Artikel
Bootstrap methods for inference in the Parks model
This paper shows how to bootstrap hypothesis tests in the context of the Parks's (1967) Feasible Generalized Least Squares estimator. It then demonstrates that the bootstrap outperforms FGLS(Parks)'s top competitor. The FGLS(Parks) estimator has been a workhorse for the analysis of panel data and seemingly unrelated regression equation systems because it allows the incorporation of cross-sectional correlation together with heteroskedasticity and serial correlation. Unfortunately, the associated, asymptotic standard error estimates are biased downward, often severely. To address this problem, Beck and Katz (1995) developed an approach that uses the Prais-Winsten estimator together with 'panel corrected standard errors' (PCSE). While PCSE produces standard error estimates that are less biased than FGLS(Parks), it forces the user to sacrifice efficiency for accuracy in hypothesis testing. The PCSE approach has been, and continues to be, widely used. This paper develops an alternative: a nonparametric bootstrapping procedure to be used in conjunction with the FGLS(Parks) estimator. We demonstrate its effectiveness using an experimental approach that creates artificial panel datasets modelled after actual panel datasets. Our approach provides a superior alternative to existing estimation options by allowing researchers to retain the efficiency of the FGLS(Parks) estimator while producing more accurate hypothesis test results than the PCSE.
- Sprache
-
Englisch
- Erschienen in
-
Journal: Economics: The Open-Access, Open-Assessment E-Journal ; ISSN: 1864-6042 ; Volume: 14 ; Year: 2020 ; Issue: 2020-4 ; Pages: 1-18 ; Kiel: Kiel Institute for the World Economy (IfW)
- Klassifikation
-
Wirtschaft
Estimation: General
Statistical Simulation Methods: General
Single Equation Models; Single Variables: Panel Data Models; Spatio-temporal Models
Multiple or Simultaneous Equation Models: Panel Data Models; Spatio-temporal Models
- Thema
-
Parks model
FGLS
PCSE
SUR
panel data
cross-sectional correlation
bootstrap
Monte Carlo
simulation
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Moundigbaye, Mantobaye
Messemer, Clarisse
Parks, Richard W.
Reed, W. Robert
- Ereignis
-
Veröffentlichung
- (wer)
-
Kiel Institute for the World Economy (IfW)
- (wo)
-
Kiel
- (wann)
-
2020
- DOI
-
doi:10.5018/economics-ejournal.ja.2020-4
- Handle
- Letzte Aktualisierung
-
10.03.2025, 11:42 MEZ
Datenpartner
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Artikel
Beteiligte
- Moundigbaye, Mantobaye
- Messemer, Clarisse
- Parks, Richard W.
- Reed, W. Robert
- Kiel Institute for the World Economy (IfW)
Entstanden
- 2020
Ähnliche Objekte (12)
Bootstrap methods for inference in the Parks model
Bootstrap methods for inference in the Parks model
Bootstrap inference in semiparametric generalized additive models
Improvements in bootstrap inference
Sieve bootstrap inference for time-varying coefficient models
Bootstrap inference in single equation error correction models
Bootstrap Inference in Single Equation Error Correction Models
Fast and reliable jackknife and bootstrap methods for cluster-robust inference
A new approach to bootstrap inference in functional coefficient models
Bootstrap and Asymptotic Inference with Multiway Clustering
Fast cluster bootstrap methods for linear regression models
Bootstrap methods in econometrics
Bootstrap methods for inference in the Parks model
Bootstrap methods for inference in the Parks model
Bootstrap inference in semiparametric generalized additive models
Improvements in bootstrap inference
Sieve bootstrap inference for time-varying coefficient models
Bootstrap inference in single equation error correction models
Bootstrap Inference in Single Equation Error Correction Models
Fast and reliable jackknife and bootstrap methods for cluster-robust inference
A new approach to bootstrap inference in functional coefficient models
Bootstrap and Asymptotic Inference with Multiway Clustering
Fast cluster bootstrap methods for linear regression models
Bootstrap methods in econometrics
Bootstrap methods for inference in the Parks model
Bootstrap methods for inference in the Parks model
Bootstrap inference in semiparametric generalized additive models
Improvements in bootstrap inference
Sieve bootstrap inference for time-varying coefficient models
Bootstrap inference in single equation error correction models
Bootstrap Inference in Single Equation Error Correction Models
Fast and reliable jackknife and bootstrap methods for cluster-robust inference
A new approach to bootstrap inference in functional coefficient models
Bootstrap and Asymptotic Inference with Multiway Clustering
Fast cluster bootstrap methods for linear regression models
Bootstrap methods in econometrics
Verbundene Objekte
