Results 251 to 260 of about 215,084 (309)

Test for cointegration based on two-stage least squares

Journal of Applied Statistics, 2005
Abstract A residual-based test for cointegration is proposed. The method of two-stage least squares is used to estimate the cointegration model parameters. The residuals are then tested for the existence of a unit root using the augmented Dickey-Fuller test.
Norah Al-Ballaa
exaly   +3 more sources

On a generalization of the test of endogeneity in a two stage least squares estimation [PDF]

Journal of Applied Statistics, 2020
In situations that the predictors are correlated with the error term, we propose a bridge estimator in the two-stage least squares estimation. We apply this estimator to overcome the multicollinearity and sparsity of the explanatory variables, when the endogeneity problem is present.The proposed estimator was applied to modify the Durbin-Wu-Hausman ...
Ayyub Sheikhi, Fatemeh Bahador, Mohammad Arashi   +2 more
openaire   +3 more sources

Two-stage, least squares design of biorthogonal filter banks

IEE Proceedings - Vision, Image, and Signal Processing, 2000
A two-stage approach is employed for the design of a class of two-channel biorthogonal filter banks. The filter banks belong to the class HPFB (halfband pair filter bank) and are defined by two kernels. The parametric Bernstein polynomial is used to construct the kernels. The design of the free parameters of the Bernstein polynomial is achieved through
David Tay (13096854)
openaire   +2 more sources

Some of the next articles are maybe not open access.

Related searches:

Two-stage Least Squares (35 Patients)

2014
The two stage least squares method assumes that the independent variable (x-variable) is problematic, meaning that it is somewhat uncertain. An additional variable can be argued to provide relevant information about the problematic variable, and is, therefore, called instrumental variable, and included in the analysis.
Ton J Cleophas, Aeilko H Zwinderman
openaire   +1 more source

Two-Stage Least-Squares Estimation with Shifts in the Structural Form

Econometrica, 1970
1. IN THIS NOTE we consider the estimation of linear models when the coefficients of the structural form are not the same for all observations for which the model is postulated to be valid. An example of such a model is given in [3], where some structural relations have a piecewise linear form.
Barten, A P, Bronsard, Lise Salvas
openaire   +1 more source

Two-Stage Least Squares

2013
Both path analysis and multistage least squares are adequate for simultaneously assessing both direct and indirect predictors. This makes interpretation less easy. Also, path analysis does not provide overall p-values.
Ton J. Cleophas, Aeilko H. Zwinderman
openaire   +1 more source

Partially Generalized Least Squares and Two-Stage Least Squares Estimators

Journal of Econometrics, 1983
Abstract A class of partially generalized least squares estimators and a class of partially generalized two-stage least squares estimators in regression models with heteroscedastic errors are proposed. By using these estimators a researcher can attain higher efficiency than that attained by the least squares or the two-stage least squares estimators ...
openaire   +1 more source

The Existence of Moments of the Ordinary Least Squares and Two-Stage Least Squares Estimators

Econometrica, 1972
This paper deals with two single-equation estimators in a set of simultaneous linear stochastic equations--namely, ordinary least squares (OLS) and two-stage least squares (2SLS). Under the assumption that all predetermined variables in the model are exogenous, necessary and sufficient conditions are obtained for the existence of even moments of the ...
openaire   +2 more sources

Jackknifing the two stage least squares estimator

Communications in Statistics - Simulation and Computation, 1984
A link is established between jackknifing smooth functions of regression parameter estimators in the general linear model and jackknifing the two stage least squares estimator in the simulta- neous equation model. Hinkley's weighted jackknife is explored and is shown to have a smaller variance than the standard jack- knife estimator in the context of ...
G. D. A. Phillips, B. P. McCabe
openaire   +1 more source