Estimation of M-equation Linear Models Subject to a Constraint on the Endogenous Variables Estimation of M-equation Linear Models Subject to a Constraint on the Endogenous Variables
Routledge Library Editions: Econometrics

Estimation of M-equation Linear Models Subject to a Constraint on the Endogenous Variables

    • $45.99
    • $45.99

Publisher Description

Originally published in 1984. This book brings together a reasonably complete set of results regarding the use of Constraint Item estimation procedures under the assumption of accurate specification. The analysis covers the case of all explanatory variables being non-stochastic as well as the case of identified simultaneous equations, with error terms known and unknown. Particular emphasis is given to the derivation of criteria for choosing the Constraint Item. Part 1 looks at the best CI estimators and Part 2 examines equation by equation estimation, considering forecasting accuracy.

GENRE
Business & Personal Finance
RELEASED
2018
March 5
LANGUAGE
EN
English
LENGTH
150
Pages
PUBLISHER
Taylor & Francis
SELLER
Taylor & Francis Group
SIZE
2.8
MB
Econometrics Econometrics
2022
FOUNDATIONS OF MODERN ECONOMETRICS: A UNIFIED APPROACH FOUNDATIONS OF MODERN ECONOMETRICS: A UNIFIED APPROACH
2020
Mathematical Statistics Mathematical Statistics
2015
Regression Analysis Under A Priori Parameter Restrictions Regression Analysis Under A Priori Parameter Restrictions
2011
Panel Data Econometrics Panel Data Econometrics
2019
Dynamic Models for Volatility and Heavy Tails Dynamic Models for Volatility and Heavy Tails
2013
Empirical Bayes Methods Empirical Bayes Methods
2018
The Statistical Method in Economics and Political Science The Statistical Method in Economics and Political Science
2018
Input/Output Databases Input/Output Databases
2018
An Introduction to Quantitative Economics An Introduction to Quantitative Economics
2018
A Structural Model of the U.S. Government Securities Market A Structural Model of the U.S. Government Securities Market
2018
Specification Analysis in the Linear Model Specification Analysis in the Linear Model
2018