Abstract
In conventional Econometrics, the unit root and cointegration analysis are the only ways to circumvent the spurious regression which may arise from missing variable (lag values) rather than the nonstationarity process in time series data. We propose the Ghouse equation solution of autoregressive distributed lag mechanism which does not require additional work in unit root testing and bound testing. This advantage makes the proposed methodology more efficient compared to the existing cointegration procedures. The earlier tests weaken their position in comparison to it, as they had numerous linked testing procedures which further increase the size of the test and/or reduce the test power. The simplification of the Ghouse equation does not attain any such type of error, which makes it a more powerful test as compared to widely cited exiting testing methods in econometrics and statistics literature.
Highlights
The most important feature that led to development of new time series econometrics was spurious regression
Spurious regression has performed a vital role in the construction of contemporary time series econometrics and have developed many tools employed in applied macroeconomics
It is well known that ordinary least square (OLS) produces a high probability of spurious regression which increases with the increase in sample size [2]
Summary
The most important feature that led to development of new time series econometrics was spurious regression. Spurious regression is a phenomenon known to econometricians since the times of [1]. This problem was attributed to missing variables until [2] showed that it can be found in nonstationary time series even with no missing variable. Spurious regression has performed a vital role in the construction of contemporary time series econometrics and have developed many tools employed in applied macroeconomics. The widespread literature considers the nonstationarity as the only reason for spurious regression. To evade the problem of spurious regression caused by the nonstationarity, researchers frequently employed unit root and cointegration procedures
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