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-?)
Nicola
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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