REDUNDANCY OF MOMENT CONDITIONS AND THE EFFICIENCY OF OLS IN SUR MODELS

2008 ◽  
Vol 24 (5) ◽  
pp. 1456-1460 ◽  
Author(s):  
Hailong Qian
Keyword(s):  
Least Squares ◽  
Asymptotic Efficiency ◽  
Generalized Method Of Moments ◽  
Sufficient Conditions ◽  
Generalized Least Squares ◽  
Ordinary Least Squares ◽  
American Statistical Association ◽  
Orthogonality Condition ◽  
Moment Conditions ◽  
Necessary And Sufficient

In this note, based on the generalized method of moments (GMM) interpretation of the usual ordinary least squares (OLS) and feasible generalized least squares (FGLS) estimators of seemingly unrelated regressions (SUR) models, we show that the OLS estimator is asymptotically as efficient as the FGLS estimator if and only if the cross-equation orthogonality condition is redundant given the within-equation orthogonality condition. Using the condition for redundancy of moment conditions of Breusch, Qian, Schmidt, and Wyhowski (1999, Journal of Econometrics 99, 89–111), we then derive the necessary and sufficient condition for the equal asymptotic efficiency of the OLS and FGLS estimators of SUR models. We also provide several useful sufficient conditions for the equal asymptotic efficiency of OLS and FGLS estimators that can be interpreted as various mixings of the two famous sufficient conditions of Zellner (1962, Journal of the American Statistical Association 57, 348–368).

ASYMPTOTIC EFFICIENCY OF THE ORDINARY LEAST SQUARES ESTIMATOR FOR REGRESSIONS WITH UNSTABLE REGRESSORS

2002 ◽  
Vol 18 (5) ◽  
pp. 1121-1138 ◽  
Author(s):  
DONG WAN SHIN ◽  
MAN SUK OH
Keyword(s):  
Least Squares ◽  
Asymptotic Efficiency ◽  
Characteristic Root ◽  
Sufficient Conditions ◽  
Generalized Least Squares ◽  
Ordinary Least Squares ◽  
Least Squares Estimator ◽  
Characteristic Roots ◽  
Generalized Least Squares Estimator ◽  
Ordinary Least Squares Estimator

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 generalized least squares estimator (GLSE) under the same normalization. A key condition for the asymptotic efficiency of the OLSE is that one multiplicity of a characteristic root of the regressor process is strictly greater than the multiplicities of the other roots. Under this condition, the covariance matrix Γ of the errors and the regressor matrix X are shown to satisfy a relationship (ΓX = XC + V for some matrix C) for V asymptotically dominated by X, which is analogous to the condition (ΓX = XC for some matrix C) for numerical equivalence of the OLSE and the GLSE.

PARTIAL REDUNDANCY OF MOMENT CONDITIONS

2002 ◽  
Vol 18 (2) ◽  
pp. 531-539 ◽  
Author(s):  
Hailong Qian
Keyword(s):  
Method Of Moments ◽  
Generalized Method Of Moments ◽  
Sufficient Conditions ◽  
The Other ◽  
Large Set ◽  
Parameter Vector ◽  
Moment Conditions ◽  
Method Of Moments Estimation ◽  
Necessary And Sufficient ◽  
Partial Redundancy

In this paper, we first transform a set of moment conditions into a set of transformed moment conditions, based on which the efficient partial generalized method of moments estimation for part of a parameter vector is defined. Given the set of transformed moment conditions, we then show that the conditions for partial redundancy of an additional set of moment conditions given an original set of moment conditions simply become the conditions for full redundancy of the second subset of transformed moment conditions given the first subset of transformed moment conditions. Thus the transformed moment conditions proposed in this paper unify partial redundancy of moment conditions with full redundancy of moment conditions. Using transformed moment conditions, we then straightforwardly derive necessary and sufficient conditions for partial redundancy of one or two subset(s) of moment conditions given the other when the large set of moment conditions consists of three subsets of moment conditions. The paper also provides several easily checkable sufficient conditions for partial redundancy of one set of moment conditions given other sets of moment conditions.

