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...

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...

We consider representation, estimation and inference on cointegration in a periodic vector autoregressive time series model (PVAR). We show that cointegration amounts to a restriction on a product of parameter matrices. We therefore use GMM to construct estimators of the long-run (cointegration)...

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

This paper presents a new simulated maximum-likelihood method that rests on estimating the likelihood nonparametrically on a simulated sample. We prove that this method, which can be used on very general models, is consistent and asymptotically efficient.

We analyse what determines the incidence of unemployment among Danish employees by estimation of a logit model for becoming unemployed. Our data is incomplete in the sense that we do not observe whether a transition was caused by the person quitting or being laid off, so we apply the...