ScholarGate
Assistent

Sammenlign metoder

Gjennomgå de valgte metodene side om side; rader som avviker, er uthevet.

Kryss-seksjonell NARDL×Lokale projeksjoner×
FagfeltØkonometriØkonometri
FamilieRegression modelRegression model
Opprinnelsesår20142005
OpphavspersonYongcheol Shin and colleaguesOscar Jorda
TypeAsymmetric panel modelMulti-horizon regression
Opprinnelig kildeShin, Y., Yu, B., & Greenwood-Nimmo, M. (2014). Modelling asymmetric cointegration and dynamic multipliers in a system of nonlinear autoregressive distributed lag equations. Econometric Reviews, 33(1), 56-87. link ↗Jorda, O. (2005). Estimation and inference of impulse responses by local projections. American Economic Review, 95(1), 161-182. DOI ↗
AliasNARDL panelLP-IR, Multi-horizon regression
Relaterte33
SammendragCS-NARDL extends the nonlinear autoregressive distributed lag (NARDL) model to panel data, capturing asymmetric long-run and short-run relationships where positive and negative changes in explanatory variables have differential effects. Introduced by Shin et al. (2014) and adapted to panels, it allows studying how cross-sectional units respond differently to positive versus negative shocks while maintaining cointegrating relationships. This approach is essential for understanding economic asymmetries in commodity markets, monetary transmission, and labor markets.Local Projections (LP) is a semi-parametric method for estimating impulse responses directly via multi-horizon regressions, bypassing VAR-model specification. Introduced by Jorda (2005), it projects outcomes h periods ahead onto current shocks and lags, producing impulse-response functions without assuming a particular lag structure or VAR order. This flexibility has made it the dominant approach in applied macroeconomics for measuring policy effects and shock transmission.
ScholarGateDatasett
  1. v1
  2. 2 Kilder
  3. PUBLISHED
  1. v1
  2. 2 Kilder
  3. PUBLISHED

Gå til søk Last ned lysbilder

ScholarGateSammenlign metoder: CS-NARDL · Local Projections. Hentet 2026-06-19 fra https://scholargate.app/no/compare