Are Market-Based Environmental Laws Really

the Best Thing Since Sliced Bread?

A Case Study of Environmental Justice and The

Toxics Release Inventory in North Carolina

Jacy GaigeUrban Economics, 2010

October 2009 - Lindsay Graham and John Kerry form bipartisan team to push a climate bill in the Senate

June 2010 – Landmark climate bill passes in the House mandating cuts in GHG through cap-and trade

July 2010 – Harry Reid announces the Senate bill won't be put for a vote this term

Mass. v. EPA (2007)

Holding that the Environmental Protection Agency must regulate Carbon Dioxide under the Clean Air Act because

it is a pollutant that may “reasonably be expected to endanger public health or welfare”

What are “market-based environmental laws”?

Green taxes, Cap-and-trade, information disclosure laws, and hybrids

Pros:Efficiency, Incentives

Cons:Distributional inequalityMorality (right to pollute)

Toxics Release Inventory (1986)

● Factories of a certain size producing certain products

● 600 named chemicals, including Carcinogens and Persistent Bio-accumulative Toxins (PBTs) such as

Mercury, Lead, and Dioxins

● Waste streams to air, water, and land + accidental spills

● The only requirement is to report

In 2008, releases included:

● 486 million pounds of Lead

● 6.2 million pounds of Mercury

● 5 million pounds of other PBT chemicals

From 2007 to 2008 total reported emissions in the

U.S decreased by 257 million pounds, or 6%

Since the first reporting year in 1988, emissions

have decreased by a total of 65%

Why does distributional inequality matter?

ConcentrationsSlower Action

Symbolic power of the law

But....

CausationFlexibilityIncentives

Data:

Census 2000, Block group data for Income, Race and Education

2008 Total On-site Emissions for all sitesin North Carolina

* Timing* Aggregation

Process:

Map, Buffer Analysis and Regression

Yi = α + β1x1 + β2x2 + β3x3 + ∑i

Yi = total on-site emissions in pounds

x1 = median household income

x2 = percent of population that is white

x3 = average number of years of education

Source | SS df MS Number of obs = 558

-------------+------------------------------ F( 3, 554) = 2.80

Model | 3.6117e+12 3 1.2039e+12 Prob > F = 0.0394

Residual | 2.3826e+14 554 4.3007e+11 R-squared = 0.0149

-------------+------------------------------ Adj R-squared = 0.0096

Total | 2.4187e+14 557 4.3424e+11 Root MSE = 6.6e+05

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sum_on_sit | Coef. Std. Err. t P>|t| [95% Conf. Interval]

-------------+----------------------------------------------------------------

avg_vari_1 | -582.9771 1526.642 -0.38 0.703 -3581.692 2415.738

lnavg_vari_2 | 296613.1 180326.7 1.64 0.101 -57594.58 650820.9

avg_vari_3 | -16780.81 5847.036 -2.87 0.004 -28265.88 -5295.735

_cons | -2744068 1797765 -1.53 0.127 -6275337 787200.6

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