David S. Bullock University of Illinois Dept. of Consumer and Agricultural Economics

1. Dangers of Using PoliticalPreferenceFunctions in Political Economy Analysis:Examples from U.S. Ethanol Policy David S. Bullock University of Illinois Dept. of Consumer and Agricultural Economics Paper prepared for presentation at the 16th ICABR Conference, ‘The Political Economy of the Bioeconomy: Biotechnology and Biofuel’ June 26, 2012 Ravello, Italy

2. Rausser and Freebairn(1974) I. PPF Political preference functionapproach. • Empirically measure political power of interest groups.

3. Many studies followed: • Paarlberg and Abbott (1986) • Lianos and Rizopoulos 1988) • Oehmke and Yao (1990)

4. And continue to be published: • Rausser and Goodhue (2002) • Redmond (2003) • Simon et al. (2003) • Burton, Love, and Rausser (2004) • Atici (2005) • Atici and Kennedy (2005) • Lence et al. (2005) • Lee and Kennedy (2007) • Francois, Nelson, and Pelkmans-Balaoing (2008) • Rausser and Roland (2008) • Ahn and Sumner (2009)

5. Typical Results “Group A was 2.72 times as powerful as group B.”

6. Two decades ago, von Cramon-Taubadel (1992) and then Bullock (1994) published serious critiques of the PPF method.

7. But, obviously, they had little impact on the literature

8. This is largely my own fault. I have been known to write arcane papers.

9. So here I present a step-by-step example of dangers of using the PPF approach.

10. To do so, I develop a model of U.S. ethanol policy, and apply the PPF approach to it.

11. The model is every bit as rich and descriptive of U.S. ethanol policy as are several that have recently been published in ag econ journals.

12. The data I use are similar to those used in many other PPF models.

13. I didn’t design this model with PPF methodology in mind. It’s just a model, like many other models in the policy literature.

14. Multi-market, multi-policy-instrument model I illustrate my arguments with a multi-market, multi-policy-instrument, partial equilibrium model of the U.S. ethanol policy. II. The Model

15. Crude Oil Refinery-specific capital and labor Ethanol-specific capital and labor Corn-specific land, capital, labor Livestock-specific land, capital, labor Biofuel Petrofuel “Fuel” Meat Labor (taxed for government revenues)

16. Policy Instruments Modeled: Ten independent policy instruments tb, per-unit tax/subsidy on biofuel tg, per-unit tax/subsidy on petrofuel (gasoline) tc, per-unit tax/subsidy on corn to, per-unit tax/subsidy on crude oil tr, per-unit tax/subsidy on refiners and distributors ta, per-unit tax/subsidy on ethanol-specific resources tl, per-unit tax/subsidy on non-corn meat input resources (livestock) tf, per-unit tax/subsidy on fuel (retail) tm, per-unit tax/subsidy on meat qbman, (producers of “fuel” must use some minimum amount of biofuel)

17. One dependent policy instrument: tw (tax on labor). Biofuels policy must be paid for.

18. Interest groups At most disaggregated: • Corn suppliers • Crude oil suppliers • Oil Refiners/Distributors • Suppliers of ethanol-specific resources (think ADM) • Livestock suppliers • Labor suppliers (“employees”) • Labor demanders (“employers”) • Consumers of fuel and meat

19. Biofuel Petrofuel Meat qcb qcm qr Corn to biofuel Refining and distribution Corn to meat qa ql qo Non-corn biofuel resources Livestock Crude oil Leontief production technologies (goods produced by zero-profit firms):

20. Simple model of fuel production: petrofuel and biofuel are perfect substitutes in the production of “fuel.” Fuel qg Petrofuel qb Biofuel

21. Feasible Welfare Manifolds Concept central to understanding PPF methodology: welfare manifolds. I discuss feasible welfare manifolds in detail in another paper.

