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Introduction to Modern Economic Growth
we have the sum over an infinite number of households. However, since endowments
P
∗
are finite, the assumption that ∞
j=0 pj < ∞ ensures that the sums in (5.15) are
indeed finite and the rest of the proof goes through exactly as in the proof of Theorem
5.5.
Ô
Theorem 5.6 will be particularly useful when we discuss overlapping generation
models.
We next briefly discuss the Second Welfare Theorem, which is the converse of
the First Welfare Theorem. It answers the question of whether a Pareto optimal
allocation can be decentralized as a competitive equilibrium. Interestingly, for the
Second Welfare Theorem whether or not H is finite is not important, but we need
to impose much more structure, essentially convexity, for consumption and produc-
tion sets and preferences. This is because the Second Welfare Theorem essentially
involves an existence of equilibrium argument, which runs into problems in the presence of non-convexities. A complete proof of the Second Welfare Theorem utilizes
more advanced tools than those we use in the rest of this book, so we only present
a sketch of the proof of this theorem.
Theorem 5.7. (Second Welfare Theorem) Consider a Pareto optimal allocation (x∗∗ , y∗∗ ) yielding utility allocation {ui∗∗ }i∈H to households. Suppose that all
production and consumption sets are convex and all utility functions {ui (·)}i∈H are
quasi-concave. Then there exists an endowment and share allocation (ω∗∗ , θ ∗∗ ) such
that economy E ≡ (H, F, u, ω ∗∗ , Y, X, θ ∗∗ ) has a competitive equilibrium (x∗∗ , y∗∗ ,p∗∗ ).
Proof. (Sketch) The proof idea goes as follows: we first represent a Pareto