Acta Math. Hungar., 2009

DOI: 10.1007/s10474-009-8248-1

THE EXISTENCE OF AN INVERSE LIMIT OF AN INVERSE SYSTEM OF MEASURE SPACES  A PURELY MEASURABLE CASE M. PINTÉR∗ Department of Mathematics, Corvinus University of Budapest, Budapest, F®vám tér 1315. H-1093, Hungary e-mail: [email protected]

(Received December 18, 2008; revised May 19, 2009; accepted July 7, 2009)

Abstract. The existence of an inverse limit of an inverse system of (probability) measure spaces has been investigated since the very beginning of the modern probability theory. Results from Kolmogorov [11], Bochner [2], Choksi [6], Metivier [15], Bourbaki [4], Mallory and Sion [12] among others have paved the way of the deep understanding of this problem. All the above results, however, call for some topological concepts, or at least the ones which are closely related topological ones. In this paper we investigate purely measurable inverse systems of (probability) measure spaces, and give a sucient condition for the existence of a unique inverse limit. An example for the considered purely measurable inverse systems of (probability) measure spaces is also given.

1. Introduction The existence of an inverse limit of an inverse system of (probability) measure spaces is an important question in probability theory (see e.g. Kolmogorov [11]), in the theory of stochastic processes (see e.g. Rao [19]), and in some sense surprisingly in game theory. On the eld of game theory, actually on the subeld of games with incomplete information, the investigation of the so called hierarchies of beliefs (see Harsányi [8])  in the language of mathematics: inverse systems of (probability) measure spaces  requires to look into the problem of the existence of an inverse limit (see Mertens and Zamir [13], Brandenburger and Dekel [5], Heifetz [9], Mertens et al. [14], Pintér [18] among others). Therefore, certain ∗ I thank the anonymous referee for the useful suggestions and remarks. Financial support by the Hungarian Scientic Research Fund (OTKA) and the János Bolyai Research Scholarship of the Hungarian Academy of Sciences is gratefully acknowledged. Key words and phrases: purely measurable inverse system of measure spaces, inverse limit, Kolmogorov's Extension Theorem. 2000 Mathematics Subject Classication: 60G05, 60G20.

c 2009 Akadémiai Kiadó, Budapest 02365294/$ 20.00 °

2

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game theoretical research calls for the applications of existence results of an inverse limit. All the previous results on the existence of an inverse limit of an inverse system of measure spaces are  Kolmogorov, Bochner [2], Choksi [6], Metivier [15], Bourbaki [4], Mallory and Sion [12] among others  based on topological or pseudo topological concepts, various compactness concepts. The case of hierarchies of beliefs is, however, a special one, it is quite natural to consider these inverse systems of measure spaces as purely measurable ones (see e.g. Heifetz and Samet [10]). Therefore in order to examine the existence of an inverse limit of an inverse system of measure spaces in the purely measurable framework we need a purely measurable existence result of an inverse limit. The main result of this paper is Theorem 3.2 which provides a purely measurable sucient condition for the existence of a unique inverse limit. Actually, in this paper we introduce the concept of ε-completeness (see Definition 3.1), and show that it is a sucient but not a necessary condition for the existence of a unique inverse limit of an inverse system of (probability) measure spaces. In our opinion, this result is a common generalization of all the previously cited results i.e. those of Kolmogorov, Bochner, Choksi, Metivier, Bourbaki, Mallory and Sion (we discuss it in more detail after Theorem 3.2). The mathematical core of the above discussed game theoretical problem as an example for a class of ε-complete inverse systems of (probability) measure spaces, is also given (Proposition 4.3). The setup of the paper is as follows. In the next section we provide some basic concepts of inverse systems and inverse limits. In Section 3 we present our main result, and Section 4 is about the above mentioned example. In the last section we mention two obvious generalizations.

