Abstract

Instability of regression coefficients can be an indication of structural break. This research investigated the existence of structural breaks and regression parameter instability using the Quandt Likelihood Ratio Test and the CUSUM Test. The Nigerian Real Gross Domestic Product was regressed on health and agricultural expenditure from 1984 to 2019. Five regression models were employed in this study (Linear, Logarithm, Inverse, Power and Exponential). The results revealed that the Quandt Likelihood Ratio (QLR) and CUSUM test identified instability of the regression parameters and structural break at different points for each of the models considered while the Harvey-Collier test was able to show nonlinearity in all the models, hence confirming existence of structural breaks. It was observed that both tests were seen to identify close structural breaks using the inverse model. The cumulated sum of scaled residuals shows that the inverse model and the exponential model’s scaled residual exhibited similar distribution patterns while linear, logarithm and power multiple regression models showed the same scaled residuals distribution behavior. Some of the structural breaks were seen 1998 which was the year the military regime ended, 1988, 2007, 2010 and 2015 which were the periods of change of various civilian regimes. In conclusion the study was able to show that the economic data considered requires to be spilt in other to avoid erroneous prediction of Nigeria Gross Domestic Product (GDP) based on agricultural and health expenditures.

Keywords

References

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