Applications of Robust Regression Techniques: An Econometric Approach. (29th May 2021)

• Record Type: Journal Article
• Authors: Khan, Dost Muhammad; Yaqoob, Anum; Zubair, Seema; Khan, Muhammad Azam; Ahmad, Zubair; Alamri, Osama Abdulaziz
• Other Names: Al-Omari Amer Academic Editor.
• Is Part Of: Mathematical problems in engineering. Volume 2021(2021)
• Publication Date: 2021-05-29
• Subjects: Engineering mathematics -- Periodicals; 510.2462
• DOI: 10.1155/2021/6525079
• Languages: English
• ISSNs: 1024-123X

Abstract

Abstract : Consistent estimation techniques need to be implemented to obtain robust empirical outcomes which help policymakers formulating public policies. Therefore, we implement the least squares (LS) and the high breakdown robust least trimmed squares (LTS) regression techniques, while using econometric regression model based on a growth equation for the two countries, namely, India and Pakistan. We used secondary annual time series data which covers a long period of 41 years. The adequacy of the time series econometric model was checked through cointegration analysis and found that there is no spurious regression. Classical and robust procedures were employed for the estimation of the parameters. The empirical results reveal that the overall fit of the model improves in case of LTS technique, while the significance of the predictors changes significantly in cases of both countries due to the removal of outliers from the data. Thus, empirical findings exhibit that the results, obtained through LTS, are better than LS techniques.