This paper examines robust estimators of core inflation for Belgian historical CPI data, and the euro area Harmonised indices of Consumer Prices.

We obtain semiparametric efficiency bounds for estimation of a location parameter in a time series model where the innovations are stationary and ergodic conditionally symmetric marginale differences but otherwise prossess general depence and distributions of unknown from. We then describe an...

This paper specifies a vertically differentiated products model for a product with a discrete/continuous choice. The model is easily estimated with the relatively limited data used in classical demand equation estimation, supplemented by readily available market characteristics data. The model,...

Recent work has suggested plant level heterogeneity and discrete production processes can produce problems for estimation. A structural model of discrete production decisions by heterogeneous plants is constructed and, as a case study, estimated for the US Portland cement industry. In...

This paper specifies a vertically differentiated products model for a product with a discrete/continuous choice. The model is easily estimated with the relatively limited data used in classical demand equation estimation, supplemented by readily available market characteristics data. The model,...

The objective of this paper is to determine how finite dimensional parameters can be efficiently estimated for an important class of economic models.

The paper derives and tests maximum likelihood parameter estimators for symmetrically correlated Weiner processes observed at discrete intervals. Such processes are arise when pricing and determining Value-at-Risk for portfolio derivatives. Cases of driftless and mean-reverting state variables...

We propose methods to test for common deterministic seasonality, while allowing for possible seasonal unit roots. For this purpose, we consider panel methods, where we allow for individualand for common dynamics. To decide on the presence of seasonal unit roots, we introduce a decision-based...