Mean absolute percentage error and bias in economic forecasting. (English) Zbl 1239.91124
Summary: This article develops a simple theoretical framework to show how forecasters may bias downward point predictions under the assumption that the asymmetric loss function is directly related to the (Mean) Absolute Percentage Error \((M)APE\).
MSC:
| 91B82 | Statistical methods; economic indices and measures |
| 62P20 | Applications of statistics to economics |
References:
| [1] | Armstrong, S.; Collopy, F., Error measures for generalising about forecasting methods: empirical comparisons, International Journal of Forecasting, 8, 69-80 (1992) |
| [2] | Elliot, G.; Timmermann, A., Economic forecasting, Journal of Economic Literature, 46, 1, 3-56 (2008) |
| [3] | Engelberg, J.; Manski, C.; Williams, J., Comparing the point predictions and subjective probability distributions of professional forecasters, Journal of Business and Economic Statistics, 27, 1, 30-41 (2009) |
| [4] | Goodwin, P.; Lawton, R., On the asymmetry of the symmetric mape, International Journal of Forecasting, 15, 405-408 (1999) |
| [5] | Gu, Z.; Wu, J., Earnings skewness and analyst forecast bias, Journal of Accounting and Economics, 35, 5-29 (2003) |
| [6] | Lim, T., Rationality and analysts’ forecast bias, Journal of Finance, 56, 1, 369-385 (2001) |
| [7] | Makridakis, S., Accuracy measures: theoretical and practical concerns, International Journal of Forecasting, 9, 527-529 (1993) |
| [8] | Zarnowitz, V.; Lambros, L., Consensus and uncertainty in economic prediction, Journal of Political Economy, 95, 3, 591-621 (1987) |
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