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Sequential regression : a neodescriptive approach to multicollinearity
Fickel, Norman - 2001
Classical regression analysis uses partial coefficients to measure the influences of some variables (regressors) on another variable (regressand). However, a descriptive point of view shows that these coefficients are very bad measures of influence. Their interpretation as an average change of...
Persistent link: https://www.econbiz.de/10011511033
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Bayesian measures of explained variance and pooling in multilevel (hierarchical) models
Gelman, Andrew; Pardoe, Iain - 2004
Explained variance (R^2) is a familiar summary of the fit of a linear regression and has been generalized in various ways to multilevel (hierarchical) models. The multilevel models we consider in this paper are characterized by hierarchical data structures in which individuals are grouped into...
Persistent link: https://www.econbiz.de/10011513072
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Bootstrap Methods for Covariance Structures
Horowitz, Joel L. - 1998
The optimal minimum distance (OMD) estimator for models of covariance structures is asymptotically efficient but has much worse finite-sample properties than does the equally-weighted minimum distance (EWMD) estimator. This paper shows how the bootstrap can be used to improve the finite-sample...
Persistent link: https://www.econbiz.de/10014075738
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Posterior Simulation and Model Choice in Longitudinal Generalized Linear Models
Chib, Siddhartha; Greenberg, Edward; Winkelmann, Rainer - 1998
This paper is concerned with the problems of posterior simulation and model choice for Poisson panel data models with multiple random effects. Efficient algorithms based on Markov Chain Monte Carlo methods for sampling the posterior distribution are developed. A new parameterization of the...
Persistent link: https://www.econbiz.de/10014076167
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Likelihood Induced by Moment Functions using Particle Filter : A Comparison of Particle GMM and Standard MCMC Methods
Franco, Fabio - 2019
Particle filtering is a useful statistical tool which can be used to make inference on the latent variables and the structural parameters of state space models by employing it inside MCMC algorithms (Flury and Shephard, 2011). It only relies on two assumptions (Gordon et al, 1993): a: The...
Persistent link: https://www.econbiz.de/10014102930
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Attrition and the estimation of employment and wage equations : the Canadian survey of labour and income dynamics
Boudarbat, Brahim; Grenon, Lee - In: Applied economics letters 20 (2013) 10/12, pp. 1139-1144
Persistent link: https://www.econbiz.de/10010197004
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Difference‐in‐difference estimation by FE and OLS when there is panel non‐response
Lechner, Michael; Rodríguez-Planas, Núria; … - 2015
there is time varying panel non-response. If such non-response does not affect the common-trend assumption, then OLS and FE … are consistent, but OLS is more precise. However, if non-response is affecting the common-trend assumption, then FE … evidence that non‐response is not ignorable for the differences-in-differences estimation. …
Persistent link: https://www.econbiz.de/10011387121
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Parameter estimates comparison of earnings functions in the PSID and CPS data : 1976 - 2007
Gouskova, Elena - In: Economics letters 122 (2014) 2, pp. 353-357
Persistent link: https://www.econbiz.de/10010395672
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Hypothesis testing of multiple inequalities: The method of constraint chaining
Chen, Le-Yu; Szroeter, Jerzy - 2009
Econometric inequality hypotheses arise in diverse ways. Examples include concavity restrictions on technological and behavioural functions, monotonicity and dominance relations, one-sided constraints on conditional moments in GMM estimation, bounds on parameters which are only partially...
Persistent link: https://www.econbiz.de/10010288421
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Hypothesis testing of multiple inequalities: the method of constraint chaining
Chen, Le-Yu; Szroeter, Jerzy - 2009
Econometric inequality hypotheses arise in diverse ways. Examples include concavity restrictions on technological and behavioural functions, monotonicity and dominance relations, one-sided constraints on conditional moments in GMM estimation, bounds on parameters which are only partially...
Persistent link: https://www.econbiz.de/10003847567