Results 261 to 270 of about 75,728 (293)

On the Moments of Ordinary Least Squares and Instrumental Variables Estimators in a General Structural Equation

Econometrica, 1984
Exact expressions are given for the first two moments of a linear combination of the elements of an instrumental variables estimator for the coefficients of the endogenous variables in a general structural equation. These results generalize previous exact results for equations containing just two or three endogenous variables.
Hillier, Grant, Kinal, T. W., Srivastava, V. K.   +2 more
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The Ordinary Least Squares Estimates

1986
With the linearization of the basic model and its covariance matrix at hand we now start on the estimation of the components. We’ll do this by calculating the ordinary least squares estimates for our linear model, and by discussing what is meant by “estimable function” in our context.
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The Exact Moments of Ordinary Least Squares Estimators for Koyck Distributed Lag Models

International Economic Review, 1986
This article has analyzed some small sample properties of the ordinary least squares estimators for the Koyck distributed lag models. Two different structures on the disturbances are assumed. Analytical expressions for exact low order moments of the OLS estimators are derived.
Hoque, Asraul, Kataoka, Yusaku, Miyashita, Hiroshi   +2 more
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The Exact Sampling Distribution of Ordinary Least Squares and Two-Stage Least Squares Estimators

Journal of the American Statistical Association, 1969
Abstract This paper presents the exact sampling distributions of the ordinary and the two-stage least squares estimators of a structural parameter in a structural equation with two endogenous variables in a complete system of stochastic equations. The results show that the distributions of the two estimators are essentially similar to each other.
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The Effects of Causal Feedback On Ordinary Least-Squares Estimators

Sociological Methods & Research, 1974
When a causal model includes a feedback loop, ordinary least-squares (OLS) is an inappropriate, biased estimation technique. Furthermore, since the system is nonrecursive, a simple application of path analysis or regression is precluded. If the causal feedback is indirect, however, or involves one or more weak causal links, the bias will tend to be ...
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A Comparison of Two Criteria for Ordinary-Least-Squares Estimators to Be Best Linear Unbiased Estimators

The American Statistician, 1988
Abstract The problem of the equality between ordinary-least-squares estimators and best linear unbiased estimators is discussed in the literature in two versions: in the context of a fixed model (design) matrix and in the context of all model (design) matrices having a fixed common linear part.
Baksalary, J.K., van Eijnsbergen, A.C.
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Recovery of Weak Common Factors by Maximum Likelihood and Ordinary Least Squares Estimation

Multivariate Behavioral Research, 2003
This article examines the relative performance of two commonly used methods of parameter estimation in factor analysis, maximum likelihood (ML) and ordinary least squares (OLS). It is shown that ML will sometimes fail to recover a known population factor structure when OLS succeeds.
Nancy E, Briggs, Robert C, MacCallum
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Ordinary Least Squares Estimation of Parameters in Exploratory Factor Analysis With Ordinal Data

Multivariate Behavioral Research, 2012
Exploratory factor analysis (EFA) is often conducted with ordinal data (e.g., items with 5-point responses) in the social and behavioral sciences. These ordinal variables are often treated as if they were continuous in practice. An alternative strategy is to assume that a normally distributed continuous variable underlies each ordinal variable. The EFA
Chun-Ting, Lee, Guangjian, Zhang, Michael C, Edwards   +2 more
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On the Inconsistency of the Ordinary Least Squares Estimator for Spatial Autoregressive Processes [PDF]

, 2000
This paper investigates the asymptotic properties of the ordinary least squares estimator for spatial autoregressive models. We show that this estimator is biased as well as inconsistent for the parameters regardless of the distribution of the error term. Illustrative examples are also provided.
Théophile AZOMAHOU, Agénor LAHATTE
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A Note on the Comparison of Ordinary and Two-Stage Least Squares Estimators

Econometrica, 1971
Richardson, David H, Wu, De-Min
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