The claim, beside its test
One page, both columns: what the claim asserts and what the one program-level test found: with each side's own caveat in its own words.
| Dimension | The claim, a McKinsey corpus from 2012 to 2023 | The test (Laamanen & Keil, 2008) |
|---|---|---|
| Question asked | Which realized deal pattern had the best excess TSR, by archetype, ex post? | Does a program's rate, rhythm and scope predict excess returns? |
| Population | Top 1,000 → "Global 2,000" companies, windows shifting by refresh | 611 U.S. acquirers with 4+ deals, 5,518 deals, 1990–99 |
| Finding | Programmatic acquirers outperform (~2%/yr excess TSR in 2021; 3.9% vs 2.9% in 2023): under a definition that changes per telling (Table 1) | Rate hurts; rhythm variability hurts; experience, size and focus buy tolerance; R² 0.02–0.04. Decade medians favor frequent acquirers (+12.6% vs −3.9%/yr): descriptive, no test reported |
| Own caveat, verbatim | "[T]his is a correlation, not necessarily a causative relationship … it is possible that better-performing companies executed more deals in the wake of their success" (2012, fn. 9) | "We cannot claim causality. Some of the performance effects we find for the most active acquirers could be due to superior prior performance of the acquirer" |
| Prior result on the same data | Apr 2011, same shop, same population: size and frequency patterns "widely distributed and overlapping" | : |
| What it licenses | A hypothesis worth testing on your own program's terms | Conditions worth checking before and during any program |
Swipe or scroll horizontally if the table is wider than your screen.
Reference & Evidence
Source: Author's assembly of Rehm, Uhlaner & West (2012) and refreshes through Daume, Lian & McCurdy (2023), against Laamanen & Keil (2008) and Cottin, Rehm & Uhlaner (2011). Each cell's source and conditions are in the text. A reading aid, not a finding of any single source.
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