ScholarGate
Asistents

Salīdzināt metodes

Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.

Robusta paneldatu analīze×Panel Data Analysis×
NozareEkonometrijaEkonometrija
SaimeRegression modelRegression model
Izcelsmes gads19871966–1978
AutorsArellano (1987); White (1980) heteroscedasticity-consistent frameworkBalestra & Nerlove (1966); Mundlak (1978); Hausman (1978)
TipsRobust estimation / inference correctionPanel regression framework
PirmavotsArellano, M. (1987). Computing robust standard errors for within-groups estimators. Oxford Bulletin of Economics and Statistics, 49(4), 431–434. link ↗Baltagi, B. H. (2021). Econometric Analysis of Panel Data (6th ed.). Springer. ISBN: 978-3030539528
Citi nosaukumirobust panel regression, cluster-robust panel estimation, panel regression with robust standard errors, HC/CR panel estimatorlongitudinal data analysis, pooled cross-sectional time-series analysis, panel regression, data panel analysis
Saistītās65
KopsavilkumsRobust panel data analysis applies standard panel estimators — fixed effects, random effects, or pooled OLS — while replacing conventional standard errors with cluster-robust or heteroscedasticity-consistent (HC) variants. The point estimates remain unchanged; what changes is the variance-covariance matrix used for inference, making t-tests and F-tests valid even when errors are heteroscedastic or correlated within cross-sectional units over time.Panel data analysis models data that track multiple units — countries, firms, individuals — over time, enabling researchers to control for unobserved unit-level heterogeneity that would otherwise bias cross-sectional or time-series estimates. The two core specifications are fixed effects and random effects, selected via the Hausman test.
ScholarGateDatu kopa
  1. v1
  2. 2 Avoti
  3. PUBLISHED
  1. v1
  2. 2 Avoti
  3. PUBLISHED

Doties uz meklēšanu Lejupielādēt slaidus

ScholarGateSalīdzināt metodes: Robust Panel Data Analysis · Panel Data Analysis. Izgūts 2026-06-15 no https://scholargate.app/lv/compare