Notice: On March 31, it was **announced** that Statalist is moving from an email list to a **forum**. The old list will shut down at the end of May, and its replacement, **statalist.org** is already up and running.

[Date Prev][Date Next][Thread Prev][Thread Next][Date Index][Thread Index]

From |
Christopher Baum <kit.baum@bc.edu> |

To |
"statalist@hsphsun2.harvard.edu" <statalist@hsphsun2.harvard.edu> |

Subject |
st: Re: ivreg2 questions |

Date |
Tue, 20 Mar 2012 08:02:49 -0400 |

<> On Mar 20, 2012, at 2:33 AM, Rob wrote: > Sorry for what is purely an econometric question at this point > (removed from Stata) but there is still one thing that I am > misunderstanding. In every text I can read, it basically says the > instrument must be correlated with the endogenous regressor (including > Mostly Harmless Econometrics and an Introduction to Modern > Econometrics Using Stata to name 2 - the latter stating the instrument > must be highly correlated). These texts do not state that the > instrument must have a high correlation with the endogenous regressor > with the effect of a set of controlling variables removed (partial > correlation). Is this just a simplification on the part of these > texts or again is there something I am missing? And does this > basically mean that the validity of an instrument is conditional on > the other independent variables included in the primary model and not > just the dependent variable and the endogenous regressor? Yes. It should be understood that when we say that an excluded instrument be highly correlated with the endogenous variable(s), that correlation is a partial correlation, reflected by the partial regression coefficient in the 'first stage regression'. Consider a case where Fahrenheit temp is an included exogenous regressor, and you attempt to use Celsius temp as an excluded instrument. The instrument matrix will be rank-deficient. Now consider using Fahrenheit temp + epsilon as an excluded instrument, where epsilon is random noise. The 'first-stage regression' (projection of endog on all exog) will be computable, but the marginal value of your excluded instrument is very low, as it really contains no marginal information that can be used to identify the model. So even though temperature may be highly correlated to the endogenous regressor (say, quantity traded in the market), and you have satisfied the rank and order conditions, the model has weak instrument problems which relate to the very low partial correlation. I suppose we could speak of the simple correlation between endogenous and excluded instrument if we added the caveat that the instrument matrix was far from ill-conditioned, but that is a harder concept to motivate and test. Kit 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/

**Follow-Ups**:**Re: st: Re: ivreg2 questions***From:*Robert Davidson <rhd773@gmail.com>

- Prev by Date:
**RE: st: Brown et al decomposition of the gender wage gap** - Next by Date:
**Re: st: xtmelogit_ 3200 conformability error** - Previous by thread:
**st: gologit2 for ordered three level dependent variable** - Next by thread:
**Re: st: Re: ivreg2 questions** - Index(es):