A common problem policymakers, economists and forecasters face is the lack of essential economic data in real time. The information needed is often only available at lower frequencies and published with a considerable lag. This is the case with real gross domestic product (GDP), which is the single most relevant variable describing the path of the economy. GDP is used, together with inflation, to substantiate the direction of monetary policy. However the delay in GDP releases makes it difficult to predict the current state of the economy with accuracy. One way to improve this accuracy is to use higher frequency economic information more readily available in real time. Although some forecasters use judgement to incorporate higher frequency data into their forecasts, most models cannot incorporate this data because of three common challenges. First, higher frequency data are not released in a synchronous fashion, which means there tend to be gaps towards the ends of the sample. Second, information is not released at the same frequency; a quarterly projection model cannot use daily data. Finally, most traditional econometric models are unable to accommodate a large set of information.