Results 161 to 170 of about 75,182 (196)

A COMPARISON OF ORDINARY LEAST SQUARES AND LEAST ABSOLUTE ERROR ESTIMATION

1986
In a linear dynamic model with heteroscedastic errors, we compare some aspects of ordinary least squares and least absolute error estimation. After deriving the properties of the estimators and the Wald, Lagrange multiplier and Likelihood ratio tests under a local alternative, we derive the Hausman test comparing the estimators.
Weiss, Andrew, Weiss, Andrew
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Ordinary Least Squares Estimation for a Dynamic Game [PDF]

, 2014
Estimation of dynamic games is known to be a numerically challenging task. A common form of the payoff functions employed in practice takes the linear-in-parameter specification. We show a least squares estimator taking a familiar OLS/GLS expression is available in such case. Our proposed estimator has a closed-form.
Fabio A. Miessi Sanches, Daniel Silva Junior, Sorawoot Srisuma   +1 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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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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ASYMPTOTIC EFFICIENCY OF THE ORDINARY LEAST SQUARES ESTIMATOR FOR REGRESSIONS WITH UNSTABLE REGRESSORS

Econometric Theory, 2002
For regression models with general unstable regressors having characteristic roots on the unit circle and general stationary errors independent of the regressors, sufficient conditions are investigated under which the ordinary least squares estimator (OLSE) is asymptotically efficient in that it has the same limiting distribution as the ...
Shin, Dong Wan, Oh, Man Suk
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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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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 Asymptotic Bias of the Ordinary Least Squares Estimator of the Tobit Model

Econometrica, 1981
This paper presents a precise characterization of the bias of least squares in two limited dependent variable models, the Tobit model and the truncated regression model. For the cases considered, the method of moments can be used to correct the bias of OLS. For more general cases, the results provide approximations which appear to be relatively robust.
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