Regression with imputed covariates: a generalized missing-indicator approach
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Publication:737915
DOI10.1016/J.JECONOM.2011.02.005zbMath1441.62658OpenAlexW2157734155MaRDI QIDQ737915
Valentino Dardanoni, Franco Peracchi, Salvatore Modica
Publication date: 12 August 2016
Published in: Journal of Econometrics (Search for Journal in Brave)
Full work available at URL: http://hdl.handle.net/2108/15883
Related Items (11)
Model averaging for generalized linear models in fragmentary data prediction ⋮ Model averaging for generalized linear models with missing at random covariates ⋮ Mallows model averaging with effective model size in fragmentary data prediction ⋮ Missing data, imputation, and endogeneity ⋮ Efficient estimation with missing data and endogeneity ⋮ Ignoring non-ignorable missingness ⋮ ON EFFICIENCY GAINS FROM MULTIPLE INCOMPLETE SUBSAMPLES ⋮ Unnamed Item ⋮ Model averaging with covariates that are missing completely at random ⋮ Model averaging for multiple quantile regression with covariates missing at random ⋮ Model averaging estimation of generalized linear models with imputed covariates
Cites Work
- Unnamed Item
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- Weighted average least squares estimation with nonspherical disturbances and an application to the Hong Kong housing market
- On the harm that ignoring pretesting can cause
- A comparison of two model averaging techniques with an application to growth empirics
- Indicator and Stratification Methods for Missing Explanatory Variables in Multiple Linear Regression
- Bayesian Model Averaging for Linear Regression Models
- Estimation of Regression Coefficients of Interest when Other Regression Coefficients are of no Interest
- Model Building for Prediction in Regression Based Upon Repeated Significance Tests
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