Estimation of M-equation Linear Models Subject to a Constraint on the Endogenous Variables
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A01=Charles Stockton Roehrig
advanced statistical inference
Affect Forecasting Accuracy
Author_Charles Stockton Roehrig
BLU Predictor
Category=KCH
CI Estimator
Coefficient Constraints
Consistent Estimator
constraint item selection
econometric estimation methods
Endogenous Explanatory Variable
eq_bestseller
eq_business-finance-law
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
eq_non-fiction
Equation Subset
Error Term Variance
Exogenous Explanatory Variables
Finite Sample Properties
Finite Samples
Forecast Error Variances
forecasting accuracy analysis
Full Information Maximum Likelihood Approach
General Linear Constraint
IA Estimator
Larger Error Variance
M1 Equation
Maximum Likelihood Estimator
Maximum Likelihood Property
Ml Estimator
non-stochastic regressors
OLS Estimator
OLS Residual
Positive Definite
simultaneous equation estimation techniques
simultaneous equations modelling
Simultaneous Equations Systems
Unobserved Error Terms
Product details
- ISBN 9780815350309
- Weight: 440g
- Dimensions: 156 x 234mm
- Publication Date: 06 Mar 2018
- Publisher: Taylor & Francis Inc
- Publication City/Country: US
- Product Form: Hardback
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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.
