A procedure for computing the parameters of latent multifactor models in econometrics is proposed based on indirect estimation methods.

In this paper, we aim at forecasting the stochastic volatility of key financial market variables with the Kalman filter using stochastic models developed by Taylor (1986, 1994) and Nelson (1990). First, we compare a stochastic volatility model relying on the Kalman filter to the conditional...

This paper describes a simple method of calculating a heteroskedasticity and autocorrelation consistent covariance matrix that is positive semi-definite by construction. It also establishes consistency of the estimated covariance matrix under fairly general conditions. (This abstract was...

We propose a new generalization of the concept of cointegration that allows for the possibility that a set of variables are involved in an unknown nonlinear relationship. Although these variables may be unit-root non-stationary, there exists a nonlinear combination of them that takes account of...

Integer-valued autoregressive (INAR) processes have been introduced to model nonnegative integervalued phenomena that evolve in time.The distribution of an INAR(p) process is determined by two parameters: a vector of survival probabilities and a probability distribution on the nonnegative...

This paper considers integer-valued autoregressive processes where the autoregression parameter is close to unity.We consider the asymptotics of this `near unit root' situation.The local asymptotic structure of the likelihood ratios of the model is obtained, showing that the limit experiment is...

The paper discusses the problem of a fallible auditor who assesses the values of sampled records, but may make mistakes.To detect these mistakes, a subsample of the checked elements is checked again, now by an infallible expert. We propose a model for this kind of double check, which takes into...

Multivariate regression is discussed, where the observations of the dependent variables are (monotone) missing completely at random; the explanatory variables are assumed to be completely observed.We discuss OLS-, GLS- and a certain form of E(stimated) GLS-estimation.It turns out that...

Many unit root and cointegration tests require an estimate of the spectral density function at frequency zero at some process. Kernel estimators based on weighted sums of autocovariances constructed using estimated residuals from an AR(1) regression are commonly used. However, it is known that...