## Fundamental theorems of welfare economics | Wikipedia audio article

There are two fundamental theorems of welfare
economics. The first theorem states that a market will tend toward a competitive equilibrium
that is weakly Pareto optimal when the market maintains the following three attributes:1.
Complete markets as no transaction costs and because of this each actor also has perfect
information. 2. Price-taking behavior as no monopolists
and easy entry and exit from a market. Furthermore, the first theorem states that
the equilibrium will be fully Pareto optimal with the additional condition of:
3. Local nonsatiation of preferences as for any original bundle of goods there is another
bundle of goods arbitrarily close to the original bundle, but that is preferred.
The second theorem states that out of all possible Pareto optimal outcomes one can achieve
any particular one by enacting a lump-sum wealth redistribution and then letting the
market take over.==Implications of the first theorem==
The first theorem is often taken to be an analytical confirmation of Adam Smith’s
“invisible hand” hypothesis, namely that competitive markets tend toward an efficient allocation
of resources. The theorem supports a case for non-intervention in ideal conditions:
let the markets do the work and the outcome will be Pareto efficient. However, Pareto
efficiency is not necessarily the same thing as desirability; it merely indicates that
no one can be made better off without someone being made worse off. There can be many possible
Pareto efficient allocations of resources and not all of them may be equally desirable
by society.This appears to make the case that intervention has a legitimate place in policy
– redistributions can allow us to select from all efficient outcomes for one that has
other desired features, such as distributional equity. The shortcoming is that for the theorem
to hold, the transfers have to be lump-sum and the government needs to have perfect information
on individual consumers’ tastes as well as the production possibilities of firms. An
additional mathematical condition is that preferences and production technologies have
to be convex.===Proof of the first theorem===
The first fundamental theorem was first demonstrated graphically by economist Abba Lerner and mathematically
by economists Harold Hotelling, Oskar Lange, Maurice Allais, Lionel McKenzie, Kenneth Arrow
and Gérard Debreu. The theorem holds under general conditions.The formal statement of
the theorem is as follows: If preferences are locally nonsatiated, and if ( X ∗ , Y ∗ , p ) {\displaystyle (\mathbf {X^{*}} ,\mathbf {Y^{*}}
,\mathbf {p} )} is a price equilibrium with transfers, then
the allocation ( X ∗ , Y ∗ ) {\displaystyle (\mathbf {X^{*}} ,\mathbf {Y^{*}}
)} is Pareto optimal. An equilibrium in this
sense either relates to an exchange economy only or presupposes that firms are allocatively
and productively efficient, which can be shown to follow from perfectly competitive factor
and production markets.Given a set G {\displaystyle G}
of types of goods we work in the real vector space over G {\displaystyle G}
, R G {\displaystyle \mathbb {R} ^{G}}
and use boldface for vector valued variables. For instance, if G
} then R G {\displaystyle \mathbb {R} ^{G}}
would be a three dimensional vector space and the vector ⟨
1 ,
2 ,
3 ⟩ {\displaystyle \langle 1,2,3\rangle }
would represent the bundle of goods containing one unit of butter, 2 units of cookies and
3 units of milk. Suppose that consumer i has wealth w i {\displaystyle w_{i}}
such that Σ i w i=p ⋅ e + Σ j p ⋅ y j ∗ {\displaystyle \Sigma _{i}w_{i}=\mathbf {p}
\cdot \mathbf {e} +\Sigma _{j}\mathbf {p} \cdot \mathbf {y_{j}^{*}} }
where e {\displaystyle \mathbf {e} }
is the aggregate endowment of goods (i.e. the sum of all consumer and producer endowments)
and y j ∗ {\displaystyle \mathbf {y_{j}^{*}} }
is the production of firm j. Preference maximization (from the definition
of price equilibrium with transfers) implies (using>i {\displaystyle>_{i}}
to denote the preference relation for consumer i): if x i>i x i ∗ {\displaystyle \mathbf {x_{i}}>_{i}\mathbf
{x_{i}^{*}} } then p ⋅ x i>w i {\displaystyle \mathbf {p} \cdot \mathbf {x_{i}}
>\mathbf {w_{i}} } In other words, if a bundle of goods is strictly
preferred to x i ∗ {\displaystyle \mathbf {x_{i}^{*}} }
