Saturday, July 10, 2010

RAND Study Should Not Be Taken As Gospel

Anyone citing to the recent RAND Corporation paper, "Altered State? Assessing How Marijuana Legalization in California Could Influence Marijuana Consumption and Public Budgets" should note two things especially:

First, the study targets not just the Regulate, Control, and Tax Cannabis Act (also known as Proposition 19) but California Assembly Bill 2254 (also known as the Ammiano bill). There are important differences. Proposition 19 is a ballot initiative directly voted on by California residents in November. The Ammiano bill is a state congressional bill which would need to pass both the state Assembly and Senate, and then receive the Governor's signature. Both end cannabis prohibition in California, but they have different provisions (for example, a $50/ounce state tax in the bill, a local tax by county and/or city, amount to be decided by locality for the ballot measure). The study appears to separate the two, but many news articles and various opposition groups do not.



Second, on page 2, they state right up front:
Our analysis reveals that projections about the impact of legalizing marijuana in Califor- nia on consumption and public budgets are subject to considerable uncertainty. Although the state could see large increases in consumption and substantial positive budget effects, it could also see increases in consumption and low revenues due to tax evasion or a “race to the bottom” in terms of local tax rates.
Decisionmakers should view skeptically any projections that claim either precision or accuracy. In particular, we highlight two distinct drivers of uncertainty that surround these estimates of consumption and tax revenues: uncertainty about parameters (such as how legal- ization will affect production costs and price) and uncertainty about structural assumptions (such as the federal response to a state that allows production and distribution of a substance that would still be illegal under federal law). Such uncertainties are so large that altering just a few key assumptions or parameter values can dramatically change the results.
In other words, these are, at best, educational guesses.

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