Kernel method to estimate nonlinear structural equation models

Ahmed Ouazza (), Noureddine Rhomari () and Zoubir Zarrouk ()
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Ahmed Ouazza: Mohamed First University
Noureddine Rhomari: Mohamed First University
Zoubir Zarrouk: Mohamed First University

Quality & Quantity: International Journal of Methodology, 2022, vol. 56, issue 5, No 26, 3465-3480

Abstract: Abstract The purpose of this paper is to provide a nonparametric kernel method to estimate nonlinear structural equation models involving the functional effects between the latent variables. This approach is based on the combination of Principal Component Analysis (PCA) and kernel smoothing technique. The results obtained from different simulations on both nonlinear and linear structural models show the great performance of this method. Furthermore, an application on real data using a recovery satisfaction model is presented in this paper. From where, we show the adequacy of our method in capturing the non linearity between some latent variables.

Keywords: Nonlinear structural equation models; Nonparametric kernel method; Principal component analysis (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1007/s11135-021-01274-9

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