Abstract

This thesis investigates the impact of vertical and horizontal mergers and acquisitions on investor wealth, specifically focusing on how economic uncertainty influences merger behavior and outcomes. The study follows Fan & Goyal's (2006) methodology and distinguishes between vertical and horizontal mergers using input-output tables from the U.S. Bureau of Economic Analysis. The first hypothesis posits that economic uncertainty increases the proportion of vertical mergers. In contrast, the second explores whether vertical mergers generate higher abnormal returns in uncertain times compared to unrelated mergers. Using a sample of over 100,000 U.S. M&A transactions from 2006 to 2020, sourced from SDC Platinum, the research classifies mergers by vertical relatedness and applies event study analysis and multiple linear regression methodology. Findings reveal a consistent statistical relationship between economic health indicators (S&P 500 variations) and the proportion of vertical mergers. Furthermore, results from event studies and regression models suggest that vertical relatedness has a significant positive effect on CAAR during periods of economic instability, particularly from 2006 to 2010 and 2016–2020. The Economic Policy Uncertainty Index (EPUI) support the selection of instability periods and confirms the findings between economic instability, uncertainty and CAR variations. The study contributes to the M&A literature by demonstrating that vertical integration may serve as a strategic risk-mitigation tool during volatile economic conditions, delivering higher value to investors than horizontal mergers under similar circumstances.