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Econometrics in Practice de Paul Turner

Econometrics in Practice

Autor Paul Turner
en Limba Engleză Hardback – 17 iun 2021
This book covers the econometric methods necessary for a practicing applied economist or data analyst. This requires both an understanding of statistical theory and how it is used in actual applications. Chapters 1 to 9 present the material concerned with basic statistical theory. Chapters 10 to 13 introduce a number of topics which form the basis of more advanced option modules, such as time series methods in applied econometrics. To get the most out of these topics, companion files include Excel datasets and 4-color figures. It includes pull down menus to graph the data, calculate sample statistics and estimate regression equations. FEATURES:
  • Integration of econometrics methods with statistical foundations
  • Worked examples of all models considered in the text
  • Includes Excel datasheets to facilitate estimation and application of models
  • Features instructor ancillaries for use as a textbook
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Specificații

ISBN-13: 9781683926603
ISBN-10: 1683926609
Pagini: 390
Dimensiuni: 183 x 235 x 27 mm
Greutate: 0.84 kg
Ediția:1. Auflage
Editura: Mercury Learning and Information

Notă biografică

Turner Paul : Paul Turner holds a PhD in economics and has over thirty years of teaching experience at the university level. He has written numerous articles for prestigious international journals and is the author of Modern Macroeconomic Analysis (McGraw-Hill).

Cuprins

1: Probability and the Statistical Foundations of Econometrics
2: Statistical Inference
3: The Bivariate Regression Model
4: The Multivariate Regression Model
5: Serial Correlation
6: Heteroscedasticity, Functional Form, and Structural Breaks
7: Binary Dependent Variables
8: Stochastic Regressors
9: Dynamic Models
10: Time Series Analysis and ARIMA Modelling
11: Unit Roots and Seasonality
12: Cointegration
13: Vector Autoregressions
References
Index

Descriere

Covers the econometric methods necessary for a practicing applied economist or data analyst. This requires both an understanding of statistical theory and how it is used in actual applications. Chapters 1 to 9 present the material concerned with basic statistical theory. Chapters 10 to 13 introduce a number of more advanced topics.