Model selection, estimation and forecasting in VAR models with short-run and long-run restrictions

Osmani Teixeira de Carvalho Guillén (), Farshid Vahid (), George Athanasopoulos and João Victor Issler ()

No 688, Economics Working Papers (Ensaios Economicos da EPGE) from Graduate School of Economics, Getulio Vargas Foundation (Brazil)

Abstract: We study the joint determination of the lag length, the dimension of the cointegrating space andthe rank of the matrix of short-run parameters of a vector autoregressive (VAR) model using modelselection criteria. We consider model selection criteria which have data-dependent penalties for alack of parsimony, as well as the traditional ones. We suggest a new procedure which is a hybridof traditional criteria and criteria with data-dependant penalties. In order to compute the fit ofeach model, we propose an iterative procedure to compute the maximum likelihood estimates ofparameters of a VAR model with short-run and long-run restrictions. Our Monte Carlo simulationsmeasure the improvements in forecasting accuracy that can arise from the joint determination oflag-length and rank, relative to the commonly used procedure of selecting the lag-length only andthen testing for cointegration.

New Economics Papers: this item is included in nep-env and nep-tur
Date: 2009-02-05
View list of references

Downloads: (external link)
http://virtualbib.fgv.br/dspace/bitstream/10438/2192/1/EnsaioEconomico04fev.pdf (application/pdf)

Related works:
Working Paper: Model selection, estimation and forecasting in VAR models with short-run and long-run restrictions (2009)
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: http://EconPapers.repec.org/RePEc:fgv:epgewp:688

Access Statistics for this paper

More papers in Economics Working Papers (Ensaios Economicos da EPGE) from Graduate School of Economics, Getulio Vargas Foundation (Brazil)
Contact information at EDIRC.
Series data maintained by Núcleo de Computação da EPGE ().