2. Inverse systems, inverse limits Notation. In this paper we work with probability measures, hence if we do not indicate dierently we mean that every measure is a probability measure. For any set A, {A is the complement of set A, and #A is for the cardinality of set A. For any A j P(X), σ(A) is the coarsest σ -eld which contains A. Let (X, M) and (Y, N ) be arbitrary measurable spaces. Then (X × Y, M ⊗ N ) or briey¡ X ⊗ Y is the measurable space on the set X × Y equipped with the ¢ σ -eld σ {A × B | A ∈ M, B ∈ N } . For any measurable space (X, M) let ∆(X, M) denote the set of the probability measures on (X, M). Acta Mathematica Hungarica, 2009

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INVERSE SYSTEM OF MEASURE SPACES

Let A j P(X) be a set ring, C j A, µ be an additive set function on A. µ is C -regular if for arbitrary A ∈ A and for arbitrary ε > 0, there exists C ∈ C such that C j A and µ(A \ C) < ε. The set system A j P(X) is a σ -compact set system if for any {An } j A, n T T∗ An = ∅ implies that there exists n∗ such that An = ∅. n

n=1

Let (X, M, µ) be an arbitrarily xed measure space. Then the set function µ∗ on P(X) is dened as follows: for all A ∈ P(X), µ∗ (A) $ inf µ(B) AjB∈M

(therefore µ∗ is an outer measure). For any topological space (X, τ ), B(X, τ ) stands for the Borel σ -eld. We say that the measurable spaces (X, M) and (Y, N ) are measurable isomorphic if there is a bijection f between them such that both f and f −1 are measurable. Next, we discuss the basic concepts of inverse systems and inverse limits. Definition 2.1. Let (I, 5) be a preordered set, (Xi )i∈I be a family of nonvoid sets, and fij : Xj → Xi for all i, j ∈ i such that i 5 j . The system ¡ ¢ Xi , (I, 5), fij is an inverse system if it meets the following conditions: (i) fii = idXi , (ii) fik = fij ◦ fjk , for all i, j, k ∈ I such that i 5 j and j 5 k . The inverse system, also called projective system, is a family of sets connected in a certain way. ¡ ¢ Definition 2.2. Let (Xi , Ai , µi ), (I, 5), fij be an inverse system such ¡that for all i ∈ I , (X¢i , Ai , µi ) is a measure space. The inverse system (Xi , Ai , µi ), (I, 5), fij is an inverse system of measure spaces if it meets the following conditions: (i) fij is a Aj -measurable function, (ii) µi = µj ◦ fij−1 , for all i, j ∈ I such that i 5 j . ¡ ¢ Q Definition 2.3. Let Xi , (I, 5), fij be an inverse system, X $ Xi i∈I © ª and P $ x ∈ X | for all i, j such that i 5 j , pri (x) = fij ◦ prj (x) , where for all i ∈ I , pri is the coordinate projection from X to ¡ ¢ Xi . Then P is called the inverse limit of the inverse system Xi , (I, 5), fij , and it is denoted by ¡ ¢ lim Xi , (I, 5), fij . ←− Moreover, let pi $ pri |P , so for all i, j ∈ I such that i 5 j , pi = fij ◦ pj . The inverse limit is a generalization of the Cartesian product. If (I, 5) is such that every element of I is related only to itself, that is for all i, j ∈ I , (i 5 j) ⇒ (i = j), then the inverse limit is the Cartesian product. Acta Mathematica Hungarica, 2009

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¢ (Xi , Ai , µi ), (I, 5), fij be an inverse system of ¡ ¢ measure spaces and P $ lim Xi , (I, 5), fij . Then the measure space ←− (P, ¡ A, µ) is the inverse ¢ limit of the inverse system of measure spaces (Xi , Ai , µi ), (I, 5), fij denoted by Definition 2.4. Let

