1. The Impact of the Acid Rain Program on Sulfur Dioxide Intensive Industries Josh Verseman

2. Background Sulfur Dioxide: chemical compound (SO 2 ). Acid Rain: forms when sulfur dioxide particles combine in the atmosphere, creates sulfuric acid. Environmental concern: Affects health (upper respiratory diseases), damages ecosystems due to increased acidity levels, deteriorates historical landmarks, buildings. Major source of SO 2 pollution comes from the burning of coal. - Power generation plants are the top polluters

3. Background 1990 Clean Air Act Congressional effort to improve national ambient air quality standards. Title IV : Acid Rain Program - Specifically aimed at reducing sulfur dioxide (SO 2 ) levels. - Implements cap-and-trade policy to achieve this

4. SO 2 Pollution Rates Nationwide SO 2 Pollution Rates Nationwide http://camddataandmaps.epa.gov/gdm/index.cfm?fuseaction=emissions.prepackaged_select Start of Phase I of the Acid Rain Program

5. This research examines the potential loss in output that might result from reactionary strategies adopted by firms under the Acid Rain Program.

6. Economic Model Theory predicts that when marginal costs increase output should decrease Increase in Abatement Costs -Under the Acid Rain Program a firm has a few options to choose from in order adhere to the pollution restrictions. The abatement costs lead to an increase in marginal costs

7. P₁P₁ P ₀ Q ₁ Q ₀ MR Q P INDUSTRY MC ₁ MC ₀ D

8. Empirical Strategy Compare gross domestic product in terms of value added and employment levels of six broadly defined industries before and after the implementation of the Acid Rain Program to capture any loss of output that might occur. Treatment IndustriesControl Industries Utilities Retail Manufacturing Professional Business Services, Mining Financial Activities Data come from BEA and BLS -Annual observations between1983-2007

9. Variables Defined VariableDescription GDPVA Gross domestic product in terms of value added by industry in billions of dollars EMP Average yearly number of employees by industry in thousands POST Dummy variable, 1 if observation is after 1995, 0 otherwise TREAT Dummy Variable, 1 if an industry is presumed to be affected (treatment), 0 otherwise (control). POST* TREAT Interaction of Post and Treat variables AHOUR Average weekly hours per production worker per industry AWAGE Average wage per production worker per industry

10. Summary Statistics Industry Means (n=26) Variables UtilitiesMiningMFG.RetailBusiness Services Financial Activities GDPVA 174.2112.71,140.9542.1844.61,532.9 EMP 651.3713.616,517.513,786.813,250.47,073.9 AWAGE 19.014.812.39.113.112.3 AHOURS 41.344.040.631.334.336.1

11. Empirical Model Equation 1. GDPVA i = β 0 + β 1 POST i + β 2 TREAT i + β 3 POST*TREAT+β 4 EMP + β 5 AHOURS + β 6 AWAGE + ε it Equation 2. EMP i = β 0 + β 1 POST i + β 2 TREAT i + β 3 POST*TREAT+β 4 GDPVA + β 5 AHOURS + β 6 AWAGE + ε it β 3 is the coefficient of importance -captures change in output measurements for treatment industries relative to the changes that occurred in the control industries. Null Hypothesis H o : β 3 = 0 Alternative Hypothesis H A : β 3 ≠ 0

12. 12 Simplified Difference-in-Difference Example Pre 1995 Levels Post 1995 Levels Difference Treatment Industries Y t1 - Y t2 = ΔYtΔYt Control Industries Y c1 - Y c2 = ΔYcΔYc DifferenceΔΔY = ( β 3 )

13. Results Dependent Variable: GDPVA Adjusted R 2 =.61 Observations = 150 VariableCoefficientsStd. Errort-StatP-value Intercept-5,306.76.00110.13.000 Employment0.07729.26-7.27.040 Post231.31116.721.98.000 Treatment-1,390.17188.36-7.38.030 Post*Treatment-282.91127.81-2.21.000 Average Earnings47.4812.063.93.000 Average Hours Week 141.4819.997.08.000

14. Results Dependent Variable: Employment Adjusted R 2 =.74 Observations = 150 VariableCoefficientsStd. Errort-StatP-value Intercept66,792.674,860.6313.74.000 GDPVA5.610.5510.13.000 Post2,729.821,000.462.73.007 Treatment14,538.351,485.849.78.000 Post*Treatment-124.651,127.35-0.11.91 Average Earnings-695.3693.03-7.43.000 Average Hours Week -1,612.56149.78-10.77.000

15. Conclusions Analysis indicates mixed results. - Able to reject null hypothesis and conclude that there is a correlation between implementation of the Acid Rain Program and a decease in gross domestic product. -In terms of employment, fail to reject null hypothesis. Conclude that the Acid Rain Program did not affect employment levels. Further research could examine the discrepancy between the two outcomes

17. Source: National Atmospheric Deposition Program, 2007 http://www.epa.gov/eroeweb1/pdf/roe_hd_layout_508.pdf Wet Sulfate Deposition 1989-1991

18. Source: National Atmospheric Deposition Program, 2007 http://www.epa.gov/eroeweb1/pdf/roe_hd_layout_508.pdf Wet Sulfate Deposition 2004-2006

19. Source: National Atmospheric Deposition Program, 2007 http://www.epa.gov/eroeweb1/pdf/roe_hd_layout_508.pdf Wet Sulfate Deposition 1989-1991 2004-2006