Note on Anderson’s “Causal Models in Educational Research: Nonrecursive Models”

1979 ◽  
Vol 16 (4) ◽  
pp. 347-350 ◽  
Author(s):  
Jonathan Shapiro
Keyword(s):  
Least Squares ◽  
Educational Research ◽  
Sufficient Conditions ◽  
Ordinary Least Squares ◽  
Causal Models ◽  
Necessary And Sufficient Conditions ◽  
Sufficient Condition ◽  
Two Stage ◽  
Matrix Notation ◽  
Necessary And Sufficient

Two comments are made concerning Anderson’s article (1978) on the identification and estimation of nonrecursive models. First, Anderson’s rule for identification is only a necessary but not sufficient condition. The necessary and sufficient conditions are presented using matrix notation and a modified version of Anderson’s rule is offered. Second, contrary to Anderson’s discussion, the choice of two-stage or ordinary least squares depends on the data results rather than the methodological properties of the estimators. A means for choosing between the estimates is provided.

scholarly journals The effect of creative corporate culture and intangibility on the performance of foreign firms traded on the NYSE

2018 ◽  
Vol 15 (4) ◽  
pp. 356-372 ◽  
Author(s):  
Marcia Martins Mendes De Luca ◽  
Paulo Henrique Nobre Parente ◽  
Emanoel Mamede Sousa Silva ◽  
Ravena Rodrigues Sousa
Keyword(s):  
New York ◽  
Least Squares ◽  
Corporate Culture ◽  
Corporate Performance ◽  
Stock Exchange ◽  
Generalized Least Squares ◽  
Ordinary Least Squares ◽  
Foreign Firms ◽  
Content Type ◽  
Negative Effect

Purpose Following the tenets of resource-based view, the present study aims to investigate the effect of creative corporate culture according to the competing values framework model at the level of corporate intangibility and its respective repercussions on performance. Design/methodology/approach The sample included 117 non-USA foreign firms traded on the New York Stock Exchange (NYSE), which issued annual financial reports between 2009 and 2014 using the 20-F form. To meet the study objectives, in addition to the descriptive and comparative analyses, the authors performed regression analyses with panel data, estimating generalized least-squares, two-stage least-squares and ordinary least-squares. Findings Creative culture had a negative effect on the level of intangibility and corporate performance, while the level of intangibility did not appear to influence corporate performance. When combined, creative culture and intangibility had a potentially negative effect on corporate results. In conclusion, creative corporate culture had a negative effect on performance, even in firms with higher levels of intangibility, characterized by elements like experimentation and innovation. Originality/value Although the study hypotheses were eventually rejected, the analyses are relevant to both the academic setting and the market because of the organizational and institutional aspects evaluated, especially in relation to intangibility and creative culture and in view of the unique cross-cultural approach adopted. Within the corporate setting, the study provides a spectrum of stakeholders with tools to identify the profile of foreign firms traded on the NYSE.

scholarly journals Two Explicit Characterizations of the General Nonnegative-Definite Covariance Matrix Structure for Equality of BLUEs, WLSEs, and LSEs

2020 ◽  
Vol 9 (6) ◽  
pp. 108
Author(s):  
Phil D. Young ◽  
Joshua D. Patrick ◽  
Dean M. Young
Keyword(s):  
Least Squares ◽  
Weighted Least Squares ◽  
Sufficient Conditions ◽  
Covariance Structure ◽  
Least Squares Estimator ◽  
Weighted Least Squares Estimator ◽  
Best Linear Unbiased ◽  
Necessary And Sufficient ◽  
Nonnegative Definite

We provide a new, concise derivation of necessary and sufficient conditions for the explicit characterization of the general nonnegative-definite covariance structure V of a general Gauss-Markov model with E(y) and Var(y) such that the best linear unbiased estimator, the weighted least squares estimator, and the least squares estimator of Xβ are identical. In addition, we derive a representation of the general nonnegative-definite covariance structure V defined above in terms of its Moore-Penrose pseudo-inverse.

