The Macroeconomic Performance of the Inflation Targeting Policy: An Approach Based on the Evolutionary Co-spectral Analysis

Zied Ftiti ()

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Abstract: This paper proposes a new methodology to check the economic performance of a monetary policy and in particular the inflation targeting policy (ITP). The main idea of this work is to consider the ITP as economically efficient when it generates a stable monetary environment. The latter is considered as stable when a long-run equilibrium exists to which the paths of economic variables (inflation rate, interest rate and GDP growth) converge. The convergence of the variables' paths implies that these variables are more predictable and implies a lower degree of uncertainty in the economic environment. To measure the degree of convergence between economic variables, we propose, in this paper, a dynamic time-varying variable presented in the frequency approach named cohesion. This variable is estimated from the evolutionary co-spectral theory as defined by Priestley and Tong (1973) and Priestley (1988-1996). We apply this theory to the measure of cohesion presented by Croux et al (2001) to obtain a dynamic time-varying measure. In the last step of the study, we apply the Bai and Perron test (1998-2003b) to determine the change in the cohesion path. The results show that the implementation of the ITP generates a high degree of convergence between economic series that implies less uncertainty into the monetary environment. We conclude that the inflation targeting generates a stable monetary environment. This result allows us to conclude that the ITP is relevant in the case of industrialized countries.

Keywords: Inflation Targeting; Co-Spectral Analysis; Cohesion; Stability Environment; Economic Performance and Structural Change (search for similar items in EconPapers)
Date: 2009
Note: View the original document on HAL open archive server: https://shs.hal.science/halshs-00422662v1
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Published in 2009

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:halshs-00422662

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