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10 - Longitudinal and Panel Data Models

Published online by Cambridge University Press:  05 June 2012

Edward W. Frees
Affiliation:
University of Wisconsin, Madison
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Summary

Chapter Preview. Longitudinal data, also known as panel data, are composed of a cross-section of subjects that we observe repeatedly over time. Longitudinal data enable us to study cross-sectional and dynamic patterns simultaneously; this chapter describes several techniques for visualizing longitudinal data. Two types of models are introduced, fixed and random effects models. This chapter shows how to estimate fixed effects models using categorical explanatory variables. Estimation for random effects models is deferred to a later chapter; this chapter describes when and how to use these models.

What Are Longitudinal and Panel Data?

In Chapters 1–6, we studied cross-sectional regression techniques that enabled us to predict a dependent variable y using explanatory variables x. For many problems, the best predictor is a value from the preceding period; the times series methods we studied in Chapters 7–9 use the history of a dependent variable for prediction. For example, an actuary seeking to predict insurance claims for a small business will often find that the previous year's claims are the best predictor. However, a limitation of time series methods is that they are based on having available many observations over time (typically 30 or more). When studying annual claims from a business, a long time series is rarely available; either businesses do not have the data, or if they do, it is unreasonable to use the same stochastic model for today's claims as for those 30 years ago.

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Publisher: Cambridge University Press
Print publication year: 2009

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  • Longitudinal and Panel Data Models
  • Edward W. Frees, University of Wisconsin, Madison
  • Book: Regression Modeling with Actuarial and Financial Applications
  • Online publication: 05 June 2012
  • Chapter DOI: https://doi.org/10.1017/CBO9780511814372.011
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  • Longitudinal and Panel Data Models
  • Edward W. Frees, University of Wisconsin, Madison
  • Book: Regression Modeling with Actuarial and Financial Applications
  • Online publication: 05 June 2012
  • Chapter DOI: https://doi.org/10.1017/CBO9780511814372.011
Available formats
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Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

  • Longitudinal and Panel Data Models
  • Edward W. Frees, University of Wisconsin, Madison
  • Book: Regression Modeling with Actuarial and Financial Applications
  • Online publication: 05 June 2012
  • Chapter DOI: https://doi.org/10.1017/CBO9780511814372.011
Available formats
×