Applied economic forecasting using time series methods /
Economic forecasting is a key ingredient of decision making both in the public and in the private sector. Because economic outcomes are the result of a vast, complex, dynamic and stochastic system, forecasting is very difficult and forecast errors are unavoidable. Because forecast precision and reli...
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| Main Authors: | , |
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| Format: | Book |
| Language: | English |
| Published: |
New York, NY :
Oxford University Press,
[2018]
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| Subjects: |
Table of Contents:
- PART I: Forecasting with the Linear Regression Model. Chapter 1 -The Baseline Linear Regression Model. Chapter 2
- Model Mis-Specification. Chapter 3
- The Dynamic Linear Regression Model. Chapter 4
- Forecast Evaluation and Combination. PART II: Forecasting with Time Series Models. Chapter 5
- Univariate Time Series Models. Chapter 6
- VAR Models. Chapter 7
- Error Correction Models. Chapter 8
- Bayesian VAR Models. PART III: TAR, Markov Switching and State Space Models. Chapter 9
- TAR and STAR Models. Chapter 10
- Markov Switching Models. Chapter 11
- State Space Models and the Kalman Filter. PART IV: Mixed Frequency, Large Datasets and Volatility. Chapter 12
- Models for Mixed Frequency Data. Chapter 13
- Models for Large Datasets. Chapter 14
- Forecasting Volatility.
