In 2025 Delaware, Texas, and Nevada each rewrote their corporate law within about ninety days of one another. This page asks one thing: when the law changed, did the market reprice the companies it governs?
An event study asks: on the day news hit, did the stock move more than it should have? The part of the move that the market and known risk factors cannot explain is the abnormal return — the market's verdict on the news.1
Every stock normally moves with the market. We first learn each firm's "normal" relationship to the market over a long quiet period before the event. Then on event day we compare what the stock actually did to what that normal relationship predicted. The gap is the reaction to the news.
A student usually scores about 5 points above the class average. This week the class averaged 80, so we predict ~85. She scores 92. The +7 is her "abnormal" score — the part not explained by how the class did. An event study does exactly this for a stock instead of a student.
Market model fit on the estimation window:
\[ R_{i,t}=\alpha_i+\beta_i' F_t+\varepsilon_{i,t} \]
Abnormal return on event day \(t\):
\[ AR_{i,t}=R_{i,t}-\big(\hat\alpha_i+\hat\beta_i' F_t\big) \]
Cumulated over a window and averaged across \(N\) firms:
\[ CAAR=\tfrac1N\sum_{i}\sum_{t\in W} AR_{i,t} \]
Our benchmark \(F_t\) is the Fama–French five-factor model plus momentum (FF5+UMD)2 — it strips out market, size, value, profitability, investment, and momentum, so what's left is closer to the news effect and not a style tilt.
Small firms, cheap firms, and profitable firms tend to move together for reasons that have nothing to do with corporate law. The factor model subtracts those common patterns so we don't mistake "this is a small-cap day" for "this is the law's effect."
Before saying a drug raised someone's heart rate, a doctor adjusts for age, caffeine, and exercise. FF5+UMD is that adjustment for a stock: subtract the known drivers, then see if anything is left.
\[ R_{i,t}-R_{f,t}=\alpha_i+\beta_{mkt}\,\mathrm{MKT}_t+\beta_{smb}\mathrm{SMB}_t \] \[ +\beta_{hml}\mathrm{HML}_t+\beta_{rmw}\mathrm{RMW}_t+\beta_{cma}\mathrm{CMA}_t+\beta_{umd}\mathrm{UMD}_t+\varepsilon_{i,t} \]
We report the test statistic robustly. Because event-day returns are fat-tailed and firms share a single event date, standard t-tests overstate significance; we report standardized and cross-sectionally adjusted statistics alongside the parametric tests.3
| Statistic | What it guards against |
|---|---|
| Patell Z (1976) | standardizes each firm by its own estimation-window noise |
| Boehmer–Musumeci–Poulsen (1991) | event-induced volatility (variance jumps on news days) |
| Kolari–Pynnönen (2010) | cross-correlation — firms sharing one event date are not independent |
| Corrado rank / sign (1989) | non-normal, outlier-heavy return distributions |
The interactive panel below shows the estimation window (used to learn each firm's normal behaviour) and the event window (the days the news effect is read), with no event-day data leaking into the baseline.
tristate_results_canonical.json (build v3, as of 2026-06-21) · BUILD_MANUAL §152.149–§152.164. Hover for values; drag/scroll where enabled; ⤢ for fullscreen inside the panel.Returns are CRSP CIZ daily (delisting-adjusted) through 2025-12-31, extended to 2026-06-18 on the reviewer-built canonical panel; fundamentals from WRDS wave-2 (130 parquet files, 1.68 GB); factors from Fama–French.4 Every excluded firm carries a named structural reason — there is no black-box dropout.5 Of the firm universe, are retained (%) after a named-reason exclusion ledger of ; the % figure reported elsewhere is the share of the reincorporation cohort linked to CRSP, a different population.
A controller-protective statute should bite hardest on controlled firms — those with a founder or insider holding a large voting block. The Delaware reform's bright line is ≥ 33⅓% of the voting power.6
Two distinct questions sit side by side here, and we report both as co-equal findings.
(a) The aggregate Delaware comparison. Following Khoo & Tallarita's design — all Delaware firms versus all non-Delaware firms, covariate-adjusted — the Delaware indicator carries a statistically significant discount at their headline [−1,+5] window: −0.85 pp (t −2.56, p .011; winsorized 1/99 per day).7 This is a genuine, significant aggregate result, not a null.
(b) The within-Delaware controlled-vs-dispersed test. The question this page set out to answer — do controlled Delaware firms move differently from dispersed ones — is null: −0.84% (p .50), statistically indistinguishable from zero. The estimate remains insignificant under alternative event windows, factor models, and winsorization. Controlling-shareholder firms are those with a single holder controlling ≥ one-third of voting power (from proxy statements).
