Regulation in Happyville1
François Salanié
Nicolas Treich
Université de Toulouse, LEERNA-INRA, France
October 15, 2003
1 We
thank Yann Bramoullé together with David Bardey, Bruno Jullien, Jack
Marshall and Bernard Salanié for useful discussions. We also thank seminar participants at the universities of Santa Barbara, Iowa State, Toulouse, Wageningen,
Lille, Grenoble and Nottingham.
Abstract
In Happyville, consumers wrongly believe that the drinking water supply
is contaminated. Will the Director of the Environment Protection in Happyville invest in a water cleanup technology? The answer is intuitively yes if
the Director is “populist”, namely if he maximizes consumers’ welfare computed with their pessimistic beliefs. We show that the answer may also be
yes if the Director is “paternalistic” and maximizes consumers’ welfare using
his own beliefs. Though often opposed in the literature, both the “populist”
and the “paternalist” approach may thus support the view that risk misperceptions justify more regulatory intervention. We also present a case where
both regulatory approaches rely on safety norms rather than taxes.
Key-words: Risk Regulation, Misperceptions, Safety Norms, Taxation,
Paternalism, Merit Goods.
JEL Classi…cation: D81, D78, H51
1
Introduction
There is a lot of evidence that people misperceive the risks they face, in
the sense that individuals’ beliefs on hazard risks di¤er from risks data frequencies and experts’ scienti…c evidence (Slovic, 2000). There is also a lot
of evidence that regulatory programs respond heavily to public risks misperceptions, even when the risks seem almost negligible compared to other
familiar and more established risks (Viscusi, 1998). Recent examples include
hazardous wastes, food-laden pesticides, mad cow disease, genetically modi…ed organisms in Europe, and the list could go on. This paper addresses the
following question: under which conditions do public risks misperceptions
call for more regulatory intervention?
In a two-page policy paper, Portney (1992) presents the following fable.
“You are Director of Environmental Protection in Happyville (...). The
drinking water supply in Happyville is contaminated by a naturally occurring substance that each and every resident believes may be responsible for
the above-average cancer rate observed there. So concerned are they that
they insist you put in place a very expensive treatment system to remove the
contaminant. (...)
You have asked the top ten risk assessors in the world to test the contaminant for carcinogenicity (...). These ten risk assessors tell you that while one
could never prove that the substance is harmless, they would each stake their
1
professional reputations on its being so. You have repeatedly and skillfully
communicated this to the Happyville citizenry, but because of a deep-seated
skepticism of all government o¢cials, they remain completely unconvinced
and truly frightened.”
Happyville is a society where people believe that the drinking water is
contaminated while all experts agree is harmless. Furthermore, any attempt
to inform people that the water is safe has had no e¤ect. People remain
anxious and they urge the Director to invest in a water cleanup technology.
What should he do? Even though the Director is convinced that citizens’
beliefs are erroneous, the decision of whether to invest or not in a water
cleanup technology is a di¢cult one, and it is at the heart of an important
debate.
On the one hand, consumers’ sovereignty arguments provide a strong basis for the Director to purchase a cleanup technology. This would improve
welfare since worried people would feel protected (see Sandmo 1983, and Pollack, 1995, 1998). On the other hand, many scholars have arguably criticized
this approach, often referring to the “populist” approach to risk regulation
(Breyer, 1993, Hird 1994, Viscusi, 2000). They stress that the choice of a risk
regulator must be driven by risk-related facts, not by citizens’ uninformed
worries. There is an obvious opportunity cost here, as the money spent to
prevent a phantom risk could be used for better purposes. Yet, this last approach is controversial as well, as it relies on a paternalistic view of citizens’
2
preferences. It presumes that the regulator better knows than the citizens
what is good for them.
This paper provides a theoretical framework for analyzing the problem
faced by the Director of the Environmental Protection in Happyville. This
framework takes into account the citizen’s responses to regulation, and that
these reactions derive from the citizens’ own beliefs.1 We use this framework
to compare the outcomes of the populist policy and the paternalist policy.
An important policy lesson emerging from our analysis is that these outcomes
are often similar. Both approaches may warrant more regulatory intervention
when risks are misperceived; and both tend to rely on safety norms instead
of uniform taxes. We comment on our assumptions and results at the end of
the paper.
