Public Goods

Some benefits cannot be sold by the kilowatt-hour

When ClearPeak maintains extra spinning reserves and storm-hardened transmission, every customer enjoys fewer blackouts whether or not their bill itemizes reliability. Public goods (non-excludable and non-rival in consumption) and quasi-public goods (rival at capacity but hard to exclude) explain why markets underprovide grid reliability and why regulators socialize some costs.

ClearPeak Energy is a regulated regional electric utility serving 1.2 million residential and commercial customers across twelve counties and the anchor organization for ECO 101. The utility faces retiring 2,400 MW of coal while adding 1,800 MW of utility-scale solar and battery storage by 2030, peak summer demand near 8,500 MW, and an average residential bundled rate of $0.118/kWh (kilowatt-hour, enough electricity to run ten 100-watt bulbs for one hour). Chief Economist Dr. Elena Vasquez, Regulatory Affairs VP Tom Bradley, and Grid Planning Director Amara Okafor use microeconomic tools for rate design, capacity planning, competitive response, and State Public Utilities Commission (PUC) testimony. Marginal generation costs differ sharply: legacy coal near $0.042/kWh, new solar near $0.031/kWh, and gas peakers near $0.067/kWh when scarcity bites.

Every lesson applies supply, demand, elasticity, marginal analysis, market structure, or incentive design to decisions ClearPeak leaders actually face: when to retire plants, how to price time-of-use tiers, how to bid in capacity auctions, and how to respond when rooftop solar erodes sales.

Free riding, cost recovery, and the Samuelson condition (sum of marginal benefits across consumers equals marginal cost) guide rate design for transmission and resilience investments.

Non-excludability and non-rivalry

Non-excludable: cannot cheaply block access (system frequency stability). Non-rival: one more consumer does not reduce others' benefit until capacity binds. Pure public goods are both; congested highways are rival but partly non-excludable.

Free rider problem

Customers who refuse voluntary reliability fees still enjoy fewer outages when neighbors pay. Voluntary models fail; mandatory tariff riders fund bulk transmission and black start (resources that restart the grid after blackout) capability.

Lindahl pricing intuition

Each consumer pays marginal benefit times cost share. Impractical with 1.2M customers and hidden valuations. Uniform average cost pricing with PUC approval approximates funding.

Club goods and congestion

Distribution grid is club good: excludable via connection fee but shared until transformer overload. Marginal pricing at peak addresses rivalry.

Public bads

Blackouts and pollution are public bads; policy mirrors public good logic with taxes or bans.

$320M line reduces outage minutes 18% region-wide for 400,000 customers served.

Part A: Benefit aggregation

If average customer values reliability at $4/month more post-line, annual WTP ≈ 400,000 × $48 = $19.2M. Payback long; society still may fund if externalities and economic development included.

Part B: Free rider

No customer can be excluded from fewer outages once line built. Voluntary subscription raises $0.

Part C: Funding

PUC approves transmission rider on all usage; satisfies cost recovery though not Lindahl perfect.

Part D: Managerial read

Amara pairs benefit-cost with equity impacts for low-income customers.

Line clearing benefits entire county air quality and fire risk reduction. Non-excludable safety benefit justifies statewide wildfire fund, not only adjacent landowners.

Why is grid frequency regulation a public good within an interconnection?

Solution

All connected users benefit simultaneously; cannot exclude one home from stable frequency; additional consumer does not reduce others' benefit until resource limits. Check ✓

Club good example on ClearPeak distribution system.

Solution

Neighborhood transformer capacity: excludable via connection, shared among connected homes until overloaded (rival at peak).

Key takeaways

• Public and quasi-public goods are underprovided by voluntary markets.
• ClearPeak funds transmission and resilience through regulated riders.
• Free riding blocks voluntary reliability payments.
• Club goods need congestion pricing when capacity binds.
• Distinguish public goods from externalities for policy choice.

1. Classify bulk transmission vs rooftop solar incentives: public, private, or club good?
2. One equity concern with uniform reliability riders.
3. Continue to Lesson 3: Regulation and Antitrust.

