It does what it says on the tin, i.e. it provides rigorous proofs of virtually all the main theorems used in applied statistical inference. There is a lengthy appendix on measure theory, and another on probability. While these are very rigorous and thorough, they are of course very concise. Better would be to already have knowledge in these subjects up to around the level of Patrick Billingsley's classic 'Probability and Measure'.
Schervish is a book for people who aspire to have a really thorough and rigorous understanding of mathematical statistics. This is not required for most people. For example, very few academic economists, even those who specialise in things like time series, will have an understanding of the measure theoretic foundations of the subject to anything remotely approaching the level of this book.
Having said that, for aspiring specialists it is an essential. For example, anyone study for a PhD in mathematical statistics should know the material in this book. To find another book that covers the material as extensively and rigorously as Schervish would be hard to find.
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