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The biggest myth in spatial econometrics

Lesage, James P.; Pace, R. Kelley - In: Econometrics : open access journal 2 (2014) 4, pp. 217-249

There is near universal agreement that estimates and inferences from spatial regression models are sensitive to particular specifications used for the spatial weight structure in these models. We find little theoretical basis for this commonly held belief, if estimates and inferences are based...

Persistent link: https://www.econbiz.de/10010479047

Spurious Regressions in Econometrics : Reconsideration

Swamy, P.A.V.B. - 2019

As every econometrician knows, in a regression with one regressor, the dependent and explanatory variables may be spuriously correlated if they may have been affected by some third variable, a common cause. In a highly regarded article, Granger and Newbold (1974) were not concerned with this...

Persistent link: https://www.econbiz.de/10012894391

Identification and estimation of categorical random coefficient models

Gao, Zhan; Pesaran, M. Hashem - 2022

This paper proposes a linear categorical random coefficient model, in which the random coefficients follow parametric categorical distributions. The distributional parameters are identified based on a linear recurrence structure of moments of the random coefficients. A Generalized Method of...

Persistent link: https://www.econbiz.de/10013183733

Identification and Estimation of Categorical Random Coefficient Models

Gao, Zhan; Pesaran, M. Hashem - 2022

Persistent link: https://www.econbiz.de/10013291320

Density Based Regression for Inhomogeneous Data : Application to Lottery Experiments

Kontek, Krzysztof - 2010

This paper presents a regression procedure for inhomogeneous data characterized by varying variance, skewness and kurtosis or by an unequal amount of data over the estimation domain. The concept is based first on the estimation of the densities of an observed variable for given values of...

Persistent link: https://www.econbiz.de/10013144565

Correcting misclassification bias in regression models with variables generated via data mining

Qiao, Mengke; Huang, Ke-Wei - In: Information systems research : ISR 32 (2021) 2, pp. 462-480

Persistent link: https://www.econbiz.de/10012599859

Conceptual understanding of linear regression among economics students at the university center of Tipaza, Algeria

Idris, Djouahra - In: Croatian review of economic, business and social … 8 (2022) 2, pp. 66-83

Solving problems related to econometrics requires a good knowledge of regression analysis concepts. The objective of …

Persistent link: https://www.econbiz.de/10014287694

Historical econometrics : instrumental variables and regression discontinuity designs

Caicedo, Felipe Valencia - 2020

Persistent link: https://www.econbiz.de/10012299251

Applied Statistics and Econometrics : Basic Topics and Tools with Gretl and R

Kivedal, Bjørnar Karlsen - 2024

This accessible textbook introduces the foundations of applied econometrics and statistics for undergraduate students …. It covers key topics in econometrics by using step-by-step examples in Gretl and R, providing a guide to using … for upper undergraduate students taking courses in introductory econometrics and statistics, as well as students in …

Persistent link: https://www.econbiz.de/10014519030

Методологические проблемы эконометрического оценивания производственных функций (Methodological Problems in The Econometric Estimation of Production Functions)...

Kazakova, Maria V - 2013

При оценивании производственных функций исследователь сталкивается с рядом проблем, которые в наиболее общем виде можно разделить на две группы: проблемы,...

Persistent link: https://www.econbiz.de/10013082561

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