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Why Capital Fled Manufacturing

Cross-sector EVA comparison using Damodaran data (2026 vintage, 90+ US sectors). Against Tier 2 capital-intensive physical manufacturing (ROC ~5.3%), software earns ~5.5x and services ~5.3x the return on capital; pharmaceuticals earn ~3.2x. Against Tier 1 broad manufacturing (ROC ~16%), the multiples are ~1.8x for software and services. Rational capital follows these spreads.

Broad Mfg ROC (Tier 1)

16.0%

22 sectors, 1,066 firms (NAICS 31–33)

Software ROC

29.3%

~1.8x broad manufacturing

Broad Mfg EVA Spread

+8.4pp

Value-creating, but half the rate of software

The Capital Flight Problem

Against Tier 1 broad manufacturing (22 sectors, 1,066 firms, weighted average ROC ~16.0%), software earns ~1.8x the return on capital (29.3%) and business and consumer services also ~1.8x (28.3%), with EVA spread gaps of +12pp and +13pp respectively. Pharmaceuticals earn ~1.1x (17.0%) after R&D capitalization — remarkably close to broad manufacturing. Against Tier 2 capital-intensive physical manufacturing (5 sectors, ROC ~5.0%), the multiples are far starker: software ~5.9x, services ~5.7x, pharma ~3.4x. Both tiers are true simultaneously — Tier 1 shows the structural underperformance, Tier 2 shows the capital destruction. The data is from Professor Aswath Damodaran's January 2026 EVA dataset covering 90+ US industry sectors, using lease- and R&D-adjusted after-tax return on invested capital.

Broad U.S. manufacturing (Tier 1: 22 NAICS 31–33 sectors, 1,066 firms) earns a weighted average ROC of ~16.0% with an EVA spread of approximately +8.4 percentage points — value-creating, but at roughly half the rate of software and services. The five capital-intensive physical sectors (Tier 2: Auto & Truck, Chemical, Steel, Rubber & Tires, Auto Parts) average just ~5.0% ROC against a ~7.2% WACC, producing a negative EVA spread of −2.2 percentage points — actively destroying economic value. Rational capital allocators have responded predictably by redirecting investment toward sectors where returns exceed the cost of capital by wider margins.

Software (System & Application, n=309 US firms) earns a lease-and-R&D-adjusted ROC of 29.3% against a 9.3% WACC, producing a +20.0pp EVA spread — approximately +12pp above Tier 1 broad manufacturing's +8.4pp spread. Business and Consumer Services (n=155 firms) earns an ROC of 28.3% with a +21.1pp spread (+13pp above Tier 1), the single largest positive spread in the dataset. Drugs/Pharmaceutical (n=228 firms) earns 17.0% ROC with a +9.1pp spread — after R&D capitalization, this is just ~1.1x Tier 1 broad manufacturing ROC and only +1pp above its spread. The pharma comparison is most powerful against Tier 2 capital-intensive sectors (3.4x ROC, +12pp spread gap).

This is not a market failure in the traditional sense — it is the market working exactly as designed. Capital flows to the highest risk-adjusted returns. The policy implication is that manufacturing will not attract adequate private capital without intervention that changes the return profile. MISA's transferable tax credits (5–6% base, 13–16% combined for strategic sectors) are designed to close precisely this gap — converting a negative-spread sector into one where the after-incentive return approaches or exceeds the cost of capital, making manufacturing investable again on a risk-adjusted basis.

Cross-Sector Comparison Summary

SectorNROCWACCEVA Spreadvs. Mfg ROC
Broad Manufacturing (Tier 1)1,06616.0%+8.4pp
Capital-Intensive Physical (Tier 2)5 sectors5.0%7.2%−2.2pp
Drugs / Pharmaceutical22817.0%7.9%+9.1pp1.1x
Business & Consumer Services15528.3%7.2%+21.1pp1.8x
Software (System & Application)30929.3%9.3%+20.0pp1.8x

Source: Damodaran Online, EVA dataset (January 2026 vintage). ROC = lease & R&D adjusted after-tax return on invested capital.

13-Year Trend: Structural, Not Cyclical

EVA spread comparison across five Damodaran vintages (2013–2026). Manufacturing sectors have deteriorated or remained negative while software and services held strong or improved. This is not a temporary dislocation — it is a permanent feature of capital-intensive, globally-competed industries.

MAJOR DECLINE

Auto Parts (15.7→0.8pp), Chemical Specialty (21.7→3.7pp), Electrical Equipment (26.7→6.6pp), Rubber & Tires (16.2→−1.3pp)

CROSSED TO NEGATIVE

Chemical Basic (+7.1→−2.5pp), Auto & Truck (−0.4→−7.1pp) — these sectors now actively destroy economic value

COMPARISON SECTORS

Software (38.0→20.0pp, still massive), Services (16.5→21.1pp, improved), Pharma (20.1→9.1pp, still positive)

Source: Damodaran Online, EVA datasets (2013–2026 vintages). Spread = ROC minus WACC. All values lease & R&D adjusted.

