A panel data regression model for defense merger and acquisition activity

Abstract

PurposeThis paper examines the relationship between a prime contractor's financial health and its mergers and acquisitions (M&A) spending in the defense industry. It aims to provide models that give the United States Department of Defense (DoD) indications of future M&A activity, informing decision-makers and contributing to ensuring competitive markets that benefit the consumer.Design/methodology/approachThe study uses panel data regression models on 40 companies between 1985 and 2021. The company's financial health is assessed using industry-standard financial ratios (i.e. measures of profitability, efficiency, solvency and liquidity) while controlling for economic factors such as national productivity, defense budgets and firm size.FindingsThe results show a significant relationship between efficiency and M&A spending, indicating that companies with lower efficiency tend to spend more on M&As. However, there was no significant relationship between M&A spending and a company's profitability or solvency. These results were consistent with previous research and the study's hypotheses for profitability and solvency. However, the effect of liquidity was the opposite of the expected result, possibly due to the defense industry's different view on liquidity compared to previous research.Originality/valueThe paper provides insights into the relationship between a prime contractor's financial health and its M&A spending, a topic with limited research. The findings can inform policymakers and regulators on the industrial base's future M&A activity, ensuring competitive markets that benefit the consumer.