A geometrical setting is constructed, based on Hilbert space, in which the asymptotic properties of estimators can be studied. Estimators are defined in the context of parametrised models, which are treated as submanifolds of an underlying Hilbert manifold, on which a parameter-defining mapping...

In an economy with one riskless and one risky asset, we compare the Sharpe ratios of investment funds that allow: i) timing strategies which forecast the market using simple regressions; ii) a strategy which uses multiple regression instead; and iii) a passive allocation which combines the funds in...

The paper deals with the problem of identifying stochastic unobserved two-component models, as in seasonal adjustment or trend-cycle decompositions. Solutions based on the properties of the unobserved component estimation error are considered, and analytical expressions for the variances and...

Many common statistical models can be specified as linear models with restrictions imposed on the parameters. A large amount of these models impose restrictions which do not allow for the analytical construction of the probability density function (pdf) of the parameters given the restrictions....

The paper deals with the problem of identifying stochastic unobserved two-component models, as in seasonal adjustment or trend-cycle decompositions. Solutions based on the properties of the unobserved component estimation error are considered, and analytical expressions for the variances and...

This paper considers GMM estimation of autoregressive processes. It is shown that, contrary to the case where the noise is independent, using high-order moments can provide subtantial efficiency gains for estimating the AR model when the noise is only uncorrelated.

We extend the basic equilibrium search model of Burdett-Mortnesen with a human capital accumulating wage function and solve for the new equilibrium distribution of wages. We find an equilibrium distribution of earned wages with no upper bound of the support and with density having a decreasing...

Procedures for estimating a linear single-equation model by means of panel data with errors-in-variables are considered. To eliminate fixed individual heterogeneity, the equation is differenced across one or more than one periods. The differenced equations can be estimated by using as...

We study the problem of estimating some unknown regression or autoregression function in a B-mixing dependent framework (for the design or the errors). For this end, we consider some collection of models which are finite dimensional spaces. A penalized least-squares estimator (PLSE) is built on...