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neural networks as an opportunity to improve upon forecast accuracy with limited data and while remaining agnostic as to … architecture outperforms benchmark models at every forecast horizon (up to four quarters) …
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This paper contributes a multivariate forecasting comparison between structural models and Machine-Learning-based tools. Specifically, a fully connected feed forward nonlinear autoregressive neural network (ANN) is contrasted to a well established dynamic stochastic general equilibrium (DSGE)...
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chapters on forecast evaluation, including evaluation of point forecasts and probability forecasts and contains chapters on …
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The highly prized ability to make financial plans with some certainty about the future comes from the core fields of economics. In recent years the availability of more data, analytical tools of greater precision, and ex post studies of business decisions have increased demand for information...
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