¡

(P, A, µ) $ lim ((Xi , Ai , µi ), (I, 5), fij |i5j ), ←− if it meets the following conditions: (i) A is the coarsest σ -eld for which the canonical projection pi is measurable for all i ∈ I , (ii) µ is a measure such that µ ◦ p−1 i = µi for all i ∈ I . Kolmogorov's [11] extension theorem is an inverse limit result. It states d the following. Consider a family of nite dimensional distributions ¡ n on nR¢ (d < ∞) such that they are consistent, that is µn dened on R , B(R ) ¡ ¢ is the marginal distribution of µn+1 dened on Rn+1 , B(Rn+1 ) for all n. ¡ ¢ Then there exists a unique distribution µ dened on RN , B(RN ) such that µn is the marginal distribution of µ for all n. This theorem is called Kolmogorov's¡ Extension Theorem. In ¢this case the inverse system of measure spaces is (Rn , B(Rn ), µn ), N, prmn , where prmn : Rn → Rm is the coordinate ¡projection. Therefore, the Kolmogorov's Extension Theorem states that ¢ lim ( Rn , B(Rn ), µn , N, prmn ) exists and is unique. ←− ¡ ¢ S Since if lim Xi , (I, 5), fij 6= ∅ then p−1 i (Ai ) is an algebra (eld), and ←− i S p−1 the set function µ dened on p−1 i (Ai ) by µ ◦ i = µi for all i ∈ I is an i

additive set function, the main problem of the existence of a measure inverse limit is the σ -additivity of µ. Numerous results discuss this existence problem, the most important ones are as follows: Kolmogorov, Bochner [2], Choksi's [6], Metivier's [15], Bourbaki's [4], Mallory and Sion's [12]. In our framework, where the index set is N, Metivier's result is the most general one among the above results. ¡ Theorem 2.5 (Metivier [15], 3.2. Theoreme). Let (Xn , Mn , µn ), N, ¢ fmn be an inverse system of measure spaces.1 If for all m, n ∈ N such that m5n (1) Cn j Mn is a σ -compact set system, (2) fmn is a surjective (onto) function, (3) fmn (Cn ) j Cm , ¡ ¢ −1 {x } ∩ C is a σ -compact set system, (4) for all xm ∈ Xm , fmn m n 1 Metivier's assumptions are weaker, he requires that the measures be non-negative σ -nite measures and the index set have a countable conal subset.

Acta Mathematica Hungarica, 2009

INVERSE SYSTEM OF MEASURE SPACES

(5) for all Ck ∈ Cn , k ∈ N,

T k

5

Ck ∈ Cn ,

(6) µn is Cn -regular, then ¡ ¢ (X, M, µ) $ lim (Xn , Mn , µn ), N, fmn |m5n ←− exists and is unique. Moreover µ is C -regular, where C consists of the sets −1 such that for all C ∈ C , there exists Cn ∈ Cn such that fnn+1 (Cn ) j Cn+1 for all n, and C = lim(Cn , N, fmn ); furthermore C is a σ -compact set system. ←− Notice that in ¡ Kolmogorov's¢ Extension Theorem the inverse system of measure spaces ( Rn , B(Rn ), µn , N, prmn ) meets the conditions of the above theorem.

3. The general result The key notion of this paper is ¡ Definition 3.1. The inverse system of measure spaces (Xn , Mn , µn ), N, ¢ fmn is ε-complete if

(µ∗n

¡

¢ ¡ ¢ −1 fmn (A) = ε) ⇒ µ∗m (A) = ε

for all ε ∈ [0, 1], m, n ∈ N such that m 5 n, and A j Xm . It is a simple calculation to verify that Halmos' [7] example (Exercise (3), pp. 214215) is not an ε-complete inverse system of measure spaces. Furthermore, the reader may wonder whether it is enough to weaken ε-completeness to the case of ε = 0. The answer is no, if we manipulate Halmos' above mentioned example in such a way that the diagonal has 1 − ε measure, and the set of the o diagonal elements has ε measure (we distort Halmos' example by ε). Then we get to a 0-complete inverse system of measure spaces having no inverse limit. A further feature: the ε-completeness is not a necessary condition for the existence of an inverse limit. For this fact see the following inverse system of measure spaces: µµ· ¶ ½ · ¶¾ ¶ ¶ 1 1 (1) 0, , ∅, 0, , δ0 , N, id[0, 1 ) , n+1 n+1 n+1 where δ0 is the Dirac measure concentrated at the point 0. It is easy to verify that (1) is an inverse system of measure spaces and its inverse limit is © ª ({0}, ∅, {0} , δ0 ). However, (1) is not ε-complete. The following theorem is our main result. Acta Mathematica Hungarica, 2009

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M. PINTÉR

¡ ¢ Let (Xn , Mn , µn ), N, fmn be an ε-complete inverse sys¡ ¢ tem of measure spaces. Then (X, M, µ) $ lim (Xn , Mn , µn ), N, fmn exists ←− and is unique. Proof. (1) X $ lim(Xn , N, fmn ) 6= ∅: for all n, let ←− ¡ ¢ −1 Qn $ {x ∈ X0 | f0n {x} = ∅}. Theorem 3.2.