it must be unaffordable at price p {\displaystyle \mathbf {p} }
. Local nonsatiation additionally implies: if x i ≥ i x i ∗ {\displaystyle \mathbf {x_{i}} \geq _{i}\mathbf
{x_{i}^{*}} } then p ⋅ x i ≥ w i {\displaystyle \mathbf {p} \cdot \mathbf {x_{i}}
\geq \mathbf {w_{i}} } To see why, imagine that x i ≥ i x i ∗ {\displaystyle \mathbf {x_{i}} \geq _{i}\mathbf
{x_{i}^{*}} } but p ⋅ x ii x i ∗ {\displaystyle \mathbf {x_{i}}>_{i}\mathbf
{x_{i}^{*}} } for some i. By the above, we know p ⋅ x i ≥ w i {\displaystyle \mathbf {p} \cdot \mathbf {x_{i}}
\geq w_{i}} for all i and p ⋅ x i>w i {\displaystyle \mathbf {p} \cdot \mathbf {x_{i}}
>w_{i}} for some i. Summing, we find: Σ i p ⋅ x i>Σ i w i=Σ j p ⋅ y j ∗ {\displaystyle \Sigma _{i}\mathbf {p} \cdot
\mathbf {x_{i}}>\Sigma _{i}w_{i}=\Sigma _{j}\mathbf {p} \cdot \mathbf {y_{j}^{*}} }
.Because Y ∗ {\displaystyle \mathbf {Y^{*}} }
is profit maximizing, we know Σ j p ⋅ y j ∗ ≥ Σ j p
⋅ y j {\displaystyle \Sigma _{j}\mathbf {p} \cdot
y_{j}^{*}\geq \Sigma _{j}p\cdot y_{j}} , so Σ i p ⋅ x i>Σ j p ⋅ y j {\displaystyle \Sigma _{i}\mathbf {p} \cdot
\mathbf {x_{i}}>\Sigma _{j}\mathbf {p} \cdot \mathbf {y_{j}} }
. But goods must be conserved so Σ i x i>Σ j y j {\displaystyle \Sigma _{i}\mathbf {x_{i}}
>\Sigma _{j}\mathbf {y_{j}} } . Hence, ( X , Y ) {\displaystyle (\mathbf {X} ,\mathbf {Y} )}
is not feasible. Since all Pareto-dominating allocations are not feasible, ( X ∗ , Y ∗ ) {\displaystyle (\mathbf {X^{*}} ,\mathbf {Y^{*}}
)} must itself be Pareto optimal.Note that while
the fact that Y ∗ {\displaystyle \mathbf {Y^{*}} }
is profit maximizing is simply assumed in the statement of the theorem the result is
only useful/interesting to the extent such a profit maximizing allocation of production
is possible. Fortunately, for any restriction of the production allocation Y ∗ {\displaystyle \mathbf {Y^{*}} }
and price to a closed subset on which the marginal price is bounded away from 0, e.g.,
any reasonable choice of continuous functions to parameterize possible productions, such
a maximum exists. This follows from the fact that the minimal marginal price and finite
wealth limits the maximum feasible production (0 limits the minimum) and Tychonoff’s theorem
ensures the product of these compacts spaces is compact ensuring us a maximum of whatever
continuous function we desire exists.==Proof of the second fundamental theorem
==The second theorem formally states that, under
the assumptions that every production set Y j {\displaystyle Y_{j}}
is convex and every preference relation ≥ i {\displaystyle \geq _{i}}
is convex and locally nonsatiated, any desired Pareto-efficient allocation can be supported
as a price quasi-equilibrium with transfers. Further assumptions are needed to prove this
statement for price equilibria with transfers. The proof proceeds in two steps: first, we
prove that any Pareto-efficient allocation can be supported as a price quasi-equilibrium
with transfers; then, we give conditions under which a price quasi-equilibrium is also a
price equilibrium. Let us define a price quasi-equilibrium with
transfers as an allocation ( x ∗ , y ∗ ) {\displaystyle (x^{*},y^{*})}
, a price vector p, and a vector of wealth levels w (achieved by lump-sum transfers)
with Σ i w i=
p ⋅
ω + Σ j p
⋅ y j ∗ {\displaystyle \Sigma _{i}w_{i}=p\cdot \omega
+\Sigma _{j}p\cdot y_{j}^{*}} (where ω {\displaystyle \omega }
is the aggregate endowment of goods and y j ∗ {\displaystyle y_{j}^{*}}
is the production of firm j) such that: i. p
⋅ y j ≤
p ⋅ y j ∗ {\displaystyle p\cdot y_{j}\leq p\cdot y_{j}^{*}}
for all y j ∈ Y j {\displaystyle y_{j}\in Y_{j}}
(firms maximize profit by producing y j ∗ {\displaystyle y_{j}^{*}}
) ii. For all i, if x i>i x i ∗ {\displaystyle x_{i}>_{i}x_{i}^{*}}
then p
⋅ x i ≥ w i {\displaystyle p\cdot x_{i}\geq w_{i}}
(if x i {\displaystyle x_{i}}
is strictly preferred to x i ∗ {\displaystyle x_{i}^{*}}
then it cannot cost less than x i ∗ {\displaystyle x_{i}^{*}}
) iii. Σ i x i ∗=
ω + Σ j y j ∗ {\displaystyle \Sigma _{i}x_{i}^{*}=\omega
+\Sigma _{j}y_{j}^{*}} (budget constraint satisfied)The only difference
between this definition and the standard definition of a price equilibrium with transfers is in
statement (ii). The inequality is weak here ( p
⋅ x i ≥ w i {\displaystyle p\cdot x_{i}\geq w_{i}}
) making it a price quasi-equilibrium. Later we will strengthen this to make a price equilibrium.
