Using forecasts of forecasters to forecast

Nolte, Ingmar; Pohlmeier, Winfried

Using forecasts of forecasters to forecast

Files

Nolte_Pohlmeier_2007_Using_Forecaster_IJF.pdf(526.22 KB)

Date

2007

Authors

Nolte, Ingmar

Pohlmeier, Winfried

Publication type

Journal article

Published in

International Journal of Forecasting ; 23 (2007), 1. - pp. 15-28

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.

Subject (DDC)

330 Economics

Keywords

Forecasting quality,Qualitative survey data,Quantification methods,Linear time series models,Turning points

Cite This

ISO 690

NOLTE, Ingmar, Winfried POHLMEIER, 2007. Using forecasts of forecasters to forecast. In: International Journal of Forecasting. 23(1), pp. 15-28. Available under: doi: 10.1016/j.ijforecast.2006.05.001

BibTex

@article{Nolte2007Using-12125,
  year={2007},
  doi={10.1016/j.ijforecast.2006.05.001},
  title={Using forecasts of forecasters to forecast},
  number={1},
  volume={23},
  journal={International Journal of Forecasting},
  pages={15--28},
  author={Nolte, Ingmar and Pohlmeier, Winfried}
}

RDF

<rdf:RDF
    xmlns:dcterms="http://purl.org/dc/terms/"
    xmlns:dc="http://purl.org/dc/elements/1.1/"
    xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"
    xmlns:bibo="http://purl.org/ontology/bibo/"
    xmlns:dspace="http://digital-repositories.org/ontologies/dspace/0.1.0#"
    xmlns:foaf="http://xmlns.com/foaf/0.1/"
    xmlns:void="http://rdfs.org/ns/void#"
    xmlns:xsd="http://www.w3.org/2001/XMLSchema#" > 
  <rdf:Description rdf:about="https://kops.uni-konstanz.de/server/rdf/resource/123456789/12125">
    <dc:creator>Pohlmeier, Winfried</dc:creator>
    <dc:format>application/pdf</dc:format>
    <void:sparqlEndpoint rdf:resource="http://localhost/fuseki/dspace/sparql"/>
    <dcterms:isPartOf rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/46"/>
    <dc:date rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2011-03-25T09:42:51Z</dc:date>
    <bibo:uri rdf:resource="http://kops.uni-konstanz.de/handle/123456789/12125"/>
    <dspace:hasBitstream rdf:resource="https://kops.uni-konstanz.de/bitstream/123456789/12125/1/Nolte_Pohlmeier_2007_Using_Forecaster_IJF.pdf"/>
    <dcterms:abstract xml:lang="eng">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., &amp; 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.</dcterms:abstract>
    <dc:creator>Nolte, Ingmar</dc:creator>
    <dcterms:bibliographicCitation>First publ. in: International Journal of Forecasting 23 (2007), 1, pp. 15-28</dcterms:bibliographicCitation>
    <dcterms:issued>2007</dcterms:issued>
    <dc:contributor>Pohlmeier, Winfried</dc:contributor>
    <dc:contributor>Nolte, Ingmar</dc:contributor>
    <dcterms:hasPart rdf:resource="https://kops.uni-konstanz.de/bitstream/123456789/12125/1/Nolte_Pohlmeier_2007_Using_Forecaster_IJF.pdf"/>
    <foaf:homepage rdf:resource="http://localhost:8080/"/>
    <dc:language>eng</dc:language>
    <dcterms:available rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2011-03-25T09:42:51Z</dcterms:available>
    <dcterms:title>Using forecasts of forecasters to forecast</dcterms:title>
    <dcterms:rights rdf:resource="http://creativecommons.org/licenses/by-nc-nd/2.0/"/>
    <dspace:isPartOfCollection rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/46"/>
    <dc:rights>Attribution-NonCommercial-NoDerivs 2.0 Generic</dc:rights>
  </rdf:Description>
</rdf:RDF>

Bibliography of Konstanz

Yes