result shows that the NSE is positively and highly correlated with the indices of these countries although the degree of correlation is highest with the German stock market (0.734), followed by the Dow Jones (0.729) and the Canadian stock market (0.728). The NSE is however less correlated with those of the United Kingdom and the French bourses. The results thus imply that the bourses move in the same direction and there is a very high tendency for the transmission of financial stress and shock from the advanced economies to the Nigerian capital market. The correlation coefficients showing the relationship among the bourses of the five advanced economies are however very high, indicative of high degrees of interdependence, co-movement and integration among them. 3600 3200 2800 2400 2000 1600 7000 6000 5000 4000 3000 2000 FTS E 100 200 300 400 500 600 700 800 900 CAC 100 200 300 400 500 600 700 800 900 381
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Table of Contents Challenges in the
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Lennart Bangens, Goteborg, Sweden C
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Local Steering Committee Jacob Musi
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Abstract Challenges in the Era of G
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Abstract Determinants of Bank Lendi
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Table 3 Determinants of Competitive
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Abstract: Study on Africa Governmen
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Abstract Challenges of Oil Revenue
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Abstract Land Based Sources of Poll
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Abstract On the Mitigation of Rever
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Assessment of pollutants in nigeria
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Conclusion Challenges in the Era of
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37. Provision of sound education fo
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The cost structure Challenges in th
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Variable Coefficient Std. Error t-S
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Abstract The Changing Requirements
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The Model, Data and Variable Defini
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Abstract Gender, poverty and sustai
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Figure 1.1: Spread of directorships
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Theoretical Framework Challenges in
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Defining the Organisational Culture
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Table 1: A Summary of Operating Ban
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Discussion and Conclusion Challenge
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Abstract What does Globalization me
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Statement of the Problem Challenges
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Banks in Ghana Challenges in the Er
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References: Challenges in the Era o
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The study seeks to: • examine typ
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Relationship Commitment Total 1264.
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firms attained below average market
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Conclusion Dissatisfied 6 3.4 3.6 7
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Methodology Challenges in the Era o
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