Define V i {\displaystyle V_{i}}
to be the set of all consumption bundles strictly preferred to x i ∗ {\displaystyle x_{i}^{*}}
by consumer i, and let V be the sum of all V i {\displaystyle V_{i}}
. V i {\displaystyle V_{i}}
is convex due to the convexity of the preference relation ≥ i {\displaystyle \geq _{i}}
. V is convex because every V i {\displaystyle V_{i}}
is convex. Similarly Y
+ {
ω } {\displaystyle Y+\{\omega \}}
, the union of all production sets Y i {\displaystyle Y_{i}}
plus the aggregate endowment, is convex because every Y i {\displaystyle Y_{i}}
is convex. We also know that the intersection of V and Y
+ {
ω } {\displaystyle Y+\{\omega \}}
must be empty, because if it were not it would imply there existed a bundle that is strictly
preferred to ( x ∗ , y ∗ ) {\displaystyle (x^{*},y^{*})}
by everyone and is also affordable. This is ruled out by the Pareto-optimality of ( x ∗ , y ∗ ) {\displaystyle (x^{*},y^{*})}
. These two convex, non-intersecting sets allow
us to apply the separating hyperplane theorem. This theorem states that there exists a price
vector p
≠ {\displaystyle p\neq 0}
and a number r such that p
⋅ z
≥ r {\displaystyle p\cdot z\geq r}
for every z
∈ V {\displaystyle z\in V}
and p
⋅ z
≤ r {\displaystyle p\cdot z\leq r}
for every z
∈ Y
+ {
ω } {\displaystyle z\in Y+\{\omega \}}
. In other words, there exists a price vector that defines a hyperplane that perfectly separates
the two convex sets. Next we argue that if x i ≥ i x i ∗ {\displaystyle x_{i}\geq _{i}x_{i}^{*}}
for all i then p
⋅ ( Σ i x i )
≥ r {\displaystyle p\cdot (\Sigma _{i}x_{i})\geq
r} . This is due to local nonsatiation: there
must be a bundle x i ′ {\displaystyle x’_{i}}
arbitrarily close to x i {\displaystyle x_{i}}
that is strictly preferred to x i ∗ {\displaystyle x_{i}^{*}}
and hence part of V i {\displaystyle V_{i}}
, so p
⋅ ( Σ i x i ′ )
≥ r {\displaystyle p\cdot (\Sigma _{i}x’_{i})\geq
r} . Taking the limit as x i ′ → x i {\displaystyle x’_{i}\rightarrow x_{i}}
does not change the weak inequality, so p
⋅ ( Σ i x i )
≥ r {\displaystyle p\cdot (\Sigma _{i}x_{i})\geq
r} as well. In other words, x i {\displaystyle x_{i}}
is in the closure of V. Using this relation we see that for x i ∗ {\displaystyle x_{i}^{*}}
itself p
⋅ ( Σ i x i ∗ )
≥ r {\displaystyle p\cdot (\Sigma _{i}x_{i}^{*})\geq
r} . We also know that Σ i x i ∗ ∈
Y +
{ ω
} {\displaystyle \Sigma _{i}x_{i}^{*}\in Y+\{\omega
\}} , so p
⋅ ( Σ i x i ∗ )
≤ r {\displaystyle p\cdot (\Sigma _{i}x_{i}^{*})\leq
r} as well. Combining these we find that p
⋅ ( Σ i x i ∗ )
=r {\displaystyle p\cdot (\Sigma _{i}x_{i}^{*})=r}
. We can use this equation to show that ( x ∗ , y ∗ ,
p ) {\displaystyle (x^{*},y^{*},p)}
fits the definition of a price quasi-equilibrium with transfers.
