Course in econometrics/

By:

Goldberger, Arthur S

Material type: Text

TextPublication details: London: Harvard University Press, 1991.Description: xvii, 405pISBN:

9780674175440

Subject(s):

Econometrics

DDC classification:

330.015195 GOL

Summary: This text prepares first-year graduate students and advanced undergraduates for empirical research in economics, and also equips them for specialization in econometric theory, business, and sociology. A Course in Econometrics is likely to be the text most thoroughly attuned to the needs of your students. Derived from the course taught by Arthur S. Goldberger at the University of Wisconsin–Madison and at Stanford University, it is specifically designed for use over two semesters, offers students the most thorough grounding in introductory statistical inference, and offers a substantial amount of interpretive material. The text brims with insights, strikes a balance between rigor and intuition, and provokes students to form their own critical opinions.

Item type:

Book

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Item type	Current library	Call number	Status	Date due	Barcode
Book	IIM Kashipur	330.015195 GOL (Browse shelf(Opens below))	Available		3783

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Previous	330.015195 END Applied econometric time series/	330.015195 END Applied econometric time series/	330.015195 FAB Basics of financial econometrics: tools, consepts, and asset management applications/	330.015195 GOL Course in econometrics/	330.015195 GOU Financial econometrics: Problems models and methods/	330.015195 GOU Econometrics of individual risk: credit, insurance, and marketing/	330.015195 GRE Econometric analysis/	Next

Includes index.

This text prepares first-year graduate students and advanced undergraduates for empirical research in economics, and also equips them for specialization in econometric theory, business, and sociology.

A Course in Econometrics is likely to be the text most thoroughly attuned to the needs of your students. Derived from the course taught by Arthur S. Goldberger at the University of Wisconsin–Madison and at Stanford University, it is specifically designed for use over two semesters, offers students the most thorough grounding in introductory statistical inference, and offers a substantial amount of interpretive material. The text brims with insights, strikes a balance between rigor and intuition, and provokes students to form their own critical opinions.

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