Uzawa-Equivalence Theorem

I found an interesting section in a nice intermediate textbook on General Equilibrium Theory by Ross M. Starr:




In Section 18.4 titled "Uzawa-Equivalence Theorem" shows the equivalence of two existence theorems:

1. The existence of equilibrium in an economy characterized by a continuous excess demand function fulfilling Walras' Law 
2. The Brouwer Fixed-Point Theorem

Interestingly, the two apparently distinct results are mathematically equivalent, which is originally shown by Hirofumi Uzawa (1962) in his short note: "Walras' Existence Theorem and Brouwer's Fixed Point Theorem." Economic Studies Quarterly, 8: 59-62.

The importance of the theorem is stressed by Prof. Starr as follows:

What are we to make of the Uzawa Equivalence Theorem? It says that use of the Brouwer Fixed-Point Theorem is not merely one way to prove the existence of equilibrium.  In a fundamental sense, it is the only way. Any alternative proof of existence will include, inter alia, an implicit proof of the Brouwer Theorem. Hence, this mathematical method is essential; one cannot pursue this branch of economics without the Brouwer Theorem. If Walras (1874) provided an incomplete proof of existence of equilibrium, it was in part because the necessary mathematics was not yet available.

The paper is included in this volume of Uzawa's collected papers. (I thank Prof. Kawamura for the information.)

Lecture 2 (Dutta): Dynamic Programming 1

Original article (link) posted: 22/09/2005

Topics in the class

1) Conditional Probability and Feller Property
(a) The definitions of a transition function: q and the conditional expectation operator: T.
(b) The properties of Tg (g is a measurable function); measurable, non-negative (if g non-negative), and bounded (if g bounded).
(c) Feller Property.

2) Dynamic Programming Set Up
(d) The def. of a reward function and a feasibility correspondence.
(e) Example; Neo-classical growth model, Portfolio choice, Capital accumulation, Search, and, Price with inertia (menu cost).
(f) The def. of history and policy (action).
(g) Setting up optimization problem and value function.

3) Bellman (Optimality) Equation
(h) Necessity: If the value function V is measurable, then TV=V.
(i) Sufficiency: If the bounded and measurable function U solves U=TU, then U is larger than or equal to V. Additionally if there is a selection from the optimality equation, then U=V. Note) a selection from TU=U is a stationary Markovian policy which solves TU=U.

Comments

Basic concepts in Measure theory such as sigma-algebra and measurability are postulated. I should check what Feller Property exactly means. (I'm not sure if it's just a definition or with necessary and sufficient conditions.)

Reny's new exsistence theorem

In the plenary session on the third day of BWGT conference (link), Professor Philip Reny talked about his new research on monotone pure strategy equilibria:

Title: On the Existence of Monotone Pure Strategy Equilibria in Bayesian Games (link to pdf)

Abstract: We generalize Athey's (2001) and McAdams' (2003) results on the existence of monotone pure strategy equilibria in Bayesian games. We allow action spaces to be compact locally-complete metrizable semilattices and type spaces to be partially ordered probability spaces. Our proof is based upon contractibility rather than convexity of best reply sets. Several examples illustrate the scope of the result, including new applications to multi-unit auctions with risk-averse bidders.

According to Prof. Reny, while the topic of the paper is related to many fields such as mathematical economics, mechanism design, and auctions, there are two seminal papers that strongly motivated his research. Athey (2001) first establishes the sufficient conditions to guarantee the existence of monotone pure strategy equilibria in Bayesian games with one-dimensional and totally ordered type and action spaces. The key condition is a Spence-Mirlees single-crossing property. McAdams (2003) extends Athey's analysis to multi-dimensional and partially ordered spaces.

Prof. Reny succeeded to derive weaker conditions than McAdams in Bayesian games with multi-dimensional strategy spaces, and also extend to the infinite type and action spaces. The key insight is to use a fixed point theorem derived by Eilenberg and Montgomery (1946) instead of Kakutani's (used by Athey) or Glicksberg's (used by McAdams) ones. The latter two theorems require best reply sets to be convex while the former requires only contractibility, which turns out to be (almost) automatically satisfied in Bayesian games.
His main result says the following:

Theorem: (Under some conditions) If, whenever the other players employ monotone pure strategies, each player's set  of monotone pure-strategy best replies is nonempty and join-closed, then a monotone pure strategy equilibrium exists.

Note that a subset of strategies is join-closed if the pointwise supremum of any pair of strategies in the set is also in the set.

The idea of join-closedness (in the different context, though) recently showed up when I discussed my jointwork on the structure of stable matchings with co-authors. It may have some connection...

References
Susan Athey (2001), "Single Crossing Properties and the Existence of Pure Strategy Equilibria in Games of Incomplete Information,"  Econometrica, Vol. 69: 861-889.
Samuel Eilenberg and Deane Montgomery (1946), "Fixed Point Theorems for Multi-Valued Transformations," American Journal of Mathematics, Vol. 68: 214-222.
David McAdams (2003), "Isotone Equilibrium in Games of Incomplete Information," Econometrica, Vol. 71:1191-1214.

Lecture 1 (Dutta): Math Preliminaries

Original article (link) posted: 13/09/2005

The class by professor Dutta started with mathematical preliminaries. It might be good to study those concepts and some theorem again because I left myself unclear of some of them during taking a math class in my first year.
Well, I am thinking to write a brief summary for each week (The class is once every week on Monday). Here is the first one.

Topics in the class

1) Correspondings and Maximum Theorem
2) Contraction Mapping Theorem

What we covered in the class

In (1):
(a) The definitions of correspondings and several versions of continuities: upper semi-continuity (USC), lower semi-continuity (LSC) (and continuity).
(b) Maximum Theorem and its proof. Note) Maximum Theorem says that the maximum value is continuous and the maximizer is USC in parameters under some conditions.

In (2):
(c) The def. of contraction, Cauchy sequences and complete metric space.
(d) Contraction Mapping Theorem and its proof. Note) The theorem says that if there is a contraction corresponding and its domain is a complete metric space, then there exists a unique fixed point.

Comments

(a) I've often mixed up USC and LSC, but finally the difference seems to be clear for me.
(b) I need to reconsider the proof. It's not so complicated but not that easy either.
(c) I realized that I had forgotten the def. of complete metric space...
(d) The proof is much easier than (b). Uniqueness is almost straight forward.

Recommended readings

SLP Chapter 3
Sundaram (1995) "A Course in Optimization Theory"