A desirable property of an autocovariance estimator is to be robust to the presence of additive outliers. It is well-known that the sample autocovariance, being based on moments, does not have this property. Hence, the use of an autocovariance estimator which is robust to additive outliers can be very useful for time-series modeling. In this paper, the asymptotic properties of the robust scale ...

Bai (2009) proposes recursive estimation for panel data models with interactive effects. We study the behaviours of this estimator. The formula is established that shows estimators depend on initial estimator, population structure and iterative steps. Under some general scenarios, we find estimator becomes consistent after first iteration from any initials. also obtain optimal number steps unde...

We extend the Berry, Levinsohn and Pakes (BLP, 1995) random coefficients discretechoice demand model, which underlies much recent empirical work in IO. We add interactive fixed effects in the form of a factor structure on the unobserved product characteristics. The interactive fixed effects can be arbitrarily correlated with the observed product characteristics (including price), which accommod...

This paper presents a Hayashi-Yoshida type estimator for the covariation matrix of continuous Itô semimartingales observed with noise. The coordinates of the multivariate process are assumed to be observed at highly frequent nonsynchronous points. The estimator of the covariation matrix is designed via a certain combination of the local averages and the Hayashi-Yoshida estimator. Our method doe...