Improved estimation in elliptical linear mixed measurement error models

Emami, Hadi

doi:10.1080/00949655.2020.1743992

Cited by 2 publications

(2 citation statements)

References 24 publications

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“…However, the further prominence of differences in the agglomeration of colleges and universities in Guiyang, differences in population distribution, and economic differences in industrial parks will also have a profound impact on regional economic growth, as shown in Figure 2 [15].…”

Section: Introductionmentioning

confidence: 99%

Application and Analysis of Spatial Spillover Effects of an Improved Panel Data Econometric Model in Universities, Population, and Industrial Parks in Guiyang

2022

Mobile Information Systems

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In the field of econometrics, panel data are an extremely important type of data. In macroeconomic research, panel data models are widely used in exchange rate determination theory, testing of cross-border economic growth and convergence theory, analysis of industrial structure, research on technological innovation, etc. The agglomeration and population distribution of colleges and universities, and the economic support of industrial parks play an important role in economic and social development as a source of research and development and a source of talents. The panel data model usually assumes that the error term follows a normal distribution, but the actual data are difficult to satisfy this assumption, and the estimation obtained by traditional methods may be biased or even invalid. This paper proposes a more robust and effective estimation method (ELS-EL) based on the panel data mean regression model, and extends this method to complex panel data models such as generalized linear models and partial linear models; in addition, this paper is based on panel data. We proposed a two-stage instrumental variable method (2S-IVFEQR) to reduce the computational complexity and generalized the new method to the quantile regression model of dynamic panel data. At the same time, this paper uses the above-improved panel data econometric model to analyze the spatial spillover effects of college aggregation, population distribution, and industrial parks in Guiyang. This study found that the agglomeration of colleges and universities has significantly promoted the economic growth of our country. These promotion effects come from both the direct contribution of college agglomeration and the positive external spillover effect of college agglomeration.

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Section: Introductionmentioning

confidence: 99%

Application and Analysis of Spatial Spillover Effects of an Improved Panel Data Econometric Model in Universities, Population, and Industrial Parks in Guiyang

2022

Mobile Information Systems

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“…In this regard, some authors considered skewed and heavy‐tailed continuous distributions, which provide alternative parametric approaches to avoid misleading inferential results. For instance, Arellano‐Valle and Bolfarine (1996), Arellano‐Valle et al (2002), and Emami (2020) introduced the elliptical generalizations of MEMs. Arellano‐Valle et al (2005) provided the likelihood and Bayesian inferences for a class of skew‐normal MEMs.…”

Section: Introductionmentioning

confidence: 99%

Multivariate measurement error models with normal mean‐variance mixture distributions

Mirfarah

Naderi

Lin

et al. 2022

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The class of normal mean‐variance mixture (NMVM) distributions is a rich family of asymmetric and heavy‐tailed distributions and has been widely considered in parametric modeling of the data for robust statistical inference. This paper proposes an extension of measurement error models by assuming the NMVM distributions for the unobserved covariates and error terms in the model, referred to as the NMVM‐MEM. An expectation conditional maximization either (ECME) algorithm is developed to compute the maximum likelihood (ML) estimates of model parameters. Furthermore, an information‐based approach is performed to derive the asymptotic covariance matrix of ML estimators. The analysis of a blood pressure dataset illustrates the superiority of NMVM‐MEM to accommodate asymmetry and outliers over the normal counterpart. Two simulation studies are undertaken to validate our proposed techniques.

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Improved estimation in elliptical linear mixed measurement error models

Cited by 2 publications

References 24 publications

Application and Analysis of Spatial Spillover Effects of an Improved Panel Data Econometric Model in Universities, Population, and Industrial Parks in Guiyang

Application and Analysis of Spatial Spillover Effects of an Improved Panel Data Econometric Model in Universities, Population, and Industrial Parks in Guiyang

Multivariate measurement error models with normal mean‐variance mixture distributions

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