Book contents
- Frontmatter
- Contents
- Preface
- User Guide
- 1 Introduction
- PART 1 DESCRIPTION
- PART 2 INFERENCE
- 9 Monte Carlo Simulation
- 10 Review of Statistical Inference
- 11 The Measurement Box Model
- 12 Comparing Two Populations
- 13 The Classical Econometric Model
- 14 The Gauss–Markov Theorem
- 15 Understanding the Standard Error
- 16 Confidence Intervals and Hypothesis Testing
- 17 Joint Hypothesis Testing
- 18 Omitted Variable Bias
- 19 Heteroskedasticity
- 20 Autocorrelation
- 21 Topics in Time Series
- 22 Dummy Dependent Variable Models
- 23 Bootstrap
- 24 Simultaneous Equations
- Glossary
- Index
20 - Autocorrelation
from PART 2 - INFERENCE
Published online by Cambridge University Press: 05 June 2012
Book contents
- Frontmatter
- Contents
- Preface
- User Guide
- 1 Introduction
- PART 1 DESCRIPTION
- PART 2 INFERENCE
- 9 Monte Carlo Simulation
- 10 Review of Statistical Inference
- 11 The Measurement Box Model
- 12 Comparing Two Populations
- 13 The Classical Econometric Model
- 14 The Gauss–Markov Theorem
- 15 Understanding the Standard Error
- 16 Confidence Intervals and Hypothesis Testing
- 17 Joint Hypothesis Testing
- 18 Omitted Variable Bias
- 19 Heteroskedasticity
- 20 Autocorrelation
- 21 Topics in Time Series
- 22 Dummy Dependent Variable Models
- 23 Bootstrap
- 24 Simultaneous Equations
- Glossary
- Index
Summary
A great deal of use has undoubtedly been made of least squares regression methods in circumstances in which they are known to be inapplicable. In particular, they have often been employed for the analysis of time series and similar data in which successive observations are serially correlated.
James Durbin and Geoffrey S. WatsonIntroduction
In this part of the book (Chapters 20 and 21), we discuss issues especially related to the study of economic time series. A time series is a sequence of observations on a variable over time. Macroeconomists generally work with time series (e.g., quarterly observations on GDP and monthly observations on the unemployment rate). Time series econometrics is a huge and complicated subject. Our goal is to introduce you to some of the main issues.
We concentrate in this book on static models. A static model deals with the contemporaneous relationship between a dependent variable and one or more independent variables. A simple example would be a model that relates average cigarette consumption in a given year for a given state to the average real price of cigarettes in that year:
In this model we assume that the price of cigarettes in a given year affects quantity demanded in that year. In many cases, a static model does not adequately capture the relationship between the variables of interest. For example, cigarettes are addictive, and so quantity demanded this year might depend on prices last year.
Information
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- Chapter
- Information
- Introductory EconometricsUsing Monte Carlo Simulation with Microsoft Excel, pp. 558 - 603Publisher: Cambridge University PressPrint publication year: 2005
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