The aggregate discount is not window-robust. At the symmetric [−1,+1] announcement window the Delaware coefficient flips to +0.25 pp (p .37); the discount appears only once the window is widened to absorb a post-event drift over days +2…+5 (window grid below). It is therefore a concentrated post-event drift, not a clean announcement-core reaction.
The controlled-minus-dispersed coefficient is statistically indistinguishable from zero, and stays insignificant across the robustness battery below — alternative event windows, factor models, and winsorization choices.7
tristate_results_canonical.json (build v3, as of 2026-06-21) · BUILD_MANUAL §152.149–§152.164. Interactive: hover for values, drag/scroll where enabled, ⤢ for fullscreen inside the panel.tristate_results_canonical.json (build v3, as of 2026-06-21) · BUILD_MANUAL §152.149–§152.164. Interactive: hover for values, drag/scroll where enabled, ⤢ for fullscreen inside the panel.tristate_results_canonical.json (build v3, as of 2026-06-21) · BUILD_MANUAL §152.149–§152.164. Interactive: hover for values, drag/scroll where enabled, ⤢ for fullscreen inside the panel.tristate_results_canonical.json (build v3, as of 2026-06-21) · BUILD_MANUAL §152.149–§152.164. Interactive: hover for values, drag/scroll where enabled, ⤢ for fullscreen inside the panel.tristate_results_canonical.json (build v3, as of 2026-06-21) · BUILD_MANUAL §152.149–§152.164. Interactive: hover for values, drag/scroll where enabled, ⤢ for fullscreen inside the panel.tristate_results_canonical.json (build v3, as of 2026-06-21) · BUILD_MANUAL §152.149–§152.164. Interactive: hover for values, drag/scroll where enabled, ⤢ for fullscreen inside the panel.A firm is "controlled" when a single holder commands at least one-third of the voting power, read from its proxy statement. On that measure the controlled-minus-dispersed reaction is , p≈.50: nothing.
Calling a company "family-controlled" because all employees together own 35% — when no single family member owns more than 10%. That is a different thing entirely.
The indicator is \( \mathbb{1}[\max_j \text{voting}_j \ge 33.3\%] \): a firm is controlled when its single largest holder commands at least one-third of the voting power, the S.B. 21 bright line.
We tried many windows, events, and cuts. With ~42 tries, one will look significant by chance. Correct for that and the p-value rises to 0.36.
Flip 42 fair coins ten times each; one will show 8 heads and "look" biased. That coin is not special — you just looked 42 times.
Romano–Wolf step-down max-\(t\) over the family \(\{\text{events}\times\text{windows}\times\text{cuts}\}\): \( p_{RW}=0.36 \). Bonferroni \(\approx\) .74–1.0; Benjamini–Hochberg FDR \(q\approx\).07. We treat the family-wise error rate (Romano–Wolf \(p_{RW}=0.36\)) as the governing criterion here, not the less conservative false-discovery rate, because the claim at issue is a single specific cell rather than a portfolio of discoveries.8
We re-ran the test on random dates where nothing happened — and the same −1.6% to −1.8% gap appeared. The controlled firms were also already falling ~6% before the window opened. So it reads as a pre-existing trend, not a reaction to the law.
If patients on a placebo "improve" as much as patients on the drug, the drug is not doing the work. A no-news date is the placebo for an event study.
Pre-event run-up \(CAAR_{[-20,-3]}=-6.08\%\). Difference-in-differences nets it out: event-window increment \(=+3.68\%\) (t=1.31). Placebo dates: −1.75% (p=.07), −1.60% (p=.10).
Remove the single most extreme firm and significance is gone (p=.066). The result is carried by five small stocks that fell 20–28% — for reasons unrelated to a Senate committee vote.
A drug trial where the "benefit" disappears if you drop one patient is not a finding — it is that patient's story.
Jackknife: \( \hat\delta_{(-i)} \) range gives \(p\in[.019,.066]\); 10 of 84 single-firm deletions flip significance.
All firms react on the same day, so their "abnormal returns" are correlated — there are not 84 independent observations. Account for it and p rises to ~0.07.
Surveying 84 people who all watched the same advertisement together is not 84 independent opinions — it is closer to one room's reaction.
Effective N with mean correlation \(\bar r\): \( N_{\text{eff}}=N/[1+(N-1)\bar r] \); Kolari–Pynnönen adjusted \( p=.072 \).
As risk factors are added, the effect shrinks step by step (−2.94% → −2.11%). A genuine governance effect would not depend on which risk model you use; a style tilt does.
If a "diet effect" shrinks every time you also control for exercise, sleep, and age, much of it was never the diet.
\( \hat\delta \): CAPM −2.94% → FF3 −2.94% → FF5 −2.28% → FF5+UMD −2.11%. Monotone decay = benchmark-dependent = not invariant.
