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Nowcasting is the prediction of the present, the very near future and the very recent past in economics. The term is a contraction for now and forecasting and has been used for a long-time in meteorology. It has recently become popular in economics as standard measures used to assess the state of an economy, e.g., gross domestic product (GDP), are only determined after a long delay, and are even then subject to subsequent revisions. Nowcasting models have been applied in many institutions, in particular Central Banks, and the technique is used routinely to monitor the state of the economy in real time.
While weather forecasters know weather conditions today and only have to predict future weather, economists have to forecast the present and even the recent past. Historically, nowcasting techniques have been based on simplified heuristic approaches. A 2008 paper by Giannone, Reichlin and Small finds that the process of nowcasting can be formalized in a statistical model which produces predictions without the need for informal judgement.
The model exploits information from a large quantity of data series at different frequencies and with different publication lags. The idea is that signals about the direction of change in GDP can be extracted from this large and heterogeneous set of information sources (e.g., jobless figures, industrial orders, the trade balance, etc.) before GDP itself is published. In nowcasting this data is used to compute sequences of current quarter GDP estimates in relation to the real time flow of data releases.
Nowcasting can additionally be combined with econometric models to improve overall forecast accuracy, as well as reduce errors.
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