2
Model: the Happyville Society
Let us present a simple model of the Happyville society. The key feature
of our model is that citizens’ belief about the risk related to the drinking
water supply may di¤er from the belief held by the Director. We suppose
for simplicity that, except from this di¤erence, the preferences of the citizens
and that of the Director are aligned.
To begin with, assume that there is a single citizen living in Happyville,
1
A well-known reference is Peltzman (1975), who discusses the e¤ects of making seatbelts compulsory on the risk-taking behaviour of drivers.
3
with preferences given by
U(s; a; b) = u(b) ¡ (1 ¡ a)sb ¡ c(a)
(1)
where
b : is the citizen’s water consumption, b ¸ 0;
u(b) : is the citizen’s gross surplus, assumed increasing and concave,
a : is the Director’s cleanup e¤ort, 0 · a · 1,
c(a) : is the per capita cleanup cost function, assumed increasing and convex,
s : is the dose-response probability of getting cancer, 0 · s · 1.
In this simple model, the Director’s decision a can be interpreted as a
reduction in the probability of getting cancer, or equivalently, as a reduction
of the total damage if the cancer actually occurs.2 The cost c(a) induced by
the decision a is ultimately borne by the citizen. The probability s represents
the citizen’s beliefs. We assume that the Director is aware of the citizen’s
beliefs s. We allow the Director to have di¤erent beliefs about the risk, represented by the scalar r. Throughout the objective will be to examine how the
di¤erence between r and s a¤ects the cleanup e¤ort a selected by the Director.
To start with, assume that the citizen’s consumption b is exogenously
given. We …rst look at the cleanup e¤ort that would be developed by a
populist Director. De…ne a populist Director as a regulator who maximizes
2
The individual damage in case of cancer is normalized to one. A price for water could
be included, at the expense of notational simplicity.
4
the citizen’s welfare computed with the citizen’s beliefs s. Hence the populist
maximizes over a the objective U (s; a; b), so that
sb = c0 (a);
that is, the marginal perceived bene…t is equal to the marginal cost of the
cleanup e¤ort a. Clearly, if the citizen is pessimistic (s > r), a populist
Director will over-invest in a cleanup technology, compared to the identical
beliefs case when s = r. Conversely, the populist Director will under-invest
in the cleanup technology if the citizen is optimistic (s < r).
What does happen if, on the other hand, the Director is paternalistic?
De…ne a paternalist Director as a regulator who maximizes the citizen’s welfare computed with his own beliefs r. In this case, it is easy to see that the
Director policy a does not depend on beliefs s at all. Indeed, the paternalist Director simply maximizes over a the objective U (r; a; b), which yields
rb = c0 (a), as if there was no beliefs distortion. To sum it up, when water
consumption is given, the populist policy is determined by the citizen’s beliefs (but neglects some valuable information) while the paternalist policy is
una¤ected by risk misperceptions (but ignores the citizen’s worries).
Few situations are such that the citizen’s risk exposure is exogenously
given. The problem becomes more realistic and more interesting when consumption b is not given, but may change as perceptions s and policy a change.
When allowing for this possibility, the citizen chooses, for a given cleanup
5
e¤ort a, his water consumption b(a; s) to maximize U (s; a; b), so that
u0 (b(a; s)) = (1 ¡ a)s:
(2)
According to the intuition, the concavity of u implies that water consumption b(a; s) is decreasing in the perceived probability of getting cancer s and
increasing in the level of cleanup e¤orts a.
Taking into account the consumption choice, the populist criterion is the
citizen’s welfare computed with beliefs s: U(s; a; b(a; s)). On the other hand,
the paternalist criterion is U(r; a; b(a; s)), and we denote by a(r; s) a maximizer of this expression. As before, the only di¤erence between the two
criteria comes from the fact that the populist Director uses the citizen’s beliefs s while the paternalist Director uses his own beliefs r. Observe however
that the fact that citizens’ consumption b(a; s) is endogenous introduces a
new subtlety into the analysis. The paternalist Director needs to account for
the citizen’s actual response, i.e. the response based on s; not on r. Clearly,
maximizing instead U (r; a; b(a; r)) would be sup-optimal for the paternalist
Director, as he would not correctly anticipate the citizen’s actual reaction.
