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Contents
Table of Contents
Book Order Form
Table of Contents
Part I: Prologue
1. Introduction to Volume III
1.1 The PcGive system
1.2 Citation
1.3 World Wide Web
Part II: Limited Dependent Models (LogitJD)
2. Discrete choice models
2.1 Introduction
2.2 Binary discrete choice
2.3 The binary logit and probit model
2.4 Multinominal discrete choice
2.5 Evaluation
2.6 Histograms
2.7 Norm observations
2.8 Observed versus predicted
2.9 Outlier analysis
3. Tutorial on Discrete Choice Modelling
6.1 Introduction
6.2 Data organization
6.3 Binary logit estimation
6.4 Binary probit estimation
6.5 Grouped logit estimation
6.6 Multinomial logit estimation
6.7 Conditional logit estimation
Part III: Panel Data Models (DPD) (with Manuel Arellano and Stephen Bond)
4. Panel Data Models
4.1 Introduction
4.2 Econometric methods for static panel data models
4.3 Econometric methods for dynamic panel data models
5. Tutorial on Static Panel Data Modelling
5.1 Introduction
5.2 Data organization
5.3 Static panel data estimation
6. Tutorial on Dynamic Panel Data Modelling
6.1 Introduction
6.2 Data organization
6.3 One-step GMM estimation
6.4 Two-step GMM estimation
6.5 IV estimation
6.6 Combined GMM estimation
7. Panel Data Implementation Details
7.1 Transformations
7.2 Static panel-data estimation
7.3 Dynamic panel data estimation
7.4 Dynamic panel data, combined estimation
7.5 Panel batch commands
Part IV: Volatility Models (GARCH) (with H. Peter Boswijk and Marius Ooms)
8. Introduction to Volatility Models (GARCH)
8.1 Introduction
9. Tutorial on GARCH Modelling
9.1 Estimating a GARCH(1,1) model
9.2 Evaluating the GARCH(1,1) model
9.3 Recursive estimation of the GARCH(1,1) model
9.4 GARCH(1,1) with regressors in the variance equation
9.5 GARCH(1,1) with Student t-distributed errors
9.6 EGARCH(1,1) GED-distributed errors
9.7 GARCH in mean
9.8 Asymmetric threshold GARCH
9.9 GARCH batch usage
10. GARCH Implementation Details
10.1 GARCH model settings
10.2 Some implementation details
10.3 GARCH batch commands
Part V: Time Series Models (ARFIMA) (with Marius Ooms)
11. Introduction to Time Series Models (ARFIMA)
12. Tutorial on ARFIMA Modelling
13. ARFIMA Implementation Details
13.1 Introduction
13.2 The Arfima model
13.3 Estimation
13.4 Estimation output
13.5 Estimation options
13.6 Forecasting
13.7 ARFIMA batch commands
Part VI: Regime Switching Models (Switching)
14 Regime Switching Models
14.1 Introduction
14.2 Markov-switching models
15 Tutorial on Regime Switching Modelling
15.1 Estimating a 2-regime MS dynamic regression model, 1985(1)-2009(1)
15.2 Estimating an MS-DR(2) model, 1948(2)-1984(4)
15.3 MS-DR(3) model with switching variance, 1948(2)-2009(1)
15.4 Estimating an MS-AR model: replicating Hamilton's estimates
16 Regime Switching Implementation Detalils
16.1 Switching mdel settings
16.2 Regime Switching bath commands
Part VII: X12arima for OxMetrics
17. Overview of X12arima for Oxmetrics
17.1 Introduction
17.2 X-12-ARIMA
17.3 Credits
17.4 Disclaimer
17.5 Limitations
17.6 Documentation
17.7 Census X-11 Seasonal Adjustment
17.8 X-12-ARIMA Seasonal Adjustment
17.9 regARIMA
17.10 X12arima menu commands
18. Tutorial on Seasonal Adjustment with X12arima for Oxmetrics
18.1 Introduction
18.2 Batch usage
19. Tutorial on ARIMA Modelling with X12arima for Oxmetrics
19.1 Introduction
19.2 regARIMA Model Example
20. Batch Usage
20.1 Additional Batch Commands
20.2 Specification Syntax, Additions and Differences
References
Author Index
Subject Index
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