Company-Level Comparisons

Three pairs illustrating the structural return gap at the firm level. In each case, the manufacturer is well-run — the gap reflects market structure, not management quality.

Steel

Nucor

Best-run steel company in America — lean, non-unionized, EAF operator. Outperformed peers for decades.

ROC

High single digits

EVA Spread

+0.3pp (2013) → −1.0pp (2026)

Software

Microsoft

Azure cloud, Office 365, enterprise licensing. Marginal cost of replication near zero.

ROC

>30%

EVA Spread

+38.0pp (2013) → +20.0pp (2026)

Key insight: No steel mill can approach software returns regardless of operational excellence. The gap is structural — commodity pricing vs. zero marginal cost.

Auto & Truck

Ford

175,000 US employees, massive physical plants, essential durable good.

ROC

Near or below WACC

EVA Spread

−0.4pp (2013) → −7.1pp (2026)

Pharmaceuticals

Eli Lilly

30–50% ROC on GLP-1 drug pricing power. One molecule (tirzepatide) generates more revenue than Ford's NA manufacturing.

ROC

30–50%

EVA Spread

+20.1pp (2013) → +9.1pp (2026)

Key insight: Patent-protected pricing vs. globally competitive commodity pricing. The asymmetry is a direct function of market structure, not management quality.

Chemical (Basic)

Dow Inc.

Capital-intensive basic chemicals. Enormous fixed asset base, energy-intensive, cyclical margins.

ROC

~3.7%

EVA Spread

+7.1pp (2013) → −2.5pp (2026)

Prof. Services

Accenture

ROIC consistently above 25%. Minimal capital base. Proprietary methodology and client relationships.

ROC

>25%

EVA Spread

+16.5pp (2013) → +21.1pp (2026)

Key insight: Assets that walk out the door every evening earn more than billion-dollar chemical plants. Dow crossed from above-WACC to below-WACC over 13 years.

A dollar deployed in software or services earns approximately 5 to 6 times what a dollar deployed in capital-intensive manufacturing earns, and does so without the fixed assets, energy costs, or global commodity competition. That is not a market performing inefficiently. That is a market performing exactly as designed, rationally allocating away from sectors that cannot clear their cost of capital. The policy question is whether the national interest can afford to let it.

Interactive ROIC Calculator

Adjust the MISA credit rate to see how it shifts the manufacturing EVA spread

Baseline:
13%
0%MISA Base: 5–6%MISA Strategic: 13–16%20%

Before MISA

5.0%

ROC (baseline)

-2.2pp

EVA Spread

MISA Credit

+13%

Added to ROC

After MISA

18.0%

After-incentive ROC

+10.8pp

EVA Spread

ROC Comparison (After MISA Credit)

Capital-Intensive Physical (Tier 2) + MISA18.0%
Software (System & App)29.3%
Business & Consumer Services28.3%
WACC (7.2%) — cost of capital threshold

Software Gap

5.9x → 1.6x

Software ROC / Mfg ROC

Spread Shift

-2.2pp → +10.8pp

EVA Spread (ROC − WACC)

Breakeven Credit

2.2%

Min credit to reach WACC

Value-creating. At a 13% MISA credit, capital-intensive physical (tier 2) manufacturing earns an after-incentive ROC of 18.0% — above its 7.2% WACC. The EVA spread turns positive at +10.8pp, making manufacturing a rational capital allocation for the first time. The software gap narrows from 5.9x to 1.6x.

Policy Implications

What the data demands — and what conventional policy gets wrong

The Diagnosis: A Structural Return Deficit

The return gap is structural, not cyclical. Core manufacturing has earned below its cost of capital for over a decade. The 2013 Damodaran data shows similar patterns — this is not a temporary dislocation but a permanent feature of capital-intensive, globally-competed industries facing state-subsidized foreign competitors. No rational capital allocator will voluntarily deploy funds into a sector that systematically destroys economic value.

The market is working exactly as designed. This is not a market failure in the traditional sense. Capital flows to the highest risk-adjusted returns. When software offers 1.8x the return on invested capital of broad manufacturing — and nearly 6x the return of capital-intensive physical sectors — pension funds, endowments, and private equity will allocate accordingly. The problem is not irrational markets; it is that the playing field has been tilted by three decades of foreign industrial subsidies that American manufacturers must compete against without equivalent support.

Why Conventional Policy Tools Fail

Tax rate cuts alone cannot solve a negative-spread problem. A 15% corporate rate for manufacturing is a good idea, but it does not work for companies that are not generating taxable income because they are investing in capacity expansion or competing against Chinese subsidies. Rate cuts help profitable incumbents — they do nothing for the new entrant building a greenfield plant that will not turn a profit for five years.

