This dissertation is intended to provide a statistical foundation for the IV models and shed lights on a number of issues related to the IV method. The first chapter shows that the theoretical Instrumental Variable model can be derived by reparameterization of a well-specified statistical model defined on the joint distribution of the involved random variables as the actual (local) data generation process. This reveals the covariance structure of the error terms of the usual theory-driven instrumental variable model. The revealed covariance structure of the IV model have important implications, particularly, for designing simulation studies. Monte Carlo simulations are used to reexamine the Nelson and Startz (1990a) findings regarding the performance of IV estimators when the instruments are weak. The results from the simulation exercises indicate that the sampling distribution of ^Î _IV is concentrated around ^Î _OLS. The second chapter considers the underlying joint distribution function of the instrumental variable (IV) model and presents an alternative definition for the exogenous and relevant instruments. The paper extracts a system of independent and orthogonal equations that covers up a non-orthogonal structural model and argues that the estimated IV regression is well-specified if the underlying system of equations is well-specified. It proposes a new instrument relevancy measure that does not suffer from the first-stage <i>R²</i> deficiencies. Third chapter argues the application of the IV method in estimation of models with omitted variable. The paper considers the implicit parametrization of statistical models and presents five conditions for an appropriate instruments. Two of them are empirically measurable and can be tested. This improves the literature by adding one more objective criterion for the selection of instruments. This chapter applies the IV method to estimate the rate of return to education in Iran. It argues that the education of two cohorts of Iranians was delayed or cut short by the Cultural Revolution. Therefore, the Cultural Revolution, as an exogenous shock to the supply of education, establishes the year of birth as the exogenous and relevant instrument for education. Using the standard Mincerian earnings function with control for experience, ethnicity, location of residence and sector of employment, the instrumental variable estimate of the return to schooling is equal to 5.6&#37;. The estimation results indicate that the Iranian labor market values degrees more than years of schooling. / Ph. D.

Diploma thesis deals with designing of algorithmus for automatic controller tunning for DC motors. Automatic tuning function consist of system identification and controller parametrization. Cascade control loop was chosen for its robustness and proper DC motor control. For electric system identification of DC motor was used recursive method of instrumental variables, because of noisy signal from current transducer. In the case of identification mechanical system, there were used least sqares method. According to identified parameters, current controller was parametrized by optimum module and revolution controller according symetrcal optimum.