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Showing 2 results for Granger Causality

Hamid Abrishami, Mohesn Mehara, Mahdi Nouri, Mohsen Mohaghegh,
Volume 1, Issue 1 (10-2010)
Abstract

  The aim of this study is to review the causal relations between TFP growth and inflation as one of the attracting issues in Macroeconomic literature. For the first time in Iran, we have used the wavelet decomposition technique to study this relation. Both TFP growth and inflation series between 1960-2006 are decomposed up to three levels. Our analysis of causality relations between all the composed and decomposed series shows that though no statically meaningful effect between original series has been proved, there are some negative relations between decomposed series in first and second level. Moreover, our study reveals some previously unknown spillover effects between various frequencies of both series as explained in paper. Finally, on the basis of relations founded between decomposed series of inflation in different frequencies, we introduce a new instrument to measure the volatility of inflation.


Abed Abbasidarkhaneh, Farid Askari, Abdolrahim Hashemi Dizaj,
Volume 11, Issue 42 (12-2020)
Abstract

In this study, using linear and nonlinear Granger causality methods and regression switching, the relationships between the returns of important industry indices in the period 2008 to 2019 in order to invest in economic growth and development were examined. Based on the results obtained in the two periods of 2008 to 2013 and 2018 to 2019: 6, the relationship between the returns of the studied industry index has reached the highest value. In the linear Granger causality approach based on centrality criteria, the returns of metals index, machinery and investment are the most important and the returns of communication and banking index are the least important. It can also be said that the degree of effectiveness and efficiency of industry index returns is well affected by the amount of stock market fluctuations and this importance is asymmetric. In the nonlinear Granger causality approach based on the centrality criterion, the communication sector is the least important and the basic metals, chemical and machinery industries are the most important. In the period 2018 to 2019, the banking sector, automotive and communications industries are the most important and oil and metal products are the least important for investment.

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