A note on GMM-estimation of probit models with endogenous regressors [PDF]
Dagenais (1999) and Lucchetti (2002) have demonstrated that the naive GMM estimator of Grogger (1990) for the probit model with an endogenous regressor is not consistent.
Joachim Wilde
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GMM Redundancy Results for General Missing Data Problems [PDF]
We consider questions of efficiency and redundancy in the GMM estimation problem in which we have two sets of moment conditions, where two sets of parameters enter into one set of moment conditions, while only one set of parameters enters into the other.
Artem Prokhorov, Peter Schmidt
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An Improved Approximation to the Distributions in GMM Estimation [PDF]
The empirical saddlepoint distribution provides an approximation to the sampling distributions for the GMM parameter estimates and the statistics that test the overidentifying restrictions.
Fallaw Sowell
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, 2014 Tujuan utama dari analisis regresi adalah menduga parameter yang tidak diketahui dalam model. Tiga metode estimasi populer yang banyak digunakan adalah kuadrat terkecil (Least-Squares) dan likelihood maksimum (Maximumum Likelihood) dan metode momen ...
ESTIMASI PARAMETER PADA STANDARD CAPM (CAPITAL ASSETS PRICING MODEL) DENGAN METODE GMM (GENERALIZED METHOD OF MOMENTS)
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The role of economic freedom and clean energy in environmental sustainability: implication for the G-20 economies. [PDF]
Environ Sci Pollut Res Int, 2022 Alola AA, Alola UV, Akdag S, Yildirim H.
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A Multi-Scale Densely Connected Convolutional Neural Network for Automated Thyroid Nodule Classification. [PDF]
Front Neurosci, 2022 Wang L +12 more
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The Asymptotic Properties of the System GMM Estimator in Dynamic Panel Data Models When Both N and T are Large [PDF]
This paper complements Alvarez and Arellano (2003) by showing the asymptotic properties of the system GMM estimator for AR(1) panel data models when both N and T tend to infinity.
Kazuhiko Hayakawa
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A new iterative initialization of EM algorithm for Gaussian mixture models. [PDF]
PLoS One, 2023 You J, Li Z, Du J.
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Heteroskedasticity and Spatiotemporal Dependence Robust Inference for Linear Panel Models with Fixed Effects [PDF]
This paper studies robust inference for linear panel models with fixed effects in the presence of heteroskedasticity and spatiotemporal dependence of unknown forms.
Min Seong Kim, Yixiao Sun
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Machine learning as an interpretive consistency approach for coupling geochemical and geophysical domains in data-limited landfills. [PDF]
PNAS NexusCostanzo-Álvarez V +7 more
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