Eviews 3 stage least squares near singular matrix

AI Thread Summary
The discussion centers on a replication paper where the author faces a "near singular matrix" error while attempting to run a system of equations in Eviews for a model with four endogenous variables and two instruments. The author originally runs four separate regressions due to under-identification but seeks to extend the analysis by considering correlated error terms across equations. The model includes fixed effects for eight countries and various culture variables, using the same instruments for each equation. Ultimately, the author resolves the issue by recognizing that including all equations in the system does not address the under-identification problem, leading to the conclusion that limiting the model to two equations eliminates the error. The discussion highlights the importance of addressing identification issues in econometric modeling.
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I'm doing a replication paper and having a bit of issues. The author uses 2 instruments and has 4 endogenous variables. Since he is under-identified, he runs 4 separate regressions, so that each equation has 1 overidentifying restrictions. I want to extend this and run the four equations as a system, because I'm sure that the error terms for each equation is correlated. however, every time I run this, I get a "near singular matrix" error. I have written my system below.

essentially, I control for the fixed effects for the 8 countries in my data set, schooling, and urbanization in 1850. Each equation has a different variable that measure culture (control, obedience, tolerance, and trust). I am using the same instruments of institutions and literacy for each equation. so the only difference with each equation is which culture variable is being used.

System:

gdp_pc_ca9500= C(1)*country1 + C(2)*country15 + C(3)*country2 + C(4)*country3 + C(5)*country4 + C(6)*country5 + C(7)*country7 + C(8)*country8 + C(9)*school + C(10)*urb_1860_1850_30 + C(100)*control

gdp_pc_ca9500= C(12)*country1 + C(12)*country15 + C(14)*country2 + C(15)*country3 + C(16)*country4 + C(17)*country5 + C(18)*country7 + C(19)*country8 + C(20)*school + C(21)*urb_1860_1850_30 + C(101)*obedience

gdp_pc_ca9500= C(23)*country1 + C(24)*country15 + C(25)*country2 + C(26)*country3 + C(27)*country4 + C(28)*country5 + C(29)*country7 + C(30)*country8 + C(31)*school + C(32)*urb_1860_1850_30 + C(102)*tolerance

gdp_pc_ca9500= C(34)*country1 + C(35)*country15 + C(36)*country2 + C(37)*country3 + C(38)*country4 + C(39)*country5 + C(40)*country7 + C(41)*country8 + C(42)*school + C(43)*urb_1860_1850_30 + C(104)*trust

@inst pc_institutions literacy1880

My question is whether or not my problem lies in bad programming (if you can call eviews programming), or in something I'm missing in the theory. If I do it in 3SLS or Multiple equation Generalized method of moments, I get the near singular matrix error (which makes sense, since 3SLS is a special case of GMM).

I would appreciate any help
 
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Nevermind: I figured out the problem. Putting it in a system doesn't solve the under-identification problem, and the near singular matrix issue goes away when I only included 2 of the equations/
 
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