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Let $(\Omega,\mathcal{F},\mathbb{P})$ be a probability space, $\mathcal{G\subseteq F}$ be a sub-$\sigma$-algebra and $X:\Omega\to \mathbb{R}$ be an integrable random variable. Can we conclude that $X$ is $\mathcal{G}$-mensurable if $X=\mathbb{E}[X|\mathcal{G}]$ a.e.?


I don't know if it's true or false, however, according to some arguments in statistics (as you can see in this link, for instance), that proposition should be true.


EDIT: The following is the definition of conditional expectation I'm using.

Let $(\Omega,\mathcal{F},\mathbb{P})$ be a probability space, $\mathcal{G\subseteq F}$ be a sub-$\sigma$-algebra and $X:\Omega\to \mathbb{R}$ be an integrable random variable. We say that $f:\Omega\to \mathbb{R}$ is a conditional expectation of $X$ given $\mathcal{G}$ if the following propositions are true:

  1. $f$ is $\mathcal{G}$-measurable and $\mathbb{P}$-integrable;
  2. $\int _Gfd\mathbb{P}=\int _GXd\mathbb{P}$ for all $G\in\mathcal{G}$.
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  • $\begingroup$ What is your definition of conditional expectation? $\endgroup$ Commented Apr 18 at 19:10
  • $\begingroup$ @JoseAvilez I just wrote the definition in the question! $\endgroup$
    – rfloc
    Commented Apr 18 at 19:18

2 Answers 2

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It follows immediately from condition 1 in your definition that $\mathbb{E}(X | \mathcal{G})$ is $\mathcal{G}$-measurable. In probability theory, one usually assumes that filtrations are complete, so all the null sets in $\mathcal{F}$ are also contained in $\mathcal{G}$. This allows you to modify the conditional expectation on a null set (i.e. pick a version of the conditional expectation) to obtain equality with $X$.

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  • $\begingroup$ But the equality $X=\mathbb{E}[X|\mathcal{G}]$ only happens almost everywhere! $\endgroup$
    – rfloc
    Commented Apr 18 at 19:23
  • $\begingroup$ @rfloc In probability theory it is common to assume that your filtration is complete (i.e. all the measure zero sets in $\mathcal{F}$ are contained in $\mathcal{G}$). If you modify $X$ on a set of measure zero contained in $\mathcal{G}$, you're done. $\endgroup$ Commented Apr 18 at 19:27
  • $\begingroup$ But even in this case we can only conclude that exists $G\in\mathcal{G}$ with $\mathbb{P}(G)=1$ and $X\mathbf{1}_G=\mathbb{E}[X|\mathcal{G}]\mathbf{1}_G$ in every point. So $X\mathbf{1}_G$ is $\mathcal{G}$-measurable. But I don't know if we can conclude from this that $X$ is $\mathcal{G}$-measurable! $\endgroup$
    – rfloc
    Commented Apr 18 at 19:31
  • $\begingroup$ @rfloc Notice that conditional expectations are defined up to a version. So you can just pick the version of the conditional expectation that agrees everywhere with $X$. $\endgroup$ Commented Apr 18 at 20:23
  • $\begingroup$ @BrianMoehring Could you please give me the idea of the proof? $\endgroup$
    – rfloc
    Commented Apr 18 at 20:29
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To expand a little bit, if you assume that all zero sets of $\mathcal F$ are contained in $\mathcal G$ (a pretty normal assumption, as mentioned in the earlier answer), and that the measure is complete, you can make a very direct answer.

Pick any Borel set $B \subset \mathbb R$; further let $S$ be the set where $X$ and $Y = E[X \mid \mathcal G]$ agree. Then $$X^{-1}(B) = \{\omega \in \Omega \mid X(\omega) \in B\} = (X^{-1}(B) \cap S) \cup (X^{-1}(B) \cap S^C).$$ Now $X^{-1}(B) \cap S^C$ is measure $0$ and by assumption in $\mathcal G$. On the other hand, $$X^{-1}(B) \cap S^C = Y^{-1}(B) \cap S^C$$ clearly differs from the $\mathcal G$-measurable set $Y^{-1}(B)$ on a null set, and by completeness is also in $\mathcal G$. So $X^{-1}(B)$ is in $\mathcal G$.

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  • $\begingroup$ In essence, arguments like this are why measure-zero modifications are OK: they're basically the same RV. $\endgroup$
    – daisies
    Commented Apr 18 at 20:36

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