Designing Incentives and Market Rules

One filing, every tool from ECO 101

ClearPeak must file an integrated distributed energy resources (DER, small-scale solar, batteries, and flexible load) market redesign with the PUC by Q3. The package touches game theory (installer and rival utility responses), auctions (capacity from aggregators), adverse selection (baseline inflation in efficiency claims), moral hazard (enrollment-only DR payments), externalities (coal displacement), public goods (distribution resilience), regulation (interconnection market power), and two-sided platforms (installer-host marketplace). Designing incentives and market rules is capstone integration: translate theory into implementable tariffs, procurement rules, and monitoring.

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. Capstone integrative lesson for ECO 101.

Dr. Elena Vasquez leads a cross-functional team building one coherent market design memo, not siloed chapters.

Six-step market design framework

Step 1: define social goal (reliability, decarbonization, affordability). Step 2: map market failures (externalities, asymmetry, public goods). Step 3: choose instruments (price, quantity, auction, platform rules). Step 4: model strategic responses (game theory). Step 5: specify monitoring and penalties (moral hazard). Step 6: simulate incidence and equity.

Integrating Unit 5 strategic tools

Expect neighboring utilities to match performance payments to aggregators (pricing game). Use sealed scoring auction for aggregator contracts to limit winner's curse. Screen hosts with telemetry-ready vs legacy meters (information asymmetry). Pay for verified kW not enrollment (moral hazard).

Integrating Unit 6 policy tools

Price carbon externality via existing RPS and allowance costs in avoided-cost calculator. Fund distribution resilience as quasi-public good via rider. Address interconnection timeline market power with mandated standards. Launch two-sided platform with phased installer subsidies.

Incidence and equity

Residential fixed charge changes affect low-usage households; performance payments may favor large commercial hosts. Incidence table required in filing.

Implementation and iteration

Pilot 18 months; PBR metrics on interconnection speed, DR performance, solar adders. Adjust rules with PUC approval; treat design as mechanism iteration, not one-shot perfection.

Goal: 600 MW peak reduction by 2028; retire 800 MW coal; improve interconnection median time 9 to 4 months.

Part A: Instruments map

| Failure | Tool | | Carbon externality | RPS + SCC in avoided cost | | DR moral hazard | Performance pay $28/kW verified | | Adverse selection on baselines | M&V + menu contracts | | Interconnection market power | Tariff timeline + penalties | | Platform cold start | Installer subsidy $100/host yr1 | | Resilience public good | Transmission rider $0.001/kWh |

Part B: Strategic response

Game theory: rival utility matches DR payments unless ClearPeak differentiates with faster interconnection (sequential credibility). Auction: aggregator RFP scoring price 50%, historical performance 30%, telemetry 20%.

Part C: Outcomes (modeled)

Peak reduction 220 MW year 2 rising 600 MW year 4; coal MWh down 12%; low-income bill impact +0.4% with lifeline discount offset. Check internal consistency ✓

Part D: Monitoring

Quarterly dashboard: DR performance %, interconnection median days, platform hosts, allowance exposure, equity index.

Part D: Managerial read

Single PUC narrative links prior unit tools; Tom Bradley presents as one mechanism design, not five appendices.

StateGrid filed DR incentives without interconnection reform; aggregators enrolled phantom kW while developers waited 14 months. Adverse selection and moral hazard fixed in silo while market power bottleneck undone. PUC rejected. ClearPeak avoids silo pattern.

Draft mechanism table row: problem = aggregator moral hazard; tool = ?; metric = ?

Solution

Tool: performance payment on verified event kW plus 10% bond forfeiture on miss; metric: event performance rate ≥85% rolling 12 months. Check ✓

Integrate course: list six ECO 101 concepts used in ClearPeak DER redesign case.

Solution

Nash/pricing games (rival matching), auction scoring (aggregator RFP), adverse selection (M&V menus), moral hazard (performance pay), externality (SCC/RPS), public good (resilience rider), regulation (interconnection), two-sided platform (installer subsidy). Any six ✓

Key takeaways

• Capstone market design maps failures to instruments in one filing.
• ClearPeak DER case integrates game theory, auctions, and information economics.
• Externalities, public goods, and regulation belong in the same framework.
• Two-sided platform rules must align with performance monitoring.
• Pilot, measure, iterate with PBR and equity incidence tables.

1. Draft six-step framework for one ClearPeak policy you choose.
2. Peer-review a sample filing outline for siloed tools.
3. Return to the unit page for assessments and applied project work.

Applying Designing Incentives and Market Rules at ClearPeak scale

When ClearPeak Energy evaluates designing incentives and market rules, 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): Designing Incentives and Market Rules 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 designing incentives and market rules 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 designing incentives and market rules. 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. Designing Incentives and Market Rules 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 designing incentives and market rules, 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. Designing Incentives and Market Rules 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 designing incentives and market rules 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, designing incentives and market rules 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 Designing Incentives and Market Rules

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 designing incentives and market rules 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. Designing Incentives and Market Rules 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 designing incentives and market rules: 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

Designing Incentives and Market Rules 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 designing incentives and market rules 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 Designing Incentives and Market Rules)

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. Designing Incentives and Market Rules 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. Designing Incentives and Market Rules 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 (Designing Incentives and Market Rules 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. Designing Incentives and Market Rules 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.

