Infrastructure Capacity, Risk, and Firm Value: Evidence from U.S. Electricity Tightness

Marcin Kacperczyk | David Licher

Nov 12, 2025

Key Takeaways

Research objective: The study investigates how electricity grid capacity and reliability shape firm operations, valuations, and expected returns, integrating theory with empirics.
Theory: The authors develop a dynamic firm model in which electricity tightness acts as a stochastic constraint on production. The model predicts grid risk depresses investment, hiring, and profitability while generating risk premia for exposed firms.
Data and method: The analysis combines county-level electricity network measures—realized outages (SAIDI) and expected capacity (AEC)—with firm-level financial and accounting data from 2005–2024. Empirical strategies include panel regressions with rich fixed effects, event studies of the 2021 Texas blackout and subsequent ERCOT reforms, and asset-pricing tests using portfolio sorts and Fama–MacBeth regressions.
Real outcomes: Firms located in areas with greater anticipated grid slack expand employment (+2.5%), capital stock (+2.1%), and profitability (+90 basis points in ROA), whereas realized outages lead to measurable contractions.
Valuation and returns: Firms with higher exposure to electricity constraints trade at lower market-to-book multiples but earn higher subsequent returns. An electricity tightness factor (ELX) delivers an annualized premium of ≈5%–6%.
Broader claim: Electricity capacity is not merely an engineering constraint; it is a priced state variable in production-based asset pricing, shaping firm behavior, labor markets, and financial markets alike.

Source Publication:

Kacperczyk, M., & Licher, D. Infrastructure Capacity, Risk, and Firm Value: Evidence from U.S. Electricity Tightness. SSRN working paper

Background and Research Framing

Modern economies depend critically on reliable electricity infrastructure. Unlike most inputs, electricity is consumed the moment it is produced, cannot be stored cost-effectively at scale, and is difficult to trade seamlessly across regions. These features mean that when regional demand nears capacity, the grid becomes a binding supply-side constraint. Firms then face outages, higher operating risks, and greater uncertainty—effects that cascade into investment, labor demand, and valuations, with macroeconomic and financial repercussions.

Yet, standard macroeconomic and finance models typically assume elastic capacity, treating infrastructure as a neutral backdrop. This assumption overlooks a crucial question: Does infrastructure scarcity directly shape firm behavior and asset prices, and if so, through what mechanisms?

The authors address this gap by developing a framework in which electricity tightness—defined as the ratio of realized supply to potential demand—alters firms’ effective production possibilities. They then bring together detailed U.S. electricity and firm-level data to evaluate whether capacity scarcity is not simply a local operational issue, but a systematic and priced state variable that links engineering constraints to corporate outcomes, labor markets, and asset pricing.

Theoretical Framework

The authors formalize their argument in a production-based asset-pricing model in which electricity is a non-storable, non-tradable input. Firms choose capital and labor in advance, but actual electricity delivered is rationed once uncertainty about demand and capacity resolves. When aggregate demand exceeds supply, a time-varying “tightness ratio” determines what share of intended usage is met.

This mechanism has two critical consequences. First, rationing acts as a stochastic productivity shock: when tightness is low, output, profits, and investment fall. Second, because these shocks coincide with high marginal utility states, they covary with the stochastic discount factor, making electricity risk systematic. Investors demand a premium to hold assets exposed to grid tightness, implying electricity scarcity should be priced in returns.

Clear predictions follow from this framework: anticipated excess capacity should increase employment, capital, and profitability, whereas realized outages should depress them; and firms with high exposure to tightness should command higher expected returns. The empirical analysis directly tests these implications.

Data and Methodology

The authors construct a plant-level panel, linking firm exposure to regional electricity constraints. Realized scarcity is proxied by the System Average Interruption Duration Index (SAIDI), whereas expected slack is measured using NERC’s Anticipated Excess Capacity (AEC). Firm fundamentals and stock returns are sourced from Capital IQ, covering 2014–2024 for operational outcomes and 2005–2024 for asset-pricing tests.

Identification leverages multiple complementary strategies. High-dimensional panel regressions include establishment (or firm) and year fixed effects and control for local weather, industrial composition, and demand shocks. Quasi-natural experiments exploit the 2021 Texas Winter Storm Uri blackout and subsequent ERCOT policy reforms. Instrumental variables account for plausibly exogenous outage variation (e.g., extreme weather, transmission failures). For asset pricing, the study estimates ELX exposure betas, constructs long–short ELX portfolios, conducts portfolio sorts, and runs Fama–MacBeth regressions to quantify cross-sectional prices of risk.

Findings

The results confirm the model’s predictions. A one-standard-deviation rise in anticipated excess capacity (AEC) increases employment by about 2.5%, capital stock by 2.1%, and ROA by 90 basis points. Conversely, realized outages (SAIDI) reduce hiring, investment, and profitability, consistent with rationing acting like a negative productivity shock.

These real effects translate into valuations: higher AEC raises market-to-book ratios by ≈1.7%, whereas higher SAIDI lowers them by ≈0.9%.

On the financial side, electricity risk is priced. The ELX factor earns an annualized premium of 5%–6%, with low correlation with standard factors. Fama–MacBeth regressions show moving from low to high ELX-beta exposure predicts a 2.1% annual increase in expected returns.

Causal inference is strengthened by natural experiments. The 2021 Texas blackout reduced abnormal returns of exposed firms by ≈120 basis points, whereas ERCOT reforms raised them by ≈106 basis points and facilitated recoveries in employment and investment.

Heterogeneity analyses show stronger effects in electricity-intensive industries and in regions with limited short-run substitutability, such as data centers. County-level results reveal broader labor market consequences: AEC predicts higher employment and business formation, whereas SAIDI depresses both.

Policy and Market Implications

The study reframes grid reliability as a macroeconomic and financial policy variable. For regulators, the results highlight the value of investments and market designs that increase capacity or internalize scarcity—such as firming obligations, scarcity pricing, and demand-response incentives. For firms, they underscore the importance of location choices, resilience investments, and hedging strategies. For investors, ELX emerges as a novel systematic risk factor that should be incorporated into portfolio construction and discount-rate assessment.

By demonstrating that electricity scarcity transmits through production sets to firm behavior, labor markets, and asset pricing, the paper establishes infrastructure as more than background engineering. It is a dynamic and priced constraint, central to understanding modern economic and financial outcomes.