Time Series Analysis of the Dynamics of Merger and Acquisition Cycles in the Global Water Sector

Manuel Monge (), Rafael Hurtado and Juan Infante
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Manuel Monge: Faculty of Law, Business and Government, Universidad Francisco de Vitoria, E-28223 Madrid, Spain
Rafael Hurtado: Faculty of Business, Economics and Law, CUNEF Universidad, E-28040 Madrid, Spain
Juan Infante: Faculty of Social Science and Law, Universidad Villanueva, E-28034 Madrid, Spain

Mathematics, 2025, vol. 13, issue 7, 1-13

Abstract: This paper examined the cyclical patterns of mergers and acquisitions (M&A) in the global water sector from 1982 to 2024, with a focus on both linear and nonlinear dynamics in M&A waves. Through a univariate analysis using ARFIMA models, we found that the data exhibited stationary behavior, meaning that in response to an exogenous shock, the series is likely to revert to its original trend over time. Additionally, the non-parametric Brock, Dechert, and Scheinkman (BDS) test revealed the complex and irregular nature of M&A cycles within the sector. To account for this complexity, we applied the Markov-switching dynamic regression (MS-DR) model, which shows that once the industry enters a high-activity regime, it tends to persist in this state for extended periods. This suggests that external shocks or trends—such as regulatory reforms or global water scarcity concerns—are key drivers that trigger and sustain waves of M&A activity in the sector.

Keywords: M&A; completed; water sector; global; ARFIMA (p,d,q) model; BDS test; Markov-switching dynamic regression (MS-DR) model (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2025
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