Financial Development and Economic Growth: A Revised Empirical Study for Ireland

Abstract

1. Introduction The issue of causal relationship between financial development and economic growth has been an intensive subject of interest for many theoretical and empirical studies (Thalassinos and Kiriazidis, 2003; Thalassinos and Pociovalisteanu, 2007). The main objective of this study is to investigate the causal relationship between economic growth and financial development taking into account the positive effect of industrial production index. Ireland consists one of the most important developed countries of European Union characterized by a high rate of economic growth, a constant monetary and fiscal economic policy and very low inflation and unemployment rates, and a healthy and competitive economy. The negative effects of financial crisis are obvious in an unstable world financial system, which is mainly characterized by an economic instability, while a possible increase of credit risk causes a highly banking uncertainty (Thalassinos et al., 2010). The remainder of the paper proceeds as follows: Initially the data and the specification of the multivariate VAR model are described. For this purpose stationarity test and Johansen cointegration analysis are examined taking into account the estimation of vector error correction model. Finally, Granger causality test is applied in order to find the direction of causality between the examined variables of the estimated model. The empirical results are presented analytically and some discussion issues resulted from this empirical study are developed shortly, while the final conclusions are summarized relatively. 2. Data and Methodology In this study the method of vector autoregressive model (VAR) is adopted to estimate the effects of stock and credit market development on economic growth through the effect of industrial production. The use of this methodology predicts the cumulative effects taking into account the dynamic response among economic growth and the other examined variables Pereira and Hu (2000). In order to test the causal relationships, the following multivariate model is to be estimated [GDP.sub.t] = f([SM.sub.t], [BC.sub.t], [IND.sub.t]) (1) Where: [GDP.sub.t] is the gross domestic product, [SM.sub.t] is the general stock market index, [BC.sub.t] are the domestic bank credits to private sector, [IND.sub.t] is the industrial production index. Relating to the econometric analysis this paper is based on the empirical studies of Chang (2002), Chang and Caudill (2005), Shan (2005), Vazakidis (2006), Vazakidis and Adamopoulos 2009a,b,c). Therefore, this empirical study based on the previous published version on 2010 tries to fill some possible theoretical and empirical gaps estimating a larger data sample taking into account the negative effects of financial crisis the last years. The used data are annual covering the period 1965-2011 for Ireland, regarding 2005 as a base year. All time series data are expressed in their levels and are obtained from International Financial Statistics, (International Monetary Fund, 2012). The selected linear model has better statistical estimations than a logarithmic one. The tested results of the logarithmic model proved to be statistical inferior. Unit root tests: Augmented Dickey-Fuller (ADF) test involves the estimation one of the following equations respectively, Seddighi et al (2000): [[DELTA]X.sub.t] = [[delta]X.sub.t-1] + [p.summation over (j=1)] [[delta].sub.j][[DELTA]X.sub.t-j] + [[epsilon].sub.t] (2) [[DELTA]X.sub.t] = [[alpha].sub.0] + [[delta]X.sub.t-1] + [p.summation over (j=1)] [[delta].sub.j][[DELTA]X.sub.t-j] + [[epsilon].sub.t] (3) [[DELTA]X.sub.t] = [[alpha].sub.0] + [[alpha].sub.1]t + [[delta]X.sub.t-1] + [p.summation over (j=1)] [[delta].sub.j][[DELTA]X.sub.t-j] + [[epsilon].sub.t] (3) If the calculated ADF statistic is higher than McKinnon's critical values, then the null hypothesis ([H. …