maximum theorem
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The maximum theorem provides conditions for the continuity of an optimized function and the set of its maximizers with respect to its parameters. The statement was first proven by
Claude Berge Claude Jacques Berge (5 June 1926 – 30 June 2002) was a French mathematician, recognized as one of the modern founders of combinatorics and graph theory. Biography and professional history Claude Berge's parents were André Berge and Geneviève ...
in 1959. The theorem is primarily used in mathematical economics and optimal control.


Statement of theorem

Maximum Theorem. Let X and \Theta be topological spaces, f:X\times\Theta\to\mathbb be a continuous function on the
product Product may refer to: Business * Product (business), an item that serves as a solution to a specific consumer problem. * Product (project management), a deliverable or set of deliverables that contribute to a business solution Mathematics * Produ ...
X \times \Theta, and C:\Theta\rightrightarrows X be a compact-valued correspondence such that C(\theta) \ne \emptyset for all \theta \in \Theta. Define the ''marginal function'' (or ''value function'') f^* : \Theta \to \mathbb by :f^*(\theta)=\sup\ and the ''set of maximizers'' C^* : \Theta \rightrightarrows X by : C^*(\theta)= \mathrm\max\ = \ . If C is continuous (i.e. both upper and lower hemicontinuous) at \theta, then f^* is continuous and C^*is upper hemicontinuous with nonempty and compact values. As a consequence, the \sup may be replaced by \max.


Interpretation

The theorem is typically interpreted as providing conditions for a parametric optimization problem to have continuous solutions with regard to the parameter. In this case, \Theta is the parameter space, f(x,\theta) is the function to be maximized, and C(\theta) gives the constraint set that f is maximized over. Then, f^*(\theta) is the maximized value of the function and C^* is the set of points that maximize f. The result is that if the elements of an optimization problem are sufficiently continuous, then some, but not all, of that continuity is preserved in the solutions.


Proof

Throughout this proof we will use the term ''neighborhood'' to refer to an
open set In mathematics, open sets are a generalization of open intervals in the real line. In a metric space (a set along with a distance defined between any two points), open sets are the sets that, with every point , contain all points that are su ...
containing a particular point. We preface with a preliminary lemma, which is a general fact in the calculus of correspondences. Recall that a correspondence is ''closed'' if its
graph Graph may refer to: Mathematics *Graph (discrete mathematics), a structure made of vertices and edges **Graph theory, the study of such graphs and their properties *Graph (topology), a topological space resembling a graph in the sense of discre ...
is closed. Lemma. ''If A, B : \Theta \rightrightarrows X are correspondences, A is upper hemicontinuous and compact-valued, and B is closed, then A \cap B : \Theta \rightrightarrows X defined by (A \cap B) (\theta) = A(\theta) \cap B(\theta) is upper hemicontinuous.'' Let \theta \in \Theta, and suppose G is an open set containing (A\cap B)(\theta). If A(\theta) \subseteq G, then the result follows immediately. Otherwise, observe that for each x \in A(\theta) \setminus G we have x \notin B(\theta), and since B is closed there is a neighborhood U_x \times V_x of (\theta, x) in which x' \notin B(\theta') whenever (\theta', x') \in U_x \times V_x. The collection of sets \ \cup \ forms an open cover of the compact set A(\theta), which allows us to extract a finite subcover G, V_, \dots, V_. By upper hemicontinuity, there is a neighborhood U_\theta of \theta such that A(U_\theta)\subseteq G \cup V_ \cup \dots \cup V_. Then whenever \theta' \in U_\theta\cap U_ \cap \dots \cap U_, we have A(\theta') \subseteq G \cup V_ \cup \dots \cup V_, and so (A \cap B)(\theta') \subseteq G. This completes the proof. \square The continuity of f^* in the maximum theorem is the result of combining two independent theorems together. Theorem 1. ''If f is upper semicontinuous and C is upper hemicontinuous, nonempty and compact-valued, then f^* is upper semicontinuous.'' Fix \theta \in \Theta, and let \varepsilon > 0 be arbitrary. For each x \in C(\theta), there exists a neighborhood U_x \times V_x of (\theta, x) such that whenever (\theta', x') \in U_x \times V_x, we have f(x', \theta') < f(x, \theta) + \varepsilon. The set of neighborhoods \ covers C(\theta), which is compact, so V_, \dots, V_ suffice. Furthermore, since C is upper hemicontinuous, there exists a neighborhood U' of \theta such that whenever \theta' \in U' it follows that C(\theta') \subseteq \bigcup_^ V_. Let U = U' \cap U_ \cap \dots \cap U_. Then for all \theta' \in U, we have f(x', \theta') < f(x_k, \theta) + \varepsilon for each x' \in C(\theta'), as x' \in V_ for some k. It follows that : f^*(\theta') = \sup_ f(x', \theta') < \max_ f(x_k, \theta) + \varepsilon \leq f^*(\theta) + \varepsilon, which was desired. \square Theorem 2. ''If f is lower semicontinuous and C is lower hemicontinuous, then f^* is lower semicontinuous.'' Fix \theta \in \Theta, and let \varepsilon > 0 be arbitrary. By definition of f^*, there exists x \in C(\theta) such that f^*(\theta) < f(x,\theta) + \frac. Now, since f is lower semicontinuous, there exists a neighborhood U_1 \times V of (\theta, x) such that whenever (\theta', x') \in U_1 \times V we have f(x, \theta) < f(x', \theta') + \frac. Observe that C(\theta) \cap V \ne \emptyset (in particular, x \in C(\theta) \cap V). Therefore, since C is lower hemicontinuous, there exists a neighborhood U_2 such that whenever \theta' \in U_2 there exists x' \in C(\theta') \cap V. Let U = U_1 \cap U_2. Then whenever \theta' \in U there exists x' \in C(\theta') \cap V, which implies :f^*(\theta) < f(x, \theta) + \frac < f(x', \theta') + \varepsilon \leq f^*(\theta') + \varepsilon which was desired. \square Under the hypotheses of the Maximum theorem, f^* is continuous. It remains to verify that C^* is an upper hemicontinuous correspondence with compact values. Let \theta \in \Theta. To see that C^*(\theta) is nonempty, observe that the function f_\theta : C(\theta) \to \mathbb by f_\theta(x) = f(x, \theta) is continuous on the compact set C(\theta). The
Extreme Value theorem In calculus, the extreme value theorem states that if a real-valued function f is continuous on the closed interval ,b/math>, then f must attain a maximum and a minimum, each at least once. That is, there exist numbers c and d in ,b/math> su ...
implies that C^*(\theta) is nonempty. In addition, since f_\theta is continuous, it follows that C^*(\theta) a closed subset of the compact set C(\theta), which implies C^*(\theta) is compact. Finally, let D : \Theta \rightrightarrows X be defined by D(\theta) = \. Since f is a continuous function, D is a closed correspondence. Moreover, since C^*(\theta) = C(\theta) \cap D(\theta), the preliminary Lemma implies that C^* is upper hemicontinuous. \square