We will denote this last sub-optimal regulatory policy a(r; r) and coin it the
“rationalist” policy. Although this policy is not very interesting per se, observe that a(r; r) corresponds to the optimal level of cleanup e¤ort without
any di¤erence in beliefs. Hence a(r; r) will be our benchmark case in the
analysis; thanks to the envelope theorem, it is given by
rb(a; r) = c0 (a):
6
(3)
To sum up, our approach allows us to consider three di¤erent cases. The
Director may select:
a(r; s) : the paternalist policy
a(s; s) : the populist policy
a(r; r) : the rationalist policy.
To illustrate the di¤erence between the three policies, consider quadratic
forms
u(b) = ¡(1 ¡ b)2 =2;
c(a) = a2 =2:
In that case, the citizen’s choice is simply b(a; s) = 1 ¡ (1 ¡ a)s; so that
we get
U (r; a; b(a; s)) ´ ¡((1 ¡ a)s)2 =2 ¡ (1 ¡ a)r(1 ¡ (1 ¡ a)s) ¡ a2 =2:
(4)
Maximizing this expression over a gives the paternalist policy
a(r; s) =
r ¡ 2rs + s2
2 [0; 1];
1 ¡ 2rs + s2
(5)
from which we derive the populist and the rationalist policies:
a(s; s) =
s
;
1+s
a(r; r) =
r
:
1+r
Figure 1 represents the three di¤erent policies as a function of the citizen’s
beliefs s. Following Viscusi (2000), we call Blissville the mirror image of
Happyville, that is a society where the citizen is optimistic.
7
Cleanup
efforts a
a(s,s)
« Populist »
« Paternalist »
a(r,s)
a(r,r)
« Rationalist »
s
BLISSVILLE
(optimist)
r
HAPPYVILLE
(pessimist)
Figure 1:
Optimal cleanup e¤ort as a function of the citizen’s beliefs for three different Directors: the populist, the paternalist and the rationalist.
8
Observe …rst that the rationalist policy a(r; r) is a straight line on the
…gure. This makes sense since this policy does not internalize the citizen’s
belief, and so is independent of s. As expected, the rationalist policy is thus
only sensitive to the objective level of risk, r. At the opposite, the populist
policy ignores the objective risk r, and it is monotonically increasing with s.
According to the intuition, the populist policy responds to citizens’ worries.
Finally, let us turn to the paternalist policy. From equation (5), decision
a(r; s) is decreasing in s then increasing in s. This function has its minimum
at s = r. Thus we have a(r; s) ¸ a(r; r): the paternalist policy is always
larger than the policy undertaken under no risk misperceptions. In other
words, the di¤erence in beliefs always calls for more regulatory intervention,
even under the paternalist approach, and no matter whether the citizen is
pessimistic or optimistic. We check the robustness of this surprising result
in the following section.
3
Direct and Spill-over E¤ects
In this section, we explain why the paternalist policy does not depend on
whether the citizen is optimistic or pessimistic. It will be shown that this
result is due to the interplay between two opposite e¤ects of the policy,
namely a direct e¤ect and a spillover e¤ect.
Let us go back to the general case. The …rst order condition for the
9
paternalist Director’s choice of a gives:
@b
rb(a; s) ¡ c0 (a) +
(a; s)[u0 (b(a; s) ¡ (1 ¡ a)r)] = 0
|
{z
}
@a
{z
}
|
Direct E¤ect
Spill-over e¤ect
The …rst e¤ect is the one we studied when consumption was given, while the
spillover e¤ect is related to the impact of the cleanup e¤ort on the citizen’s
consumption, and therefore to characteristics of the water demand function.
In order to further interpret this last equality, let us de…ne more precisely
this demand function D(½) by the familiar identity u0 (D(½)) = ½; where the
parameter ½ is a shadow price of water that depends both on the cleanup
e¤ort and on risks perceptions (see eq. (2)). It is also useful to introduce the
following function:
T (b) = ¡
u0 (b)
> 0;
u00 (b)
so that it is then easy to see that T (D(½)) = ¡½D0 (½) = D(½)"(½), where
"(½) is the elasticity of water demand at the shadow price ½. Using (2), one
can then rewrite the …rst-order condition in a more compact manner:3
rb(a; s) ¡ c0 (a) + T (b(a; s))[s ¡ r] = 0:
|
{z
}
|
{z
}
Direct E¤ect
Spill-over e¤ect
(6)
In the absence of risk misperceptions (s = r), the spillover e¤ect is zero,
and we are back to our benchmark (3). The spillover e¤ect is also zero in
the populist case: since the Director uses the agent’s beliefs s, there is no
3
We use the fact that
¡ 1s T (b(a; s)):
@b
@a
=
1
1¡a T (b(a; s)).
