Why Do We Believe in God? An Analysis of the Motives of the Believing Behaviour in Human Beings

This article explores the motives of the human believing behaviour. The author postulates that to believe in God is natural and not to believe is a deviation from the true and pure human nature. This fact has, also, been admitted by many philosophers, psychologists and geneticists. A brief debate with reference to philosophy, anthropology, psychology and genetics has been presented to have a review the opinions of some eminent philosophers, psychologists and anthropologists about the believing behavior of the human nature. The traces of the religiosity of the primitive tribes without exception are a further evidence for the said fact. Some evidences have been presented from history and also from the examples of some living primitive tribes of Australia and Africa to accentuate the stance that to believe in God is a natural, innate, instinctual motive in the human nature. Author also quotes certain verses from the Qur’an to confirm the conformity of the historical, philosophical, psychological and genetical facts and findings with the Qur’anic stance about the believing behaviour of the human nature. The motives behind human behaviour in believing God are counted by the author as: rationality, anxiousness for God and the Life hereafter, Love of God, Affiliation with the native culture, Influence and Inspiration, Religion: A Remedy or Solution and Preaching in Terms of addresses.

Dynamics of Exchange Rate and Stock Prices: A Study on Emerging Asian Economies

The Purpose of this study is to explore the behavior of exchange rates in five Asian economies; namely Pakistan, India, Indonesia, Korea and Sri Lanka. The causality between capital and currency markets has been investigated in the first section of study. In second section, the link between exchange rate and economic variables has been scrutinized, while in the third section, forecasting performance of economic models has been compared with that of random walk and autoregressive integrated moving average model. Using Granger Causality test and Johansen Cointegration, the causality between stock and currency markets has been explored. Link between macro economic fundamentals and exchange rates has been investigated using ordinary least square method and Johansen’s cointegration, while forecasting performance of economic models has been compared with that of random walk and autoregressive integrated moving average model using one graphical and four statistical measures. These measures are Perfect Forecast Line (PFL), Root Mean Square Error (RMSE), Mean Absolute Error (MAE), Median of Absolute Deviation (MAD) and Success Ratio (SR). Nature of short run causality between stock and currency markets has been found different in different countries. In Pakistan and Sri Lanka, causality runs from stock market to currency market while feed back relationship has been found in case of Indonesia and Korea. In India, causality running from exchange rate to stock market has been found significant. However, no long run causality between stock and currency markets has been found in sample economies. Thus these two financial markets support asset market theory in the long run. However, regression analysis proves that economic variables are not senseless, whereas Johansen cointegration technique affirm the existence of long run relationship between exchange rate and macro economic variables. Johansen’s cointegration reports three cointegrating equations in Pakistan, India, Korea and Sri Lanka while two cointegration equations in case of Indonesia. Vector Error Correction Mechanism has been applied to gauge the speed of adjustment in relationship between exchange rate and macroeconomic fundamentals. Lastly predictive capacity of economic fundamentals based models namely Purchasing Power Parity, Interest Rate Parity and Adhoc model has been compared to that of Random Walk and Autoregressive Integrated Moving Average Model. In the sample forecasting has been used for comparison. Predictive capacity has been investigated using one graphical method called Perfect Forecast Line and four statistical methods. Statistical xiimethods include Root Mean Square Error, Mean Absolute Error, Median of Absolute Deviation and Success Ratio. All the four measures support fundamentals based approaches in all the sample economies except Indonesia where Random Walk Model has the power to beat fundamentals’ based approaches on the basis of all the four measures of statistical evaluation.