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Are There Waves in Merger Activity after All

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TLDR
In this article, the authors investigated the merger wave hypothesis for the US and the UK employing a Markov regime switching model and identified the beginning of a merger wave in the mid 1990s but not the much-discussed 1980s merger wave.
Abstract
This paper investigates the merger wave hypothesis for the US and the UK employing a Markov regime switching model. Using quarterly data covering the last thirty years, for the US, we identify the beginning of a merger wave in the mid 1990s but not the much-discussed 1980s merger wave. We argue that the latter finding can be ascribed to the refined methods of inference offered by the Gibbs sampling approach. As opposed to the US, mergers in the UK exhibit multiple waves, with activity surging in the early 1970s and the late 1980s.

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Rationality on the Rise: Why Relative Risk Aversion Increases with Stake Size

TL;DR: The authors show that the increase in relative risk aversion over gains cannot be captured by the curvature of the utility function, driven predominantly by a change in probability weighting of a majority group of individuals who exhibit more rational probability weightings at high stakes.
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Merger waves : a model of endogenous mergers

TL;DR: This paper developed a model of endogenous mergers to study their dynamic process and showed that mergers are strategic complements and therefore tend to occur in waves and some mergers occur for strategic reasons in order to precipitate further mergers.
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Validity of Discrete-Choice Experiments - Evidence for Health Risk Reduction

TL;DR: External validity of DCE concerning the reduction of a health risk is examined by comparing the value of a statistical life with other preference elicitation techniques, such as revealed preference anderion validity is shown by comparing WTP values derived from stated choices in the experiment with those derived from actual choices made by the same individuals.
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The determinants of merger waves: An international perspective.

TL;DR: This work finds significant differences between listed and unlisted firms as predicted by behavioral theories of merger waves, as well as natural way to discriminate between pure stock market influences on firm decisions and other influences.
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Exploring the effects of competition for railway markets

TL;DR: In this paper, the effects of introducing competition for local passenger railway markets in the German state of Baden-Wurttemberg were investigated. And the results suggest that the competitively procured lines enjoyed a stronger growth of the frequency of service than those that were not procured competitively, even after controlling for various line characteristics that might have had an independent influence on the operator.
References
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Journal ArticleDOI

Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images

TL;DR: The analogy between images and statistical mechanics systems is made and the analogous operation under the posterior distribution yields the maximum a posteriori (MAP) estimate of the image given the degraded observations, creating a highly parallel ``relaxation'' algorithm for MAP estimation.
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A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle.

James D. Hamilton
- 01 Mar 1989 - 
TL;DR: In this article, the parameters of an autoregression are viewed as the outcome of a discrete-state Markov process, and an algorithm for drawing such probabilistic inference in the form of a nonlinear iterative filter is presented.
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Sampling-Based Approaches to Calculating Marginal Densities

TL;DR: In this paper, three sampling-based approaches, namely stochastic substitution, the Gibbs sampler, and the sampling-importance-resampling algorithm, are compared and contrasted in relation to various joint probability structures frequently encountered in applications.
Journal Article

Sampling-based approaches to calculating marginal densities

TL;DR: Stochastic substitution, the Gibbs sampler, and the sampling-importance-resampling algorithm can be viewed as three alternative sampling- (or Monte Carlo-) based approaches to the calculation of numerical estimates of marginal probability distributions.
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