It is clear that Qn j Qn+1 for all n. S From ε-completeness µ∗0 (Qn ) = 0 for all n, hence µ∗0 ( Qn ) = 0, therefore n S S {( Qn ) 6= ∅. Finally, from the denition of {Qn }n , for all x0 ∈ {( Qn ), n

n

there exists x ∈ X such that x0 = p0 (x), where p0 : X → X0 is the canonical projection. S (2) p−1 n (Mn ) is a eld, and µ is an additive set function on it: From (1), S −1 n pn (Mn ) is a eld. n S ˆ ˆ For all A ∈ p−1 n (Mn ), let µ(A) $ µn (A), where n and A ∈ Mn are n

ˆ ˆ ˆ p−1 ˆ such that A = p−1 n (A). Let A ∈ Mm and B ∈ Mm0 be such that m (A) ∗ ∗ ∗ 0 ˆ = p−1 m0 (B). Then there exists n such that n = m and n = m . Then for all ∗ n = n , let ¡ ¢ Q0n $ {x ∈ Xn∗ | fn−1 = ∅}. ∗ n {x} It is clear that Q0n j Q0n+1 for all n = n∗ . S 0 From ε-completeness µ∗n∗ (Q0n ) = 0 for all n = n∗ , therefore µ∗n∗ ( Qn ) n=n∗

= 0. Now

ˆ p−1 m (A)

=

ˆ p−1 m0 (B)

implies that

−1 −1 ˆ ˆ fmn ∗ (A) 4 fm0 n∗ (B) j

[

Q0n ,

n=n∗ −1 ˆ where 4 is for the symmetric dierence. Put it dierently, fnn ∗ (A) 4 ¡ ¢ −1 −1 −1 ˆ ˆ ˆ ˆ ˆ , fm0 n∗ (B) ∈ Mn∗ and µn∗ fmn∗ (A) 4 fm0 n∗ (B) = 0. Then µm (A) = µm0 (B) that is µ is well-dened (unique). By repeating the above reasoning we get that µ is additive. −1 (3) µ is σ -additive: Let {An }n j Mn be sets such that fnn+1 (An ) k An+1 T −1 for all n, and pn (An ) = ∅ (that is, we show that µ is upper σ -continuous n

at ∅). For all n, let

¡ ¢ −1 Ln $ {x ∈ A0 | f0n {x} ∩ An = ∅}. Acta Mathematica Hungarica, 2009

INVERSE SYSTEM OF MEASURE SPACES

7

It is clear that Ln j Ln+1 for all n. −1 Since fnn+1 (An ) k An+1 for all n, therefore −1 −1 f0n (Ln ) j f0n (A0 ) \ An ,

and

¡ −1 ¢ µ∗n f0n (Ln ) 5 µ0 (A0 ) − µn (An )

for all n. ε-completeness implies that

µ∗0 (Ln ) 5 µ0 (A0 ) − µn (An )

© ª for all n. µn (An ) n is a bounded monotone decreasing sequence of real numbers, hence it is convergent. µ0 is a probability measure, thus µ[ ¶ ∗ µ0 Ln = lim µ∗0 (Ln ) 5 µ0 (A0 ) − lim µn (An ). n

n→∞

n→∞

T From the monotonicity of {An }n and that p−1 lim Ln n (An ) = ∅, hence n→∞ n ¡ ¢ S = A0 , µ∗0 ( Ln ) = µ0 (A0 ), moreover, from (2), µ p−1 n (An ) $ µn (An ) for n¡ ¢ all n, thus µ p−1 n (An ) → 0. (4) The extension of µ: From the previous arguments, µ is a probability S measure on the eld p−1 n (Mn ), hence it can be uniquely extended onto n S −1 M $ σ ( pn (Mn )). ¤ n

