This paper discusses regression models with aggregated covariate data. Reparameterized likelihood function is found to be separable when one endogenous variable corresponds to one instrument. In that case, the full-information maximum likelihood estimator has an analytic form, and thus...

Data from surveys often include errors, and such errors can have a serious effect on inferences about behavior or perceptions. In this paper a model is developed for making inferences based on dichotomous survey data with possible errors. A likelihood analysis reveals an identification problem,...

In estimation of the normal covariance matrix, finding a least favorable sequence of prior distributions has been an open question for a long time. This paper addresses the classical problem and accomplishes the specification of such a sequence, which establishes minimaxity of the best...

This paper examines the predictive performance of two representative agent models of earnings momentum using the US S & P 500 sample frame in the years 1991–2006. For successive sequences of quarterly earnings outcomes over a three year horizon of quarterly increases/decreases, etc., we ask...

Markov-switching models are usually specified under the assumption that all the parameters change when a regime switch occurs. Relaxing this hypothesis and being able to detect which parameters evolve over time is relevant for interpreting the changes in the dynamics of the series, for...

Предложен новый класс моделей надежности программного обеспечения, в основу которых положены известные модели, использующие неоднородные процессы Пуассона,...