This study investigates the effects of oil price shocks on volatility of selected agricultural and metal commodities. To achieve this goal, we decompose an oil price shock to its underlying components, including macroeconomics and oil specific shocks. The applied methodology is the structural vector autoregressive (SVAR) model and the time span is from April 1983 to December 2013. The investigation is divided into two subsamples, before and after 2006 for agricultures taking into account the 2006-2008 food crisis, and before and after 2008 for metals considering the recent global financial crisis. The validity of time divisions is confirmed by historical decomposition accomplishment. We find that, based on impulse response functions, the response of volatility of each commodity to an oil price shock differs significantly depending on the underlying cause of the shock for the both pre and post-crisis periods. moreover, according to variance decomposition the explanatory power of oil shocks becomes stronger after the crisis. The different responses of commodities are described in detail by investigating market characteristics in each period.