Missing observations in stochastic difference equation with arma errors

Pedro Valls Pereira

Brazilian Review of Econometrics, 1987, vol. 7, issue 1

Abstract: This paper considers the estimation of stochastic difference equation with missing observations. Time series data is available at different levels of aggregations. The most common is the annual-quarterly model, where for the first part of the time series data, some of the endogenous and/or exogenous variables are available on an annual basis and the second part on a quarterly basis. A method of estimation, based on the Kalman Filter, enables us to obtain the exact maximum likelihood estimates of the model.

Date: 1987
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