10
For further use, note also that
@b
@s
=
con‡ict between the Director and the citizen. Then the …rst-order condition
reduces to
sb(a; s) = c0 (a)
so that the populist cleanup e¤ort is increasing with s if the elasticity of
water demand is less than one, as in the case illustrated in Figure 1. Note
however that if the demand elasticity is larger than one, then the populist
cleanup e¤ort decreases with s. This e¤ect is surprising: more pessimism
may decrease the cleanup e¤ort of the populist. The idea is the following.
When demand elasticity is large, more pessimism leads to a strong reduction
in water demand, and thus reduces the need for a more stringent regulation.4
In the paternalist case, beliefs r and s di¤er so that both the direct e¤ect
and the spillover e¤ect matter. The direct e¤ect represents the usual tradeo¤ between the marginal bene…t of increasing cleanup e¤orts rb(a; s) and its
marginal cost c0 (a); the citizen’s response being held constant at b(a; s). If
only this direct e¤ect was at play, risks misperceptions would lead to increase
cleanup e¤orts if and only if the citizen is optimistic (s < r), or equivalently
if he consumes too much water (b(a; s) > b(a; r)). The intuition is quite
simple: water must be cleaned because the optimistic citizen chooses an
excessive exposure to risk.
4
Few studies have analyzed the elasticity of citizens’ response to a change in perceived
safety. Interestingly, Viscusi (1998) found a correlation between child-resistant packages
and an increase in accidental poisonings, which he attributes to the unanticipated e¤ect
that consumers might have become less safety conscious due to the existence of safety
caps. This particular case suggests a strong demand elasticity.
11
In addition, the spillover e¤ect captures the citizen’s response to the regulatory e¤ort. In the paternalistic case, it tends to increase cleanup e¤orts
if and only if the citizen is pessimistic (s > r). The intuition is very simple
as well. When the citizen is pessimistic, he does not consume water enough
and increasing the regulatory e¤ort precisely leads the citizen to increase his
consumption.
We have thus indicated that in the paternalistic case, the direct and the
spillover e¤ects go in opposite directions; and that they both change sign at
r = s. We now examine whether an e¤ect dominates in general. To answer
this question, let us examine the sign of the variation of the total e¤ect with
respect to s, that is,
r
@b
@b
(a; s) + T 0 (b(a; s)) (a; s)(s ¡ r) + T (b(a; s))
@s
@s
= T (b(a; s))(1 ¡ T 0 (b(a; s)))(s ¡ r)=s:
This last equality makes it clear that, for given preferences, the total e¤ect
of an increase in s is generally controlled by the sign of s ¡ r.5 If for example
T 0 (b) < 1 for any b, then this expression is negative for s < r and positive
for s > r. Hence, even though the direct and the spill-over e¤ects go in
opposite direction, this equality shows that the global e¤ect is unambiguous.
The cleanup e¤ort is indeed decreasing with s when the citizen is optimistic
(s < r), and increasing with s when the citizen is pessimistic. In other words,
5
In a more technical paper, Salanié and Treich (2002) show that this cross-derivative
must change sign at s = r, whatever the shape of U . Moreover, we derive conditions on
preferences under which this cross-derivative changes sign only once; here these conditions
reduce to signing (1 ¡ T 0 ).
12
under T 0 (b) < 1; the cleanup e¤ort of the paternalist Director increases with
the di¤erence in beliefs. This case was precisely the case illustrated in Figure
1. One can indeed verify that T 0 (b) < 1 for any quadratic u or equivalently for
any linear demand function; the same property holds for constant elasticity
demand functions with an elasticity below one.
Conversely, when T 0 (b) > 1 the paternalistic decision a(r; s) is increasing
then decreasing with s, thus reaching a maximum in s = r. This is the
case for constant elasticity demand functions with an elasticity above one.
