I Got More Data, My Model is More Refined, but My Estimator is Getting Worse! Am I Just Dumb?

DOI10.1080/07474938.2013.808567zbMath1491.62116OpenAlexW1969936327MaRDI QIDQ5080444

Xianchao Xie, Xiao-Li Meng

Publication date: 31 May 2022

Published in: Econometric Reviews (Search for Journal in Brave)

Full work available at URL: http://nrs.harvard.edu/urn-3:HUL.InstRepos:10886849

zbMATH Keywords

Fisher informationunit rootestimating equationJeffreys priornon-informative priorAR(1) modelgeneralized method of moments (GMM)relative informationfraction of missing informationself-efficiencyobservation structurespartial plug-in

Mathematics Subject Classification ID

Applications of statistics to economics (62P20) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Asymptotic distribution theory in statistics (62E20) Bayesian inference (62F15) Foundations and philosophical topics in statistics (62A01)

Related Items (6)

Reply ⋮ Discussion: The Q‐q Dynamic for Deeper Learning and Research ⋮ Is there a role for statistics in artificial intelligence? ⋮ Judicious judgment meets unsettling updating: dilation, sure loss and Simpson's paradox ⋮ An Examination of Discrepancies in Multiple Imputation Procedures Between SAS® and SPSS® ⋮ Tarpey, T., Ogden, R. T., Petkova, E., and Christensen R. (2014), “A Paradoxical Result in Estimating Regression Coefficients,”The American Statistician, 68, 271–276 (this issue): Comment by Peng Ding

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Uniform moment bounds of Fisher's information with applications to time series
• From unit root to Stein's estimator to Fisher's \(k\) statistics: If you have a moment, I can tell you more
• Cross-fertilizing strategies for better EM mountain climbing and DA field exploration: a graphical guide book
• From EM to data augmentation: the emergence of MCMC Bayesian computation in the 1980s
• On the sample information about parameter and prediction
• Decoding the h-likelihood
• Asymptotic properties of multivariate nonstationary processes with applications to autoregressions
• Multivariate maximum entropy identification, transformation, and dependence
• A weakly informative default prior distribution for logistic and other regression models
• Generalized autoregressive conditional heteroscedasticity
• Single observation unbiased priors
• A note on mean squared prediction error under the unit root model with deterministic trend
• When are observed failures more informative than observed survivals?
• On Asymptotic Distributions of Estimates of Parameters of Stochastic Difference Equations
• The Limiting Distribution of the Serial Correlation Coefficient in the Explosive Case
• Pushing the Limits of Contemporary Statistics: Contributions in Honor of Jayanta K. Ghosh
• The Calculation of Posterior Distributions by Data Augmentation
• Testing for a unit root in time series regression
• The Parameter Inference for Nearly Nonstationary Time Series
• Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation
• Conditional likelihood and unconditional optimum estimating equations
• Assessing the accuracy of the maximum likelihood estimator: Observed versus expected Fisher information
• The Selection of Prior Distributions by Formal Rules
• Sampling-50 years after Shannon
• Time Series Regression with a Unit Root
• Asymptotic Inference for Mixture Models by Using Data-Dependent Priors
• An Optimum Property of Regular Maximum Likelihood Estimation

This page was built for publication: I Got More Data, My Model is More Refined, but My Estimator is Getting Worse! Am I Just Dumb?