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Blackwell's informativeness theorem 2/2 https://en.wikipedia.org/wiki/Blackwell's_informativeness_theorem reference science, encyclopedia 2026-05-05T14:37:27.550245+00:00 kb-cron

=== Feasibility === A mixed strategy in the context of a decision-making problem is a function

    α
    :
    S
    →
    Δ
    A
  

{\displaystyle \alpha :S\rightarrow \Delta A}

which gives, for every signal

    s
    ∈
    S
  

{\displaystyle s\in S}

, a probability distribution

    α
    (
    a
    
      |
    
    s
    )
  

{\displaystyle \alpha (a|s)}

over possible actions in

    A
  

{\displaystyle A}

. With the information structure

    (
    S
    ,
    σ
    )
  

{\displaystyle (S,\sigma )}

, a strategy

    α
  

{\displaystyle \alpha }

induces a distribution over actions

      α
      
        σ
      
    
    (
    a
    
      |
    
    ω
    )
  

{\displaystyle \alpha _{\sigma }(a|\omega )}

conditional on the state of the world

    ω
  

{\displaystyle \omega }

, given by the mapping

    ω
    ↦
    
      α
      
        σ
      
    
    (
    a
    
      |
    
    ω
    )
    =
    
      ∑
      
        s
        ∈
        S
      
    
    α
    (
    a
    
      |
    
    s
    )
    σ
    (
    s
    
      |
    
    ω
    )
    ∈
    Δ
    A
  

{\displaystyle \omega \mapsto \alpha _{\sigma }(a|\omega )=\sum _{s\in S}\alpha (a|s)\sigma (s|\omega )\in \Delta A}

That is,

      α
      
        σ
      
    
    (
    a
    
      |
    
    ω
    )
  

{\displaystyle \alpha _{\sigma }(a|\omega )}

gives the probability of taking action

    a
    ∈
    A
  

{\displaystyle a\in A}

given that the state of the world is

    ω
    ∈
    Ω
  

{\displaystyle \omega \in \Omega }

under information structure

    (
    S
    ,
    σ
    )
  

{\displaystyle (S,\sigma )}

notice that this is nothing but a convex combination of the

    α
    (
    a
    
      |
    
    s
    )
  

{\displaystyle \alpha (a|s)}

with weights

    σ
    (
    s
    
      |
    
    ω
    )
  

{\displaystyle \sigma (s|\omega )}

. We say that

      α
      
        σ
      
    
    (
    a
    
      |
    
    ω
    )
  

{\displaystyle \alpha _{\sigma }(a|\omega )}

is a feasible strategy (or conditional probability over actions) under

    (
    S
    ,
    σ
    )
  

{\displaystyle (S,\sigma )}

. Given an information structure

    (
    S
    ,
    σ
    )
  

{\displaystyle (S,\sigma )}

, let

      Φ
      
        σ
      
    
    =
    {
    
      α
      
        σ
      
    
    (
    a
    
      |
    
    ω
    )
  

{\displaystyle \Phi _{\sigma }=\{\alpha _{\sigma }(a|\omega )}

|

    α
    :
    S
    →
    Δ
    A
    }
  

{\displaystyle \alpha :S\rightarrow \Delta A\}}

be the set of all conditional probabilities over actions (i.e., strategies) that are feasible under

    (
    S
    ,
    σ
    )
  

{\displaystyle (S,\sigma )}

. Given two information structures

    (
    S
    ,
    σ
    )
  

{\displaystyle (S,\sigma )}

and

    (
    S
    ,
    
      σ
      
    
    )
  

{\displaystyle (S,\sigma ')}

, we say that

    σ
  

{\displaystyle \sigma }

yields a larger set of feasible strategies than

      σ
      
    
  

{\displaystyle \sigma '}

if

      Φ
      
        
          σ
          
        
      
    
    ⊂
    
      Φ
      
        σ
      
    
  

{\displaystyle \Phi _{\sigma '}\subset \Phi _{\sigma }}

== Statement == Blackwell's theorem states that, given two information structures

    σ
  

{\displaystyle \sigma }

and

      σ
      
    
  

{\displaystyle \sigma '}

, the following are equivalent:

    W
    (
    
      σ
      
    
    )
    ≤
    W
    (
    σ
    )
  

{\displaystyle W(\sigma ')\leq W(\sigma )}

for any decision-making problem

    (
    Ω
    ,
    A
    ,
    u
    ,
    p
    )
  

{\displaystyle (\Omega ,A,u,p)}

: that is, the decision maker attains a higher expected utility under

    σ
  

{\displaystyle \sigma }

than under

      σ
      
    
  

{\displaystyle \sigma '}

for any utility function. There exists a stochastic map

    γ
  

{\displaystyle \gamma }

such that

      σ
      
    
    (
    
      s
      
    
    
      |
    
    w
    )
    =
    
      ∑
      
        s
        ∈
        S
      
    
    γ
    (
    s
    ,
    
      s
      
    
    )
    σ
    (
    s
    
      |
    
    w
    )
  

{\displaystyle \sigma '(s'|w)=\sum _{s\in S}\gamma (s,s')\sigma (s|w)}

: that is,

      σ
      
    
  

{\displaystyle \sigma '}

is a garbling of

    σ
  

{\displaystyle \sigma }

.

      Φ
      
        
          σ
          
        
      
    
    ⊂
    
      Φ
      
        σ
      
    
  

{\displaystyle \Phi _{\sigma '}\subset \Phi _{\sigma }}

: that is,

    σ
  

{\displaystyle \sigma }

yields a larger set of feasible strategies than

      σ
      
    
  

{\displaystyle \sigma '}

.

== Blackwell order ==

=== Definition === Blackwell's theorem allows us to construct a partial order over information structures. We say that

    σ
  

{\displaystyle \sigma }

is more informative in the sense of Blackwell (or simply Blackwell more informative) than

      σ
      
    
  

{\displaystyle \sigma '}

if any (and therefore all) of the conditions of Blackwell's theorem holds, and write

      σ
      
    
    
      ⪯
      
        B
      
    
    σ
  

{\displaystyle \sigma '\preceq _{B}\sigma }

. The order

      ⪯
      
        B
      
    
  

{\displaystyle \preceq _{B}}

is not a complete one, and most experiments cannot be ranked by it. More specifically, it is a chain of the partially-ordered set of information structures.

=== Applications === The Blackwell order has many applications in decision theory and economics, in particular in contract theory. For example, if two information structures in a principal-agent model can be ranked in the Blackwell sense, then the more informative one is more efficient in the sense of inducing a smaller cost for second-best implementation.

== References ==