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
Paper prepared for presentation at the
16th ICABR Conference,
‘The Political Economy of the Bioeconomy: Biotechnology and Biofuel’
June 26, 2012
Ravello, Italy
I. PPF
Political preference function approach.
• Rausser and Freebairn (1974)
• 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-bystep 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.
Multi-market, multi-policy-instrument model
II. The Model
I illustrate my arguments
with a multi-market, multipolicy-instrument, partial
equilibrium model of the
U.S. ethanol policy.
Crude Oil
Corn-specific
Refinery-specific Ethanol-specific
land, capital,
capital and labor capital and labor
labor
Petrofuel
“Fuel”
Livestock-specific
land, capital,
labor
Biofuel
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 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)
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):
Biofuel
qr
Petrofuel
qcm
qa
Non-corn biofuel resources
Meat
Corn to meat
Corn to biofuel
Refining and distribution
qcb
ql
qo
Crude oil
Livestock
Simple model of fuel production:
petrofuel and biofuel are perfect
substitutes in the production of “fuel.”
Fuel
Petrofuel
qg
qb
Biofuel
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: government
Groups 1, …, n: other interest groups
Government’s strategies
involve policy instruments
x2
(Production mandate)
X, set of feasible policies
x´
A particular policy
x1 Per-unit
biofuels
subsidy
(tax if < 0)
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,))
Every place the
government can
send the
interest groups
u2
x2
h(x)
X
h(x´)
x´
x1
H{1,2}(X)
“feasible welfare manifold”
{1,2} here is the set of utility-bearing groups
u1
Welfare manifolds are a
generalization of Josling’s
(1974) and Gardner’s (1983)
surplus transformation curves.
“feasible welfare manifold”
“feasible welfare submanifold”
u2
x2
H{1,2}(T)
h(x´)
X
T
x´
x1
H{1,2}(X)
u1
{1,2} here is the set of utility-bearing groups
III. PPF Results using the
model
A. One policy instrument,
two interest groups
“Everybody else’s” welfare
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)
Corn farmer/ethanol
producer welfare
Decrease ethanol tax
or increase ethanol
subsidy
PPF weights
would be:
Political
power
“Everybody else’s”
welfare weights:
Farmers/ethanol producers: 0.514
Corn/ethanol industry: 0.514
Everyone
else: 0.486
0.486
Everyone
else:
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.”
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
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.
Corn farmer/ethanol
producer welfare
“Everybody else’s”
welfare
Say we had observed
an ethanol
subsidy of $1.50/gal. What would
our PPF method say that the
political power weights were?
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
So what seems like a fairly
small change in political
power weights leads to a
huge change in transfers!
“Everybody else’s” welfare
Corn farmer/ethanol
producer welfare
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?
To a point, raising
the gasoline tax
improves the welfare
of both groups!
Status
quo
What’s going
on? Higher
gas tax
allows a
lower labor
tax, less
distortion.
Positive slope!
But “negative”
political power
weight means
that
government
can’t be
solving the
max problem.
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.
“Everybody else’s” welfare
Using
instruments
separately
petrofuel tax/subsidy
Corn farmer/ethanol
Better
how
are these
instruments
best
that even
a very
good
question?
Is one question:
ofIsthese
instruments
“better”
than
the
producer welfare
combined?
others?
biofuel use mandate
biofuel tax/subsidy
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
else’s”
Instruments“Everybody
used
simultaneously:
welfare
•biofuel tax/subsidy
•Petro-fuel tax/subsidy
Corn farmer/ethanol
producer welfare
Result: 2-dimensional welfare manifold
else’s”
Most PPF“Everybody
studies
just assume away this
welfare
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
Corn farmer/ethanol
producer welfare
C. Three instruments, two
interest groups
“Everybody else’s” welfare
Instruments used
simultaneously:
•biofuel tax/subsidy
•petrofuel tax/subsidy
•biofuel use mandate
If we allow the third instrument to be used,
and
Corn farmer/ethanol
producer
our model has two interest groups, this
justwelfare
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
“Everybody
else’s” welfare
Corn
farmer/
biofuel
producer
welfare
Petrofuel
producers’
welfare
unon-intervention
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.
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).”