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Unformatted text preview: Second Order Stochastic Dominance Definition Suppose the random variables X and Y have support on [ l, u ]. Then X secondorder stochastically dominates Y if Z a l Pr[ X > t ] dt ≥ Z a l Pr[ Y > t ] dt for all a . Results 1. If X first order stochastically dominates Y , then X secondorder stochastically dom inates Y . Proof. If X first order stochastically dominates Y , then Pr[ X > t ] ≥ Pr[ Y > t ] for all t . Integrating both sides over t gets the desired result. 2. If X secondorder stochastically dominates Y , then E [ X ] ≥ E [ Y ]. Proof. Recall that E [ X ] = l + Z u l [1 F ( t )] dt By second order stochatic dominance, this is greater than E [ Y ] = l + Z u l [1 G ( t )] dt 3. X secondorder stochastically dominates Y if and only if E [ h ( X )] ≥ E [ h ( Y )] for all increasing and concave function h . Proof. Let h ( t ) = t if t ≤ a a if t > a 1 Obviously h is increasing and concave. Now, E [ h ( X )] = Z a l tf ( t ) dt + Z u a af ( t ) dt = [ t (1 F ( t ))]...
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This note was uploaded on 04/01/2008 for the course ECON 3330 taught by Professor Mbiekop during the Spring '08 term at Cornell.
 Spring '08
 MBIEKOP
 Economics

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