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The Econometric Analysis of Recurrent Events in Macroeconomics and Finance$
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Don Harding and Adrian Pagan

Print publication date: 2016

Print ISBN-13: 9780691167084

Published to Princeton Scholarship Online: January 2018

DOI: 10.23943/princeton/9780691167084.001.0001

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Accounting for Observed Cycle Features with a Range of Statistical Models

Accounting for Observed Cycle Features with a Range of Statistical Models

Chapter:
(p.122) Chapter 7 Accounting for Observed Cycle Features with a Range of Statistical Models
Source:
The Econometric Analysis of Recurrent Events in Macroeconomics and Finance
Author(s):

Don Harding

Adrian Pagan

Publisher:
Princeton University Press
DOI:10.23943/princeton/9780691167084.003.0007

This chapter looks at observed features of the cycle in a variety of time series. It sets out these features for the United States and a number of other countries, and then asks whether these features can be replicated by the use of a particular statistical model—a linear autoregression. For such linear models it is possible to broadly account for the observed features using moments of the series for growth rates, and this strategy is employed in the chapter. It then uses a particular nonlinear statistical model to see if it can match all the features, and further looks at two other nonlinear models first dealt with in Chapter 4. The chapter concludes with an examination of whether the binary indicators summarizing the recurrent states can be used in the context of standard multivariate methods such as vector autoregressions. This turns out not to be straightforward owing to the nature of the binary variables.

Keywords:   cycles, linear autoregression, business cycles, recurrent states, time series

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