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Introduction to Time Series Analysis
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Comment from the Stata technical group
Introduction to Time Series Analysis is a concise book that provides an intuitive, but deep, discussion of many methods currently used for estimation and inference in time-series modeling. A nice mix of intuition, formulas, graphs, causal diagrams, and empirical examples are used to explain each topic covered. While there is no output in the text, the Stata code used to produce many of the examples in the book are available here.
After describing what time series are and explaining why they need special techniques, the book progresses through models and estimators that become increasingly dynamic. Most of the book covers models for stationary processes, but the last chapter provides a sound introduction to models and estimators for integrated and cointegrated processes.
This book is an excellent introduction to time-series analysis for students and researchers who have limited experience in the area.
Table of contents
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Series Editor's Introduction
About the Author
1. Thinking Time-Serially
2. Fundamental Concepts in Time Series Analysis
3. Static Time Series Models and Ordinary Least Squares Estimation
4. Introducing Dynamic Time Series Models
5. Autoregressive Moving Average Models
6. Models for Integrated and Cointegrated Data
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Last updated: 16 November 2022
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