Variants and generalizations

A natural generalization from the above results gives sufficient ''local'' conditions for f^*to be continuous and C^*to be nonempty, compact-valued, and upper semi-continuous. If in addition to the conditions above, f is quasiconcave in x for each \theta and C is convex-valued, then C^* is also convex-valued. If f is strictly quasiconcave in x for each \theta and C is convex-valued, then C^* is single-valued, and thus is a continuous function rather than a correspondence. If f is
concave Concave or concavity may refer to: Science and technology * Concave lens * Concave mirror Mathematics * Concave function, the negative of a convex function * Concave polygon, a polygon which is not convex * Concave set * The concavity of a ...
and C has a
convex Convex or convexity may refer to: Science and technology * Convex lens, in optics Mathematics * Convex set, containing the whole line segment that joins points ** Convex polygon, a polygon which encloses a convex set of points ** Convex polytop ...
graph, then f^* is concave and C^* is convex-valued. Similarly to above, if f is strictly concave, then C^* is a continuous function. It is also possible to generalize Berge's theorem to non-compact
correspondences Correspondence may refer to: *In general usage, non-concurrent, remote communication between people, including letters, email, newsgroups, Internet forums, blogs. Science * Correspondence principle (physics): quantum physics theories must agree ...
if the objective function is K-inf-compact.Theorem 1.2 in


Examples

Consider a
utility maximization problem Utility maximization was first developed by utilitarian philosophers Jeremy Bentham and John Stuart Mill. In microeconomics, the utility maximization problem is the problem consumers face: "How should I spend my money in order to maximize my u ...
where a consumer makes a choice from their budget set. Translating from the notation above to the standard consumer theory notation, * X=\mathbb_+^l is the space of all bundles of l commodities, * \Theta=\mathbb_^l \times \mathbb_ represents the price vector of the commodities p and the consumer's wealth w, * f(x,\theta)=u(x) is the consumer's
utility function As a topic of economics, utility is used to model worth or value. Its usage has evolved significantly over time. The term was introduced initially as a measure of pleasure or happiness as part of the theory of utilitarianism by moral philosoph ...
, and * C(\theta)=B(p,w)=\ is the consumer's
budget set In economics, a budget set, or the opportunity set facing a consumer, is the set of all possible consumption bundles that the consumer can afford taking as given the prices of commodities available to the consumer and the consumer's income. Let the ...
. Then, * f^*(\theta)=v(p,w) is the
indirect utility function __NOTOC__ In economics, a consumer's indirect utility function v(p, w) gives the consumer's maximal attainable utility when faced with a vector p of goods prices and an amount of income w. It reflects both the consumer's preferences and market con ...
and * C^*(\theta)=x(p,w) is the
Marshallian demand In microeconomics, a consumer's Marshallian demand function (named after Alfred Marshall) is the quantity they demand of a particular good as a function of its price, their income, and the prices of other goods, a more technical exposition of the s ...
. Proofs in general equilibrium theory often apply the Brouwer or
Kakutani fixed-point theorem In mathematical analysis, the Kakutani fixed-point theorem is a fixed-point theorem for set-valued functions. It provides sufficient conditions for a set-valued function defined on a convex set, convex, compact set, compact subset of a Euclidean sp ...
s to the consumer's demand, which require compactness and continuity, and the maximum theorem provides the sufficient conditions to do so.


See also

*
Envelope theorem In mathematics and economics, the envelope theorem is a major result about the differentiability properties of the value function of a parameterized optimization problem. As we change parameters of the objective, the envelope theorem shows that, ...
* Brouwer fixed point theorem * Kakutani fixed point theorem for correspondences


Notes


References

* * * {{Convex analysis and variational analysis Theory of continuous functions Convex optimization Mathematical economics Mathematical optimization Mathematical theorems Theorems in analysis