Messy Data - Missing Observations, Outliers and Mixed Frequency Data Vol. 13

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ISBN: 9780762303038 | 0762303034
Cover: Hardcover
Copyright: 1/19/1999

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Often applied econometricians are faced with working with data that is less than ideal. The data may be observed with gaps in it, a model may suggest variables that are observed at different frequencies, and sometimes econometric results are very fragile to the inclusion or omission of just a few observations in the sample. Papers in this volume discuss new econometric techniques for addressing these problems.

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List of contributors
Introduction
Testing for random individual and time effects using unbalanced panel data
A statistical approach for disaggregating mixed-frequency economic time series data
An extended Yule-Walker method for estimating a vector autoregressive model with mixed-frequency data
Missing data from infrequency of purchase: Bayesian estimation of a linear expenditure system
Messy time series: a unified approach
Simulation of multinomial probit probabilities and imputation of missing data
Temporal disaggregation, missing observations, outliers, and forecasting: a unifying non-model based procedure
Testing for unit roots in economic time-series with missing observations
Influential data diagnostics for transition data
The effects of different types of outliers on unit root tests
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Messy Data - Missing Observations, Outliers and Mixed Frequency Data Vol. 13

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Table of Contents

Supplemental Materials