Statistical modeling of the Cobb-Douglas production function: a multiple linear regression approach in presence of stable distribution noise

DOI10.1134/S1995080224600572MaRDI QIDQ6586754

Mohammed El Khomssi, B. D. Coulibaly, G. Chaibi

Publication date: 13 August 2024

Published in: Lobachevskii Journal of Mathematics (Search for Journal in Brave)

zbMATH Keywords

maximum likelihood estimationstable distributionsforecastinglinear regressionCobb-Douglas production functionheavy tailed regression

Mathematics Subject Classification ID

Parametric inference (62Fxx) Distribution theory (60Exx) Statistical distribution theory (62Exx)

Cites Work

• Title not available (Why is that?)
• Title not available (Why is that?)
• Linear and nonlinear regression with stable errors
• One-step R-estimation in linear models with stable errors
• Maximum likelihood estimation of stable Paretian models.
• Stable Paretian models in finance
• Simple consistent estimators of stable distribution parameters
• Regression-Type Estimation of the Parameters of Stable Laws
• An iterative procedure for the estimation of the parameters of stable laws
• A Method for Simulating Stable Random Variables
• Chance and Stability
• Principal component analysis for α-stable vectors
• Univariate Stable Distributions
• Long-Run Linearity, Locally Gaussian Process, H-Spectra and Infinite Variances
• Stable Distributions in Statistical Inference: 1. Symmetric Stable Distributions Compared to Other Symmetric Long-Tailed Distributions
• Computational aspects of stable distributions
• Financial modeling with heavy-tailed stable distributions

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