22. Framework n+1 interest groups: Group 0: government Groups 1, …, n: other interest groups

23. x2 (Production mandate) X, set of feasible policies x´ x1 Per-unit biofuels subsidy (tax if < 0) A particular policy Government’s strategies involve policy instruments

24. A vector of market parameters , (supply and demand elasticities, perhaps)

25. Group i’s welfare depends on government policy: ui = hi(x,),i = 0,1, … , n.

26. Payoff vector function h maps set of feasible policies into “welfare space.” u = h(x, ) = (h0(x, ), h1(x,),…, , hn(x,))

27. Every place the government can send the interest groups x´ u2 h(x´) H{1,2}(X) u1 x2 h(x) X x1 “feasible welfare manifold” {1,2} here is the set of utility-bearing groups

28. Welfare manifolds are a generalization of Josling’s (1974) and Gardner’s (1983) surplus transformation curves.

29. “feasible welfare manifold” “feasible welfare submanifold” u2 x2 H{1,2}(T) h(x´) T X x´ H{1,2}(X) x1 u1 {1,2} here is the set of utility-bearing groups

30. III. PPF Results using the modelA. One policy instrument, two interest groups

31. “Everybody else’s” welfare Status quo policy result: (∆U1, ∆U2) = (0, 0) Increase ethanol tax or decrease ethanol subsidy Corn farmer/ethanol producer welfare If in PPF model we assume ethanol tax/subsidy is the only instrument: Decrease ethanol tax or increase ethanol subsidy

32. Political power weights: Corn/ethanol industry: 0.514 Everyone else: 0.486 PPF weights would be: Farmers/ethanol producers: 0.514 Everyone else: 0.486 “Everybody else’s” welfare Corn farmer/ethanol producer welfare Slope = -1.059 Interpretation: “The corn/ethanol industry is just a little bit more powerful than the rest of society.”

33. Say we had observed an ethanol tax of $1.00/gal. What would our PPF method say that the political power weights were? “Everybody else’s” welfare B Corn farmer/ethanol producer welfare Slope = -0.93 Political Power Weights Corn/ethanol industry: 0.482 Everybody else: 0.518 Because their weight droped by 0.03, corn/ethanol industry loses about $23 billion.

34. Say we had observed an ethanol subsidy of $1.50/gal. What would our PPF method say that the political power weights were? “Everybody else’s” welfare Slope = -1.22 Corn farmer/ethanol producer welfare Political Power Weights Corn/ethanol industry: 0.551 Everybody else: 0.449 Compared to status quo, corn/ethanol industry gains about $42 billion. C D

35. So what seems like a fairly small change in political power weights leads to a huge change in transfers!

36. “Everybody else’s” welfare Corn farmer/ethanol producer welfare Reason: the welfare submanifold is nearly linear.

37. What if instead of looking at the ethanol tax/subsidy, we decided to look at the gasoline tax?

38. What’s going on? Higher gas tax allows a lower labor tax, less distortion. To a point, raising the gasoline tax improves the welfare of both groups! Status quo

39. But “negative” political power weight means that government can’t be solving the max problem. Positive slope!

40. Now say we assume that the policy instrument is the ethanol mandate:

41. Increasing the mandate benefits the corn/ethanol industry, but hurts everyone else.

42. “True” political power Your measurement of political power A little weird: surplus transformation curve is not concave. If you measure the slope to get a political power measurement, you may be using the wrong measure, because the actual solution might be a corner solution.

43. “Everybody else’s” welfare Using instruments separately petrofuel tax/subsidy Corn farmer/ethanol producer welfare biofuel use mandate biofuel tax/subsidy Better question: how are these instruments best combined? Is that even a very good question? Is one of these instruments “better” than the others?

44. Also, it should be clear that the political power measure obtained from PPF methodology very much depends on which instruments are modeled.

45. B. Two instruments, two interest groups

46. Instruments used simultaneously: • biofuel tax/subsidy • Petro-fuel tax/subsidy “Everybody else’s” welfare Corn farmer/ethanol producer welfare Result: 2-dimensional welfare manifold

47. Most PPF studies just assume away this problem by having the number of interest groups be 1 more than the number of policy instruments in their models. “Everybody else’s” welfare But then the “observed” policy outcome will almost never be Pareto efficient, and therefore you can’t get PPF weights. Corn farmer/ethanol producer welfare

48. C. Three instruments, two interest groups

49. “Everybody else’s” welfare • Instruments used simultaneously: • biofuel tax/subsidy • petrofuel tax/subsidy • biofuel use mandate Corn farmer/ethanol producer welfare If we allow the third instrument to be used, and our model has two interest groups, this just expands the welfare manifold, and we still can’t get PPF weights from the observed policy.

50. D. Two instruments, three interest groups