Over the last decade, market-based incentives have become the regulatory tool of choice when trying to solve difficult environmental problems. Evidence of their dominance can be seen in recent proposals for addressing global warming (through an emissions trading scheme in the Kyoto Protocol) and for amending the Clean Air Act (to add a new emissions trading systems for smog precursors and mercury–the Bush administration's "Clear Skies" program). They are widely viewed as more efficient than traditional command and control regulation. This collection of essays takes a critical look at this question, and evaluates whether the promises of market-based regulation have been fulfilled.
The US Office of Management and Budget introduced in 2003 a new requirement for the treatment of uncertainty in Regulatory Impact Analyses (RIAs) of proposed regulations, requiring agencies to carry out a formal quantitative uncertainty assessment regarding a regulation’s benefits and costs if either is expected to reach \$1 billion annually. Despite previous use in other contexts, such formal assessments of uncertainty have rarely been employed in RIAs or other regulatory analyses. We describe how formal quantitative assessments of uncertainty – in particular, Monte Carlo analyses – can be conducted, we examine the challenges and limitations of such analyses in the context of RIAs, and we assess how the resulting information can affect the evaluation of regulations. For illustrative purposes, we compare Monte Carlo analysis with methods typically used in RIAs to evaluate uncertainty in the context of economic analyses carried out for the US Environmental Protection Agency’s Nonroad Diesel Rule, which became effective in 2004. [ABSTRACT FROM AUTHOR] Copyright of Regulation & Governance is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
We estimate the price elasticity of water demand with household-level data, structurally modeling the piecewise-linear budget constraints imposed by increasing block pricing. We develop a mathematical expression for the unconditional price elasticity of demand under increasing block prices and compare conditional and unconditional elasticities analytically and empirically. We test the hypothesis that price elasticity may depend on price structure, beyond technical differences in elasticity concepts. Due to the possibility of endogenous utility price structure choice, observed differences in elasticity across price structures may be due either to a behavioral response to price structure, or to underlying heterogeneity among water utility service areas.