Book contents
- Frontmatter
- Contents
- Acknowledgments
- List of Contributors
- Introduction
- 1 The ET Interview: Professor Clive Granger
- PART ONE SPECTRAL ANALYSIS
- PART TWO SEASONALITY
- PART THREE NONLINEARITY
- 6 Non-Linear Time Series Modeling
- 7 Using the Correlation Exponent to Decide Whether an Economic Series is Chaotic
- 8 Testing for Neglected Nonlinearity in Time Series Models: A Comparison of Neural Network Methods and Alternative Tests
- 9 Modeling Nonlinear Relationships Between Extended-Memory Variables
- 10 Semiparametric Estimates of the Relation Between Weather and Electricity Sales
- PART FOUR METHODOLOGY
- PART FIVE FORECASTING
- Index
9 - Modeling Nonlinear Relationships Between Extended-Memory Variables
Published online by Cambridge University Press: 06 July 2010
- Frontmatter
- Contents
- Acknowledgments
- List of Contributors
- Introduction
- 1 The ET Interview: Professor Clive Granger
- PART ONE SPECTRAL ANALYSIS
- PART TWO SEASONALITY
- PART THREE NONLINEARITY
- 6 Non-Linear Time Series Modeling
- 7 Using the Correlation Exponent to Decide Whether an Economic Series is Chaotic
- 8 Testing for Neglected Nonlinearity in Time Series Models: A Comparison of Neural Network Methods and Alternative Tests
- 9 Modeling Nonlinear Relationships Between Extended-Memory Variables
- 10 Semiparametric Estimates of the Relation Between Weather and Electricity Sales
- PART FOUR METHODOLOGY
- PART FIVE FORECASTING
- Index
Summary
Many economic variables have a persistence property which may be called extended memory and the relationship between variables may well be nonlinear. This pair of properties allow for many more types of model misspecification than encountered with stationary or short-memory variables and linear relationships, and misspecifications lead to greater modeling difficulties. Examples are given using the idea of a model being balanced.
Alternative definitions of extended memory are considered and a definition based on the properties of optimum forecasts is selected for later use. An important but not necessarily pervasive class of processes are those that are extended-memory but whose changes are short-memory. For this case, called I(1), standard cointegration ideas will apply.
Tests of linearity are discussed in both the I(1) case, where a possible group of tests is easily found, and more generally. Similarly, methods of building nonlinear models based on familiar techniques, such as neural networks and projection pursuit, are briefly considered for I(1) and the more general case. A number of areas requiring further work in this new area are emphasized.
Keywords: Extended memory, nonlinear, integrated processes, balanced equations.
INTRODUCTION
The objective of this paper is to relate the apparently widely held belief that relationships between economic variables are often nonlinear with the empirically observed fact that many macro-economic time series have a smoothness property which, for the moment, will just be called “persistence.”
- Type
- Chapter
- Information
- Essays in EconometricsCollected Papers of Clive W. J. Granger, pp. 230 - 246Publisher: Cambridge University PressPrint publication year: 2001