Artikel

Which panel data estimator should I use? A corrigendum and extension

This study uses Monte Carlo experiments to produce new evidence on the performance of a wide range of panel data estimators. It focuses on estimators that are readily available in statistical software packages such as Stata and Eviews, and for which the number of cross-sectional units (N) and time periods (T) are small to moderate in size. The goal is to develop practical guidelines that will enable researchers to select the best estimator for a given type of data. It extends a previous study on the subject (Reed and Ye, Which panel data estimator should I use? 2011), and modifies their recommendations. The new recommendations provide a (virtually) complete decision tree: When it comes to choosing an estimator for efficiency, it uses the size of the panel dataset (N and T) to guide the researcher to the best estimator. When it comes to choosing an estimator for hypothesis testing, it identifies one estimator as superior across all the data scenarios included in the study. An unusual finding is that researchers should use different estimators for estimating coefficients and testing hypotheses. The authors present evidence that bootstrapping allows one to use the same estimator for both.

Language
Englisch

Bibliographic citation
Journal: Economics: The Open-Access, Open-Assessment E-Journal ; ISSN: 1864-6042 ; Volume: 12 ; Year: 2018 ; Issue: 2018-4 ; Pages: 1-31 ; Kiel: Kiel Institute for the World Economy (IfW)

Classification
Wirtschaft
Single Equation Models; Single Variables: Panel Data Models; Spatio-temporal Models
Multiple or Simultaneous Equation Models: Panel Data Models; Spatio-temporal Models
Subject
Panel data estimators
Monte Carlo simulation
PCSE
Parks model

Event
Geistige Schöpfung
(who)
Moundigbaye, Mantobaye
Rea, William S.
Reed, W. Robert
Event
Veröffentlichung
(who)
Kiel Institute for the World Economy (IfW)
(where)
Kiel
(when)
2018

DOI
doi:10.5018/economics-ejournal.ja.2018-4
Handle
Last update
10.03.2025, 11:43 AM CET

Data provider

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Object type

  • Artikel

Associated

  • Moundigbaye, Mantobaye
  • Rea, William S.
  • Reed, W. Robert
  • Kiel Institute for the World Economy (IfW)

Time of origin

  • 2018

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