Applying Public Goods at ClearPeak scale

When ClearPeak Energy evaluates public goods, Dr. Elena Vasquez starts from operational facts: 1,200,000 customers, peak demand near 8,500 MW, residential bundled rate $0.118/kWh, and a portfolio transition that retires 2,400 MW of coal while adding 1,800 MW of solar. externalities, public goods, regulation, and market design is not textbook decoration; it is how Tom Bradley prepares State Public Utilities Commission (PUC) filings and how Amara Okafor ranks transmission and storage options under binding capital budgets.

Graph (described in prose): Public Goods at ClearPeak. Imagine a standard microeconomics diagram with quantity (megawatt-hours or customer count, depending on the decision) on the horizontal axis and price ($/kWh) or marginal cost ($/kWh) on the vertical axis. The demand curve slopes downward: at higher retail rates, customers conserve, shift load to off-peak hours, or install rooftop solar. The supply curve in the short run reflects rising marginal cost as ClearPeak dispatches coal, combined-cycle gas, and expensive peakers. Equilibrium is where quantity demanded equals quantity supplied at a price regulators allow; in regulated markets, equilibrium is a negotiated outcome, not only a frictionless auction. When ${title.toLowerCase()} changes, curves shift: new solar lowers long-run supply cost; heat waves shift demand right; competitor solar leases shift demand left for utility energy. Shaded consumer surplus and producer surplus (or deadweight loss when prices depart from marginal cost) translate directly into affordability testimony and earnings impacts.

Work a magnitude check. Suppose a policy tied to public goods moves residential sales by 1% at current scale. One percent of 1,200,000 customers is 12,000 accounts. At roughly 900 kWh per month average use and $0.118/kWh, a 1% quantity change moves monthly revenue by about $1.3 million before fuel cost adjustments. Executives who skip arithmetic like this debate symbols without stakes.

Extended ClearPeak scenario: regulatory and competitive read

Imagine ClearPeak's quarterly review on public goods. Finance asks whether a rate increase recovers rising gas peaker costs. Operations asks whether demand response can defer a $400 million substation upgrade. Commercial customers ask for advanced metering discounts. Rooftop solar installers tell regulators ClearPeak exercises market power. A weak externalities, public goods, regulation, and market design answer addresses only one audience. A strong answer links curves, elasticities, and marginal costs to each stakeholder's metric.

Dr. Vasquez uses a three-panel narrative. Panel one: short-run dispatch when peak load hits 8,500 MW and peakers set marginal cost near $0.067/kWh. Panel two: long-run portfolio when solar at $0.031/kWh displaces coal at $0.042/kWh plus carbon compliance. Panel three: competitive fringe where distributed solar at $0.09/kWh effective price steals high-margin afternoon sales. Public Goods supplies vocabulary to keep the panels consistent.

Numerical discipline example: if price elasticity of residential demand is -0.35 (a 1% price rise cuts quantity about 0.35%), a 4% rate increase reduces energy sales roughly 1.4% in the short run. Combined with weather normalization, Elena reports a bounded revenue forecast instead of pretending demand is fixed. Regulators punish utilities that ignore elasticity in revenue requirement testimony.

Technical mechanics and reconciliation checks

For public goods, ClearPeak analysts show work the way accountants show trial balances. A supply table lists plant, capacity MW, heat rate, variable O&M, fuel cost, and marginal cost per MWh (megawatt-hour). A demand table lists customer class, price, quantity, and expenditure. Equilibrium checks that quantity demanded equals scheduled dispatch within reserve margin rules. Elasticity checks recompute percent changes with the same denominator conventions used in the tariff filing.

Use explicit formula lines before plugging numbers. Elasticity = percent change in quantity demanded divided by percent change in price. Marginal cost = change in total cost divided by change in output. Marginal revenue = change in total revenue divided by change in quantity sold. Consumer surplus approximates the area below demand and above price for the units consumed. When lessons use linear demand shortcuts, state the assumption: "linear between two observed tariff points."

Spreadsheet grain matters. Utility models often run hourly for dispatch, monthly for billing, and annual for regulatory revenue requirements. Public Goods fails silently when rows mix grains. Elena requires a grain column in every workbook: hour, month, customer-month, or plant-year.

Common executive questions (and disciplined answers)

Executives ask short questions that need long disciplined answers. "Can we pass fuel costs through?" maps to allowed riders, elasticity, and affordability indices, not anger on social media. "Will solar kill the utility?" maps to cross-price elasticity with distributed energy and fixed cost recovery. "Why not cut rates to grow?" maps to marginal revenue sign when |elasticity| < 1. "What is fair return?" maps to allowed revenue requirement and cost of capital, not last year's earnings plus 10%.

