Author: Phoebus J. Dhrymes
Publisher:
ISBN:
Category :
Languages : en
Pages : 54
Book Description
Asymptotic Properties of Simultaneous Least Squares Estimators
Author: Phoebus J. Dhrymes
Publisher:
ISBN:
Category :
Languages : en
Pages : 54
Book Description
Publisher:
ISBN:
Category :
Languages : en
Pages : 54
Book Description
Asymptotic Properties of the Ordinary Least Squares Estimator in Simultaneous Equations Models
Author: Virendra K. Srivastava
Publisher:
ISBN:
Category : Econometrics
Languages : en
Pages : 18
Book Description
Publisher:
ISBN:
Category : Econometrics
Languages : en
Pages : 18
Book Description
Asymptotic Properties of Some Estimators in Moving Average Models
Author: Stanford University. Department of Statistics
Publisher:
ISBN:
Category : Time-series analysis
Languages : en
Pages : 318
Book Description
The author considers estimation procedures for the moving average model of order q. Walker's method uses k sample autocovariances (k> or = q). Assume that k depends on T in such a way that k nears infinity as T nears infinity. The estimates are consistent, asymptotically normal and asymptotically efficient if k = k (T) dominates log T and is dominated by (T sub 1/2). The approach in proving these theorems involves obtaining an explicit form for the components of the inverse of a symmetric matrix with equal elements along its five central diagonals, and zeroes elsewhere. The asymptotic normality follows from a central limit theorem for normalized sums of random variables that are dependent of order k, where k tends to infinity with T. An alternative form of the estimator facilitates the calculations and the analysis of the role of k, without changing the asymptotic properties.
Publisher:
ISBN:
Category : Time-series analysis
Languages : en
Pages : 318
Book Description
The author considers estimation procedures for the moving average model of order q. Walker's method uses k sample autocovariances (k> or = q). Assume that k depends on T in such a way that k nears infinity as T nears infinity. The estimates are consistent, asymptotically normal and asymptotically efficient if k = k (T) dominates log T and is dominated by (T sub 1/2). The approach in proving these theorems involves obtaining an explicit form for the components of the inverse of a symmetric matrix with equal elements along its five central diagonals, and zeroes elsewhere. The asymptotic normality follows from a central limit theorem for normalized sums of random variables that are dependent of order k, where k tends to infinity with T. An alternative form of the estimator facilitates the calculations and the analysis of the role of k, without changing the asymptotic properties.
Asymptotic Properties of Nonlinear Least Squares Estimators in a Replicated Time Series Model
Author: Jeremy Sin-hing Wu
Publisher:
ISBN:
Category :
Languages : en
Pages : 246
Book Description
Publisher:
ISBN:
Category :
Languages : en
Pages : 246
Book Description
Comparison of Estimators in Simultaneous Equation Econometric Models when the Residuals are Small
Author: Joseph B. Kadane
Publisher:
ISBN:
Category : Economics, Mathematical
Languages : en
Pages : 108
Book Description
Publisher:
ISBN:
Category : Economics, Mathematical
Languages : en
Pages : 108
Book Description
Asymptotic Properties of Maximum Likelihood Estimators in the General Sampling Framework, and Some Results in Non-normal Linear Regression
Author: Robert Ernest Tarone
Publisher:
ISBN:
Category :
Languages : en
Pages : 190
Book Description
Publisher:
ISBN:
Category :
Languages : en
Pages : 190
Book Description
Asymptotic Properties of an Iterate of Two Stage Least Squares Estimator
Author: Phoebus J. Dhrymes
Publisher:
ISBN:
Category :
Languages : en
Pages : 36
Book Description
Publisher:
ISBN:
Category :
Languages : en
Pages : 36
Book Description
The Maximum Likelihood Stage Least Squares Estimator in the Nonlinear Simultaneous Equations Model
Author: Takeshi Amemiya
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
Book Description
The consistency and the asymptotic normality of the maximum likelihood estimator in the general nonlinear simultaneous equation model are proved. It is shown that the proof depends on the assumption of normality unlike in the linear simultaneous equation model. It is proved that the maximum likelihood estimator is asymptotically more efficient than the nonlinear three-stage least squares estimator if the specification is correct, However, the latter has the advantage of being consistent even when the normality assumption is removed. Hausrnan' s instrumental-variable-interpretation of the maximum likelihood estimator is extended to the general nonlinear simultaneous equation model.
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
Book Description
The consistency and the asymptotic normality of the maximum likelihood estimator in the general nonlinear simultaneous equation model are proved. It is shown that the proof depends on the assumption of normality unlike in the linear simultaneous equation model. It is proved that the maximum likelihood estimator is asymptotically more efficient than the nonlinear three-stage least squares estimator if the specification is correct, However, the latter has the advantage of being consistent even when the normality assumption is removed. Hausrnan' s instrumental-variable-interpretation of the maximum likelihood estimator is extended to the general nonlinear simultaneous equation model.
Asymptotic Properties of Econometric Estimators
Author: Jeffrey M. Wooldridge
Publisher:
ISBN:
Category : Econometrics
Languages : en
Pages : 544
Book Description
Publisher:
ISBN:
Category : Econometrics
Languages : en
Pages : 544
Book Description
Asymptotic Properties of a Least-squares Estimator Using Incomplete Data
Author: Anders Klevmarken
Publisher:
ISBN:
Category :
Languages : en
Pages : 22
Book Description
Publisher:
ISBN:
Category :
Languages : en
Pages : 22
Book Description