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Re: st: Binary variables and ivreg2

From   [email protected]
To   [email protected]
Subject   Re: st: Binary variables and ivreg2
Date   Sat, 01 Sep 2007 12:42:09 +0200

No problem about using dummy variables as instruments. Sorry, no suggestions for the underidentification problem (can you move to some panel methods which don't need instruments, like fixed effects or -xtabond-?)


At 02.33 30/08/2007 -0400, Jeremy Cheesman wrote:
>I am estimating a "quasi-dated" water crop production function. My dataset
>contains variables describing the average amount of water applied per
>irrigation, the length of the irrigation season in days (IrrS), the average
>number of days between irrigation events (IrrD) and dummy variables for 4
>climatic zones (with each respondent belonging to one climate zone only).
>The start of the crop's irrigation season is determined by the end of the
>local wet season. The length of the irrigation season is also determined by
>the length of the dry season. It is logical to assume that IrrS is
>endogenous to local climate conditions. IrrD could also be endogenous.
>I have modelled a 2SLS using ivreg2 defining Clim2 Clim3 Clim4 as
>instruments for IrrS and lnIrrS. It's my first time estimating such models.
>The Durbin-Wu-Hausman chi-sq test is signficant and the Sargan statistic is
>insignificant. I have done the same with (IrrD lnIrrD = Clim2 Clim3 Clim4)
>and get a significant DWH and insignificant Sargan result. The results
>suggest I should treat all 4 irrigation timing variables as endogenous, but
>I cant do this because of underidentification. Can anyone suggest a way to
>get around this problem? I can't get anymore data and I don't want to have
>to drop IrrD lnIrrD from the model as these are key variables. I am also
>wondering if there is any problem with using dummy variables as instruments?
>I haven't found any literature on this and just want to confirm what I am
>doing is OK.
>Many thanks 
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