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

Dangers of Using Political Preference Functions in

Political Economy Analysis:Examples from U.S. Ethanol Policy

David S. BullockUniversity 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, 2012Ravello, Italy

• Rausser and Freebairn (1974)

I. PPF

Political preference function approach.

• Empirically measure political power of interest groups.

Many studies followed:

• Paarlberg and Abbott (1986) • Lianos and Rizopoulos 1988) • Oehmke and Yao (1990)

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)

Typical Results

“Group A was 2.72 times as powerful as

group B.”

Two decades ago, von Cramon-Taubadel (1992) and then Bullock (1994)

published serious critiques of the PPF method.

But, obviously, they had little impact on the literature

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

arcane papers.

So here I present a step-by-step example of dangers of

using the PPF approach.

To do so, I develop a model of U.S. ethanol policy, and apply

the PPF approach to it.

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.

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

models.

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

models in the policy literature.

I illustrate my arguments with a multi-market, multi-policy-instrument, partial equilibrium model of the

U.S. ethanol policy.

Multi-market, multi-policy-instrument model

II. The Model

Crude Oil Refinery-specific capital and labor

Ethanol-specific capital and labor

Corn-specific land, capital,

labor

Livestock-specific land, capital,

labor

Petrofuel Biofuel

“Fuel” Meat

Labor (taxed for government revenues)

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 cornto, per-unit tax/subsidy on crude oiltr, per-unit tax/subsidy on refiners and distributorsta, per-unit tax/subsidy on ethanol-specific resourcestl, 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 meatqbman, (producers of “fuel” must use some minimum amount of biofuel)

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

for.

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

Leontief production technologies (goods produced

by zero-profit firms):

qo

qr

Crude oil

Ref

inin

g an

d di

strib

utio

n

qa

qcb

Non-corn biofuel resources

Cor

n to

bio

fuel

ql

qcm

LivestockC

orn

to m

eat

Biofuel Petrofuel Meat

Simple model of fuel production: petrofuel and biofuel are perfect

substitutes in the production of “fuel.”

qb

qg

Biofuel

Pet

rofu

elFuel

Feasible Welfare Manifolds

Concept central to understanding PPF methodology: welfare

manifolds.

I discuss feasible welfare manifolds in detail in another paper.

Framework

n+1 interest groups:

Group 0: governmentGroups 1, …, n: other interest groups

Government’s strategies involve policy instruments

x1

x2

Per-unit biofuels subsidy (tax if < 0)

(Production mandate)

A particular policy

X, set of feasible policies

x´

A vector of market parameters ,

(supply and demand elasticities, perhaps)

Group i’s welfare depends on government policy:

ui = hi(x, i = 0,1, … , n.

Payoff vector function h maps set of feasible policies into

“welfare space.”

u = h(x, ) = (h0(x, ), h1(x,),…, , hn(x,))

x1

X

x2

u2

u1

H{1,2}(X)

h(x´)h(x)

“feasible welfare manifold”

Every place the government can send the interest groups

x´

{1,2} here is the set of utility-bearing groups

Welfare manifolds are a generalization of Josling’s

(1974) and Gardner’s (1983) surplus transformation curves.

x1

X

x2

u2

u1

H{1,2}(X)

“feasible welfare manifold”

{1,2} here is the set of utility-bearing groups

Th(x´)

H{1,2}(T)

“feasible welfare submanifold”

x´

III. PPF Results using the model

A. One policy instrument, two interest groups

Corn farmer/ethanol producer welfare

“Everybody else’s” welfare

Decrease ethanol tax or increase ethanol subsidy

Increase ethanol tax or decrease ethanol subsidy

If in PPF model we assume ethanol tax/subsidy is the only instrument:

Status quo policy result: (∆U1, ∆U2) = (0, 0)

PPF weights would be:

Farmers/ethanol producers: 0.514

Everyone else: 0.486Corn farmer/ethanol producer welfare


Slope = -1.059

Political power weights:

Corn/ethanol industry: 0.514Everyone else: 0.486

Interpretation: “The corn/ethanol industry is just a little bit more powerful than the rest of society.”



Slope = -0.93

Because their weight droped by 0.03, corn/ethanol industry loses about $23 billion.

BSay we had observed an ethanol tax of $1.00/gal. What would our PPF method say that the political power weights were?

Political Power WeightsCorn/ethanol industry: 0.482Everybody else: 0.518

Slope = -1.22

D



Compared to status quo, corn/ethanol industry gains about $42 billion. C

Say we had observed an ethanol subsidy of $1.50/gal. What would our PPF method say that the political power weights were?

Political Power WeightsCorn/ethanol industry: 0.551Everybody else: 0.449

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



Reason: the welfare submanifold is nearly linear.

What if instead of looking at the ethanol tax/subsidy, we

decided to look at the gasoline tax?

Status quo

To a point, raising the gasoline tax improves the welfare of both groups!

What’s going on? Higher gas tax allows a lower labor tax, less distortion.

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

Positive slope!

Now say we assume that the policy instrument is the

ethanol mandate:

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

“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.



biofuel use mandate

petrofuel tax/subsidy

biofuel tax/subsidy

Using instruments separately

Is one of these instruments “better” than the others?

Is that even a very good question?Better question: how are these instruments best combined?

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

B. Two instruments, two interest groups


“Everybody else’s” welfareInstruments used simultaneously:•biofuel tax/subsidy•Petro-fuel tax/subsidy

Result: 2-dimensional welfare manifold


“Everybody else’s” welfareMost 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.

But then the “observed” policy outcome will almost never be Pareto efficient, and therefore you can’t get PPF weights.

C. Three instruments, two interest groups



Instruments used simultaneously:•biofuel tax/subsidy•petrofuel tax/subsidy•biofuel use mandate

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.

D. Two instruments, three interest groups

And if we disaggregate the interest groups a little more, it changes the whole picture: a 2-dimension manifold in 3-space: Now we can get PPF weights again…

Welfare submanifold when only the petrofuel tax/subsidy and the biofuel tax/subsidy are used

E. Three instruments, three interest groups

Corn farmer/ biofuel producer welfare


Petrofuel producers’ welfare

Allowing the use of another policy instrument changes the whole picture again. Now we have 3 instruments and 3 interest groups. Again, an “observed” policy will take us to an interior point in the welfare manifold. Result: Can’t get PPF weights.

unon-intervention

Conclusions

• The best way to measure the “political power” of interest groups is by examining the sizes of the transfers brought about by policy, not by measuring the slopes of a contrived surplus transformation manifold at a contrived “observed” point.

Conclusions

• Like this: “Group A received $x, which was taken from group B, which lost $y.”

• Not this: “Group A’s political power weight is 0.xx and group B’s is (1 – 0.xx).”

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

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