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## Cointegration and Modelling the Long Run

*Simon Price*

### in Research Strategies in the Social Sciences: A Guide to New Approaches

- Published in print:
- 1998
- Published Online:
- November 2003
- ISBN:
- 9780198292371
- eISBN:
- 9780191600159
- Item type:
- chapter

- Publisher:
- Oxford University Press
- DOI:
- 10.1093/0198292376.003.0008
- Subject:
- Political Science, Reference

Extending the regression model to the analysis of non‐stationary, or trended, data. The examples demonstrate the application of unit root methodology, Engle‐Granger co‐integration procedures, and ... More

## Dynamic Econometrics

*David F. Hendry*

- Published in print:
- 1995
- Published Online:
- November 2003
- ISBN:
- 9780198283164
- eISBN:
- 9780191596384
- Item type:
- book

- Publisher:
- Oxford University Press
- DOI:
- 10.1093/0198283164.001.0001
- Subject:
- Economics and Finance, Econometrics

This systematic and integrated framework for econometric modelling is organized in terms of three levels of knowledge: probability, estimation, and modelling. All necessary concepts of econometrics ... More

## Co-integration, Error Correction, and the Econometric Analysis of Non-Stationary Data

*Anindya Banerjee, Juan J. Dolado, John W. Galbraith, and David Hendry*

- Published in print:
- 1993
- Published Online:
- November 2003
- ISBN:
- 9780198288107
- eISBN:
- 9780191595899
- Item type:
- book

- Publisher:
- Oxford University Press
- DOI:
- 10.1093/0198288107.001.0001
- Subject:
- Economics and Finance, Econometrics

This book considers the econometric analysis of both stationary and non‐stationary processes, which may be linked by equilibrium relationships. It provides a wide‐ranging account of the main tools, ... More

## Machine Learning in Non-Stationary Environments: Introduction to Covariate Shift Adaptation

*Masashi Sugiyama and Motoaki Kawanabe*

- Published in print:
- 2012
- Published Online:
- September 2013
- ISBN:
- 9780262017091
- eISBN:
- 9780262301220
- Item type:
- book

- Publisher:
- The MIT Press
- DOI:
- 10.7551/mitpress/9780262017091.001.0001
- Subject:
- Computer Science, Machine Learning

As the power of computing has grown over the past few decades, the field of machine learning has advanced rapidly in both theory and practice. Machine learning methods are usually based on the ... More

## Consumption and Permanent Income

*Angus Deaton*

### in Understanding Consumption

- Published in print:
- 1992
- Published Online:
- November 2003
- ISBN:
- 9780198288244
- eISBN:
- 9780191596131
- Item type:
- chapter

- Publisher:
- Oxford University Press
- DOI:
- 10.1093/0198288247.003.0003
- Subject:
- Economics and Finance, Macro- and Monetary Economics

Discusses the permanent income hypothesis and the mechanisms by which consumption smoothing responds to short‐run changes in income. It also reviews the role played by income and expectations in ... More

## The Volatility of Consumption

*Angus Deaton*

### in Understanding Consumption

- Published in print:
- 1992
- Published Online:
- November 2003
- ISBN:
- 9780198288244
- eISBN:
- 9780191596131
- Item type:
- chapter

- Publisher:
- Oxford University Press
- DOI:
- 10.1093/0198288247.003.0004
- Subject:
- Economics and Finance, Macro- and Monetary Economics

Develops the themes of Ch. 3 by exploring how consumption responds to innovations in income. The focus is on the econometric enquiry and presents insights into how measured income differs from ... More

## Bayesian Discrimination

*Michio Hatanaka*

### in Time-Series-Based Econometrics: Unit Roots and Co-integrations

- Published in print:
- 1996
- Published Online:
- November 2003
- ISBN:
- 9780198773535
- eISBN:
- 9780191596360
- Item type:
- chapter

- Publisher:
- Oxford University Press
- DOI:
- 10.1093/0198773536.003.0010
- Subject:
- Economics and Finance, Econometrics

This chapter reviews Bayesian studies of the unit root. It identifies three different categories of discrimination that have emerged in Bayesian unit-root literature, where stationarity is ... More

