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From |
Rashmi Shankar <rashmi@brandeis.edu> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: help on granger causality |

Date |
Tue, 28 Jun 2005 13:02:53 -0400 |

Thank you very much, Mike. Rashmi Quoting "Michael S. Hanson" <mshanson@mac.com>: > On Jun 27, 2005, at 4:56 PM, Rashmi Shankar wrote: > > > Hi, all: After running a var in first differences, 4 lags, I use > > vargranger to > > run a pair-wise causality test. The output is as follows. How do I > > interpret > > the causality test result? > > > > . var bp_level lnpetrol lndomcred if cnum==1,lags(1/4) > > [output deleted] > > > . vargranger > > > > Granger causality Wald tests > > +------------------------------------------------------------------+ > > | Equation Excluded | chi2 df Prob > chi2 | > > |--------------------------------------+---------------------------| > > | bp_level lnpetrol | 14.108 4 0.007 | > > | bp_level lndomcred | 6.0917 4 0.192 | > > | bp_level ALL | 19.279 8 0.013 | > > |--------------------------------------+---------------------------| > > | lnpetrol bp_level | 5.9199 4 0.205 | > > | lnpetrol lndomcred | 5.4121 4 0.248 | > > | lnpetrol ALL | 10.121 8 0.257 | > > |--------------------------------------+---------------------------| > > | lndomcred bp_level | 49.78 4 0.000 | > > | lndomcred lnpetrol | 7.3881 4 0.117 | > > | lndomcred ALL | 57.215 8 0.000 | > > +------------------------------------------------------------------+ > > "Granger causality" tests -- or more correctly perhaps, Granger > non-causality tests -- are statistical tests of "causality" in the > sense of determining whether lagged observations of another variable > have incremental forecasting power when added to a univariate > autoregressive representation of a variable. > > The test itself is just an F-test (or, as above, a chi-squared test) > of the joint significance of the other variable(s) in a regression that > includes lags of the dependent variable. For example: in your above > results, at traditional levels of significance, one would reject the > null hypothesis that 'lnpetrol' does not "Granger cause" 'bp_level'. > On the other hand, at traditional significance levels, one would reject > Granger causality of either 'bp_level' or 'lndomcred' for 'lnpetrol'. > That is, neither of these variables appear to have incremental > forecasting power for 'lnpetrol' once one conditions on 4 of its own > lags. > > It is very important to understand what Granger causality is _not_. > First, it cannot establish causality in a theoretical sense. In a > classic example, a rooster may "Granger cause" the sunrise. Second, > Granger causality tests may be misleading if, for example, the > processes determining the variables of interest involve expectations. > Third, Granger causality is not a test for strict exogeneity. For > these issues and additional critiques of the (mis-)use of Granger > causality, consult any of the textbooks mentioned in the [TS] entry for > -vargranger-, such as Luetkepohl (1993), pp. 35-43, Hamilton (1994), > pp. 302-309, or Enders (2004), pp. 283-287 and 357-358. > > -- Mike > > * > * For searches and help try: > * http://www.stata.com/support/faqs/res/findit.html > * http://www.stata.com/support/statalist/faq > * http://www.ats.ucla.edu/stat/stata/ > -- Rashmi Shankar Asst. Professor, Department of Economics, Brandeis International Business School Brandeis University, 415 South Street, Waltham, MA 02454 Phone: 781-736-2265 Fax: 781-736-2269 * * For searches and help try: * http://www.stata.com/support/faqs/res/findit.html * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**References**:**st: help on granger causality***From:*Rashmi Shankar <rashmi@brandeis.edu>

**Re: st: help on granger causality***From:*"Michael S. Hanson" <mshanson@mac.com>

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