The Markov-Switching Vector Autoregressive Model

1997 ◽  
pp. 6-28 ◽  
Author(s):  
Hans-Martin Krolzig
Keyword(s):  
Autoregressive Model ◽  
Markov Switching ◽  
Vector Autoregressive Model ◽  
Vector Autoregressive

scholarly journals Causality between inflation and inflation uncertainty in South Africa: Evidence from a Markov-switching vector autoregressive model

2015 ◽  
Vol 24 ◽  
pp. 46-68 ◽  
Author(s):  
Adnen Ben Nasr ◽  
Mehmet Balcilar ◽  
Ahdi N. Ajmi ◽  
Goodness C. Aye ◽  
Rangan Gupta ◽  
...  
Keyword(s):  
South Africa ◽  
Autoregressive Model ◽  
Markov Switching ◽  
Vector Autoregressive Model ◽  
Inflation Uncertainty ◽  
Vector Autoregressive

scholarly journals Markov Switching Intercept Vector Autoregressive Model (MSI(2)-VAR(2)) of Nigeria Inflation Rate and Crude Oil Price (Using Views 11)

2021 ◽  
Vol 4 (2) ◽  
pp. 88-100
Author(s):  
Wiri L. ◽  
Sibeate P.U. ◽  
Isaac D.E.
Keyword(s):  
Crude Oil ◽  
Regime Switching ◽  
Autoregressive Model ◽  
Inflation Rate ◽  
Markov Switching ◽  
Information Criterion ◽  
Information Criteria ◽  
Vector Autoregressive Model ◽  
Vector Autoregressive ◽  
Crude Oil Prices

To model inflation rate and crude oil prices, we used Markov Switching intercept heteroscedasticity Vector Autoregressive models. The data for this analysis was gathered from the Central Bank of Nigeria Statistical Bulletin monthly. The upward and downward movement in the series revealed by the time plot suggests that the series exhibit a regime-switching pattern: the period of expansion and contraction. The variable was stationary at first differences, the Augmented Dickey-Fuller test was used to screen for stationarity. The information criteria were used to test the number of regime and regime two were selected. Eight models were estimated for the MSI-VAR model. The best model was chosen based on the criterion of least information criterion, Markov-switching intercept heteroscedasticity – Vector Autoregressive model (MSIH(2)-VAR(2)) with AIC (8.596641) and SC (8.973119). The model was used to predict the series' values over a one-year cycle (12 months).

Sign in / Sign up

Export Citation Format

Share Document