This would lead to an alternative Figure in which the populist decision is
decreasing with s (as we said above), and in which the paternalist decision
decreases when s moves away from r. In the limit case, that is when T 0 (b) = 1,
or equivalently when u is logarithmic, the cleanup e¤ort is una¤ected by the
di¤erence in beliefs. To summarize, risk misperceptions may call for always
more, or always less, cleanup e¤ort; this is essentially an empirical matter
that depends on demand elasticity.6
Finally, let us conclude this section by recalling that we have considered a
Happyville society with only one representative citizen, or equivalently with a
homogeneous population with identical beliefs. This assumption is strong, as
there may be both pessimistic and optimistic citizens within society. Clearly,
this will matter for the populist Director, whose preferred policy crucially
depends on whether citizens are globally optimistic or pessimistic. However,
6
In the particular case of water demand, empirical studies generally …nd an elasticity
below one (see, e.g., Nauges and Thomas, 2000) and thus would tend to support an increase
in the regulatory e¤ort.
13
it is easy to understand that beliefs heterogeneity has few consequences for
the paternalist policy. One can easily see that on Figure 1. Observe that the
e¤ect of the beliefs distortion on the paternalist policy always go in the same
direction, no matter whether people are optimistic or pessimistic. Hence,
beliefs heterogeneity would not change the comparative statics analysis in
that case, still leading to increase the regulatory e¤ort. In contrast, notice
that heterogeneity in preferences, such as heterogeneity in demand elasticity,
would clearly matter for both the paternalist policy and the populist policy.
In the next section, we consider both types of heterogeneity, that is beliefs
and utility heterogeneity. We also introduce taxation into the model.
4
Taxes in Happyville
A relevant literature for analyzing the paternalist policy is the literature on
merit goods. A merit good is a good whose value is underestimated by the
consumers, so that the regulator wants to support its consumption. The general message of this literature is easily summarized (Sandmo, 1983, Glazer,
1985, Besley, 1988). Merit goods such as education should be subsidized
while demerit goods such as gambling should be taxed. Besides, adequate
taxation permits to retrieve …rst-best e¢ciency. In line with this literature,
we now ask the following simple question: what does happen if the Director
can tax (or subsidize) water consumption in Happyville?
Consider a population of N agents where agent i = 1; ::; N has beliefs si
and utility ui from water consumption. Agent i’s optimal consumption bi is
14
now characterized by
u0i (bi ) = (1 ¡ a)si + ti
where ti is the tax that the regulator sets on agent’s i water consumption.
Because ui is concave, water consumption is increasing with a and decreasing
with the tax ti and the pessimism index si .
We assume that the redistribution of tax is costless, so that the paternalist
Director’s program is
max
a;(ti )
N
X
i=1
¸i [ui (bi ) ¡ (1 ¡ a)rbi ] ¡ c(a);
(7)
where ¸i represents the proportions of individuals i in the economy and bi is
de…ned above. It is easily shown that the Director will set personalized taxes
so as to correct the impact of erroneous beliefs:7
t¤i = (1 ¡ a)(r ¡ si ):
Hence, water consumption is taxed in Blissville where consumption is a demerit good. On the other hand, water consumption is subsidized in Happyville since consumption is a merit good there. See Figure 2.
7
As an immediate corollary, notice that taxation is useless for a populist Director.
15
ti*
TAX
0
SUBSIDIZE
si
BLISSVILLE
(optimist)
r
HAPPYVILLE
(pessimist)
Figure 2:
Optimal personalized tax as a function of the citizens’ beliefs.
16
Hence, the optimal tax is monotonic in the di¤erence in beliefs. This
monotonicity property of the tax is emphasized in the merit goods literature
(see, e.g., Besley, 1988). It corresponds to the idea that a well-chosen tax
corrects erroneous beliefs from the viewpoint of the regulator. As a consequence, each citizen now behaves as if he shared the same beliefs r as the
regulator. Hence the citizens’ misperceptions problem is fully alleviated by
the use of a perfect taxation scheme so that it is possible to restore …rst-best
e¢ciency. This implies that under personalized taxation the cleanup e¤ort is
una¤ected by the heterogeneity in beliefs and is the same as in the benchmark
cleanup e¤ort a(r; r).
Such a personalized taxation is however di¢cult to implement in practice, since it requires information on both utility functions and beliefs. It
is therefore appropriate to turn to a second-best analysis of the economy
by constraining the regulator to set a uniform tax on water consumption.
