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Using forecasts of forecasters to forecast

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Using forecasts of forecasters to forecast. / Nolte, Ingmar; Pohlmeier, Winfried.
In: International Journal of Forecasting, Vol. 23, No. 1, 01.2007, p. 15-28.

Research output: Contribution to Journal/Magazine › Journal article › peer-review

Harvard

Nolte, I & Pohlmeier, W 2007, 'Using forecasts of forecasters to forecast', International Journal of Forecasting, vol. 23, no. 1, pp. 15-28. https://doi.org/10.1016/j.ijforecast.2006.05.001

APA

Nolte, I., & Pohlmeier, W. (2007). Using forecasts of forecasters to forecast. International Journal of Forecasting, 23(1), 15-28. https://doi.org/10.1016/j.ijforecast.2006.05.001

Vancouver

Nolte I, Pohlmeier W. Using forecasts of forecasters to forecast. International Journal of Forecasting. 2007 Jan;23(1):15-28. doi: 10.1016/j.ijforecast.2006.05.001

Author

Nolte, Ingmar ; Pohlmeier, Winfried. / Using forecasts of forecasters to forecast. In: International Journal of Forecasting. 2007 ; Vol. 23, No. 1. pp. 15-28.

Bibtex

@article{88d014ef874b46a3ae96d3d50bf3c19c,
title = "Using forecasts of forecasters to forecast",
abstract = "Quantification techniques are popular methods in empirical research for aggregating the qualitative predictions at the microlevel into a single figure. In this paper, we analyze the forecasting performance of various methods that are based on the qualitative predictions of financial experts for major financial variables and macroeconomic aggregates. Based on the Centre of European Economic Research's Financial Markets Survey, a monthly qualitative survey of around 330 financial experts, we analyze the out-of-sample predictive quality of probability methods and regression methods. Using the modified Diebold-Mariano test of Harvey, Leybourne and Newbold (Harvey, D., Leybourne, S., & Newbold, P. (1997). Testing the equality of prediction mean squared errors. International Journal of Forecasting, 13, 281-291), we compare the forecasts based on survey methods with the forecasting performance of standard linear time series approaches and simple random walk forecasts. ",
keywords = "forecasting quality, qualitative survey data, quantification methods, linear time series models, turning points, INFLATION-EXPECTATIONS, PRICE EXPECTATIONS, RESPONSES",
author = "Ingmar Nolte and Winfried Pohlmeier",
year = "2007",
month = jan,
doi = "10.1016/j.ijforecast.2006.05.001",
language = "English",
volume = "23",
pages = "15--28",
journal = "International Journal of Forecasting",
issn = "0169-2070",
publisher = "Elsevier Science B.V.",
number = "1",

}

RIS

TY - JOUR

T1 - Using forecasts of forecasters to forecast

AU - Nolte, Ingmar

AU - Pohlmeier, Winfried

PY - 2007/1

Y1 - 2007/1

N2 - Quantification techniques are popular methods in empirical research for aggregating the qualitative predictions at the microlevel into a single figure. In this paper, we analyze the forecasting performance of various methods that are based on the qualitative predictions of financial experts for major financial variables and macroeconomic aggregates. Based on the Centre of European Economic Research's Financial Markets Survey, a monthly qualitative survey of around 330 financial experts, we analyze the out-of-sample predictive quality of probability methods and regression methods. Using the modified Diebold-Mariano test of Harvey, Leybourne and Newbold (Harvey, D., Leybourne, S., & Newbold, P. (1997). Testing the equality of prediction mean squared errors. International Journal of Forecasting, 13, 281-291), we compare the forecasts based on survey methods with the forecasting performance of standard linear time series approaches and simple random walk forecasts. 

AB - Quantification techniques are popular methods in empirical research for aggregating the qualitative predictions at the microlevel into a single figure. In this paper, we analyze the forecasting performance of various methods that are based on the qualitative predictions of financial experts for major financial variables and macroeconomic aggregates. Based on the Centre of European Economic Research's Financial Markets Survey, a monthly qualitative survey of around 330 financial experts, we analyze the out-of-sample predictive quality of probability methods and regression methods. Using the modified Diebold-Mariano test of Harvey, Leybourne and Newbold (Harvey, D., Leybourne, S., & Newbold, P. (1997). Testing the equality of prediction mean squared errors. International Journal of Forecasting, 13, 281-291), we compare the forecasts based on survey methods with the forecasting performance of standard linear time series approaches and simple random walk forecasts. 

KW - forecasting quality

KW - qualitative survey data

KW - quantification methods

KW - linear time series models

KW - turning points

KW - INFLATION-EXPECTATIONS

KW - PRICE EXPECTATIONS

KW - RESPONSES

U2 - 10.1016/j.ijforecast.2006.05.001

DO - 10.1016/j.ijforecast.2006.05.001

M3 - Journal article

VL - 23

SP - 15

EP - 28

JO - International Journal of Forecasting

JF - International Journal of Forecasting

SN - 0169-2070

IS - 1

ER -