Because p
⋅ ( Σ i x i ∗ )
=r {\displaystyle p\cdot (\Sigma _{i}x_{i}^{*})=r}
and Σ i x i ∗=
ω + Σ j y j ∗ {\displaystyle \Sigma _{i}x_{i}^{*}=\omega
+\Sigma _{j}y_{j}^{*}} we know that for any firm j: p
⋅ (
ω + y j + Σ h y h ∗ )
≤ r
=p
⋅ (
ω + y j ∗ + Σ h y h ∗ ) {\displaystyle p\cdot (\omega +y_{j}+\Sigma
_{h}y_{h}^{*})\leq r=p\cdot (\omega +y_{j}^{*}+\Sigma _{h}y_{h}^{*})}
for h
≠ j {\displaystyle h\neq j}
which implies p
⋅ y j ≤
p ⋅ y j ∗ {\displaystyle p\cdot y_{j}\leq p\cdot y_{j}^{*}}
. Similarly we know: p
⋅ ( x i + Σ k x k ∗ )
≥ r
=p
⋅ ( x i ∗ + Σ k x k ∗ ) {\displaystyle p\cdot (x_{i}+\Sigma _{k}x_{k}^{*})\geq
r=p\cdot (x_{i}^{*}+\Sigma _{k}x_{k}^{*})} for k
≠ i {\displaystyle k\neq i}
which implies p
⋅ x i ≥
p ⋅ x i ∗ {\displaystyle p\cdot x_{i}\geq p\cdot x_{i}^{*}}
. These two statements, along with the feasibility of the allocation at the Pareto optimum, satisfy
the three conditions for a price quasi-equilibrium with transfers supported by wealth levels w i=
p ⋅ x i ∗ {\displaystyle w_{i}=p\cdot x_{i}^{*}}
for all i. We now turn to conditions under which a price
quasi-equilibrium is also a price equilibrium, in other words, conditions under which the
statement “if x i>i x i ∗ {\displaystyle x_{i}>_{i}x_{i}^{*}}
then p
⋅ x i ≥ w i {\displaystyle p\cdot x_{i}\geq w_{i}}
” imples “if x i>i x i ∗ {\displaystyle x_{i}>_{i}x_{i}^{*}}
then p
⋅ x i>w i {\displaystyle p\cdot x_{i}>w_{i}}
“. For this to be true we need now to assume that the consumption set X i {\displaystyle X_{i}}
is convex and the preference relation ≥ i {\displaystyle \geq _{i}}
is continuous. Then, if there exists a consumption vector x i ′ {\displaystyle x’_{i}}
such that x i ′ ∈ X i {\displaystyle x’_{i}\in X_{i}}
and p
⋅ x i ′i x i ∗ {\displaystyle x_{i}>_{i}x_{i}^{*}}
and p
⋅ x i=w i {\displaystyle p\cdot x_{i}=w_{i}}
, and x i {\displaystyle x_{i}}
exists. Then by the convexity of X i {\displaystyle X_{i}}
we have a bundle x i ″=
α x i +
( 1
− α
) x i ′ ∈ X i {\displaystyle x”_{i}=\alpha x_{i}+(1-\alpha
)x’_{i}\in X_{i}} with p
⋅ x i ″i x i ∗ {\displaystyle \alpha x_{i}+(1-\alpha )x’_{i}>_{i}x_{i}^{*}}
. This is a contradiction, because this bundle is preferred to x i ∗ {\displaystyle x_{i}^{*}}
and costs less than w i {\displaystyle w_{i}}
. Hence, for price quasi-equilibria to be price
equilibria it is sufficient that the consumption set be convex, the preference relation to
be continuous, and for there always to exist a “cheaper” consumption bundle x i ′ {\displaystyle x’_{i}}
. One way to ensure the existence of such a bundle is to require wealth levels w i {\displaystyle w_{i}}
to be strictly positive for all consumers i.==Related theorems==
Because of welfare economics’ close ties to social choice theory, Arrow’s impossibility
theorem is sometimes listed as a third fundamental theorem.The ideal conditions of the theorems,
however are an abstraction. The Greenwald-Stiglitz theorem, for example, states that in the presence
of either imperfect information, or incomplete markets, markets are not Pareto efficient.
Thus, in real world economies, the degree of these variations from ideal conditions
must factor into policy choices. Further, even if these ideal conditions hold, the First