ClearPeak's credible answer format for public goods is three bullets: recommendation, key elasticities or marginal costs behind it, and what evidence would reverse the view within two quarters. A fourth bullet names deadweight loss or equity tradeoffs when policy moves price away from marginal cost.

Practice the translation loop until habit: business question → curves and elasticities → quantity and revenue arithmetic → stakeholder table → filing language. Broken loops produce pretty charts that fail cross-examination.

Practice extension: graph and arithmetic self-check

Before re-reading solutions, sketch four items on paper. Item one: draw (in words) demand and supply for ClearPeak summer peak hours with labels. Item two: write one shift that increases price and one that decreases quantity without a price change. Item three: compute percent ΔQ and percent ΔP for a scenario in the lesson and verify elasticity sign. Item four: state who gains and who loses in surplus terms.

Compare your sketch to the worked example. Gaps tell you what to re-read. If you work outside utilities, substitute your product but keep the same structure: define market, state margins, show equilibrium, stress-test with elasticity.

Connection to ACC 101, MKT 202, and capstone design

ACC 101 taught you to reconcile statements; ECO 101 teaches you to reconcile marginal stories with average costs regulators allow. MKT 202 taught evidence ladders; here the ladder is descriptive load research → elasticity estimation → pricing experiment or pilot tariff → regulatory approval. Unit six capstone on designing incentives expects you to combine externalities, public goods, regulation, and market design with game theory and externality tools from earlier units.

Integrated narrative example: ClearPeak proposes a peak-pricing pilot (MKT-style segmentation), estimates elasticity −0.35 (ECO 101 Unit 2), models revenue with marginal cost dispatch (Unit 3), and defends fairness to the PUC (Unit 6). Courses compound when vocabulary and numbers stay consistent.

Deep dive: ClearPeak data definitions reused every month

Residential bundled rate includes energy, distribution, and mandated riders; pilots may unbundle for time-of-use. Peak demand is the highest hourly load in a month; coincident peak may determine transmission charges. Marginal cost of service for pricing studies uses forward-looking dispatch, not historical average embedded cost. Lost revenue from energy efficiency or solar is offset by decoupling mechanisms in some filings. Elasticity estimates separate weather, price, income, and appliance stock effects.

Definition drift fakes wins. If operations reports peak MW using one weather adjustment and finance uses another, public goods recommendations flip. Elena publishes a one-page data dictionary before each major filing.

Monthly reconciliation: billed energy ≈ generation net losses ± inventory; revenue ≈ Σ quantity × tariff by class; marginal cost tables sum to dispatch cost within rounding. Elasticity replays on holdout months. When reconciliations fail, fix data before arguing policy.

Managerial judgment prompts for Public Goods

1. If elasticity is inelastic short run but elastic long run, how should ClearPeak sequence a multi-year rate path?
2. If marginal solar cost is below coal but fixed grid costs rise, is average cost or marginal cost the right public narrative?
3. Which stakeholder loses most if ClearPeak underestimates cross-price elasticity with rooftop solar?
4. What observable would convince you the demand curve shifted versus movement along the curve?
5. When does surplus language help regulators and when does it sound like economist jargon?

Write ninety-word memo answers using ClearPeak numbers. This converts lesson prose into testimony reflexes.

Additional study path: compare this lesson's practice problem to the worked example. Identify one assumption that changed elasticity or marginal cost and explain how the decision flips. Capstone integration is intentional; reuse ClearPeak names and units across units.

Numerical walk-through: peak hour dispatch

Consider a summer peak hour with 8,500 MW demand. ClearPeak dispatches 3,200 MW coal at $0.042/kWh variable, 3,800 MW combined-cycle gas at $0.055/kWh, 800 MW solar at near-zero variable cost, and 700 MW peakers at $0.067/kWh. The marginal unit sets price in competitive benchmarks; in regulation, the filing may use average revenue requirement. Weighted average variable cost ≈ (3200×0.042 + 3800×0.055 + 800×0.005 + 700×0.067) / 8500 ≈ $0.046/kWh before T&D (transmission and distribution).