Grants and loans pick winners. Government grant programs (CHIPS Act, DOE LPO) require bureaucrats to select which companies receive funding. This is implicit industrial policy disguised as neutral allocation. It concentrates risk in government decision-making, creates political capture, and leaves most of the manufacturing base — the thousands of mid-market firms that form the supply chain — without support.

Tariffs are necessary but insufficient. Tariffs can level the price playing field against subsidized imports, but they do not change the fundamental return profile of domestic manufacturing. A 25% tariff on Chinese steel does not make a new American steel mill earn above its cost of capital — it merely makes the existing spread less negative. Tariffs protect; they do not incentivize investment in new capacity.

The Free-Market Alternative: Explicit, Rules-Based Incentives

MISA closes the spread gap through transferable tax credits. The combined 13–16% transferable credit on domestic value-added costs is calibrated to shift the after-incentive return profile of strategic manufacturing sectors from value-destroying to value-creating. Unlike grants, these credits are available to every qualifying manufacturer — no application, no bureaucratic selection, no political favoritism. Produce domestically, earn the credit. The market decides who competes; the policy decides that competing is worth doing.

Mannie Mac provides the financing layer. Even with improved returns, manufacturers face a capital access problem. Banks have spent three decades de-skilling manufacturing lending. The Manufacturing Finance Corporation ("Mannie Mac") creates a GSE-style secondary market for manufacturing loans — the same structure that made 30-year mortgages possible for housing. It does not lend directly; it buys and securitizes qualifying loans, drawing private capital back into manufacturing finance at scale.

MERA rewards the entrepreneurs. The Manufacturing Entrepreneur Rewards Act ensures that the founders and key employees who build these new manufacturing enterprises are rewarded with capital gains treatment on their equity — the same tax treatment that has fueled Silicon Valley for decades. If we want manufacturing entrepreneurs, we must reward them like technology entrepreneurs.

Explicit Policy Beats Implicit Policy

Industrial policy should be explicit at the sub-sector, sector, and industry levels. The United States already has industrial policy — it is simply implicit, inconsistent, and often counterproductive. CHIPS Act grants for semiconductors, DOE loans for clean energy, defense procurement preferences — these are all industrial policy, but they are ad hoc, siloed, and leave most of the manufacturing supply chain uncovered. An explicit policy framework with clear rules, defined sectors, and automatic qualification criteria is more transparent, more efficient, and more accountable than the current patchwork.

Free-market mechanisms with guardrails outperform government allocation. Tax incentives, regulatory reforms, and rules-based programs let the market allocate capital while government sets the direction. The three-bill package — MISA (incentives), Mannie Mac (financing), MERA (entrepreneurship) — uses exclusively free-market mechanisms: transferable credits, secondary loan markets, and capital gains treatment. No grants. No government lending. No picking winners. The guardrails are built into the rules: domestic production requirements, value-added thresholds, and sunset provisions that force periodic reauthorization.

The Bottom Line

The Damodaran real-data comparison supports three conclusions: (1) Physical manufacturing has been systematically sub-WACC or deteriorating for over a decade — not just since COVID or China escalation. (2) The higher interest rate environment makes capital incentives more necessary, not less, to close the WACC gap. (3) Categories that appear high-ROIC (Semiconductor, Computers, Telecom Equipment) are entirely driven by FGP/fabless firms with no physical manufacturing footprint. The policy case — MINA, DO IT NOW, Mannie Mac — addresses exactly the physical manufacturing tier that has persistently earned sub-WACC returns. The goal is not to override the market — it is to correct a playing field distorted by foreign subsidies and restore manufacturing to a sector where rational capital allocation and national interest align.

Documents

Damodaran EVA Cross-Sector Comparison (Annotated)

Full annotated workbook with 2013 vs. 2026 EVA data across 90+ US sectors, policy summary, paragraph derivations with cell-level audit trail, NAICS 31–33 manufacturing subset, and methodology comparison.

Excel SpreadsheetDamodaran_EVA_Cross_Sector_Comparison_Annotated.xlsx
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Manufacturing versus Other Industries

Tier 1 vs. Tier 2 analysis: broad manufacturing (ROC ~16%) vs. capital-intensive physical sectors (ROC ~5.3%). Company-level comparisons (Nucor vs. Microsoft, Ford vs. Eli Lilly, Dow vs. Accenture) and 2013–2026 longitudinal deterioration across Auto, Chemical, Steel, Rubber, and Auto Parts.

Word DocumentManufacturing_versus_Other_Industries.docx
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Contact: Mark Rosenblatt, Rationalwave, [email protected], 914-584-5400