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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 in 1959. The theorem is primarily used in
mathematical economics Mathematical economics is the application of mathematical methods to represent theories and analyze problems in economics. Often, these applied methods are beyond simple geometry, and may include differential and integral calculus, difference an ...
and
optimal control Optimal control theory is a branch of mathematical optimization that deals with finding a control for a dynamical system over a period of time such that an objective function is optimized. It has numerous applications in science, engineering and ...
.


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 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 In mathematics, the notion of the continuity of functions is not immediately extensible to multivalued mappings or correspondences between two sets ''A'' and ''B''. The dual concepts of upper hemicontinuity and lower hemicontinuity facilitate s ...
) 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 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 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 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 mathematics, a quasiconvex function is a real-valued function defined on an interval or on a convex subset of a real vector space such that the inverse image of any set of the form (-\infty,a) is a convex set. For a function of a single v ...
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 and C has a convex 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 if the objective function is K-inf-compact.Theorem 1.2 in


Examples

Consider a utility maximization problem 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, and * C(\theta)=B(p,w)=\ is the consumer's budget set. Then, * f^*(\theta)=v(p,w) is the indirect utility function and * C^*(\theta)=x(p,w) is the Marshallian demand. Proofs in
general equilibrium theory In economics, general equilibrium theory attempts to explain the behavior of supply, demand, and prices in a whole economy with several or many interacting markets, by seeking to prove that the interaction of demand and supply will result in an ov ...
often apply the Brouwer or Kakutani fixed-point theorems 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 *
Brouwer fixed point theorem Brouwer's fixed-point theorem is a fixed-point theorem in topology, named after L. E. J. (Bertus) Brouwer. It states that for any continuous function f mapping a compact convex set to itself there is a point x_0 such that f(x_0)=x_0. The simplest ...
* 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