Capstone integrative case: DER market redesign memo (part 17)

ClearPeak must redesign distributed energy resource (DER, rooftop solar, batteries, and flexible load) compensation over eighteen months. The capstone stitches designing incentives and market rules with prior units. Demand and elasticity: compensation shifts effective price; elasticity −0.35 short run implies export growth if buyback rises. Market power: ClearPeak remains regulated monopolist in wires; generation is competitive fringe. Game theory: solar installers and ClearPeak play a repeated pricing-and-marketing game; credible commitment to stable buyback rules prevents boom-bust installer entry. Information: moral hazard if export payments lack metering verification; adverse selection if only high-export homes enroll in premium programs. Externalities: carbon benefit of solar exports to the grid; congestion externality on feeders. Public goods: advanced grid visibility data helps all customers but is underprovided without regulation.

Quantified scenario for commissioners: 180,000 rooftop systems by 2028, average export 320 kWh/month, buyback $0.06/kWh vs retail $0.118/kWh. Annual export payments ≈ 180,000 × 320 × 12 × $0.06 ≈ $41.5M. If buyback rises to $0.08/kWh, modeled participation rises 12% (elastic supply of exports). Incremental cost ≈ $41.5M × 0.12 × ($0.08/$0.06) ≈ $6.6M plus inframarginal payments on existing exporters ≈ $8.3M; total ≈ $14.9M before avoided energy purchases. Avoided energy at $0.042/kWh average marginal value on 180,000 × 320 × 12 kWh ≈ $29.1M fuel-side savings. Net depends on capacity deferral: if 15 MW local peak deferral avoids $40M substation, buyback increase can be net positive for society even if utility earnings need decoupling adjustment.

Elena recommends: time-varying buyback aligned to marginal cost, low-income bill protection fund, third-party M&V (measurement and verification) for export claims, and three-year commitment window to solve installer hold-up. Tom prepares PUC testimony mapping each element to statute criteria. Amara links feeder-level hosting capacity maps to enrollment caps preventing congestion externalities.

Check: 180,000 × 320 × 12 = 691,200,000 kWh exported annually ✓

Applying Designing Incentives and Market Rules at ClearPeak scale

When ClearPeak Energy evaluates designing incentives and market rules, 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): Designing Incentives and Market Rules 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 designing incentives and market rules 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 designing incentives and market rules. 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. Designing Incentives and Market Rules 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 designing incentives and market rules, 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. Designing Incentives and Market Rules 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 designing incentives and market rules 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, designing incentives and market rules 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 Designing Incentives and Market Rules

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 designing incentives and market rules 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. Designing Incentives and Market Rules 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 designing incentives and market rules: 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.

Capstone synthesis: eighteen-month implementation timeline

Months 1–3: Elena publishes marginal cost map by feeder; Tom files notice of rulemaking on DER compensation. Months 4–6: Pilot buyback at marginal cost peaks in two counties; M&V vendor audits 5% of exporters. Months 7–12: Expand program with enrollment cap tied to hosting capacity; low-income bill credit funded from carbon compliance savings. Months 13–18: Full territory rollout if peak reduction ≥4% and feeder overload incidents do not rise. KPI dashboard tracks export MWh, peak MW, incremental payments, avoided fuel $, and equity metrics on low-income bill burden.

Stakeholder sign-off matrix: Operators own hosting capacity maps; Finance owns decoupling true-up; Commercial owns large C&I export contracts; Regulatory owns PUC narrative; Customer advocates review equity tier. Each sign-off ties to a metric in the memo, not a vague endorsement.

Deliverable checklist for students mirroring the capstone: one-page executive summary; appendix A with elasticity and marginal cost tables; appendix B with game-tree sketch of installer–utility interaction; appendix C with externality ledger (carbon benefit minus congestion cost); appendix D with equity impacts on bottom income quintile bill share. Each appendix must include at least one reconciliation check line.

Capstone extension 1: integrated policy read

Dr. Vasquez closes the DER redesign memo by naming deadweight loss from retail price above marginal cost on peak hours, deadweight loss from buyback below marginal value of solar exports, and transfer effects when low-income credits move dollars across customer classes. Quantify one margin: if 50,000 households each shift 40 peak kWh monthly at avoided peaker cost $0.067/kWh, monthly savings ≈ 50,000 × 40 × $0.067 ≈ $134,000 in fuel and wear, before capacity deferral. If program admin costs $420,000 annually, breakeven requires sustained participation and verified load shift, not marketing claims.

Tom Bradley adds regulatory language: the filing seeks performance-based compensation tied to measured peak reduction, not permanent subsidy. Amara Okafor attaches feeder hosting maps showing where export enrollment must cap to avoid congestion externalities. This integrative paragraph deliberately cites Unit 1 curves, Unit 2 elasticity, Unit 3 marginal cost, Unit 4 market power, Unit 5 information, and Unit 6 policy tools in one decision narrative.

Capstone extension 2: integrated policy read

Dr. Vasquez closes the DER redesign memo by naming deadweight loss from retail price above marginal cost on peak hours, deadweight loss from buyback below marginal value of solar exports, and transfer effects when low-income credits move dollars across customer classes. Quantify one margin: if 50,000 households each shift 40 peak kWh monthly at avoided peaker cost $0.067/kWh, monthly savings ≈ 50,000 × 40 × $0.067 ≈ $134,000 in fuel and wear, before capacity deferral. If program admin costs $420,000 annually, breakeven requires sustained participation and verified load shift, not marketing claims.

Tom Bradley adds regulatory language: the filing seeks performance-based compensation tied to measured peak reduction, not permanent subsidy. Amara Okafor attaches feeder hosting maps showing where export enrollment must cap to avoid congestion externalities. This integrative paragraph deliberately cites Unit 1 curves, Unit 2 elasticity, Unit 3 marginal cost, Unit 4 market power, Unit 5 information, and Unit 6 policy tools in one decision narrative.