We explore how biased investors affect the market for real assets and estimate the resulting efficiency losses. Investors subject to non-proportional thinking ask (too) high merger premia to sell low-price targets and offer (too) low merger premia to buy high-price targets. As a result, M&A premia are lower for high-price targets and both low- and high-price firms are less likely to be acquired than firms in the middle of the price distribution. We test these predictions using a large sample of M&A transactions. We also quantify the value lost because positive-synergy deals do not happen due to non-proportional thinking. Our structural estimation suggests that investors’ mistakes reduce the frequency of M&A transactions by about 8% and the value created by the

M&A market by about 6%.

This paper provides the first quantification of the contribution of mergers and acquisitions (M&A) to rising industry concentration. We use comprehensive firm-level microdata from the U.S. Economic Census to show that M&A account for 44% of the increase in aggregate concentration. We classify M&A using the numerical criteria in the merger guidelines and show that presumed anticompetitive M&A account for 12% of the increase in aggregate concentration. We provide evidence indicating that low rates of intervention by the federal competition agencies reflect limited regulatory capacity rather than successful deterrence that prevented firms from attempting anticompetitive mergers.

We study how non-price deal terms shape outcomes in merger contests. We assemble a novel dataset of 738 U.S. mergers completed between 2015 and 2022 that records every formal offer, including price, payment method, financing contingencies, regulatory approval conditions, due diligence requirements, and exclusivity provisions. Three facts emerge. First, non-price terms are pervasive in private bidding. Second, their use varies systematically across bidder types, especially between strategic and financial acquirers. Third, price alone does not determine the winner: in 22% of contests with multiple formal bids, the highest price per share loses. We estimate a structural model to recover target valuations for these contractual provisions. The estimates imply that non-price deal terms have economically large effects and play a central role in determining which bidder ultimately acquires the target.