Show that if \(f\left(x_{1}, x_{2}\right)\) is a concave function then it is also a quasi-concave function. Do this by comparing Equation 2.114 (defining quasi-concavity) with Equation 2.98 (defining concavity). Can you give an intuitive reason for this result? Is the converse of the statement true? Are quasi-concave functions necessarily concave? If not, give a counterexample.

Short Answer

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Question: Prove that a concave function is also a quasi-concave function. Answer: To prove that a concave function is also a quasi-concave function, we need to show that if function \(f\) is concave, it also satisfies the definition of a quasi-concave function. Since, for any two points \(x\) and \(y\) and for any scalar \(\alpha \in [0,1]\), a concave function \(f\) satisfies: $$ f(\alpha x + (1-\alpha) y) \ge \alpha f(x) + (1-\alpha) f(y) $$ We can see that for any \(x, y\) and \(\alpha \in [0,1]\), if \(f(x) \le f(y)\), then $$ f(\alpha x + (1-\alpha) y) \ge f(x) $$ and if \(f(x) > f(y)\), then $$ f(\alpha x + (1-\alpha) y) \ge f(y) $$ In both cases, we have that $$ f(\alpha x + (1-\alpha) y) \ge \min\{f(x), f(y)\} $$ meaning that \(f\) is also quasi-concave.

Step by step solution

01

Definition of Concave Function

A function \(f\left(x_{1}, x_{2}\right)\) is said to be concave if, for any two points \(x\) and \(y\) and for any scalar \(\alpha \in [0,1]\): $$ f(\alpha x + (1-\alpha) y) \ge \alpha f(x) + (1-\alpha) f(y) $$
02

Definition of Quasi-Concave Function

A function \(f\left(x_{1}, x_{2}\right)\) is said to be quasi-concave if, for any two points \(x\) and \(y\) and for any scalar \(\alpha \in [0,1]\): $$ f(\alpha x + (1-\alpha) y) \ge \min\{f(x), f(y)\} $$ Now, let's prove the given statement.
03

Comparing Concave with Quasi-Concave Definition

Suppose \(f\) is a concave function, then for any \(x, y\) and \(\alpha \in [0,1]\), $$ f(\alpha x + (1-\alpha) y) \ge \alpha f(x) + (1-\alpha) f(y) $$ Now, we want to show that \(f(\alpha x + (1-\alpha) y)\) is at least as big as the minimum of \(f(x)\) and \(f(y)\). Consider the two cases below: 1. If \(f(x) \le f(y)\), then $$ \alpha f(x) + (1-\alpha) f(y) \ge \alpha f(x) + (1-\alpha) f(x) = f(x) \Rightarrow f(\alpha x + (1-\alpha) y) \ge f(x) $$ 2. If \(f(x) > f(y)\), then $$ \alpha f(x) + (1-\alpha) f(y) \ge \alpha f(y) + (1-\alpha) f(y) = f(y) \Rightarrow f(\alpha x + (1-\alpha) y) \ge f(y) $$ In both cases, we have that \(f(\alpha x + (1-\alpha) y) \ge \min\{f(x), f(y)\}\), meaning that \(f\) is also quasi-concave.
04

Intuitive Reason

Intuitively, this result suggests that concave functions are a special case of quasi-concave functions where not only do they fulfill the quasi-concavity requirement, but are also "more concave" due to following the stricter condition posed by concavity.
05

Converse Statement

The converse is not always true. Quasi-concave functions are not necessarily concave. A counterexample is the function \(f(x) = x^3\), which we illustrate in the following steps: 1. \(f(x) = x^3\) is quasi-concave because for any \(x, y\) and \(\alpha \in [0,1]\): $$ f(\alpha x + (1-\alpha) y) = (\alpha x + (1-\alpha) y)^3 \ge \min\{x^3, y^3\} = \min\{f(x), f(y)\} $$ 2. However, \(f(x) = x^3\) is not concave because its second derivative \(f''(x) = 6x\) is positive for \(x>0\), which violates the condition for concavity (a concave function should have a non-positive second derivative). In conclusion, a concave function is always quasi-concave, but a quasi-concave function is not necessarily concave.

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