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IK977
The present study tries to establish a causal relationship between the nominal exchange rate and foreign direct investment in India using a time series data between 1992 and 2010. It tries to understand whether the fluctuation in the exchange rate in turn causes the change in the quantum of foreign direct investments inflows and vice-versa which is of enormous importance in the wake of unprecedented depreciation of Indian Rupee against US dollar. Our analysis uses unit root test and Johenson cointegration test to show whether the variables under consideration exhibit stationarity and a long run association respectively. The test indicates absence of any long term association between the two variables under consideration. In the present context it appears that the data is not stationary at level and is stationary at first difference. The Vector Auto regression (VAR) model depicts that the coefficients do not have any long run association.
Dr. J. V. Ramana Raju. 1970. \u201cEmpirical Analysis of the Causal Relationship between Nominal Exchange Rate and Foreign Direct Investment in India Using VAR (Vector Autoregression Model)\u201d. Unknown Journal GJMBR Volume 12 (GJMBR Volume 12 Issue 22): .
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Total Score: 107
Country: India
Subject: Uncategorized
Authors: Dr. Mayuresh S. Gokhale, J. V. Ramana Raju (PhD/Dr. count: 1)
View Count (all-time): 165
Total Views (Real + Logic): 20782
Total Downloads (simulated): 11020
Publish Date: 1970 01, Thu
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The present study tries to establish a causal relationship between the nominal exchange rate and foreign direct investment in India using a time series data between 1992 and 2010. It tries to understand whether the fluctuation in the exchange rate in turn causes the change in the quantum of foreign direct investments inflows and vice-versa which is of enormous importance in the wake of unprecedented depreciation of Indian Rupee against US dollar. Our analysis uses unit root test and Johenson cointegration test to show whether the variables under consideration exhibit stationarity and a long run association respectively. The test indicates absence of any long term association between the two variables under consideration. In the present context it appears that the data is not stationary at level and is stationary at first difference. The Vector Auto regression (VAR) model depicts that the coefficients do not have any long run association.
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