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This paper presents a GARCH type volatility model that allows for time-varying uncondi-tional volatility that is a function of macroeconomic variables. It is an extension of the SPLINE GARCH model proposed by Engle and Rangel (2005). The advantage of the model proposed in this paper is that the macroeconomic information available is used in the parameter estimation process and that forecasts of macroeconomic variables have an obvious role when forecasting volatility. Based on an application of this model to S&P500 share index returns, it is demonstrated that forecasts of macroeconomic variables can be easily incorporated into volatility forecasts for share index returns. It transpires that the model proposed here can lead to improved volatility forecasts compared to traditional GARCH type volatility models