ScholarGate
Msaidizi

Linganisha mbinu

Pitia mbinu ulizochagua bega kwa bega; safu zinazotofautiana zinaangaziwa.

Mchanganuo wa Athari za Kibatari za Fourier×Mfumo wa Athari Nasibu za Paneli×
NyanjaEkonometrikiEkonometriki
FamiliaRegression modelRegression model
Mwaka wa asili2006-20121966
MwanzilishiBecker, Enders & Lee; Enders & LeeBalestra & Nerlove
AinaPanel regression with Fourier approximationPanel data estimator
Chanzo asiliaBecker, R., Enders, W., & Lee, J. (2006). A stationary test in the presence of an unknown number of smooth breaks. Journal of Time Series Analysis, 27(3), 381-409. DOI ↗Balestra, P., & Nerlove, M. (1966). Pooling cross section and time series data in the estimation of a dynamic model: The demand for natural gas. Econometrica, 34(3), 585–612. DOI ↗
Majina mbadalaFourier RE model, FFF random effects, flexible Fourier random effects, Fourier augmented random effectsrandom effects estimator, RE model, GLS random effects, error components model
Zinazohusiana55
MuhtasariThe Fourier Random Effects Model extends the standard random effects panel estimator by incorporating trigonometric (Fourier) terms to approximate smooth, gradual structural change in time trends or intercepts. It retains the GLS efficiency advantages of the random effects estimator while allowing parameters to shift continuously over time without requiring knowledge of exact break dates.The panel random effects (RE) model treats individual-specific effects as random draws from a population distribution rather than fixed constants, enabling efficient estimation by generalised least squares and allowing inference about time-invariant regressors that are swept away in fixed effects estimation.
ScholarGateSeti ya data
  1. v1
  2. 2 Vyanzo
  3. PUBLISHED
  1. v1
  2. 2 Vyanzo
  3. PUBLISHED

Nenda kwenye utafutaji Pakua slaidi

ScholarGateLinganisha mbinu: Fourier Random Effects Model · Panel Random Effects Model. Imepatikana 2026-06-17 kutoka https://scholargate.app/sw/compare