How does accounting data contribute to the accuracy of GDP growth forecasts using machine learning algorithms?
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Accounting data contributes to the accuracy of GDP growth forecasts using machine learning algorithms. For near-term GDP growth forecasts, accounting does not improve the out-of-sample accuracy of predictions due to the efficiency of professional forecasters' predictions. However, for more distant-term GDP growth forecasts, accounting variables are useful and increase the model's out-of-sample predictive accuracy by 13 to 46%. Four categories of accounting variables, including profits, accrual estimates, capital raises or distributions, and capital allocation decisions, are particularly informative for the longer-term outlook of the economy .
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17 Mar 2023 | The provided paper does not mention how accounting data contributes to the accuracy of GDP growth forecasts using machine learning algorithms. |
| The provided paper does not mention accounting data or its contribution to the accuracy of GDP growth forecasts using machine learning algorithms. | |
| The provided paper does not mention accounting data or its contribution to the accuracy of GDP growth forecasts using machine learning algorithms. | |
| Accounting data contributes to the accuracy of GDP growth forecasts using machine learning algorithms by improving the out-of-sample predictive accuracy for more distant-term forecasts by 13 to 46%. | |
| The paper does not mention the contribution of accounting data to the accuracy of GDP growth forecasts using machine learning algorithms. |
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