Central bank intervention and exchange rate behaviour : empirical evidence for India

This paper examines the causal relationship between central bank intervention and exchange returns in India. Using monthly data from December 1997 to December 2011, the empirical results derived from the CCF approach of Cheung and Ng (1996) suggest that there is causality-in-variance from exchange rate returns to central bank intervention, but not vice versa. These findings are robust in the sense that they hold in cases where the returns were measured from either the spot rate or the forward rate. Therefore, the results of this paper suggest that the Indian central bank has intervened in the foreign exchange market to respond to exchange rate volatility, although the volatility has not been influenced by central bank intervention in the form of net purchases of foreign currency in the market.

The causal relationships in mean and variance between stock returns and foreign institutional investment in India

This paper examines the causalities in mean and variance between stock returns and Foreign Institutional Investment (FII) in India. The analysis in this paper applies the Cross Correlation Function approach from Cheung and Ng (1996), and uses daily data for the timeframe of January 1999 to March 2008 divided into two periods before and after May 2003. Empirical results showed that there are uni-directional causalities in mean and variance from stock returns to FII flows irrelevant of the sample periods, while the reverse causalities in mean and variance are only found in the period beginning with 2003. These results point to FII flows having exerted an impact on the movement of Indian stock prices during the more recent period.

Causality Relationships between Total Exports with Agricultural and Manufacturing GDP in Tanzania

This paper, investigates causal relationships among agriculture, manufacturing and export in Tanzania by using time series data for the period between 1970 and 2005. The empirical results show in both sectors there is Granger causality where agriculture causes both exports and manufacturing. Exports also cause both agricultural GDP and manufacturing GDP and any two variables out of three jointly cause the third one. There is also some evidence that manufacturing does not cause export and agriculture. Regarding cointegration, pairwise agricultural GDP and export are cointegrated, export and manufacture are cointegrated. Agriculture and manufacture are cointegrated but they are lag sensitive. However, three variables, manufacturing, export and agriculture both together are cointegrated showing that they share long run relation and this has important economic implications.