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- W1497100165 abstract "In practice structural equations are often estimated by least-squares, thus ne- glecting any simultaneity. This paper reveals why this may often be justifiable and when. Assuming data stationarity and existence of the first four moments of the disturbances we study the limiting distribution of the ordinary least-squares (OLS) estimator in a linear simultaneous equations model. In simple static mod- els we compare the asymptotic e¢ ciency of this inconsistent estimator with that of consistent simple instrumental variable (IV) estimators and depict cases where - due to relative weakness of the instruments or mildness of the simultaneity - the inconsistent estimator is more precise. In addition, we examine by simulation to what extent these first-order asymptotic findings are reflected in finite sam- ples, taking into account non-existence of moments of the IV estimator. In all comparisons we distinguish between conditional and unconditional (asymptotic) distributions. By dynamic visualization techniques we enable to appreciate any di¤erences in e¢ ciency over a parameter space of a much higher dimension than just two, viz. in colored animated image sequences (which are not very e¤ective in print, but much more so in live-on-screen projection)." @default.
- W1497100165 created "2016-06-24" @default.
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- W1497100165 date "2009-01-01" @default.
- W1497100165 modified "2023-09-23" @default.
- W1497100165 title "The asymptotic and finite sample (un)conditional distributions of OLS and simple IV in simultaneous equations" @default.
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