We therefore add the constraint ti = t so that the …rst-order condition to
program (7) becomes
N
X
¸i
i
@bi 0
(u (bi ) ¡ (1 ¡ a)r) = 0;
@t i
and, using the new …rst order condition u0i (bi ) = (1 ¡ a)si + t; we get
¤¤
t
= (1 ¡ a)
P
i
17
i
¸i @b
(r ¡ si )
;
P@t @bi
i ¸i @t
or equivalently,
t¤¤
P @bi ¤
¸i t
= Pi @t@bi i :
i ¸i @t
Therefore the optimal uniform tax is an average of the …rst-best taxes,
computed with weights which indicate the sensitivity of individual water
demand to the tax. If the citizens’ beliefs are identical, then personalized
taxes t¤i need not be di¤erentiated, and we are back to the result above:
taxation permits to retrieve …rst-best e¢ciency and the cleanup e¤ort is
una¤ected by the di¤erence in beliefs. On the other hand, if citizens hold
di¤erent beliefs, then every citizen i chooses his consumption according to
a shadow price of water equal to (1 ¡ a)si + t¤¤ . Interestingly, the above
formula implies that this shadow price is on average equal to (1 ¡ a)r, which
is the shadow price with no risk misperceptions:
P
i
i
¸i @b
[(1 ¡ a)si + t¤¤ ]
@t
= (1 ¡ a)r:
P @bi
i ¸i @t
In other words, the use of a uniform tax allows the Director to correct the
average misperception. The remaining heterogeneity in beliefs will then drive
the regulatory response of the Director after the imposition of the uniform
tax.
Finally it may be that initially citizens do not misperceive the risk on
average; that is, some of them are optimistic while others are pessimistic.
18
Moreover assume that there is no correlation between the sensitivity to the
price of individual water demand and the degree of optimism or pessimism (as
in the quadratic utility case). The optimal second-best tax must then be set
to zero, and we are back to the problem analyzed in the previous sections.
As before, the optimal cleanup e¤ort will depend on citizens’ preferences,
and will be higher under risks misperceptions if individual demand functions
verify the condition T 0 (b) < 1. Besides, this shows that a uniform regulatory
policy a (such as a safety norm) may be more powerful than uniform taxes t
(even under costless redistribution) in the domain of risk policies.
5
Discussion
Although there is an important literature on risk misperceptions on the one
hand, and on risk regulation on the other hand, there exists no systematic
analysis of the interplay between the two.8 An economic analysis would
naturally proceed as follows: i) write down the assumptions about citizens’
perceptions and preferences; ii) posit the welfare criterion that the regulator
is maximizing; iii) sort out the policy instruments available to the regulator
and examine the ones, or the combination of those, that maximize the above
welfare criterion. In this section, we use our Happyville model to discuss
these points in turn, and to relate our assumptions to the existing literature.
The key assumption in the Happyville model is that citizens misperceive
8
A recent exception is Johansson-Stenman (2003).
19
the risks they face. There is a lot of empirical evidence supporting this. For
instance, individuals systematically overestimate the rare causes of death
such as cataclysmic storms or plane crashes and underestimate more common causes of death like cancers or automobile accidents (Lichtenstein et al.,
1978).9 Recent evidence on citizens’ risk over-estimation of publicly-supplied
drinking water may be found in Adamowizc et al. (2003). Notice that such
misperceptions do not necessarily imply that citizens have a bounded rationality. Misperceptions may simply be the consequence of costly information
acquisition by rational citizens (e.g., because the information is highly technical).
A second important feature of the Happyville model is that citizens do
not revise their beliefs s, even after they observe the Director’s cleanup e¤ort
a. Maybe they know the Director’s beliefs and they simply disagree with
him; so that the Director’s choice of a has no informational content and does
not lead to any revision of beliefs. Another possibility is that the citizens do
not trust the Director, as in Portney’s fable, and attribute the choice of a to
other irrelevant considerations. The realism of this assumption is ultimately
an empirical question. Do citizens revise their beliefs when they observe the
regulatory policy, or do they stick to their opinion? The answer is likely to
depend on the experts’ credibility, and may vary between the fully rational
Bayesian model (as in Barigozzi and Villeneuve, 2002) and the no-inference
9
There is a very well documented literature on Psychology on risk misperceptions (see,
e.g., Kahneman and Tversky, 2000).
