Contributions to Econometrics: Volume 1

Contributions to Econometrics: Volume 1
Author :
Publisher : CUP Archive
Total Pages : 328
Release :
ISBN-10 : 0521325706
ISBN-13 : 9780521325707
Rating : 4/5 (707 Downloads)

Book Synopsis Contributions to Econometrics: Volume 1 by : John Denis Sargan

Download or read book Contributions to Econometrics: Volume 1 written by John Denis Sargan and published by CUP Archive. This book was released on 1988-06-16 with total page 328 pages. Available in PDF, EPUB and Kindle. Book excerpt:


Contributions to Econometrics: Volume 1 Related Books

Contributions to Econometrics: Volume 1
Language: en
Pages: 328
Authors: John Denis Sargan
Categories: Business & Economics
Type: BOOK - Published: 1988-06-16 - Publisher: CUP Archive

GET EBOOK

Contributions to Econometric Theory and Application
Language: en
Pages: 378
Authors: R.A.L. Carter
Categories: Business & Economics
Type: BOOK - Published: 2012-12-06 - Publisher: Springer Science & Business Media

GET EBOOK

The purpose of this volume is to honour a pioneer in the field of econometrics, A. L. Nagar, on the occasion of his sixtieth birthday. Fourteen econometricians
Advances in Econometrics: Volume 1
Language: en
Pages: 332
Authors: Christopher A. Sims
Categories: Business & Economics
Type: BOOK - Published: 1994-04-21 - Publisher: Cambridge University Press

GET EBOOK

The topics covered in this volume include time series methods, semiparametric methods, seasonality, financial economics, model solution techniques, economic dev
Contributions to Econometrics
Language: en
Pages: 314
Authors: John Denis Sargan
Categories: Business & Economics
Type: BOOK - Published: 1988-06-16 - Publisher: CUP Archive

GET EBOOK

Advances in Econometrics: Volume 2
Language: en
Pages: 434
Authors: Christopher A. Sims
Categories: Business & Economics
Type: BOOK - Published: 1996-03-07 - Publisher: Cambridge University Press

GET EBOOK

This 1994 two-volume set of articles reflects the state of research in theoretical and applied econometrics. The topics covered include time series methods, sem