The journal-standard fix for a few extreme returns is to cap the top and bottom 1%. Do that and the controlled-firm result stays null at every level.
If one lottery winner makes the "average income" of a town look rich, you cap the extremes before averaging. Same idea.
Winsorize \( CAR \) at \([1,99]\): −0.89% (p=.46); at \([2.5,97.5]\) the result remains insignificant.9
We ran the full endogeneity battery — none of it resurrects an effect.10
| Method | What it corrects | Result |
|---|---|---|
| OLS baseline (SIC FE) | covariate adjustment only | |
| Propensity-score matching (1:3 NN) | observable confounding | |
| Entropy / IPW reweighting | covariate imbalance (no exclusion needed) | |
| Heckman two-step | self-selection into "controlled" | |
| Instrumental variables (2SLS) | endogenous incorporation choice |
If the −0.84% announcement estimate (or K-T's −1.4%) were a real revaluation, controlled firms should have kept underperforming. With the panel extended through 2026-06-18 we held the portfolio over the full ~14–16 months after the event and tested two ways, with daily returns winsorized 1/99.11
tristate_results_canonical.json (build v3, as of 2026-06-21) · BUILD_MANUAL §152.149–§152.164. Hover for values; drag/scroll where enabled; ⤢ for fullscreen inside the panel.Over the full year-plus, did the controlled firms stay down, recover, or bounce? They reverted — the gap closed. To the data's edge (June 18, 2026, ~16 months) the cumulative gap is , not significant.
A patient dips after a treatment, then recovers to baseline over the year. The dip was transient, not a permanent decline.
Calendar-time hedge \(\alpha\): \[ R^{hedge}_t=\alpha+\beta'F_t+\varepsilon_t \] Through the full window to 2026-06-18 (334 td): unconditional \( \bar R^{hedge}=+0.005\%/\text{day} \), \(t_{NW}=0.14\), \(p=.89\), cum +0.9%; CAPM \(\hat\alpha=+0.003\%/\text{day}\), \(p=.93\). FF5+UMD \(\hat\alpha\) (\(p=.82\), cum +2.8%) is factor-bounded at 2026-04-30. BHAR = +3.1% (median −17.7%, 95% CI [−21.8, +34.8]). Returns winsorized 1/99.
On the dates S.B. 29 actually moved through the legislature, nothing happened. The only negative window (April 3) sits on the "Liberation Day" tariff crash and is concentrated in nine oil & gas names — remove them and it vanishes.12
tristate_results_canonical.json (build v3, as of 2026-06-21) · BUILD_MANUAL §152.149–§152.164. Hover for values; drag/scroll where enabled; ⤢ for fullscreen inside the panel.A "no detectable reaction" finding only means something if the test could have found a reaction. With Texas firms, the smallest effect we could reliably detect is ~2%. So we can say "no large reaction," not "the law is proven irrelevant."
A negative result is meaningful only if the test is sensitive enough at the stage you are testing. A weak test giving a negative tells you little. The Texas leg is a weak test.
Minimum detectable effect: \[ MDE=(z_{1-\alpha/2}+z_{power})\cdot \sigma_{CAR}/\sqrt N \approx 2\% \] Equivalence (TOST) against ±50 bp does not clear — the band we can support is ~±2%, not ±0.5%.13
We held the Texas-incumbent cohort from the S.B. 29 signing forward and asked whether any abnormal return accumulated over 1, 3, 6, and 12 months — a calendar-time portfolio (factor-model alpha) and buy-and-hold abnormal returns vs the market.13
For the firms whose reincorporation we have locked to an as-of-event date, we measure buy-and-hold abnormal returns vs the market at 1, 3, 6, and 12 months from each firm's own move date — the move is the event, not the legislative date. The mover track is reported separately from incumbents and is small, so read it as directional.15
tristate_results_canonical.json (build v3, as of 2026-06-21) · BUILD_MANUAL §152.149–§152.164. Hover for values; drag/scroll where enabled; ⤢ for fullscreen inside the panel.Destination by firm count: the DExit wave is overwhelmingly to Nevada, then Texas, with a small set going to other states and a counterflow back to Delaware. The flow diagram below maps each destination cohort to its current result status.
tristate_results_canonical.json (build v3, as of 2026-06-21) · BUILD_MANUAL §152.149–§152.164. Hover for values; drag/scroll where enabled; ⤢ for fullscreen inside the panel.Thirty-five tests across seven families. Status is reported as executed: nothing is marked run before it was.