20
case that we have considered here (see also Spence, 1977).
Let us now turn to the discussion of the welfare criterion. The Happyville
model has exempli…ed the populist and paternalist criteria as de…ning a fundamental normative opposition. An early economic approach to this debate
can be traced back to the de…nitions of ex-ante and ex-post e¢ciency in
Hammond (1981). Unsurprisingly, this opposition has long been discussed in
the Economics and Philosophy literature (Sen and Williams, 1982, Harsanyi,
1997). Nowadays, this normative opposition is mostly pursued in the Law
and Economics literature (Adler and Posner, 2000, Sunstein, 2002).
Alternatively, one may want to give positive foundations to this debate.
From a political economy viewpoint, the populist approach …ts well the case
when the Director faces elections in the short-term. In this case, responding
to the citizens’ current demands may increase the chances of the Director to
be reappointed. However, notice that the incentives may di¤er for a long-term
Director. In the long run, the public will likely observe the trends of the early
damages. A populist approach may then face ex-post public contestation
based on these observations. As a consequence, a long-term Director may
prefer to adapt the prevention e¤ort to sound information about expected
future damages.10 This strategy is clearly more in line with the paternalist
approach. Hence, a political economy viewpoint of the policy problem still
10
A similar point is analyzed in Maskin and Tirole (2002), who study the optimal
incentive schemes for short-term or long-term politicians.
21
opposes the paternalist and the populist approach as two important policy
benchmarks.
Our analysis has shown that in some cases both criteria support an increase in the regulatory e¤ort. As a consequence, a more general welfare
function “mixing” the populist and paternalist criteria would also prescribe
an increase in the regulatory e¤ort. Di¤erent criteria could also be used. An
early reference is the Akerlof and Dickens (1982)’s paper on cognitive dissonance. They introduce preferences, not only over the states of world, but
also over the beliefs about the states of the world. Marshall (1989) discusses
various criteria, in particular in relation with state-inconsistency. More recently, Caplin and Leahy (2001) extend the expected utility framework to
account for anticipatory feelings and anxiety.
Finally let us turn to the instruments of regulation. In a world where
citizens’ perceptions are biased, information policies provide natural instruments. Consistently with the Portney’s fable, we assumed that information
policies have already been used in Happyville, and that, for some reasons, a
belief perception gap persists between the Director and the citizens. We have
thus focused on two other instruments which are prevalent in risk policies,
namely public safety provision and taxes. The model is general enough to
accommodate various examples of public safety provisions, including some
safety burden devices imposed by law on risky activities.
However, the possibility that risk perceptions are biased, and more gen22
erally that people behave in an “irrational” manner, signi…cantly enlarges
the set of policy instruments that needs to be considered. Indeed, many
instruments that would be routinely viewed as useless in a world free of misperceptions, may become more e¤ective in a more realistic world.11 This last
remark underlines the subtleties of the policy design in the presence of irrationalities. It is worth noticing that certain devices may be of great help for
irrational citizens while they do little harm on those who are fully rational.
This is the case in our Happyville model. Indeed, in the neighborhood of
the benchmark cleanup e¤ort a(r; r); the gain for citizens with beliefs s 6= r
corresponds to a …rst-order e¤ect while the loss for rational citizens with
beliefs s = r corresponds to a second-order e¤ect.12 These aspects are discussed at length in Camerer et al. (2003), under the name of “asymmetric
paternalism”.13
To conclude this section, it is natural to relate our analysis to the expanding literature on time-inconsistency and hyperbolic discounting models.
In particular, recent papers by Gruber and Koszegi (2002) and O’Donoghue
and Rabin (2003) have examined the role for government intervention in
such models. Their approach is consistent with the three-step analysis de11
A striking example is given in Saint-Paul (2002). He considers a model where “irrational” agents make random mistakes in transactions, and rational agents may want
to extract a pro…t from these irrational agents. If the regulator has a superior ability
to make statistical inference about the true desirability of the transactions, he may try
to limit these transactions by introducing some price restrictions. Such an instrument is
useless when all agents are rational.
12
Mathematically: @U (r;a;b(a;r))
ja=a(r;r) = 0 and @U (r;a;b(a;s))
ja=a(r;r) 6= 0:
@a
@a
13
Another approach is that of Sunstein and Thaler (2003), who de…ne “libertarian paternalism” as the idea that paternalism should not restrict the freedom of choice of agents.