Remark 3.3. It is worth noticing that the conditions of Metivier's the-

orem (Theorem 2.5) imply the ε-completeness. ¡ −1 ¢ Let n ∈ N and A j Xn be arbitrarily xed, and ε $ µ∗n+1 fnn+1 (A) . −1 Since Mn+1 is a σ -eld, there exists B ∈ Mn+1 such that B j {fnn+1 (A) and µn+1 (B) = 1 − ε. From condition (6) of Theorem 2.5, there exists {Cm }m j Cn+1 such that Cm j B for all m, and lim µn+1 (Cm ) = 1 − ε. m→∞ ¡ ¢ From condition (3) of Theorem 2.5, fnn+1 (Cm ) ∈ Mn and µn fnn+1 (Cm ) −1 −1 = µn+1 (Cm ) for all m. fnn+1 ({A) = {fnn+1 (A), fnn+1 (Cm ) j {A for all m, and lim µn+1 (Cm ) = 1 − ε, hence µn (A) = ε. m→∞

At rst glance it seems that while Theorem 3.2 requires much less than Theorem 2.5, it provides the same result. From the viewpoint of the existence of a unique inverse limit of an inverse system of measure spaces this is true. However, generally we can say only that while all the previous results require more (Theorem 2.5 is included) they also provide more, they state not only that an inverse limit exists and is unique, but they characterize it. Actually, they use their characterizations to prove the existence of an inverse limit. Acta Mathematica Hungarica, 2009

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4. An example First we introduce the measurable structure used in this section. Definition 4.1. Let (X, M) be an arbitrarily xed measurable space, and denote ∆(X, M) the set of the probability measures on it. Then the σ -eld A∗ on ∆(X, M) is dened as follows:

© ª A∗ $ σ ({ µ ∈ ∆(X, M) | µ(A) = p , A ∈ M, p ∈ [0, 1]}). In other words, ∗

A $σ

µ [

pr−1 A

¶ ¢ (B [0, 1] ) , ¡

A∈M

¯ where prA : [0, 1]M ¯ ∆(X,M) → [0, 1]A , [0, 1]A is the A copy of [0, 1]M . The σ -eld A∗ is specially interesting in interactive epistemology. Games with incomplete information are such that the players are uncertain about some parameters of the game (about the description of the game). In such games it is a cardinal question what the players believe about the game, and what the players believe about the other players' beliefs about the game, and so on. Interactive epistemology is on this problem, it deals with the players' beliefs and knowledge. It is usual in the literature that the players' beliefs are modeled by probability measures. In order to talk about the players' beliefs we need sentences like player i believes with at least probability α that event A happens (see e.g. Aumann [1], Heifetz and Samet [10]). This requirement is formalized in Denition 4.1. More precisely, the σ -eld in Denition 4.1 is the weakest σ -eld among those meeting the above requirement. Notice that A∗ is not a xed σ -eld, it depends on the measurable space on which the probability measures are dened. Therefore A∗ is similar to the weak∗ topology which depends on the topology of the base space. Henceforth the non-written σ -elds are the A∗ σ -elds. The following diagram introduces the mathematical problem considered in this section. Although Mertens et al. [14] consider topological spaces, Borel σ -elds, compact regular measures, but our model is purely measurable. The following formalization of the problem is conceptually theirs.

Acta Mathematica Hungarica, 2009

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INVERSE SYSTEM OF MEASURE SPACES

Definition 4.2. In the diagram

Θi

∆(S ⊗ ΘN \{i} )

pin+1

?

?

(2)

\{i} pN n

idS

Θin+1

$

qinn+1

∆(S ⊗

Θin

?

$

)

\{i} qN n−1n

idS ?

?

\{i} ΘN n

∆(S ⊗

?

