  The main goal of this paper is to develop a methodology for estimating time
varying parameter vector auto-regression (TVP-VAR) models with a timeinvariant
long-run relationship between endogenous variables and changes in exogenous
variables. We propose a Gibbs sampling scheme for estimation of model
parameters as well as time-invariant long-run multiplier parameters. Further we
demonstrate the applicability of the proposed method by analyzing examples of
the Norwegian and Russian economies based on the data on real GDP, real
exchange rate and real oil prices. Our results show that incorporating the time
invariance constraint on the long-run multipliers in TVP-VAR model helps to
significantly improve the forecasting performance.
