Case Detail

Case Summary

Practical Regression: Time Series and Autocorrelation

Case Number: 7-112-012, Year Published: 2012

HBS Number: KEL646

Request PreviewBuy

Authors: David Dranove

Key Concepts

Economics, Market Research, Statistical Methods


This is the twelfth in a series of lecture notes which, if tied together into a textbook, might be entitled “Practical Regression.” The purpose of the notes is to supplement the theoretical content of most statistics texts with practical advice based on nearly three decades of experience of the author, combined with over one hundred years of experience of colleagues who have offered guidance. As the title “Practical Regression” suggests, these notes are a guide to performing regression in practice.
This technical note discusses time-series data. The note explains the concept of a time trend and how to capture the trend using regression. Most of the note is devoted to the problem of autocorrelation. The note concludes by discussing the use of leads and lags as predictor variables.

Learning Objectives

Students will learn the following:
-How to detect and control for time trends in regression
-The definition of autocorrelation
-The Durbin-Watson autocorrelation statistic
-How to incorporate autocorrelation into standard regression analysis
-Making predictions with autocorrelated data
-When to use lagged predictor variables and the dangers of using a lagged dependent variable on the right hand side

Number of Pages: 7

Extended Case Information

Teaching Areas: Finance