Zapis dokaza metode

Bayesian NARDL

Bayesian NARDL combines the Nonlinear Autoregressive Distributed Lag framework of Shin, Yu, and Greenwood-Nimmo (2014) with Bayesian posterior inference. It models asymmetric long-run cointegration — allowing positive and negative shocks to a regressor to have different equilibrium effects — while incorporating prior knowledge and producing full posterior distributions over all parameters, including the asymmetry gap.

Sources recorded, not reviewed

Izvorni zapis

Citati kopirani doslovno iz izvornog zapisa metode. Ne impliciraju nikakvu provjeru na razini tvrdnje.

Bayesian Nonlinear Autoregressive Distributed Lag Model

Taksonomski zapis metode · regression-model / econometrics

Shin, Y., Yu, B., & Greenwood-Nimmo, M. (2014). Modelling asymmetric cointegration and dynamic multipliers in a nonlinear ARDL framework. In W. C. Horrace & R. C. Sickles (Eds.), Festschrift in Honor of Peter Schmidt: Econometric Methods and Applications (pp. 281–314). Springer. · URL
Koop, G. (2003). Bayesian Econometrics. Wiley. · ISBN 978-0470845677

Otvori cijelu metodu

Uređene tvrdnje

Tvrdnje pohranjene u knjigu dokaza, svaka s vlastitom procjenom.

Nema uređenih tvrdnji

Ovaj prikaz ne izmišlja procjenu tvrdnje kada knjiga dokaza nema nijednu.

Povezane metode

Generirano iz grafa metode i prikazano kao strojno predložene relacije — ne implicira se nikakva tvrdnja dokaza.

Taxonomic bucketArellano-Bond GMM estimatormachine-suggested · Relational suggestion, not evidence.Taxonomic bucketBayesian ARDL Bounds Testmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketBayesian VECMmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketNonlinear ARDLmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketPanel NARDLmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketVector Error Correction Modelmachine-suggested · Relational suggestion, not evidence.