Backcasting

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Backcasting is a planning method that starts with defining a desirable future and then works backwards to identify policies and programs that will connect that specified future to the present. The fundamentals of the method were outlined by John B. Robinson from the University of Waterloo in 1990. The fundamental question of backcasting asks: "if we want to attain a certain goal, what actions must be taken to get there?" While forecasting involves predicting the future based on current trend analysis, backcasting approaches the challenge of discussing the future from the opposite direction; it is "a method in which the future desired conditions are envisioned and steps are then defined to attain those conditions, rather than taking steps that are merely a continuation of present methods extrapolated into the future". In statistics and data analysis, backcasting can be considered to be the opposite of forecasting; thus: forecasting involves the prediction of the future (unknown) values of the dependent variables based on known values of the independent variable. backcasting involves the prediction of the unknown values of the independent variables that might have existed, in order to explain the known values of the dependent variable.