This paper proposes a new model-averaging method, called the Heteroskedasticity-Robust Cp (HRCp) method, for linear regression models with heteroskedastic errors. We provide a feasible form of the Mallows' Cp-like criterion for choosing the weighting vector for averaging. Under some regularity...

This paper demonstrates the importance of simultaneously considering two behavioral biases, correlation neglect and overprecision, in characterizing belief formation. Our laboratory experiments reveal that, relative to independent signals, subjects overvalue moderately or strongly correlated...

This paper considers linear panel data models with a grouped pattern of heterogeneity when the latent group membership structure and/or the values of slope coefficients change at a break point. We propose a least squares approach to jointly estimate the break point, group membership structure,...

We consider instrumental variables estimation of a possibly infinite order dynamic panel autoregressive (AR) process with individual effects. The estimation is based on the sieve AR approximation with its lag order increasing with sample size. Transforming the variable to eliminate individual...