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


From   David Greenberg <dg4@nyu.edu>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: Why include leads (in a model with lags)?
Date   Thu, 01 Oct 2009 15:30:06 -0400

Sometimes leads are included on the basis of the following reasoning: The future cannot cause its past, so if there is a relation between, say x[t+1] and y[t], it is not causal. Consequently it must reflect some type of non-causal relationship such as reverse causality or spuriousness. If that is the case it may raise questions about the nature of a relationship between x[t-1] and y[t]. 
   - David Greenberg, Sociology Department, New York University

----- Original Message -----
From: Misha Spisok <misha.spisok@gmail.com>
Date: Wednesday, September 30, 2009 8:47 pm
Subject: st: Why include leads (in a model with lags)?
To: statalist@hsphsun2.harvard.edu


> Hello, Statalist!
> 
> My question in brief is, "What does including leads in a model that
> 'should' only have lags tell me?"
> 
> My intuition is that if leads are statistically signficant, then
> something funky is going on (e.g., "How could future crime rates
> 'predict' current law enforcement expenditures?", or "How could future
> unemployment rates 'predict' current GDP growth?").  However,
> "something funky" is not intellectually satisfying.
> 
> I am considering a model of the following form:
> 
> y_t = b_0 + b_1*X_t + b_2*X_t-1 + b_3*X_t-2 + u_t
> 
> It was suggested to me to use lead values of X, e.g., estimating a
> model of the form,
> 
> y_t = b_0 + b_1*X_t + b_2*X_t-1 + b_3*X_t-2 + b_4*X_t+1 + b_5*X_t+2 + 
> e_t
> 
> If the coefficients b_4 or b_5 are statistically different from zero,
> should this be cause for alarm?  If so, why?
> 
> Is there a command in Stata (or other references, a tutorial, etc.)
> that can help me understand this (possible) problem better?
> 
> Best,
> 
> Misha
> Using Stata 10.1
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