23
scribed above, where i) assumes sophisticated hyperbolic consumers, ii) assumes “long run” preferences and iii) explores the e¤ect of taxation. Although the approach is globally similar, there is a key di¤erence though.
Our model has studied the e¤ect of a regulatory policy that directly changes
the risks borne by consumers. For instance, this is a policy that, on top of a
taxation policy, would also change, say, the tar content of cigarettes (Gruber
and Koszegi, 2002), or the salt content of potato chips (O’Donoghue and
Rabin, 2003). Our analysis suggests that, due to the citizen’s response to
the perceived change in risk, the analysis of such regulatory policies generally
o¤ers di¤erent policy messages compared to the analysis of the sole e¤ect of
taxation.
6
Conclusion
An important policy question is whether consumers’ deviant beliefs may justify the observed heavy-handed risk policy interventions. In this paper, we
have used the Portney (1992)’s Happyville fable as a metaphor for analyzing
this question.
We have …rst set up a simple model of the Happyville society. Citizens
consume a good whose health consequences are unknown. Citizens have a
subjective and potentially erroneous beliefs over these consequences. These
beliefs may di¤er from the beliefs used by an informed regulator. We have
then examined how the regulatory policy is a¤ected by this di¤erence in
beliefs. In particular, we have examined under which conditions citizens’
24
risks misperceptions call for more regulatory intervention.
We have found two such conditions. The …rst condition is met if the society is mostly composed of pessimist citizens. Moreover the risk regulator
must be populist, namely he must maximize citizens’ expected utility computed with their erroneous beliefs. In that case, there is no con‡ict between
the regulator and consumers’ objectives so that it makes sense that the policy responds to citizens worries by a more stringent regulation. To illustrate,
the Superfund program in the US and GMO regulatory policy in Europe are
often presented as typical examples of populist policies. Many scholars have
indeed suggested that these massive risk-prevention policies were primarily
designed to reassure people rather than adequately respond to the risks in
presence.
The second situation arises when the regulator is paternalistic, namely he
maximizes citizens’ welfare but computed with his own beliefs. Compared
to the case of no belief distortion, the increase in the regulatory e¤ort is due
here to the presence of two distinct e¤ects: a direct and a spill-over e¤ect.
The direct e¤ect occurs when people are optimistic so that risk-exposure is
too high in the society. As a result, the regulator simply increases his e¤ort
to reduce the level of risk in the society. Examples of regulations of this kind
include home safety prevention, compulsory seatbelts, tolerance standard for
pollutants or food additives, namely situations where people are prone to
take too much risk.
In contrast, the spill-over e¤ect occurs when people are pessimistic so
25
that consumption of the considered good is too low. A more stringent policy
may be e¢cient in this case as well, since it reduces the perceived level
of risk by consumers, and therefore helps increase consumption. A typical
example could be the European stringent beef regulation in the late 90s that
permitted to mitigate the huge decrease in beef consumption following the
mad cow crisis.
Obviously, the last two e¤ects go in opposite direction, and an important
purpose of the analysis has been to compare their relative strength. A striking result has been then to show that a more stringent prevention policy may
be always warranted both in a society with optimistic or pessimistic citizens.
Hence an important message of the paper is that one may provide an economic rationale for increasing regulatory intervention when people beliefs are
distorted, no matter the type of distortion.
Besides, we have o¤ered a simple explanation for the prevalence of safety
norms in the domain of risk policies. A tax (or a subsidy) can correct an overexposure (or under-exposure) to risk if it is set at the appropriate level. Such
taxes are useless if the regulator is populist, since by de…nition there is no
con‡ict of objectives between the regulator and the consumers. Conversely,
in the presence of multiple agents with heterogeneous beliefs, a paternalist
regulator then has to set individualized taxes, a di¢cult task in practice.
It is therefore likely that a uniform tax shall be set at an average level. In
particular, if citizens do not misperceive the risk on average, then the optimal
uniform tax may be quite close to zero, and thus quite useless. In contrast,
26
a norm may be useful, since we have seen that it can be chosen irrespective
of whether citizens under-estimate or over-estimate the risk. Consequently,
our analysis suggests that uniform taxes (or uniform subsidies) may be poor
instruments to regulate misperceived risks compared to safety norms.
27
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