On estimating long-run effects in models with lagged dependent variables

W. Reed () and Min Zhu

Economic Modelling, 2017, vol. 64, issue C, 302-311

Abstract: A common procedure in economics is to estimate long-run effects from models with lagged dependent variables. For example, macro panel studies frequently are concerned with estimating the long-run impacts of fiscal policy, international aid, or foreign investment.

Keywords: Hurwicz bias; Auto-Regressive Distributed-Lag (ARDL) models; Dynamic Panel Data (DPD) models; DPD estimators; long-run impact; long-run propensity; Fieller’s method; indirect inference; jackknifing (search for similar items in EconPapers)
JEL-codes: C22 C23 (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (9)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S026499931730562X
Full text for ScienceDirect subscribers only

Related works:
Working Paper: On Estimating Long-Run Effects In Models with Lagged Dependent Variables (2016)
Working Paper: On Estimating Long-Run Effects in Models with Lagged Dependent Variables (2015)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:ecmode:v:64:y:2017:i:c:p:302-311

DOI: 10.1016/j.econmod.2017.04.006

Access Statistics for this article

Economic Modelling is currently edited by S. Hall and P. Pauly

More articles in Economic Modelling from Elsevier
Bibliographic data for series maintained by Catherine Liu ().