Sector aggregation bias in survival-adjusted Goodwill Valuation: evidence from 85 NAICS industries

Survival-adjusted goodwill valuation requires a sector-calibrated hazard parameter. Prior work has calibrated this parameter at the two-digit NAICS sector level, using 19 broad industry groupings. We ask whether sector aggregation at the two-digit level introduces material valuation bias — that is, whether the within-sector dispersion in survival probability is large enough to affect transaction pricing when the assigned multiplier corresponds to the sector average rather than the firm's specific industry group. Using 30 years of establishment cohort data from the U.S. Census Bureau Business Dynamics Statistics program (1994–2023) and maximum likelihood estimation with bootstrap confidence intervals, we calibrate the Business Survival Value Multiplier (BSVM) for 85 three-digit NAICS sub-sectors and document the distribution of calibrated values at the four-digit industry group level (287 groups). We find that cross-sector dispersion expands from 10.5 percentage points at the two-digit level to 24.3 percentage points at three digits and 37.3 percentage points at four digits — a 3.5-fold amplification. The sectors exhibiting the largest within-parent dispersion are Health Care (21.1 pp), Real Estate (19.7 pp), and Finance and Insurance (18.7 pp). Applying a two-digit sector multiplier to a firm whose four-digit group has a materially different survival profile introduces a systematic bias that is invisible to analysts relying on aggregated data. We provide the complete calibration for 85 three-digit sub-sectors and illustrate the magnitude of aggregation bias through six sector case studies. The findings imply that sector granularity is the most consequential single parameter choice in survival-adjusted goodwill valuation, exceeding in magnitude the sensitivity to the valuation horizon or the choice of parametric survival model. Keywords: sector aggregation bias, goodwill valuation, survival analysis, M&A, NAICS granularity, BSVM, purchase price allocation, impairment testing, business mortality

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-04-20
DOI
https://doi.org/10.5281/zenodo.19673364
Primary Topic
Auditing, Earnings Management, Governance
Type
article
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article

Sector aggregation bias in survival-adjusted Goodwill Valuation: evidence from 85 NAICS industries

Ruben Freitas
Zenodo (CERN European Organization for Nuclear Research)
Auditing, Earnings Management, Governance
article

Sector aggregation bias in survival-adjusted Goodwill Valuation: evidence from 85 NAICS industries

Ruben Freitas
article en

Abstract

Survival-adjusted goodwill valuation requires a sector-calibrated hazard parameter. Prior work has calibrated this parameter at the two-digit NAICS sector level, using 19 broad industry groupings. We ask whether sector aggregation at the two-digit level introduces material valuation bias — that is, whether the within-sector dispersion in survival probability is large enough to affect transaction pricing when the assigned multiplier corresponds to the sector average rather than the firm's specific industry group. Using 30 years of establishment cohort data from the U.S. Census Bureau Business Dynamics Statistics program (1994–2023) and maximum likelihood estimation with bootstrap confidence intervals, we calibrate the Business Survival Value Multiplier (BSVM) for 85 three-digit NAICS sub-sectors and document the distribution of calibrated values at the four-digit industry group level (287 groups). We find that cross-sector dispersion expands from 10.5 percentage points at the two-digit level to 24.3 percentage points at three digits and 37.3 percentage points at four digits — a 3.5-fold amplification. The sectors exhibiting the largest within-parent dispersion are Health Care (21.1 pp), Real Estate (19.7 pp), and Finance and Insurance (18.7 pp). Applying a two-digit sector multiplier to a firm whose four-digit group has a materially different survival profile introduces a systematic bias that is invisible to analysts relying on aggregated data. We provide the complete calibration for 85 three-digit sub-sectors and illustrate the magnitude of aggregation bias through six sector case studies. The findings imply that sector granularity is the most consequential single parameter choice in survival-adjusted goodwill valuation, exceeding in magnitude the sensitivity to the valuation horizon or the choice of parametric survival model. Keywords: sector aggregation bias, goodwill valuation, survival analysis, M&A, NAICS granularity, BSVM, purchase price allocation, impairment testing, business mortality

Zenodo (CERN European Organization for Nuclear Research)
Industry, innovation and infrastructure
Openalex Percentile: Top 4%
Auditing, Earnings Management, Governance
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