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Econometric Modelling with Time Series (English, Vance Martin | Stan Hurn | David Harris)
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Specifications
| Publisher | Cambridge University Press |
| Language | English |
| ISBN-13 | 9780521196604 |
| ISBN-10 | 0521196604 |
| Author | Vance Martin | Stan Hurn | David Harris |
Product Description
Here on GlowMirror, you'll find Econometric Modelling with Time Series filed under Economics -- everything you need to know is covered below.
About the Book
This book provides a general framework for specifying, estimating, and testing time series econometric models. Special emphasis is given to estimation by maximum likelihood, but other methods are also discussed, including quasi-maximum likelihood estimation, generalized method of moments estimation, nonparametric estimation, and estimation by simulation. An important advantage of adopting the principle of maximum likelihood as the unifying framew…
ISBN: 9780521196604
Book Insights
What You'll Learn
- ·In-depth exploration of topics covered in Econometric Modelling with Time Series
- ·Key concepts explained with clarity and practical examples
- ·Insights valuable for anyone studying or working in Economics
Who Should Read This
Students and professionals interested in Economics, as well as general readers looking to expand their knowledge.
Key Highlights
- ·Brand new physical book delivered across India
- ·15-day hassle-free return policy
Frequently Asked Questions
What is the price of Econometric Modelling with Time Series?
Econometric Modelling with Time Series is available at ₹4,379 on GlowMirror. The original MRP is ₹13,955, saving you 69%.
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GlowMirror offers a 15-day hassle-free return policy for Econometric Modelling with Time Series. Returns are free of charge. Contact us at info@glowmirror.in or call +91 99446 78357 to initiate a return.
Is Econometric Modelling with Time Series available in English?
Econometric Modelling with Time Series is available in English on GlowMirror.
Who is the author of Econometric Modelling with Time Series?
Econometric Modelling with Time Series is authored by Vance Martin | Stan Hurn | David Harris.
Who published Econometric Modelling with Time Series?
Econometric Modelling with Time Series is published by Cambridge University Press.
How many pages does Econometric Modelling with Time Series have?
Page count information for Econometric Modelling with Time Series is available in the specifications section of this page.
How long does it take to read Econometric Modelling with Time Series?
At an average reading speed of 250 words per minute, reading Econometric Modelling with Time Series takes a few hours to a few days depending on reading pace.
What is Econometric Modelling with Time Series about?
About the Book
This book provides a general framework for specifying, estimating, and testing time series econometric models. Special emphasis is given to estimation by maximum likelihood, but other methods are also discussed, including quasi-maximum likelihood estimation, generalized method of mo...
Is Econometric Modelling with Time Series suitable for beginners?
Whether Econometric Modelling with Time Series is suitable for beginners depends on your background in Economics. Review the product description and specifications above for details on the target audience and difficulty level.
What edition is Econometric Modelling with Time Series?
Econometric Modelling with Time Series is from the Cambridge University Press edition/year. Check the specifications section for full edition details.
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To order Econometric Modelling with Time Series on GlowMirror, click the "Add to Cart" button on this page, proceed to checkout, and choose your preferred payment method — online payment or Cash on Delivery. Delivery takes 2–7 business days across India.
Is Econometric Modelling with Time Series a new or used book?
Econometric Modelling with Time Series listed on GlowMirror is a brand new book in good condition.
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Yes, GlowMirror delivers Econometric Modelling with Time Series across India. Use the pincode checker on this page to verify delivery availability to your location.