N \{i} Θn−1

)

• N is an arbitrary non-empty set, • i ∈ N is an arbitrarily element of N , • n ∈ N, • (S, A) is an arbitrary measurable space. Moreover for all j ∈ N , • #Θj−1 = 1, • qj−10 : Θj0 → Θj−1 , N N \{j} • Θn $ Θkn for all n ∈ N ∪ {−1}, k∈N \{j}

• qjmn (µ) $ µ|S⊗ΘN \{j} for all m, n ∈ N such that m 5 n, µ ∈ Θjn , therem−1

fore qjmn is a measurable mapping, ¡ ¢ • Θj $ lim Θjn , N ∪ {−1}, qjmn , ←− • pjn : Θj → Θjn is the canonical projection for all n ∈ N ∪ {−1}, N \{j} • for all m, n ∈ N ∪ {−1} such that m 5 n, qmn is the product of the N \{j} mappings qkmn , k ∈ N \ {j}, and so is pn of pkn , k ∈ N \ {j}, therefore both mappings are measurable, N • ΘN \{j} $ Θk . k∈N \{j}

Some intuitions what the above denition is about: let i be an arbitrary player and (S, A) be the parameter space. The parameter space can be interpreted as the space that contains every parameter of the game (e.g. payos, etc.). Then Θi0 is the space of the so called rst order beliefs of player i, that is, this consists of player i's beliefs about the parameters of the game. We assume that every player knows his/her own beliefs, so does player i, therefore it is enough his/her to focus on the beliefs of the other players. Acta Mathematica Hungarica, 2009

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Then Θi1 is the space of the so called second order beliefs of player i, that is, this consists of player i's beliefs about the other players' beliefs about parameters of the game. In the same way we can interpret Θin as the space of player i's (n + 1)th order beliefs. Finally ΘN consists of all players' all hierarchies of beliefs that is, of all players' arbitrary high order beliefs. Now the goal is to construct an object, the so called type space (see Heifetz and Samet), which consists of the parameters and all the hierarchies of all the players. Moreover it is true that for any player i, and for any probability measure µ on S ⊗ ΘN \{i} there exists θi ∈ Θi such that \{i} pi \{i} S ⊗ ΘN , n+1 (θi )), N ∪ {−1}, (idS , qN (S ⊗ ΘN \{i} , µ) = lim )). n mn ←− ((

An object having the above properties is an ideal one for the considered problem of game theory. The following proposition formalizes the above discussed goal. Since every previous result on this problem  Mertens and Zamir [13], Brandenburger and Dekel [5], Heifetz [9], Mertens et al., Pintér [18] among others  applies topological assumptions and ours does not, the next result is new. Proposition 4.3. Θi = ∆(S ⊗ ΘN \{i} ),

morphic for all i ∈ N .

that is, they are measurable iso-

It is easy to verify that all we need to prove is that for all i ∈ N , θi ∈ Θi , the inverse system of measure spaces (3)

((S ⊗ ΘNn \{i} , pin+1 (θi )), N ∪ {−1}, (idS , qNmn\{i} )) N \{i}

admits a unique inverse limit, where (idS , qmn ) is the product of the given mappings. In order to apply Theorem 3.2 we have to show that the inverse system of measure spaces (3) is ε-complete. Lemma 4.4. The inverse system of measure spaces

((S ⊗ ΘNn \{i} , pin+1 (θi )), N ∪ {−1}, (idS , qNmn\{i} )) is ε-complete, for all i ∈ N , θi ∈ Θi . Proof. We have to show that ³ ³ ´ ´ ¡ ¢ ∗ \{i} −1 pin+2 (θi )∗ (idS , qN (A) = ε ⇒ pin+1 (θi ) (A) = ε ) nn+1 N \{i}

for all i ∈ N , θi ∈ Θi , n ∈ N ∪ {−1}, A j S ⊗ Θn Acta Mathematica Hungarica, 2009

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INVERSE SYSTEM OF MEASURE SPACES

If n = −1 then the proof is obvious. Therefore let n = 0 be arbitrary xed. Moreover, let O (X, M2 ) $ (S ⊗ ΘNn \{j} ) j∈N \{i}

and

(X, M1 ) $ (

−1 N \{j} idS , qn−1n j∈N \{i}

)

