Instrumental Variables Two-Stage Least Squares (2SLS) vs. Maximum Likelihood Structural Equation Modeling of Causal Effects in Linear Regression Models

2019 ◽  
Vol 26 (6) ◽  
pp. 876-892 ◽  
Author(s):  
Alberto Maydeu-Olivares ◽  
Dexin Shi ◽  
Yves Rosseel
Keyword(s):  
Structural Equation Modeling ◽  
Maximum Likelihood ◽  
Linear Regression ◽  
Least Squares ◽  
Instrumental Variables ◽  
Regression Models ◽  
Structural Equation ◽  
Causal Effects ◽  
Equation Modeling ◽  
Linear Regression Models

scholarly journals How Financial Literacy Affects Household Wealth Accumulation

2012 ◽  
Vol 102 (3) ◽  
pp. 300-304 ◽  
Author(s):  
Jere R Behrman ◽  
Olivia S Mitchell ◽  
Cindy K Soo ◽  
David Bravo
Keyword(s):  
Linear Regression ◽  
Instrumental Variables ◽  
Financial Literacy ◽  
Regression Models ◽  
Household Wealth ◽  
Causal Effects ◽  
Wealth Accumulation ◽  
Linear Regression Models

This study isolates the causal effects of financial literacy and schooling on wealth accumulation using a new household dataset and an instrumental variables (IV) approach. Financial literacy and schooling attainment are both strongly positively associated with wealth outcomes in linear regression models, whereas the IV estimates reveal even more potent effects of financial literacy. They also indicate that the schooling effect only becomes positive when interacted with financial literacy. Estimated impacts are substantial enough to imply that investments in financial literacy could have large wealth payoffs.

scholarly journals DOES ENVIRONMENTAL, SOCIAL AND GOVERNANCE PERFORMANCE INFLUENCE ECONOMIC PERFORMANCE?

2020 ◽  
Vol 21 (4) ◽  
pp. 1165-1184 ◽  
Author(s):  
Kemal Cek ◽  
Serife Eyupoglu
Keyword(s):  
Structural Equation Modeling ◽  
Linear Regression ◽  
Longitudinal Data ◽  
Economic Performance ◽  
Significant Relationship ◽  
Environmental Performance ◽  
Regression Models ◽  
Structural Equation ◽  
Equation Modeling ◽  
Company Performance

The purpose of this paper is to evaluate the influence of environmental, social and governance performance on the economic performance of the Standard & Poor’s 500 companies. Structural equation modeling and linear regression have been utilized to measure the overall and individual influence of environmental, social and governance (ESG) performance on economic performance using longitudinal data comprising the years from 2010 to 2015. The overall ESG model had a significant relationship on economic performance. Furthermore, the findings of this study show that social and governance performance significantly affects economic performance in all regression models. However, environmental performance failed to show a significant relationship. The research contributes to the literature by providing insights for investors, managers and employees about the influence of ESG performance on company performance.

scholarly journals Addressing Endogeneity in International Marketing Applications of Partial Least Squares Structural Equation Modeling

2018 ◽  
Vol 26 (3) ◽  
pp. 1-21 ◽  
Author(s):  
G. Tomas M. Hult ◽  
Joseph F. Hair ◽  
Dorian Proksch ◽  
Marko Sarstedt ◽  
Andreas Pinkwart ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Structural Equation Modeling ◽  
Least Squares ◽  
Partial Least Squares ◽  
Instrumental Variables ◽  
Structural Equation ◽  
International Marketing ◽  
Marketing Research ◽  
Equation Modeling ◽  
Sem Analyses

Partial least squares structural equation modeling (PLS-SEM) has become a key method in international marketing research. Users of PLS-SEM have, however, largely overlooked the issue of endogeneity, which has become an integral component of regression analysis applications. This lack of attention is surprising because the PLS-SEM method is grounded in regression analysis, for which numerous approaches for handling endogeneity have been proposed. To identify and treat endogeneity, and create awareness of how to deal with this issue, this study introduces a systematic procedure that translates control variables, instrumental variables, and Gaussian copulas into a PLS-SEM framework. We illustrate the procedure's efficacy by means of empirical data and offer recommendations to guide international marketing researchers on how to effectively address endogeneity concerns in their PLS-SEM analyses.

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