One structural fact stands: on the single-holder ≥33⅓% measure, controller density runs Nevada (≈13.8%) > Delaware (≈2.6%) > Texas (0%). Texas's cohort is dominated by dispersed banks and royalty trusts, with no controlled firm at the bright line; Delaware sits in the middle; Nevada — whose NRS 78.138 extends business-judgment protection to directors and officers and whose NRS 78.240 limits controller fiduciary duties — is the densest.14
tristate_results_canonical.json (build v3, as of 2026-06-21) · BUILD_MANUAL §152.149–§152.164. Hover for values; drag/scroll where enabled; ⤢ for fullscreen inside the panel.The forest plot collects each leg's headline estimate with its status badge; the governance matrix records, per cohort, the legislative event and the per-leg result. Every value binds to the canonical dataset.
Khoo & Tallarita (“KT”) study the Delaware S.B. 21 episode by comparing the top 1,000 Delaware-incorporated firms to the top 1,000 non-Delaware firms around the February 18, 2025 event date.7 We re-ran that design on our as-of-event incorporation panel ( usable Delaware firms, non-Delaware), then carried the two cohorts forward through to test whether any short-window difference persists. This section reports the replication, the size-decomposition that drives it, an identification battery, and the long-horizon path — including the windows where the difference is null.
Reading the counts (they are nested, not contradictory). The Delaware cohort is the top 1,000 firms by 2024 market cap (≈1,000); of these, ≈988–993 have an estimable event-window CAR (those with sufficient estimation-window returns), which is the basis for the per-window CAAR and the buy-and-hold horizons; the cross-sectional regression pools both legs and so runs on n = 1,904 firms (Delaware plus non-Delaware) that also carry the full Compustat control set.
Cumulative average abnormal returns (CAAR), winsorized 1%/99% per day, against the Khoo–Tallarita Table 5 targets. The Delaware leg tracks their estimates closely; the non-Delaware control leg falls rather than rises, so the published positive spread does not reproduce in our panel.
Khoo & Tallarita's own voting-block analysis uses three groups keyed to the S.B. 21 33⅓% bright line, over the [-1,+5] window. We reproduce their published values here for a paper-faithful comparison. Any finer five-bin split (15–20, 20–25, 25–30, 30–35, >35%) shown elsewhere on this page is our finer refinement of K–T's voting-block cut, low-power, and not part of their published result.
A sequential Gelbach decomposition of the regression coefficient on the Delaware indicator, window [-1,+5]. The raw coefficient is positive; it turns negative once firm size (log assets) enters, and settles near the published magnitude under the full control set — locating the difference in the size gap between the two cohorts rather than in the law.
Five estimators recover the Delaware–minus–non-Delaware effect under progressively stronger balance. The pre-match imbalance is large (max standardized mean difference ), driven by size; how aggressively that imbalance is removed determines the answer.
Carrying the two cohorts forward, the chart below traces cumulative calendar-time portfolio paths for the Delaware–minus–non-Delaware hedge; the second chart shows buy-and-hold abnormal returns at fixed horizons. Factor-alpha regressions are capped at the Fama–French factor availability date (); the window beyond is shown as a market-adjusted path only.
stage5_longhorizon_results.json (Stage 5, run 2026-06-21). Equal- and value-weighted self-financing spreads; FF3 and FF5+UMD calendar-time alphas with Newey–West HAC. Interactive: hover for values.stage5_longhorizon_results.json (Stage 5, run 2026-06-21). BHAR vs panel value-weighted market; Lyon–Barber–Tsai skewness-adjusted t. Interactive: hover for values.ff5_umd_daily_2020_2026.csv.v3plus_wrds_data_2026-06-19, 130 parquet, 1.68 GB). BUILD_MANUAL §152.144, §152.154–155.07_REDTEAM/redteam_grid.py.06_OUTPUTS/winsorization_sensitivity_2026-06-19.md; BUILD_MANUAL §152.166. Convention: 1/99 cross-sectional, disclosed ex ante, robustness reported across levels.07_REDTEAM/extrev_b_selection.py; BUILD_MANUAL §152.164.daily_returns_panel_2026-06-20_v3.parquet (CRSP-canonical →2025-12-31, Compustat-canonical 2026-01..06-18), keyed on gvkey, returns winsorized 1/99. The FF5+UMD factor-model alpha is bounded at 2026-04-30 by Ken-French daily factor availability; the unconditional long-short hedge and a panel-EW-market CAPM alpha extend to the data edge 2026-06-18 (cum +0.9%, p=.89/.93), as does the BHAR. BUILD_MANUAL §152.171, §152.173 (supersedes the ~10.4-month CRSP-only result, §152.167).tristate_results_canonical.json (single source). Provenance: BUILD_MANUAL §152.136–§152.167. SMU Cox · Corporate Governance Initiative · Cox & Dedman Law. Empirical research only — not legal, investment, or tax advice. All interpretations are the author's own and do not represent SMU. Working draft v3 — not for external distribution until the voting-power rebuild + as-of-event lock land.