Contents

pp ix-xii

Acknowledgments

pp xiii-xvi

List of Contributors

pp xvii-xx

Introduction

pp 1-27

1 - The ET Interview: Professor Clive Granger

pp 28-82

PART ONE - SPECTRAL ANALYSIS

pp 83-84

2 - Spectral Analysis of New York Stock Market Prices

pp 85-105

3 - The Typical Spectral Shape of an Economic Variable

pp 106-118

PART TWO - SEASONALITY

pp 119-120

4 - Seasonality: Causation, Interpretation and Implications

pp 121-146

5 - Is Seasonal Adjustment a Linear or Nonlinear Data-Filtering Process?

pp 147-174

PART THREE - NONLINEARITY

pp 175-176

6 - Non-Linear Time Series Modeling

pp 177-187

7 - Using the Correlation Exponent to Decide Whether an Economic Series is Chaotic

pp 188-207

8 - Testing for Neglected Nonlinearity in Time Series Models: A Comparison of Neural Network Methods and Alternative Tests

pp 208-229

9 - Modeling Nonlinear Relationships Between Extended-Memory Variables

pp 230-246

10 - Semiparametric Estimates of the Relation Between Weather and Electricity Sales

pp 247-270

PART FOUR - METHODOLOGY

pp 271-272

11 - Time Series Modeling and Interpretation

pp 273-288

12 - On the Invertibility of Time Series Models

pp 289-295

13 - Near Normality and Some Econometric Models

pp 296-301

14 - The Time Series Approach to Econometric Model Building

pp 302-316

15 - Comments on the Evaluation of Policy Models

pp 317-335

16 - Implications of Aggregation with Common Factors

pp 336-352

PART FIVE - FORECASTING

pp 353-354

17 - Estimating the Probability of Flooding on a Tidal River

pp 355-365

18 - Prediction with a Generalized Cost of Error Function

pp 366-374

19 - Some Comments on the Evaluation of Economic Forecasts

pp 375-390

20 - The Combination of Forecasts

pp 391-410