If public goods motivates shifting 200 MW from peak to off-peak via time-of-use pricing, peaker runs drop, variable cost falls roughly 200×$0.067 = $13,400 per hour, plus avoided capacity charges if sustained. Demand response programs trade customer incentives against this savings. Elena documents both gross savings and participation costs; net benefit drives the filing.

Check: 3200+3800+800+700 = 8500 MW ✓. Any lesson using partial portfolios should show similar capacity checks.

Surplus, equity, and policy tradeoffs

Microeconomics is not only efficiency. Public Goods at ClearPeak intersects affordability programs for low-income households, equity when time-of-use shifts burden evening home use, and environmental justice when retired coal plants sit in vulnerable communities. Consumer surplus gains for average bills may hide losses for heat-vulnerable customers.

When lessons recommend raising price toward marginal cost, pair the recommendation with a transfer or assistance mechanism or explain why the PUC weights equity constraints. Dr. Vasquez tables deadweight loss of under-pricing peak energy alongside hardship metrics. Regulators accept tradeoffs stated clearly; they reject efficiency claims that ignore distributional facts.

For externalities, public goods, regulation, and market design, practice writing one paragraph that a non-economist commissioner could read aloud. Avoid surplus jargon without translation: "customers who value afternoon cooling less than the cost of peaker plants would consume less under peak pricing, freeing capacity for hospitals and industrial employers."

Historical filing pattern (synthetic but consistent)

ClearPeak's 2024 time-of-use pilot covered 42,000 households. Control group average peak kWh fell 2.1% from weather normalization; pilot group fell 6.8%. Difference-in-differences estimate 4.7% peak reduction. With pilot peak price +18% versus control flat rate, arc elasticity ≈ 4.7/18 ≈ 0.26 in absolute value on the pilot margin (illustrative, not a policy filing). Revenue net of lost sales rose 1.2% because peak price uplift exceeded quantity loss on inelastic inframarginal hours.

Tom Bradley's lesson for public goods: pilot evidence beats theory slides, but pilots need control groups and pre-registered metrics. Amara links observed peak reduction to deferred substation timing: 4.7% on 420 MW local peak ≈ 20 MW relief, extending asset life two years under stated loading rules.

Cross-price and income effects reminder

Public Goods rarely operates in isolation. Income elasticity matters when recession hits commercial load. Cross-price elasticity with rooftop solar matters when federal tax credits change. Cross-price elasticity with natural gas matters for dual-fuel customers. Elena keeps a small table of estimated elasticities by class: residential -0.35, commercial -0.55, industrial −0.22 short run.

When interpreting ClearPeak results, ask which elasticity dimension the decision uses. Price-only stories mislead if income or substitute prices moved simultaneously. Multiple-regression control variables belong in advanced courses; the managerial habit here is to name confounds even if you cannot quantify them yet.

Closing integration: from lesson to testimony bullet

Translate public goods into a single testimony bullet ClearPeak could use: claim, mechanism, magnitude, caveat. Example structure: "We recommend expanding time-of-use because peak demand elasticity is modest short run but pilot evidence shows 4–7% peak kWh reduction at +18% peak price, deferring $40M substation spend if sustained two years, with low-income bill protection via tiered credits." Compare your bullet to the lesson takeaways. If magnitude or caveat is missing, deepen the quantitative thread before moving on.

Step-by-step elasticity replay (when relevant to Public Goods)

Suppose ClearPeak raises the residential energy charge from $0.095/kWh to $0.099/kWh, a 4.2% increase. Prior monthly sales averaged 720 GWh (gigawatt-hours). Estimated short-run own-price elasticity is -0.35. Expected quantity change ≈ -0.35 × 4.2% ≈ −1.47%. New sales ≈ 720 × (1 − 0.0147) ≈ 709.4 GWh.

Revenue before ≈ 720,000,000 kWh × $0.095 ≈ $68.4M per month (energy portion only). Revenue after ≈ 709,400,000 × $0.099 ≈ $70.2M. Despite lower volume, revenue rises because demand is inelastic (|ε| < 1). Tom Bradley uses this arithmetic in filings; Elena notes long-run elasticity may exceed −0.6, reversing the revenue gain over three years. Public Goods lessons should always pair short-run and long-run elasticity stories when pricing is involved.

