To purchase hard copies of this book, please email:
orders@intechopen.com
By only printing on demand InTech ensures our carbon footprint is kept to a minimum.
The data below shows the environmental impact of printing one single book:
16.74 kg wood
0.9 g CO2
15.2 ml Water
Share this page
Advances in Econometrics - Theory and Applications
Edited by Miroslav Verbič, ISBN 978-953-307-503-7, Hard cover, 116 pages, Publisher: InTech, Published: July 27, 2011 under CC BY-NC-SA 3.0 license, in subject Business, Management and Economics
DOI: 10.5772/828
Econometrics is becoming a highly developed and highly mathematicized array of its own sub disciplines, as it should be, as economies are becoming increasingly complex, and scientific economic analyses require progressively thorough knowledge of solid quantitative methods. This book thus provides recent insight on some key issues in econometric theory and applications. The volume first focuses on three recent advances in econometric theory: non-parametric estimation, instrument generating functions, and seasonal volatility models. Additionally, three recent econometric applications are presented: continuous time duration analysis, panel data analysis dealing with endogeneity and selectivity biases, and seemingly unrelated regression analysis. Intended as an electronic edition, providing immediate “open access†to its content, the book is easy to follow and will be of interest to professionals involved in econometrics.
This book is indexed in:
Book contents
- Chapter 1The Limits of Econometrics: Nonparametric Estimation in Hilbert Spaces
- Chapter 2Instrument Generating Function and Analysis of Persistent Economic Times Series: Theory and Application
- Chapter 3Recent Developments in Seasonal Volatility Models
- Chapter 4The Impact of Government-Sponsored Training Programs on the Labor Market Transitions of Disadvantaged Men
- Chapter 5Are Education and Experience Equally Remunerated across Employment Statuses? An Instrumental Variable Approach for Panel Data
- Chapter 6Using the SUR model of tourism demand for neighbouring regions in Sweden and Norway
