Panel Data Analysis: A Non-technical Introduction for Marketing Researchers

Arnd Vomberg () and Simone Wies ()
Additional contact information
Arnd Vomberg: University of Groningen
Simone Wies: Goethe University Frankfurt

A chapter in Handbook of Market Research, 2022, pp 411-467 from Springer

Abstract: Abstract The analysis of panel data is now part of the standard repertoire of marketers and marketing researchers. Compared to the analysis of cross-sectional data, panel data allow marketers to alleviate endogeneity concerns when linking an independent variable (e.g., price) to an outcome variable (e.g., sales volume). The more accurate estimates that result from panel data analysis help improve marketers’ decision-making in focal areas such as price setting and marketing budget allocation. Besides, panel data allow marketers to track customer behavior changes and distinguish real loyalty effects (i.e., same customer repeatedly buys a brand) from spurious effects (i.e., the same number of, but each time different set of, customers buys a brand). This chapter provides a nontechnical introduction to panel data analysis. Marketers will learn how to manage and analyze panel datasets in Stata. They will learn about the focal panel data estimators (pooled OLS, fixed effects, and random effects estimator), their underlying assumptions, advantages, and pitfalls. Besides, we introduce the between effects estimator, the combined approach, the Hausman-Taylor approach, and the first differences estimator as further techniques to analyze panel data. Finally, readers will receive an introduction to advanced topics such as dynamic panel models, panel data multilevel modeling, and using panel data to address measurement errors.

Keywords: Cluster-robust standard errors; Dynamic panel data models; Endogeneity; Fixed effects estimator; Hausman test; Hausman-Taylor method; Measurement error; Omitted variable bias; Panel data analysis; Pooled OLS; Random effects estimator; Serial correlation (search for similar items in EconPapers)
Date: 2022
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-319-57413-4_19

Ordering information: This item can be ordered from
http://www.springer.com/9783319574134

DOI: 10.1007/978-3-319-57413-4_19

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().