scholarly journals Two-Stage Least Squares Algorithms with QR Decomposition for Simultaneous Equations Models on Heterogeneous Multicore and Multi-GPU Systems

2012 ◽  
Vol 9 ◽  
pp. 2004-2007
Author(s):  
Carla Ramiro ◽  
Jose J. López-Espín ◽  
Domingo Giménez ◽  
Antonio M. Vidal
Keyword(s):  
Least Squares ◽  
Qr Decomposition ◽  
Simultaneous Equations ◽  
Two Stage ◽  
Heterogeneous Multicore ◽  
Simultaneous Equations Models ◽  
Two Stage Least Squares

scholarly journals CDSIMEQ: A Program to Implement Two-stage Probit Least Squares

2003 ◽  
Vol 3 (2) ◽  
pp. 157-167 ◽  
Author(s):  
Omar M. G. Keshk
Keyword(s):  
Least Squares ◽  
Estimation Method ◽  
Least Squares Estimation ◽  
Simultaneous Equations ◽  
The Other ◽  
Endogenous Variable ◽  
Standard Errors ◽  
Two Stage ◽  
Simultaneous Equations Models ◽  
Endogenous Variables

The cdsimeq command implements the two-stage probit least squares estimation method described in Maddala (1983) for simultaneous equations models in which one of the endogenous variables is continuous and the other endogenous variable is dichotomous.1 The cdsimeq command implements all the necessary procedures for obtaining consistent estimates for the coefficients, as well as their corrected standard errors.

Nonparametric Two-Stage Estimation of Simultaneous Equations with Limited Endogenous Regressors

1996 ◽  
Vol 12 (2) ◽  
pp. 305-330 ◽  
Author(s):  
Myoung-Jae Lee
Keyword(s):  
Least Squares ◽  
Nuisance Parameter ◽  
Least Squares Estimation ◽  
Simultaneous Equations ◽  
Two Stage ◽  
Infinite Dimensional ◽  
Second Stage ◽  
Endogenous Regressors ◽  
Two Stage Least Squares ◽  
Stage Estimation

Estimation of simultaneous equations with limited (or transformed) endogenous regressors has been difficult in the parametric literature for various reasons. In this paper, we propose a nonparametric two-stage method that is analogous to two-stage least-squares estimation. A simultaneous censored model is used to illustrate our approach, and then its generalization to other cases is developed. The technical highlight is in handling a nondifferentiable second-stage minimand with an infinite-dimensional first-stage nuisance parameter when the first-stage error is not orthogonal to the second.

An introduction to model implied instrumental variables using two stage least squares (MIIV-2SLS) in structural equation models (SEMs).

2021 ◽  
Author(s):  
Kenneth A. Bollen ◽  
Zachary F. Fisher ◽  
Michael L. Giordano ◽  
Adam G. Lilly ◽  
Lan Luo ◽  
...  
Keyword(s):  
Least Squares ◽  
Instrumental Variables ◽  
Structural Equation ◽  
Structural Equation Models ◽  
Two Stage ◽  
Two Stage Least Squares

scholarly journals Model Persamaan Simultan pada Analisis Hubungan Kemiskian dan PDRB

2014 ◽  
Vol 5 (2) ◽  
pp. 810
Author(s):  
Rokhana Dwi Bekti ◽  
David David ◽  
Gita N ◽  
Priscillia Priscillia ◽  
Serlyana Serlyana
Keyword(s):  
Economic Growth ◽  
Least Squares ◽  
Least Squares Estimation ◽  
Two Stage ◽  
Two Stage Least Squares ◽  
Regional Product ◽  
The Relationship ◽  
Simultaneous Model

Simultaneous model is a model for some equation which have simultaneous relationships. It was often found in econometrics, such as the relationship between Gross Domestic Regional Product (GDRP) and poverty. GDP is a common indicator that can be used to determine the economic growth occurred in region. Meanwhile, poverty is one of the indicators to measure the society welfare. Information about these relathionships were important to perform the relathionsips between GDP and poverty. So this research conducted an analysis to obtain simultaneous models between GDRP and poverty. Estimation of the parameters used is Two-Stage Least Squares Estimation (2SLS). The data used are 33 provinces in Indonesia at 2010. By α = 5%, it was conclude that variable which significant effect on GDRP is poverty, export, and import. Meanwhile, the variables that significantly affect poverty are population. The simultaneous model (α = 5%) also conclude that there is no simultaneous relationship between GDRP and poverty. However, with α = 25%, there is a simultaneous relationship between GDRP and poverty.

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