ABSTRACT
In recent years, numerous studies demonstrated that the effect of exchange rate regimes on economic growth is influenced by several factors. However, the literature rarely takes into account the possible costs associated with improving institutional quality on the choice of exchange systems and the analysis of the effects of shocks in the case of each type of regime. Throughout this research, we analyze the extent of bidirectional shocks according to each regime and compare the shock effects accordingly. The results show that the real exchange rate is less volatile and the shock effect is lower in countries that adopt a fixed exchange rate regime while the exchange rate is more volatile and the shock is higher in countries that adopt a flexible exchange rate regime. To show the effect and persistence of shocks, we carried out a Panel-VAR regression completed by impulse response functions, VAR decomposition and Granger causality tests for 20 countries adopting the first type of exchange regime compared with 20 countries practicing an alternative exchange rate regime in the period from 1996 to 2012.
Disclosure statement
No potential conflict of interest was reported by the authors.
Notes
1 Even if this study is in the same direction of our paper, it differs from our work in the sense that it is a static analysis not specifying the nature of this relationship and does not provide a detailed analysis of the links between exchange rate volatility and real economy over a longer period depending on the nature of the exchange rate regime.
2 Major studies confirm non-neutrality of exchange rate regime in explaining exchange volatility effect on economic fundamentals without analyzing or assessing this effect which can support originality of our work.
3 Note that the growth model contains other variables such as government size, initial per capita income, population growth, trade openness and M2 to reserves ratio (Barro, Citation1991) but for the simplicity of the analysis we take only three variables which will be subject to our analysis.
4 With the presence of delayed dependent variables in the right side of the system of equations, estimates would be biased even with a large number of delays (Nickell, Citation1981). Although the bias is close to zero, the time T is of high value. The simulations by Judson and Owen (Citation1999) show a large bias even when T = 30.
5 We assume that variables are endogenous.
6 It is done by determining how much of an s-step ahead MSE forecast error variance for each variable is explained by innovations to each explanatory variable (we report s until 10).
7 To avoid redundancy, we note that responses of governance composite index are not statistically significant for all shocks.
Additional information
Notes on contributors
Salma Haj fraj
Fraj Salma Hadj Fraj is a PhD student in economics from the Tunisian University of El Manar, Tunisia, and is currently a contractual assistant in economics at the Department of Economics of the Higher Institute of Applied Sciences and Technology of Sousse. Her research interests include exchange markets, exchange rate regime, economic policy, governance and the finance-growth relationship.
Mekki Hamdaoui
Dr. Mekki hamdaoui holds a PhD in Economics from University of Tunis El Manar, Tunisia, and is currently a Contractual Assistant of Economics in the Department Economics, Faculty of Economic Sciences and Management of Sousse. His areas of research interests include exchange markets, financial crisis and related issues, finance-growth relationship, inequality of opportunity with special focus in Tunisia.
Samir Maktouf
Mr. Samir Maktouf holds a PhD in economics from University of Montreal, Canada, and is currently a professor of Economics in the Department Economics, Faculty of Economic Sciences and Management of Tunis El Manar. His area of research interests includes exchange issues, international economics, finance growth relationship, environmental economics, poverty, economic policies.