Financial Development and Economic Growth: Static and Dynamic Panel Data Analysis

Abstract

The relationship between financial development and economic growth has received a lot of attention in the economic literature in recent years. This study aims to revisit different econometric approaches used in panel data in relation of financial sector development and growth. In what follows, we extend our previous study by employing updated data and also exploring more questions related to the empirical link between financial development and growth. More specifically, we will investigate the issues relevant to static and dynamic panel data effect. We investigate the role of financial development (as measured by the credits to the private sector to GDP) in enhancing growth for different groups of countries. Estimations are conducted with a panel data of 70 countries over the period 1970-2009 using both LS (fixed effect) and GMM-Difference and GMM-System estimators for dynamic panel data. While the finding of a positive correlation between indicators of financial development and economic growth cannot settle this debate, advances in computational capacity and availability of large cross-country data sets with relatively large time dimensions have enabled researchers to rigorously explore the relationship between financial development and economic growth. Empirical results reinforce the idea that financial development promotes economic growth in all econometric approaches used in this paper.

Financialization and Its Impact on Process of Deindustrialization in the Eu

“…Hsiao (2003) and Klevmarken (1989) list several benefits from using panel models (e.g. : controlling of individual heterogeneity, more variability, less collinearity among the variables, more degrees of freedom and more efficiency of the data, etc.).…”

“…35 • no. 2 • 583-610 financial liberalisation and deregulation (Obsfeld, 1992;De Gregorio and Guidotti, 1995;Levine, 2001;Bekaert, et al, 2005;Khadraoui and Smida, 2012).…”

Is There a Non-linear Relationship between Net Trade Cycle and Corporate Performance in Turkey?

“…GMM approach is also fundamentally an instrumental variable method and it is more suitable for the analysis in which cross-section dimension is greater than time dimension (as it is case for our study) (Cameron & Trivedi, 2009). Likewise in this method it is taken into account the fact that error terms may have heteroscedasticity when two-stage calculation is chosen (Khadraoui, 2012). Hence Arellano and Bover (1995) and Blundell and Bond (1998) system Panel GMM method is used to obtain reliable results.…”

The effects of sectoral trade composition on inequality: evidence from emerging economies

“…That means we have seven periods; the first period denotes the data averaged between 1994 and 1996; the second period indicates averaged data between 1997 and 1999; and so on. We use averaged data in the regression analysis following some previous studies (Khadraoui & Smida, 2012;Seven & Coskun, 2016) which argue that averaging data solves the problem of missing data and smooths out short-run fluctuations in growth rate and it is also suitable for growth models. Although empirical literature uses three, four or five-year averages, the study uses three-year average to maximize the number of periods as well as solve missing data problems.…”