Nonlinear Instrumental Variable Estimation of Autoregression
Instrumental variable (IV) estimation methods that allow for certain nonlinear functions of the data as instruments are studied. The context of the discussion is the simple unit root model where certain advantages to the use of nonlinear instruments are revealed. In particular, certain classes of IV estimators and associated t -tests are shown to have simpler (standard) limit theory in contrast to the least squares estimator, providing an opportunity for the study of optimal estimation in certain IV classes and furnishing tests and conﬁdence intervals that allow for unit root and stationary alternatives. The Cauchy estimator studied in recent work by So and Shin (1999) is shown to have such an optimality property in the class of certain IV procedures with bounded instruments.
Phillips, Peter C.B.; Park, Joon Y.; and Chang, Yoosoon, "Nonlinear Instrumental Variable Estimation of Autoregression" (2001). Cowles Foundation Discussion Papers. 1593.