1. Corn Ethanol and U.S. Biofuel Policy Ten Years Later: A Systematic Review and Meta-analysis Gal Hochman and David Zilberman NAREA 2016: Bar Harbor

2. US ethanol policy: 10 years after NAREA 2016: Bar Harbor

3. Meta-analysis*  Combine results from different studies in the hope of  identifying repeating patterns and disagreement  Studying trends  Evaluated multiple criteria  Greenhouse gases and land use changes  Food and fuel prices  Term of trade, welfare, and employment  Learning by doing NAREA 2016: Bar Harbor

4. Greenhouse gases

5. The ugly: GHG effect of ethanol GHG savings/cost depends on location and land used to grow the crop:  Carbon debt of corn grown in US central grassland: 134 Mg CO2/ha  Carbon debt of corn grown in US abandoned crop land: 69 Mg CO2/ha Magnitude of ILUC calculations changed overtime, resulting in GHG declining overtime (Searchinger to Hertel) NAREA 2016: Bar Harbor

6. The Searchinger effect NAREA 2016: Bar Harbor The average ILUC reported in the literature is 0.8143 kg CO2 per liter of corn ethanol. Without the Searchinger paper, the average is 0.67 kg CO2 per liter of corn ethanol

7. Corn ethanol  On average, the literature suggests a decline of 0.19 kg CO2 per liter of corn-ethanol  That is, if gasoline emits 3 kg CO2 per liter, then corn-ethanol emits 2.81 kg CO2 per liter, on average.  However, there is much variability:  The standard deviation is 0.87  While some papers argue for carbon savings, other calculate a carbon debt NAREA 2016: Bar Harbor

8. Sources for differences among studies  We estimate a stepwise regression: an approach to selecting a subset of effects for a regression model when there is little theory to guide the selection. NAREA 2016: Bar Harbor

9. Sources for differences among studies Variable Stepwise (0.2) OLS regression with cluster standard errors Stepwise (0.2) OLS regression with weights OLS regression with cluster standard errors Crude oil dummy 0.4412*** (0.0780) 0.4089* (0.2216) 0.5041* (0.2772) Period model calibrated Removed () Removed () 0.0147 (0.0421) LCA / Agent Model dummy -0.1879*** (0.0501) Removed () -0.1388 (0.2464) Constant -0.2314** (0.0848) -0.3879* (0.2148) -29.6703 (84.4438) R2R2 0.1485 0.10110.1504 N58 NAREA 2016: Bar Harbor

10. Food (commodity) prices

11. The bad: Food versus fuel On average, ethanol results in price of corn increasing by 24.5% Larger impact on short-run prices than long-run NAREA 2016: Bar Harbor

12. Biofuel and food commodity prices Variable Stepwise (0.2) OLS regression with weights Weighted OLS regression Gasohol market Removed (p = 0.94520.2) -0.0310 (0.4440) Oil/petroleum markets (dummy variable) -1.1992*** (0.3850) -1.1708** (0.4590) Rest of the world (dummy variable) Removed (p = 0.53220.2) 0.0733 (0.2855) Demand elasticity of crops 1.4119*** (0.2145) 1.4222*** (0.3584) Supply elasticity of crops -0.7796* (0.3976) -0.6917 (0.6939) Year calibrated 0.1004*** (0.0327) 0.0988** (0.0368) 2007/08 food commodity Inflation (dummy variable) 0.2662* (0.1498) 0.2245 (0.1752) Constant -200.15*** (65.4768) -196.89** (73.8508) N25 R2R2 0.54360.5448

13. Biofuel and food commodity prices  Introducing the oil and petroleum markets, in addition to gasohol markets, results in a smaller effect of biofuels on food commodity prices.  More inelastic demand or supply for corn yields a larger effect on food commodity prices (recall that demand elasticity is negative while supply elasticity is positive, and more inelastic curves are those with elasticity closer to zero).  During 2007/2008, the effect of corn ethanol on food commodity prices increases further NAREA 2016: Bar Harbor

14. Food prices and the introduction of biofuels  While the effect of biofuels on the US Consumer Price Index averaged less than 1 percent point, it was about 3 percent points for dairy  The economy responds to prices, altering investments and inventories.  The dynamics of the system are very important. NAREA 2016: Bar Harbor

15. The dynamics of agriculture  The literature suggests adjustments to the short-run shocks  Rural communities gain from the introduction of biofuels – both within as well as outside the US  Challenge – assessing welfare over time NAREA 2016: Bar Harbor

