Page 155 - Contributed Paper Session (CPS) - Volume 5

CPS1159 Philip Hans Franses et al.
August, year t 0.576 (0.310) 0.776 (0.101) 0.083
September, year t 0.602 (0.302) 0.773 (0.098) 0.066
October, year t 0.516 (0.291) 0.799 (0.094) 0.102
November, year t 0.535 (0.278) 0.802 (0.090) 0.087
December, year t 0.516 (0.272) 0.820 (0.088) 0.115

References
1. Bertrand, P. and F. Goupil (1999), Descriptive statistics for symbolic data,
in Symbolic Data Analysis (H.H. Bock and E. Diday, editors), Berlin:
Springer Verlag, 103-124.
2. Billard, L. and E. Diday (2000), Regression analysis for interval-valued
data, in Data Analysis, Classification, and Related Methods (H.A.L. Kiers,
J.-P. Rasson, P.J.F. Groenen and M. Schader, editors), Berlin: Springer
Verlag, 369-374.
3. Billard, L. and E. Diday (2003), From the statistics of data to the statistics
of knowledge, Journal of the American Statistical Association, 98, 470-
487.
4. Billard, L. and E. Diday (2007), Symbolic Data Analysis: Conceptual
Statistics and Data Mining, Chichester: Wiley
5. Capistran, C., and A. Timmermann (2009), Disagreement and biases in
inflation expectations, Journal of Money, Credit and Banking 41 (2-3),
365-396.
6. Clements, M.P. (2010), Explanations of the inconsistencies in survey
respondents forecasts, European Economic Review, 54 (4), 536-549.
7. Clements, M.P. (2017), Do forecasters target first or later releases of
national accounts data? ICMA Centre Discussion Papers in Finance icma-
dp2017-03, Henley Business School, Reading University.
8. Dovern, F., U. Fritsche and J. Slacalek (2012), Disagreement among
forecasters in G7 countries, The Review of Economics and Statistics 94
(4), 1081-1096.
9. Efron, B. and R.J. Tibshirani (1993). An Introduction to the Bootstrap.
London: CRC Press.
10. Engelberg, J. C.F. Manski, and J. Williams (2009), Comparing the point
predictions and subjective probability distributions of professional
forecasters, Journal of Business & Economic Statistics, 27 (1), 30-41.
11. Genre, V., G. Kenny, A. Mayler and A. Timmermann (2013), Combining
expert forecasts: Can anything beat the simple average? International
Journal of Forecasting 29 (1), 108-121.
12. Lahiri, K., and X. Sheng (2010), Measuring forecast uncertainty by
disagreement: The missing link, Journal of Applied Econometrics 25 (4),
514-538.
13. Laster, D., P. Bennett and I.S. Geoum (1999), Rational bias in
macroeconomic forecasts, Quarterly Journal of Economics 114 (1),

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