Dynamic econometric modeling for market analysis

ABSTRACT: Structural-Time series models have not gained much ground in commodity market modeling despite the overwhelming popularity of time series approaches in forecasting and dynamic analyses. This study tries to adopt a structural model for the commodity market and estimates important econometric specifications. This paper contributes by applying developments in seasonal cointegration and structural-time series analysis to the study of commodity markets. The conclusions may be summarized as follows. First, quarterly data in the commodity market have seasonal unit roots and also in a forecasting context, seasonally cointegrated VECMs perform uniformly better that their nonseasonal counterpart. Finally, DSEM with seasonal cointegration, however, perform better than VECMs at longer forecast horizons.