Merger waves and the structure of merger and acquisition time-series
Article first published online: 7 NOV 2006
Copyright © 1992 John Wiley & Sons, Ltd.
Journal of Applied Econometrics
Supplement: Special Issue on Nonlinear Dynamics and Econometrics
Volume 7, Issue Supplement S1, pages S83–S100, December 1992
How to Cite
Town, R. J. (1992), Merger waves and the structure of merger and acquisition time-series. J. Appl. Econ., 7: S83–S100. doi: 10.1002/jae.3950070507
- Issue published online: 7 NOV 2006
- Article first published online: 7 NOV 2006
- Manuscript Revised: MAR 1992
- Manuscript Received: MAY 1991
What is the best characterization of mergers and acquisitions time-series? The traditional response is that mergers occur in ‘waves’. I estimate a two-state, Markov switching-regime model which should capture wave structure if it is present in the data. Linear and nonlinear diagnostics tests suggest that the switching regime model fits the data well, and better than ARIMA models. Said differently, the underlying pattern in the M&A data can be characterized by dichotomous shifts between high and low levels of activity. In addition, objective inferences about the precise dates for these waves are available through a nonlinear filter.