TY - JOUR
T1 - Limitations of Fixed-Effects Models for Panel Data
AU - Hill, Terrence D.
AU - Davis, Andrew P.
AU - Roos, J. Micah
AU - French, Michael T.
N1 - Funding Information:
The authors thank Alfred DeMaris, Michael McFarland, and Amy Burdette for valuable comments on previous drafts. However, we take full responsibility for the final content of our submission. The author(s) received no financial support for the research, authorship, and/or publication of this article.
Publisher Copyright:
© The Author(s) 2019.
PY - 2020/6/1
Y1 - 2020/6/1
N2 - Although fixed-effects models for panel data are now widely recognized as powerful tools for longitudinal data analysis, the limitations of these models are not well known. We provide a critical discussion of 12 limitations, including a culture of omission, low statistical power, limited external validity, restricted time periods, measurement error, time invariance, undefined variables, unobserved heterogeneity, erroneous causal inferences, imprecise interpretations of coefficients, imprudent comparisons with cross-sectional models, and questionable contributions vis-à-vis previous work. Instead of discouraging the use of fixed-effects models, we encourage more critical applications of this rigorous and promising methodology. The most important deficiencies—Type II errors, biased coefficients and imprecise standard errors, misleading p values, misguided causal claims, and various theoretical concerns—should be weighed against the likely presence of unobserved heterogeneity in other regression models. Ultimately, we must do a better job of communicating the pitfalls of fixed-effects models to our colleagues and students.
AB - Although fixed-effects models for panel data are now widely recognized as powerful tools for longitudinal data analysis, the limitations of these models are not well known. We provide a critical discussion of 12 limitations, including a culture of omission, low statistical power, limited external validity, restricted time periods, measurement error, time invariance, undefined variables, unobserved heterogeneity, erroneous causal inferences, imprecise interpretations of coefficients, imprudent comparisons with cross-sectional models, and questionable contributions vis-à-vis previous work. Instead of discouraging the use of fixed-effects models, we encourage more critical applications of this rigorous and promising methodology. The most important deficiencies—Type II errors, biased coefficients and imprecise standard errors, misleading p values, misguided causal claims, and various theoretical concerns—should be weighed against the likely presence of unobserved heterogeneity in other regression models. Ultimately, we must do a better job of communicating the pitfalls of fixed-effects models to our colleagues and students.
KW - critique
KW - fixed-effects
KW - limitations
KW - longitudinal
KW - panel data
UR - http://www.scopus.com/inward/record.url?scp=85070264378&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85070264378&partnerID=8YFLogxK
U2 - 10.1177/0731121419863785
DO - 10.1177/0731121419863785
M3 - Article
AN - SCOPUS:85070264378
VL - 63
SP - 357
EP - 369
JO - Sociological Perspectives
JF - Sociological Perspectives
SN - 0731-1214
IS - 3
ER -