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From |
Sami Alameen <samialameen@gmail.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: first-difference regression |

Date |
Wed, 28 Sep 2011 00:05:04 +0300 |

It's, I guess, a matter of of what we believe about the data: if the data is very long (t is large) and we believe the independent variable is constant, on average, over time (the sum of its differences over time should be zero) then not including a constant is ok. but usually the mean change in the independent variable is not zero especially in short panels (short t), then the constant measures the average of changes in the independent variable and a constant should be included. I don't know of a theoretical justification of which, but this piece of information is the usual practical justification. If we believe that the unemployment rate is 6 (the hypothesized natural rate), then if the difference in the unemployment rate is the independent variable, the expected value is zero, thus no constant. However, in advanced economies, in normal times, the expected and targeted inflation rate is 2% for example, then a constant is needed. (assuming a continuously updated chain price index for example) * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**Follow-Ups**:**Re: st: first-difference regression***From:*Sami Alameen <samialameen@gmail.com>

**References**:**st: first-difference regression***From:*donsaane dontsi <donsaane@yahoo.fr>

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