Tashkent institute of finance “Statistics and econometrics” department subject of econometrics phd jumayev Akbar Makhmudovich

TASHKENT INSTITUTE OF FINANCE “Statistics and econometrics” department subject of ECONOMETRICS PhD Jumayev Akbar Makhmudovich

Theme: Simultaneous Equations Models Plan: 1. Explain why estimation of a supply and demand model requires an alternative to least squares. 2. Explain the difference between exogenous and endogenous variables. 3. Define the ‘‘identification’’ problem in simultaneous equations models. 4. Define the reduced form of a simultaneous equations model and explain its usefulness. 5. Explain why it is acceptable to estimate reduced-form equations by least squares. 6. Describe the two-stage least squares estimation procedure for estimating an equation in a simultaneous equations model, and explain how it resolves the estimation problem for least squares.

The 10th lecture

Keywords

• endogenous variables
• exogenous variables
• identification
• reduced-form equation
• reduced-form errors
• reduced-form parameters
• simultaneous equations
• structural parameters
• two-stage least squares

General concept of system of equations used in Econometrics

• In previous lectures, we were concerned exclusively with single-equation models, models in which there was a single dependent variable Y and one or more explanatory variables, the X’s.
• In such models the emphasis was on estimating and/or predicting the average value of Y conditional upon the fixed values of the X variables. The cause-and-effect relationship, if any, in such models therefore ran from the X’s to the Y.

General concept of system of equations used in Econometrics

• But in many situations, such a one-way or unidirectional cause-and-effect relationship is not meaningful.
• This occurs if Y is determined by the X’s, and some of the X’s are, in turn, determined by Y.
• In short, there is a two-way, or simultaneous, relationship between Y and (some of) the X’s, which makes the distinction between dependent and explanatory variables of dubious value.