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From |
Misha Spisok <misha.spisok@gmail.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: Re: Why include leads (in a model with lags)? |

Date |
Thu, 8 Oct 2009 13:44:41 -0700 |

Thank you for pointing out that my question is related to Granger causality. I assume that a test of Granger causality that includes leads (rather than only lags) would address my initial question. I have questions about implementing this below. I also appreciated David Greenberg's intuitive response. The short version of my new question is, "How can I test for Granger causality with more than two variables in a panel data setting?" I may be asking the wrong question, so I give more detail below. In short, -var- does not allow panel data or leads and the only suggestion I found to address this mentioned -levinlin-, the application of which is not clear to me. Going back and revising my proposed model, I suppose I should add some of the complications that I face. y_i,t = b_0 + b_1*X_i,t + b_2*X_i,t-1 + b_3*X_i,t-2 + P'Z_i,t + u_i,t To be clear, I have added a subscript 'i' to indicate that this is a panel and have also included a number of other regressors, Z_i,t, and their coefficients, P. Also, let's suppose that the Z_i,t are "accepted" as being explanatory variables for y_i,t, but testing the role of X_i,t is the goal. So the suggestion is to add leads of X_i,t to the proposed model. y_i,t = b_0 + b_1*X_i,t + b_2*X_i,t-1 + b_3*X_i,t-2 + b_4*X_i,t+1 + b_5*X_i,t+2 + P'Z_i,t + e_i,t If I understand correctly from the wiki, I would begin by estimating the following, Delta y_i,t = a_0 + a_1*Delta y_i,t-1 + ... + a_k*Delta y_i,t-k adding Delta y_i,t-k until the p-value increased (or t-stat decreased) past some threshold. The next step would be to add Delta X_i,t-j as long as the addition of Delta X_i,t-j is statistically significant and provides explanatory power. In the context of a model with additional regressors, should those regressors be included? If so, should they be included while adding Delta y_i,t-k? Or only after determining the appropriate number of lags to include of Delta y_i,t? Also, when adding Delta X_i,t-j, does the order of adding leads or lags matter? Finally, if I had, instead of only one variable of interest (here, X_i,t), I had an additional variable of interest (say, W_i,t), would the procedure be the same except that I would add incremental leads and lags of X and W at the same time? Or would it be of interest to carry out the procedure with, say, X, then repeat the procedure with W and see whether that differs from the results when carrying out the procedure with W and then X? The wiki article mentions that a test of more than two variables can be handled with vector autoregression. However, Stata's -var- command does not work on panel data (at least in Stata 10.1); moreover, -var- does not seem to allow leads (which assumes that this would be an appropriate way to test for the significance of leads). Assuming I haven't bollocksed up everything to this point, can someone suggest a "manual" way to test for Granger causality among three variables in a panel data setting? I noted a thread titled "Granger with fixed effect - panel data", but I am unsure of (1) how testing for a unit root using -levinlin- relates to Granger causality and (2) how this could be extended to two or more variables. Many thanks for your time and attention. Misha On Thu, Oct 1, 2009 at 3:55 AM, Kit Baum <baum@bc.edu> wrote: > <> > > wikipedia granger causality > > On Oct 1, 2009, at 2:33 AM, Misha wrote: > > My question in brief is, "What does including leads in a model that > 'should' only have lags tell me?" >> >> >> Is there a command in Stata (or other references, a tutorial, etc.) >> that can help me understand this (possible) problem better? > > > Kit Baum | Boston College Economics & DIW Berlin | > http://ideas.repec.org/e/pba1.html > An Introduction to Stata Programming | > http://www.stata-press.com/books/isp.html > An Introduction to Modern Econometrics Using Stata | > http://www.stata-press.com/books/imeus.html > > * > * 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/ > * * 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/

**References**:**st: Re: Why include leads (in a model with lags)?***From:*Kit Baum <baum@bc.edu>

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