Nuisance vs. Substance: Specifying and Estimating Time-Series-Cross-Section Models

1996 ◽  
Vol 6 ◽  
pp. 1-36 ◽  
Author(s):  
Nathaniel Beck ◽  
Jonathan N. Katz
Keyword(s):  
Time Series ◽  
Least Squares ◽  
Cross Section ◽  
Generalized Least Squares ◽  
Ordinary Least Squares ◽  
Correlated Errors ◽  
Section Data ◽  
Variable Approach ◽  
Parameter Heterogeneity ◽  
Lagged Dependent Variable

In a previous article we showed that ordinary least squares with panel corrected standard errors is superior to the Parks generalized least squares approach to the estimation of time-series-cross-section models. In this article we compare our proposed method with another leading technique, Kmenta's “cross-sectionally heteroskedastic and timewise autocorrelated” model. This estimator uses generalized least squares to correct for both panel heteroskedasticity and temporally correlated errors. We argue that it is best to model dynamics via a lagged dependent variable rather than via serially correlated errors. The lagged dependent variable approach makes it easier for researchers to examine dynamics and allows for natural generalizations in a manner that the serially correlated errors approach does not. We also show that the generalized least squares correction for panel heteroskedasticity is, in general, no improvement over ordinary least squares and is, in the presence of parameter heterogeneity, inferior to it. In the conclusion we present a unified method for analyzing time-series-cross-section data.

Shadow Economy, Corruption, and Economic Growth: An Empirical Analysis

2019 ◽  
Vol 47 (3) ◽  
pp. 276-294 ◽  
Author(s):  
Nedra Baklouti ◽  
Younes Boujelbene
Keyword(s):  
Economic Growth ◽  
Least Squares ◽  
Public Administration ◽  
Method Of Moments ◽  
Fixed Effects ◽  
Shadow Economy ◽  
Generalized Method Of Moments ◽  
Ordinary Least Squares ◽  
Negative Effects ◽  
Considerable Debate

There is considerable debate over the effects of both corruption and shadow economy on growth, but few studies have considered how the interaction between them might affect economic growth. We study how corruption levels in public administration affect economic growth and how this effect depends on the shadow economy. Using Ordinary Least Squares (OLS), fixed effects, and system generalized method of moments (GMM) on a dataset of 34 OECD countries over the period 1995-2014. The estimation results indicate that increased corruption and a larger shadow economy lead to decrease in economic growth. Results additionally indicate that the shadow economy magnifies the effect of corruption on economic growth. These results imply significant complementarities between corruption and the shadow economy, suggesting that the reduction of corruption will lead to a fall in the size of the shadow economy and will also reduce the negative effects of corruption on economic growth through the underground economy.

Inter­Effect­Orthogonality in Factorial Experiments

1979 ◽  
Vol 28 (1-4) ◽  
pp. 83-108 ◽  
Author(s):  
Rahul Mukerjbe
Keyword(s):  
Sufficient Conditions ◽  
Orthogonality Condition ◽  
Necessary And Sufficient Conditions ◽  
Factorial Designs ◽  
Factorial Experiments ◽  
Necessary And Sufficient

A set of necessary and sufficient conditions has been established for best linear estimates of estimable treatment contrasts belonging to different facotrial effects to be mutually orthogonal. The cases of both connected and disconnected designs have been considered. The analysis of connected designs satisfying the orthogonality condition has been derived. The orthogonality condition obtained is seen to throw new light on some of the existing methods of construction of symmetric and asymmetric factorial designs. Extension of the conditions to designs eliminating heterogeneity in several directions is immediate

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