Uncertainty, Monitoring & Enforcement

1. Uncertainty, Monitoring & Enforcement Using economic models to help inform which instruments are most effective at controlling pollution

2. Motivation • Group Project: New rules are being promulgated by the Santa Barbara Air Pollution Control District for regulation of VOC emissions from stationary sources. They are concerned about the cost of monitoring compliance and want your Bren Group Project to design a cost-effective monitoring program.

3. Group Project (cont) • Problem: How to assure compliance. • Some possible options • Install continuous emission monitors • Rely on voluntary self-reporting • Use self-reporting with teeth • Random audits • Hefty fines for violators • Will all do the job? • Which is likely to be cheapest?

4. Today’s Menu • Uncertainty – how does uncertainty influence your choice of regulation? • Monitoring – how do you construct a regulation if monitoring is tough; ie, cannot observe emissions? • Enforcement – how to construct a cost-effective enforcement program

5. Uncertainty – Unobserved costs • Choice of regulatory instrument: tradable permits vs. emission fees. • Case 1: certainty • Case 2: uncertainty in costs and benefits • Unobserved costs called “Adverse Selection”

6. Case 1: Observed control costs • If MB and MC curves known, regulator can choose efficient pollution level. $ MC (society) • 2 equivalent policies: • Set quota of Q • Set tax of t. t MB (firm) Q Electricity

7. Case 2: Unobserved control costs • Think of MC as the “damage” to society of pollution (accompanying electricity). • Think of MB as the “savings” to the firm from being able to pollute. • Both MC and MB may be uncertain to regulator • Which instrument should be used? • “Price” instrument: polluter pays $t per unit pollution • “Quantity” instrument: polluter emits exactly Q.

8. Price vs. quantity regulation $ MC If tax t is imposed: May get eL, e*, or eH t MBH MB may be high or may be low; MBM right in the middle MBM MBL eL e* eH Pollution

9. Basic Problem • Errors occur in case of either tax or permits • Tax: MC set equal to the tax; can generate big swings in pollution output and thus big deadweight loss • Quantities: Always know how much pollution but there can be big swings in MC, leading to large deadweight loss

10. When MC is steep (rel. to MB) $ Deadweight loss from tax, When MB turns out to be H MC MB Tax Deadweight loss from Permits, when MB low Use quantity- based regulation Q* Pollution

11. When MC is flat (rel. to MB) $ Use price- based regulation MB MC t* Deadweight loss from taxes Deadweight Loss from permits Pollution

12. Slopes of MB, MC? • Marginal Benefit of pollution is akin to the cost of abatement to the firm • Steep when very few alternatives – firm must produce fixed amount of pollution as by-product of production • Flat when each unit of abatement is equally costly • Marginal Cost of pollution is the health & environmental cost • Steep when threshold effects (no cost at low levels, then quickly rises to high cost) (e.g. water temp on fish) • Flat when each unit has same environmental cost (e.g. carbon – within a range)

13. Monitoring—Unobserved Actions • Suppose we cannot observe something a firm is doing (like “midnight dumping”)? • How do we construct a regulation to deal with problem? • Unobserved actions called “moral hazard”

14. Illegal dumping • If “proper disposal” is costly… • People have an incentive to “midnight dump”. • If monitoring free, just impose tax on polluters when they are caught. • If monitoring very expensive, could tax sale of the good (consumption tax). • Want a mechanism that taxes polluters, but rewards non-polluters (but we have imperfect enforcement).

15. Deposit-refund [1 of 2] • What happens if we place a tax on dumping equal to marginal environmental damage? • Illegal dumping occurs if monitoring is not perfect. • Instead, want to reward proper disposal & punish illegal disposal.

16. Deposit-refund [2 of 2] • How it works • Potential polluter pays $X on purchase of waste product (eg, solvent) • Receives $Y upon return (dirty solvent) • Why is this different than simply taxing illegal dumping or subsidizing clean disposal?….It’s both.

17. Deposit-refund: a clever policy • Remember, potential polluter effectively pays tax up front. Is reimbursed (at least) upon return. • A clever disclosure mechanism: • Refund is paid when potential polluter proves compliance (by returning). • All polluters pay tax ($X) all non-polluters pay nothing (or make money).

18. Enforcement • Laws worthless if they are not enforced • Enforcement can be very costly • How to construct low cost enforcement program?

19. Enforcement • Polluter may be doing something other than what he tells regulator • Regulator can audit polluter, at a cost • Clear interplay between frequency and stringency of audit and fine if caught. • Probability of detection vs. fine • E.g. traffic laws, income tax reporting, self-reporting in RECLAIM, etc..

20. Auditing an emissions standard • e = total emissions, B(e) = Benfit of emissions • S = emissions standard • f = fine per excess emissions if caught • p = prob of detection • F(e) = expected fine (treated as a cost to firm) • F(e) = p*f*(e - S)+(1-p)*0 if e > S, = 0 if e < S • Net expected benefit to firm ex ante: • NB(e) = B(e) - F(e)

21. How much will firm pollute? • NB(e) = B(e) - F(e) • MB(e) - MF(e) = 0 at the optimum • MB(e) = MF(e): Firm pollutes where marginal benefit from polluting equals marginal expected fine. • MB(e)= pf • Note: If firm only cares about pf, the marginal expected fine, can adjust either. MB pf e e* e0

22. Should regulator increase fine or p? • If firm only cares about pf, regulator wants high fine, low p (this makes auditing costs very small) • But assets of firm may be limited (I.e. bankruptcy) • Often the case for pollution (potentially high damage from cheating) • May require environmental bond • Bottom line: costs of cheating must exceed costs of adhering to regulation