µ O

(S ⊗

N \{j} Θn−1

¶ ) .

j∈N \{i} N \{i}

It is clear that M1 j M2 . N \{i} Λ(X, M2 ) $ Θn+1 . N \{i} moreover S ⊗ Θn

Furthermore, let Λ(X, M1 ) $ Θn

It is also clear that Λ(X, Mk ) j [0, 1]

Mk

and

, k = 1, 2,

N \{i} Θn+1

= S ⊗ Λ(X, M1 ) and S ⊗ = S ⊗ Λ(X, M2 ). Furthermore, it is easy to see that the σ -eld of S ⊗ Λ(X, M2 ) is generated ¡ 0 by the semiring of the measurable rectangles having the form C × pr−1 1 (C ) ¯ ¢ ∩ pr−1 (C 00 ) ¯ , where C ∈ A, C 0 ∈ [0, 1]M1 , C 00 ∈ [0, 1]σ(M2 \M1 ) , and 2

Λ(X,M2 )

M2

pr1 : [0, 1] → [0, 1]M1 and pr2 : [0, 1]M2 → [0, 1]σ(M2 \M1 ) are coordinate projections. In other words, since [0, 1]M2 = [0, 1]M1 × [0, 1]M2 \M1 , the σ -eld of N \{i}

S ⊗ Θn+1

is generated by the measurable rectangles having sides of the

three components of S , [0, 1]M1 and [0, 1]M2 \M1 . Let A j S ⊗ Λ(X, M1 ) be an arbitrary set, and {Cn }n j S ⊗ Λ(X, M2 ) be measurable rectangles  that is, there exists Cn0 ∈ A, Cn1 ∈ [0, 1]M1 and ¡ ¢¯ −1 1 2 ¯ Cn2 ∈ [0, 1]σ(M2 \M1 ) such that Cn = Cn0 × pr−1 1 (Cn ) ∩ pr2 (Cn ) Λ(X,M2 ) for S N \{i} −1 all n  such that (idS , qnn+1 ) (A) j Cn . Then it is easy to see that for n

M1

such that Bn j Cn1 and [ [ ¡ ¢¯ \{i} −1 ¯ (B ) j Cn . (idS , qNnn+1 ) (A) j (Cn0 × pr−1 ) n 1 Λ(X,M2 )

all n, there exists Bn ∈ [0, 1]

n

n

In other words, ³ ³ ´ ´ ¡ ¢ ∗ \{i} −1 pin+2 (θi )∗ (idS , qN (A) = ε ⇒ pin+1 (θi ) (A) = ε . ) nn+1

¤

Proof of Proposition 4.3. Lemma 4.4 implies that the inverse system

of measure spaces (3) is ε-complete for all i ∈ N , θi ∈ Θi , so from Theorem 3.2 it has a unique inverse limit. Therefore Θi = ∆(S ⊗ ΘN \{i} ) for all i ∈ N . ¤ Acta Mathematica Hungarica, 2009

