Regression: Insignificant Intercept





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I ran a regression and the intercept is statistically insignificant (the p-value is greater than 0.05). I tried to look in some textbooks as to how to handle this problem but I am still unsure. One textbook I looked at 'Basic Econometrics'by Gujarati and Porter says that if the intercept is insignificant then we have a regression through the origin and that if we remove the intercept, in this case, the model will be more precise. On the other hand, 'Introductory Econometrics'by Chris Brooks says that even if the intercept is insignificant, we should not remove it from the model.



Which one of these textbooks is correct? Should I leave the insignificant intercept in the model or run a regression through the origin?










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    I ran a regression and the intercept is statistically insignificant (the p-value is greater than 0.05). I tried to look in some textbooks as to how to handle this problem but I am still unsure. One textbook I looked at 'Basic Econometrics'by Gujarati and Porter says that if the intercept is insignificant then we have a regression through the origin and that if we remove the intercept, in this case, the model will be more precise. On the other hand, 'Introductory Econometrics'by Chris Brooks says that even if the intercept is insignificant, we should not remove it from the model.



    Which one of these textbooks is correct? Should I leave the insignificant intercept in the model or run a regression through the origin?










    share|cite|improve this question
























      up vote
      1
      down vote

      favorite









      up vote
      1
      down vote

      favorite











      I ran a regression and the intercept is statistically insignificant (the p-value is greater than 0.05). I tried to look in some textbooks as to how to handle this problem but I am still unsure. One textbook I looked at 'Basic Econometrics'by Gujarati and Porter says that if the intercept is insignificant then we have a regression through the origin and that if we remove the intercept, in this case, the model will be more precise. On the other hand, 'Introductory Econometrics'by Chris Brooks says that even if the intercept is insignificant, we should not remove it from the model.



      Which one of these textbooks is correct? Should I leave the insignificant intercept in the model or run a regression through the origin?










      share|cite|improve this question













      I ran a regression and the intercept is statistically insignificant (the p-value is greater than 0.05). I tried to look in some textbooks as to how to handle this problem but I am still unsure. One textbook I looked at 'Basic Econometrics'by Gujarati and Porter says that if the intercept is insignificant then we have a regression through the origin and that if we remove the intercept, in this case, the model will be more precise. On the other hand, 'Introductory Econometrics'by Chris Brooks says that even if the intercept is insignificant, we should not remove it from the model.



      Which one of these textbooks is correct? Should I leave the insignificant intercept in the model or run a regression through the origin?







      regression linear-model intercept






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      user198848

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          If the regression line pass through point (0,0) physically, then excluded intercept, otherwise keep the intercept even it is not significant. One example of the regression line pass through point (0,0) physically is: response variable (Y) is distance the can run, and the covariate (X) is volume of gasoline consumed by the car. When X = 0, Y = 0.






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            If the regression line pass through point (0,0) physically, then excluded intercept, otherwise keep the intercept even it is not significant. One example of the regression line pass through point (0,0) physically is: response variable (Y) is distance the can run, and the covariate (X) is volume of gasoline consumed by the car. When X = 0, Y = 0.






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              If the regression line pass through point (0,0) physically, then excluded intercept, otherwise keep the intercept even it is not significant. One example of the regression line pass through point (0,0) physically is: response variable (Y) is distance the can run, and the covariate (X) is volume of gasoline consumed by the car. When X = 0, Y = 0.






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                up vote
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                down vote










                up vote
                2
                down vote









                If the regression line pass through point (0,0) physically, then excluded intercept, otherwise keep the intercept even it is not significant. One example of the regression line pass through point (0,0) physically is: response variable (Y) is distance the can run, and the covariate (X) is volume of gasoline consumed by the car. When X = 0, Y = 0.






                share|cite|improve this answer












                If the regression line pass through point (0,0) physically, then excluded intercept, otherwise keep the intercept even it is not significant. One example of the regression line pass through point (0,0) physically is: response variable (Y) is distance the can run, and the covariate (X) is volume of gasoline consumed by the car. When X = 0, Y = 0.







                share|cite|improve this answer












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                share|cite|improve this answer










                answered 1 hour ago









                user158565

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