INTRODUCTION TO ECONOMETRICS II ECO 306 NOUN 118
UNIT 2: AUTOCORRELATION CONTENTS 4.2.1.0
Introduction 4.2.2.0 Objectives
4.2.3.0
Main Content 4.2.3.1 Possible Causes of Autocorrelation
4.2.3.2 Detection of First-Order Autocorrelation: the Durbin–Watson Test
4.2.4.0
Summary 4.2.5.0 Conclusion
4.2.6.0
Tutor-Marked Assignment 4.2.7.0 References/Further Reading
4.2.1.0 INTRODUCTION Autocorrelation is the correlation between the error terms arising in time series data. Such correlation in the error terms often arises from the correlation of the omitted variables that the error term captures. Furthermore, the assumption in the third Gauss–
Markov condition is that the value taken by the disturbance term in any observation and determined independently of its values
in all the other observations, is satisfied, and hence that
the population covariance of and is 0 for
i ≠ j. When the condition is not satisfied, the disturbance term is said to
be subject to autocorrelation, often called serial correlation or cross-autocorrelation.
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