16. Fuel prices

17. The good: Impact of ethanol on fuel prices On average, introduction of biofuels resulted in a decline of a few percent points in the price of gasoline. NAREA 2016: Bar Harbor On average, fuel prices declined by a few percent point with the introduction of biofuels

18. When including all data points, the effect of the introduction of biofuels on gasoline prices increased over time NAREA 2016: Bar Harbor

19. But when we exclude Due and Hayes (2008), there is no change overtime with biofuel, on average, resulting in fuel prices declining by -4.5%  The petroleum refineries are responding to the introduction of biofuels (although biofuel production increases, its effect on gasoline prices is relatively constant).  But the numbers suggest that the refineries’ response is limited and that biofuels do make a dent in the refineries profit margins. NAREA 2016: Bar Harbor

20. Linkages among markets matter:  Models that included food commodity, as well as fuel markets, resulted in estimates that on average predict the introduction of biofuels resulted in a few percent points decline in fuel prices.  Models that focused more on fuel/ethanol markets predict introduction of biofuels resulted in a larger impact on fuel prices NAREA 2016: Bar Harbor

21. Economic surplus

22. Economic surplus:  Median around 0%, with US (and Brazil) slightly positive but the rest of the world slightly negative  Some employ CGE models while others use multi-market models  Analysis is static NAREA 2016: Bar Harbor

23. Employment:  Modernize bioenergy systems in developing countries, maybe loosing some jobs but raising economic level  Analysis is static NAREA 2016: Bar Harbor

24. Claims in the literature about the macro effect of biofuel: rural communities  Farming in Asia is generally labor-intensive.  The Government of Indonesia has stated the need to increase the farming land, or to use more intensive agricultural methods to grow sufficient biofuel crops to meet demand. Thousands more farm workers will be required.  It has been observed in Brazil that biofuel production has led to a positive stimulation of rural economies and helped improve conditions for the production of other crops.  In India, the sugarcane industry is a very big industry, employing 45.5 million people. NAREA 2016: Bar Harbor

25. Claims in the literature about the macro effect of biofuel: employment  There are plans to get rural villages involved in the biofuels process chain.  Indonesia is creating energy self sufficient villages to help get the rural villagers involved in the energy industry, thus potentially creating many more jobs (figures suggest about 3.5 million in 2010). NAREA 2016: Bar Harbor

26. Learning-by- doing

27. Learning by doing A concept to measure and quantify the aggregated effect of technological development is the experience curve approach. This concept states that costs decline with a fixed percentage over each doubling in cumulative production. Mean PR production = 0.32 (1-0.32 = 0.68), but PR processing = 0.86 (1- 0.86 = 0.14) NAREA 2016: Bar Harbor

28. The political economy of energy policy NAREA 2016: Bar Harbor

29. The balance of trade effect  Although biofuel and other "green" policies achieve only modest environmental improvements, if any, they do result in substantial improvements to the US balance-of-trade and its energy balance, resulting in a significant positive effect on rural employment.  While focusing on US energy policy, similar conclusions can be demonstrated using the petroleum refining and coal industries as an example. NAREA 2016: Bar Harbor

30. Biofuel and the balance of trade  Although in 2005, the US consumed 3.3 billion barrels of gasoline annually, in 2011 US consumption declined to 3.2 billion of barrels annually.  The amount of ethanol consumed in the US in 2011 equaled 67.25% of the decline of finished motor gasoline consumption from 2005 to 2011.  On the other hand, production of US gasoline in 2005 was 3.0 billion of barrels annually but it increased to 3.3 in 2011 – an increase of 9%.  In 2005 net import of gasoline.3 billion barrels  In 2011 net export of gasoline.1 billion barrels  Net gain of 16 billion gallons of gasoline NAREA 2016: Bar Harbor

31. Concluding remarks NAREA 2016: Bar Harbor

32. The meta analysis  Biofuels resulted in  A moderate increase of food commodity prices, yet a small impact on food prices  A small reduction in fuel prices  Although first generation biofuels did not yield much benefit to the environment, it did substantially impact the macro economy and rural development.  Evidence suggests a small positive net effect on US welfare.  Biofuel policy, similar to oil, natural gas and coal policies, result in political economic gains and impacts macro economic parameters. NAREA 2016: Bar Harbor

33. Regarding energy policy  Macro-level aggregate considerations, in addition to special interests, guide policy and have a profound effect.  While focusing on the macro-level effects from the introduction of biofuels, we conclude that macro-level aggregate considerations that are emphasized by the executive branch, yield substantial economic benefits to the economy. But this comes at the expense of the environment. NAREA 2016: Bar Harbor