In recent weeks I've had several people email to ask if I can recommend a book that goes into all of the details about the "Seemingly Unrelated Regression Equations" (SURE, or just SUR) model.
Any decent econometrics text discusses this model, of course. However, the treatment usually focuses on the asymptotic properties of the standard estimators - iterated feasible GLS, or MLE.
This is fine, but what about things like:
- A comprehensive treatment of the finie-sample properties of these estimators.
- A rigorous treatment of the "unbalanced sample" situation.
- Extending the model to allow for heteroskedastic errors.
- Stein-rule and ridge regression versions of the SURE model.
- etc., etc.
To the best of my knowledge the only monograph that is devoted entirely to a comprehensive discussion of the SURE model is one that my late friend an colleague, Viren Srivastava, and I published in 1987.
That book is V. K Srivastava and D. E. A. Giles, Seemingly Unrelated Regression Equations Models: Estimation and Inference (Marcel Dekker, New York). Marcel Dekker subsequently became part of Chapman & Hall/CRC Press.
At the risk of unashamed self-promotion (!), it's a book that I still recommend quite frequently.
There's quite a story relating to the actual writing of this book with Viren - but more on that, perhaps, in a subsequent post.
© 2012, David E. Giles