Munich Personal RePEc Archive

Linear regression using both temporally aggregated and temporally disaggregated data: Revisited

Qian, Hang (2010): Linear regression using both temporally aggregated and temporally disaggregated data: Revisited.

[img]
Preview
PDF
MPRA_paper_32686.pdf

Download (360kB) | Preview

Abstract

This paper discusses regression models with aggregated covariate data. Reparameterized likelihood function is found to be separable when one endogenous variable corresponds to one instrument. In that case, the full-information maximum likelihood estimator has an analytic form, and thus outperforms the conventional imputed value two-step estimator in terms of both efficiency and computability. We also propose a competing Bayesian approach implemented by the Gibbs sampler, which is advantageous in more flexible settings where the likelihood does not have the separability property.

UB_LMU-Logo
MPRA is a RePEc service hosted by
the Munich University Library in Germany.