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M. PINTÉR

5. Final remarks In our main result (Theorem 3.2) we have assumed that the index set of an inverse system of measure spaces is N. In this section we drop this assumption and consider the case when the index set is an arbitrary right directed set. The main dierence between the two cases (N and an arbitrary right directed set) is that in the former case ε-completeness ensures that the inverse limit is not empty (P 6= ∅), see (1) in the proof of Theorem 3.2. In the general case, however, it can happen that even if the projections in an inverse system are surjective (onto), the inverse limit is empty, see Bourbaki's [3] example, Exercise 7/4, pp. 251252. In the following we provide two such generalizations of Theorem 3.2 where the index set is not necessarily N. The role of the new conditions is to ensure that the inverse limit is not empty. We provide the two generalizations without proofs, since they are direct corollaries of Theorem 3.2. The rst generalization is an obvious one, we recommend that the index set has a countable conal subset, that is, practically (I, 5) = N. ¡ ¢ Theorem 5.1. Let (Xi , Mi , µi ), (I, 5), fij be an inverse system of measure spaces such that it is (1) ε-complete, (2) (I,¡5) has a countable conal ¢ subset. Then lim (Xi , Mi , µi ), (I, 5), fij exists and is unique. ←− For the second generalization we need a notion. In order to ensure that the inverse limit is not empty, Bochner [2] introduced the concept of sequential maximality. Later, Millington and Sion [16] weakened that, and provided the concept of almost sequential maximality. ¡ Definition 5.2. The inverse system of measure spaces (Xi , Mi , µi ), ¢ (I, 5), fij is almost sequentially maximal, if for all chains i1 5 i2 5 · · · ∈ I , there exists Ain j Xin such that for all m, n such that n 5 m, (i) fi−1 (Ain ) j Aim , n im ∗ (ii) µin (Ain ) = 0, ¡ ¢ (iii) xin ∈ (Xin \ Ain ) and xin = fin in+1 (xin+1 ) for all n ⇒ (there exists ¡ ¢ x ∈ lim Xi , (I, 5), fij such that xin = pin (x) for all n). ←− The second generalization is as follows: ¡ ¢ Theorem 5.3. Let (Xi , Mi , µi ), (I, 5), fij be an inverse system of measure spaces such that it is (1) ε-complete, (2) almost sequentially maximal. ¡ ¢ Then lim (Xi , Mi , µi ), (I, 5), fij exists and is unique. ←− Acta Mathematica Hungarica, 2009

INVERSE SYSTEM OF MEASURE SPACES

13

References [1] R. J. Aumann, Interactive epistemology II, Probability, International J. Game Theory, 28 (1999), 301314. [2] S. Bochner, Harmonic Analysis and the Theory of Probability, University of California Press (1955). [3] N. Bourbaki, Elements of Mathematics, Theory of Sets, Hermann (1968). [4] N. Bourbaki, Éléments de Mathématque, Intégration, Livre VI, Chapitre IX, Intégration sur Les Espaces Topologiques Séparés, Hermann (1969). [5] A. Brandenburger and E. Dekel, Hierarchies of beliefs and common knowledge, J. Economic Theory, 59 (1993), 189198. [6] J. R. Choksi, Inverse limits of measure spaces, Proc. London Math. Soc., 8 (Ser 3) (1958), 321342. [7] P. R. Halmos, Measure Theory, Springer-Verlag (1974) [8] J. Harsányi, Games with incomplete information played by bayesian players I, II, III, Management Science, 14 (19671968), 159182, 320334, 486502. [9] A. Heifetz, The bayesian formulation of incomplete information  the non-compact case, International J. Game Theory, 21 (1993), 329338. [10] A. Heifetz and D. Samet, Topology-free typology of beliefs, J. Economic Theory, 82 (1998), 324341. [11] A. N. Kolmogorov, Foundations of the Theory of Probability, Second English Edition, translation edited by Nathan Morrison, Chelsea Publishing Company (1956). [12] D. J. Mallory and M. Sion, Limits of inverse systems of measures, Ann. Inst. Fourier, 21 (1971), 2557. [13] J. F. Mertens and S. Zamir, Formulations of bayesian analysis for games with incomplete informations, International J.Game Theory, 14 (1985), 129. [14] J. F. Mertens, S. Sorin and S. Zamir, Repeated games, part A, CORE Discussion Paper No. 9420 (1994). [15] M. Metivier, Limites projectives de measures, martingales, applications, Annali di Matematica, 63 (1963), 225352. [16] H. Millington and M. Sion, Inverse systems of group-valued measures, Pacic J. Math., 44 (1973), 637650. [17] J. von Neumann and O. Morgenstern, Theory of Games and Economic Behavior, Princeton University Press (1953). [18] M. Pintér, Type space on a purely measurable parameter space, Economic Theory, 26 (2005), 129139. [19] M. M. Rao, Stochastic Processes and Integration, Sijtho and Noordhoof (1979).

Acta Mathematica Hungarica, 2009

the existence of an inverse limit of an inverse system of ...

Key words and phrases: purely measurable inverse system of measure spaces, inverse limit ... For any topological space (X, τ), B(X, τ) stands for the Borel σ- eld.

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