Most hypotheses in binary response models are composite. The null hypothesis is usually that one or more slope coefficients are zero. Typically, the sequence of alternatives of interest is one in which the slope coefficients are increasing in absolute value. In this papar, we prove that the...

This paper considers the case of Bayesian learning about the relationship between the greenhouse-gas level and temperature rise. Learning takes time because of a stochastic shock to the realized global mean temperature. The paper illustrates the difficulty of quickly learning about the...

In this paper we obtain bounds under weaker nonparametric assumptions and explore how the bounds with assumptions imposed.

In this paper we analyse the problem of the modelling of individual transitions in presence of an incomplete sampling scheme.

We obtain an inequality for th esmaple varaince of a Brownian motion on [0,1] and an associated Ornstein-Uhlenbeck process. The result is applied to a regression involving a near-integrated regressor, and establishes that in the limit the dispersion of the least squares estimator is greater in...

The paper deals with estimation of missing observations in possibly nonstationary ARIMA models. First, the model is assumed known, and the structure of the interpolation filter is analysed. Using the inverse or dual autocorrelation function it is seen how estimation of a missing observation is...

The paper contains some implications for applied econometric research. Two important ones are, first, that invertible models, such as AR or VAR models, cannot in general be used to model seasonally adjusted or detrended data. The second one is that to look at the business cycle in detrended...