Ramin Khochiani; Younes Nademi
Abstract
The purpose of this paper is to revisit the relationship between inflation and output gap by using wavelet coherence approach. This approach attempts to combine the classical time series analysis with frequency domain analysis, and presents the advantages of assessing the co-movement of two series in ...
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The purpose of this paper is to revisit the relationship between inflation and output gap by using wavelet coherence approach. This approach attempts to combine the classical time series analysis with frequency domain analysis, and presents the advantages of assessing the co-movement of two series in the context of both time and frequency dimentions. Using continuous wavelet transform approach, the relationship between inflation and output gap, by considering GDP with oil sector and without oil sector, was studied by annual and quarterly data from 1959 to 2016 in Iran. The results showed that in the long run, the relashionship between inflation and output gap is positive. This result confirms existence of a Phillips curve with negative slope in the long run. However, the relationship between the two variables in the short term and also for the period before Islamic Revolution reflects a Phillips curve with positive slope. Friedman noted this type of curve for high inflation economies for a period of several years in 1977 in his Nobel Prize lecture. This result could have been very important in testing Phillips curve theory in Iranian economy.
reza tehani; Shapur Mohammadi; Arash Mohamadalizadeh
Volume 11, Issue 41 , July 2011, , Pages 225-244
Abstract
This paper presents a new perspective on the Fisher hypothesis, which states a positiverelationship between nominal stock returns and inflation. The new approach is based on a waveletmultiscaling method that decomposes a given time series on a scale-by-scale basis. The time series of inflation and stock ...
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This paper presents a new perspective on the Fisher hypothesis, which states a positiverelationship between nominal stock returns and inflation. The new approach is based on a waveletmultiscaling method that decomposes a given time series on a scale-by-scale basis. The time series of inflation and stock return are decomposed into three wavelet details and one wavelet smooth. Empirical results show that there is a positive relationship between stock returns and inflation at 2month period and at 8-month period, while a negative relationship is shown 4-month period. Also,no significant relationship was revealed in one month time horizon. This indicates that the nominal return results are supportive of the Fisher hypothesis for risky Assets in d2 and s3 of the wavelet domain, while the stock returns do not play a role as an inflation hedge at one month and four month timescales.
