Maximum theorem
The maximum theorem provides conditions for the continuity of an optimized function and the set of its maximizers as a parameter changes. The statement was first proven by Claude Berge in 1959.[1] The theorem is primarily used in mathematical economics.
Statement of theorem
Let 
 and 
 be metric spaces, 
 be a function jointly continuous in its two arguments, and 
 be a compact-valued correspondence.
For 
 in 
 and 
 in 
, let
-  
 and 
-  
. 
If 
 is continuous (i.e. both upper and lower hemicontinuous) at some 
, then 
 is continuous at 
 and 
 is non-empty, compact-valued, and upper hemicontinuous at 
.
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, 
 is the parameter space, 
 is the function to be maximized, and 
 gives the constraint set that 
 is maximized over. Then, 
 is the maximized value of the function and 
 is the set of points that maximize 
.
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
The proof relies primarily on the sequential definitions of upper and lower hemicontinuity.
Because 
 is compact-valued and 
 is continuous, the extreme value theorem guarantees the constrained maximum of 
 is well-defined and 
 is non-empty for all 
 in 
. Then, let 
 be a sequence converging to 
 and 
 be a sequence in 
. Since 
 is upper hemicontinuous, there exists a convergent subsequence 
. 
If it is shown that 
, then
which would simultaneously prove the continuity of 
 and the upper hemicontinuity of 
.
Suppose to the contrary that 
, i.e. there exists an 
 such that 
. Because 
 is lower hemicontinuous, there is a further subsequence of 
 such that 
 and 
. By the continuity of 
 and the contradiction hypothesis,
-  
. 
But this implies that for sufficiently large 
,
which would mean 
 is not a maximizer, a contradiction of 
. This establishes the continuity of 
 and the upper hemicontinuity of 
.
Because 
 and 
 is compact, it is sufficient to show 
 is closed-valued for it to be compact-valued. This can be done by contradiction using sequences similar to above.
Variants and generalizations
If in addition to the conditions above, 
 is quasiconcave in 
 for each 
 and 
 is convex-valued, then 
 is also convex-valued. If 
 is strictly quasiconcave in 
 for each 
 and 
 is convex-valued, then 
 is single-valued, and thus is a continuous function rather than a correspondence.
If 
 is concave and 
 has a convex graph, then 
 is concave and 
 is convex-valued. Similarly to above, if 
 is strictly concave, then 
 is a continuous function.[2]
It is also possible to generalize Berge's theorem to non-compact set-valued correspondences if the objective function is K-inf-compact.[3]
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,
-  
 is the space of all bundles of 
 commodities, -  
 represents the price vector of the commodities 
 and the consumer's wealth 
, -  
 is the consumer's utility function, and -  
 is the consumer's budget set. 
Then,
-  
 is the indirect utility function and -  
 is the Marshallian demand. 
Proofs in general equilibrium theory 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
Notes
References
- Claude Berge (1963). Topological Spaces. Oliver and Boyd.
 - Efe Ok (2007). Real analysis with economics applications. Princeton University Press. ISBN 0-691-11768-3.
 - Rangarajan K. Sundaram (1996). A first course in optimization theory. Cambridge University Press. ISBN 978-0-521-49770-1.
 - Feinberg, Eugene A.; Kasyanov, Pavlo O.; Zadoianchuk, Nina V. (January 2013). "Berge’s theorem for noncompact image sets". Journal of Mathematical Analysis and Applications 397 (1): 255–259. doi:10.1016/j.jmaa.2012.07.051.
 