Check: percent change formula uses consistent base (midpoint or initial); document which you use ✓

Marginal versus average cost at ClearPeak (cost ladder)

Average cost spreads fixed capital and O&M across all units; regulators use it in revenue requirements. Marginal cost tells Elena which plant runs next and what the last megawatt costs on a hot afternoon. Public Goods decisions fail when teams argue average while the grid dispatches marginal. For peak pricing pilots, marginal peaker cost near $0.067/kWh is the opportunity cost of an extra peak kWh.

Weighted check for variable dispatch stack (8500 MW example): coal+gas+solar+peaker shares sum to 100% ✓

Capstone linkage note (Public Goods in the full ECO 101 arc)

Unit one gave you curves; unit two gave elasticities; unit three gave costs and scale; unit four gave market power; unit five gave games and information; unit six gives policy design. Public Goods sits in that arc at ClearPeak: every formula should connect to a filing paragraph Tom Bradley could defend. When you draft recommendations, cite at least two prior-unit tools by name (for example, elasticity from Unit 2 plus externality pricing from Unit 6).

Dr. Vasquez's integrative standard: one page, five bullets, each bullet ties a concept to a number and a stakeholder. No bullet without magnitude. No magnitude without assumption. This is the difference between MBA fluency and undergraduate definition recall.

Applying Public Goods at ClearPeak scale

When ClearPeak Energy evaluates public goods, Dr. Elena Vasquez starts from operational facts: 1,200,000 customers, peak demand near 8,500 MW, residential bundled rate $0.118/kWh, and a portfolio transition that retires 2,400 MW of coal while adding 1,800 MW of solar. externalities, public goods, regulation, and market design is not textbook decoration; it is how Tom Bradley prepares State Public Utilities Commission (PUC) filings and how Amara Okafor ranks transmission and storage options under binding capital budgets.

Graph (described in prose): Public Goods at ClearPeak. Imagine a standard microeconomics diagram with quantity (megawatt-hours or customer count, depending on the decision) on the horizontal axis and price ($/kWh) or marginal cost ($/kWh) on the vertical axis. The demand curve slopes downward: at higher retail rates, customers conserve, shift load to off-peak hours, or install rooftop solar. The supply curve in the short run reflects rising marginal cost as ClearPeak dispatches coal, combined-cycle gas, and expensive peakers. Equilibrium is where quantity demanded equals quantity supplied at a price regulators allow; in regulated markets, equilibrium is a negotiated outcome, not only a frictionless auction. When ${title.toLowerCase()} changes, curves shift: new solar lowers long-run supply cost; heat waves shift demand right; competitor solar leases shift demand left for utility energy. Shaded consumer surplus and producer surplus (or deadweight loss when prices depart from marginal cost) translate directly into affordability testimony and earnings impacts.

Work a magnitude check. Suppose a policy tied to public goods moves residential sales by 1% at current scale. One percent of 1,200,000 customers is 12,000 accounts. At roughly 900 kWh per month average use and $0.118/kWh, a 1% quantity change moves monthly revenue by about $1.3 million before fuel cost adjustments. Executives who skip arithmetic like this debate symbols without stakes.

Extended ClearPeak scenario: regulatory and competitive read

Imagine ClearPeak's quarterly review on public goods. Finance asks whether a rate increase recovers rising gas peaker costs. Operations asks whether demand response can defer a $400 million substation upgrade. Commercial customers ask for advanced metering discounts. Rooftop solar installers tell regulators ClearPeak exercises market power. A weak externalities, public goods, regulation, and market design answer addresses only one audience. A strong answer links curves, elasticities, and marginal costs to each stakeholder's metric.

Dr. Vasquez uses a three-panel narrative. Panel one: short-run dispatch when peak load hits 8,500 MW and peakers set marginal cost near $0.067/kWh. Panel two: long-run portfolio when solar at $0.031/kWh displaces coal at $0.042/kWh plus carbon compliance. Panel three: competitive fringe where distributed solar at $0.09/kWh effective price steals high-margin afternoon sales. Public Goods supplies vocabulary to keep the panels consistent.

Numerical discipline example: if price elasticity of residential demand is -0.35 (a 1% price rise cuts quantity about 0.35%), a 4% rate increase reduces energy sales roughly 1.4% in the short run. Combined with weather normalization, Elena reports a bounded revenue forecast instead of pretending demand is fixed. Regulators punish utilities that ignore elasticity in revenue requirement testimony.