Dear Stata-users,
I am working with panel data and I have the following issue. I first made a regression using the regular iv estimation, with 4 excluded instruments for one potential endogenous variable.
However, since I am working with panel data and I suspect the presence of time-invariant unobservables to create endogeneity, I also have performed a fixed-effects estimation (with the same instruments as above). I included clustered standard errors in both.
The problem is that my instruments are not weak when using regular IV, but they are weak when adding the fixed effects (Kleibergen-Paap rk Wald F statistic is much smaller than the critical values reported). Below I report my steps and the outcomes for the fixed effects.
My question is: is there something I can do to still use fixed effects together with instruments? I have already tried different instruments but my data set is limited and none of them improved the situation. I have done quite an extensive literature research but have not found a method that can do inference with weak instruments in IV. Please note, I am aware of the 'weakiv' module but this does inference only for the endogenous variable.
Please let me know if my question is unclear. Thank you for your time and consideration.
I am working with panel data and I have the following issue. I first made a regression using the regular iv estimation, with 4 excluded instruments for one potential endogenous variable.
However, since I am working with panel data and I suspect the presence of time-invariant unobservables to create endogeneity, I also have performed a fixed-effects estimation (with the same instruments as above). I included clustered standard errors in both.
The problem is that my instruments are not weak when using regular IV, but they are weak when adding the fixed effects (Kleibergen-Paap rk Wald F statistic is much smaller than the critical values reported). Below I report my steps and the outcomes for the fixed effects.
Code:
ivreg2 some_variable (isntrumentedvariable = 5 instruments ) some _othervariables, cluster(hhidpn) ffirst xtivreg2 some_variable (isntrumentedvariable = 5 instruments ) some _othervariables, cluster(hhidpn) ffirst fe
Code:
Underidentification test (Kleibergen-Paap rk LM statistic): 11.188 Chi-sq(3) P-val = 0.0108 ------------------------------------------------------------------------------ Weak identification test (Cragg-Donald Wald F statistic): 5.243 (Kleibergen-Paap rk Wald F statistic): 3.655 Stock-Yogo weak ID test critical values: 5% maximal IV relative bias 13.91 10% maximal IV relative bias 9.08 20% maximal IV relative bias 6.46 30% maximal IV relative bias 5.39 10% maximal IV size 22.30 15% maximal IV size 12.83 20% maximal IV size 9.54 25% maximal IV size 7.80 Source: Stock-Yogo (2005). Reproduced by permission. NB: Critical values are for Cragg-Donald F statistic and i.i.d. errors. ------------------------------------------------------------------------------ Hansen J statistic (overidentification test of all instruments): 1.310 Chi-sq(2) P-val = 0.5195 ------------------------------------------------------------------------------
Please let me know if my question is unclear. Thank you for your time and consideration.