## On the Time‐Series Approach to Econometric Model Building

*David F. Hendry*

### in Econometrics: Alchemy or Science?: Essays in Econometric Methodology

- Published in print:
- 2000
- Published Online:
- November 2003
- ISBN:
- 9780198293545
- eISBN:
- 9780191596391
- Item type:
- chapter

- Publisher:
- Oxford University Press
- DOI:
- 10.1093/0198293542.003.0006
- Subject:
- Economics and Finance, Econometrics

The ‘time‐series’ approach to econometrics is critically evaluated, and analytical test power response surfaces presented. Non‐stationarity, differencing and ‘error‐correction’ models (though not yet ... More

## Econometric Tools and Techniques

*David F. Hendry*

### in Dynamic Econometrics

- Published in print:
- 1995
- Published Online:
- November 2003
- ISBN:
- 9780198283164
- eISBN:
- 9780191596384
- Item type:
- chapter

- Publisher:
- Oxford University Press
- DOI:
- 10.1093/0198283164.003.0003
- Subject:
- Economics and Finance, Econometrics

Least squares and recursive methods for estimating the values of unknown parameters and the logic of testing in empirical modelling, are discussed. The tools needed for investigating the properties ... More

## Properties of Integrated Processes

*Anindya Banerjee, Juan J. Dolado, John W. Galbraith, and David F. Hendry*

### in Co-integration, Error Correction, and the Econometric Analysis of Non-Stationary Data

- Published in print:
- 1993
- Published Online:
- November 2003
- ISBN:
- 9780198288107
- eISBN:
- 9780191595899
- Item type:
- chapter

- Publisher:
- Oxford University Press
- DOI:
- 10.1093/0198288107.003.0003
- Subject:
- Economics and Finance, Econometrics

Presents the important properties of integrated variables and sets out some of the preliminary asymptotic theories essential for the consideration of such processes. It explores the concepts of unit ... More

## Modelling Multivariate Counts Varying Continuously in Space *

*Alexandra M. Schmidt and Marco A. Rodríguez*

### in Bayesian Statistics 9

- Published in print:
- 2011
- Published Online:
- January 2012
- ISBN:
- 9780199694587
- eISBN:
- 9780191731921
- Item type:
- chapter

- Publisher:
- Oxford University Press
- DOI:
- 10.1093/acprof:oso/9780199694587.003.0020
- Subject:
- Mathematics, Probability / Statistics

We discuss models for multivariate counts observed at fixed spatial locations of a region of interest. Our approach is based on a continuous mixture of independent Poisson distributions. The mixing ... More

## 1 Concepts, models, and definitions

*Timo Teräsvirta, Dag Tjøstheim, and W. J. Granger*

### in Modelling Nonlinear Economic Time Series

- Published in print:
- 2010
- Published Online:
- May 2011
- ISBN:
- 9780199587148
- eISBN:
- 9780191595387
- Item type:
- chapter

- Publisher:
- Oxford University Press
- DOI:
- 10.1093/acprof:oso/9780199587148.003.0001
- Subject:
- Economics and Finance, Econometrics

This chapter gives a brief overview of the basic concepts and topics used in the book. There exists a large literature on linear stationary models. The purpose of the present book is to look at ... More

## Selecting Forecasting Models

*David F. Hendry*

### in Empirical Model Discovery and Theory Evaluation: Automatic Selection Methods in Econometrics

- Published in print:
- 2014
- Published Online:
- January 2015
- ISBN:
- 9780262028356
- eISBN:
- 9780262324410
- Item type:
- chapter

- Publisher:
- The MIT Press
- DOI:
- 10.7551/mitpress/9780262028356.003.0023
- Subject:
- Economics and Finance, Econometrics

Forecasting is different: the past is fixed, but the future is not. Practical forecasting methods rely on extrapolating presently available information into the future. No matter how good such ... More

## Introduction to Linear Time Series Models

*Jeffrey S. Racine*

### in Reproducible Econometrics Using R

- Published in print:
- 2019
- Published Online:
- January 2019
- ISBN:
- 9780190900663
- eISBN:
- 9780190933647
- Item type:
- chapter

- Publisher:
- Oxford University Press
- DOI:
- 10.1093/oso/9780190900663.003.0001
- Subject:
- Economics and Finance, Econometrics

This chapter introduces time series data and outlines how it differs from cross sectional data. It also highlights how the object of interest when modelling time series data is the forecast, which ... More

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