Environmental policy with uncertainty/imperfect information Price or quantity? M Weitzman, 1974, Prices vs quantities, RevEconstudies

Concepts Risk and uncertainty: often used to characterise various situations in which less than complete information is available. Risk: usually taken to mean situations in which some chance process is taking place in which the set of possible outcomes is known and probabilities can be attached to each possible outcome. However, it is not known which possible outcome will occur. Uncertainty: usually taken to mean situations in which the set of possible outcomes is known but probabilities cannot be attached to each possible outcome. Radical uncertainty: circumstances in which it would not be possible even to enumerate all the possible outcomes.

Limited information and uncertainty arises from: The data collected may not properly represent what the investigator is seeking to obtain. Abatement costs: those who possess relevant information may have incentives not to truthfully reveal it. Difficulties in indentifying and evaluating the benefits of pollution abatement (i.e. the benefits of avoided damages). Scientific knowledge about pollution impacts is far from complete, and arguably can never be complete because of the stochastic and complex nature of ecosystem functioning. Valuation of environmental services is beset by a host of theoretical and practical problems, and there is little consensus about the validity of current valuation techniques.

t*t* M*M* Uncertainty about abatement costs (initial situation) Emissions, M MDamages MC (true) MC (assumed) tHtH LHLH MtMt Loss when licenses used Loss when taxes used Equal slopes, Losses are equalised Higher than optimal tax Emissions with tax Th Optimal emissions Optimal tax Higher than optimal emissions with licence L

When true MC are lower Taxes overproduce emission abatement (underproduce emissions) permits underproduce emission abatement (overproduce emissions) When true MC are higher permits overproduce emission abatement (underproduce emissions) Taxes underproduce emission abatement (overproduce emissions)

SLOPES MAY DIFFER..

MARGINAL DAMAGES STEEPER

t*t* M*M* Uncertainty about abatement costs: DIFFERENT SLOPES costs OVER estimated Emissions, M MD MC (true) MC (assumed) tHtH LHLH MtMt Loss when licenses used Loss when taxes used STEEPER More emissions than optimal less emissions than optimal H stays for Higher than optimal

t*t* M*M* costs underestimated  the tax is too low Emissions, M MD MC (true) MC (assumed) tLtL L MtMt Loss when taxes used Loss when licenses used L stays for lower than optimal

ABATEMENT COSTS STEEPER

t*t* M*M* Uncertainty about abatement costs – costs overestimated Emissions, M MC (true) MC (assumed) tHtH LHLH MtMt MD MC now STEEPER

t*t* M*M* Uncertainty about abatement costs – costs underestimated Emissions, M MC (true) MC (assumed) tLtL L MtMt MD

GENERAL RESULTS FOR POLICY CHOICE UNDER UNCERTAINTY What differentiates these two pairs of cases is the relative slopes of the MC and MD functions. We obtain the following general results (Weitzman, 1974): 1.When the (absolute value of the) slope of the MC curve is less than the slope of the MD curve, licences are preferred to taxes (as they lead to smaller efficiency losses). 2.When the (absolute value of the) slope of the MC curve is greater than the slope of the MD curve, taxes are preferred to licences (as they lead to smaller efficiency losses).

MICROECONOMIC THINKING RELIES ON ‘RELATIVE’ ASSESSMENTS EFFICIENCY CONSIDERATIONS AND ‘BURDEN’ ALLOCATIONS ARE DRIVEN BY RELATIVE CONDITIONS IN THE MARKETS (CAPTURED BY SLOPES) SUPPLY AND DEMAND MAC VS MD WITH POLLUTION

EXAMPLE Where the marginal benefit function is quite steep, close control over quantity becomes important. For various hazardous wastes, a permit system may well be preferable since it provides greater assurance against excessive and destructive emissions….