Abstract:
The study examined that the linear relationship between Gross Domestic Product (Y_t) and Money Supply (X_t) from 1981 to 2014 is spurious and could be avoided by dynamic regression modeling. The fact that spurious regression always results in misleading correlations between two time series was a big motivation for undertaking this study. Therefore, exploring data from the Central Bank of Nigeria Statistical Bulletin, we found that the linear relationship between the dependent variable (Y_t) and the independent variable (X_t) seemed spurious as the errors of the regression model were found to be autocorrelated. In a bid to correct this problem of spurious regression, we identified lags 0, -1 and -2 of X_t as predictors of Y_t using cross correlation function. Hence, the dynamic regression of current lag and past lags 1, 2 of X_t as predictors of Y_t revealed that the errors are uncorrelated and the coefficient of determination is as low as 0.2086, indicating that Y_t and X_t are totally unrelated.
Reference this Research Paper (copy & paste below code):
Emmanuel Alphonsus Akpan, Imoh Udo Moffat (2018); Dynamic Time Series Regression: A Panacea for Spurious Correlations;
Int J Sci Res Publ 6(10) (ISSN: 2250-3153). http://www.ijsrp.org/research-paper-1016.php?rp=P585910