IDEAS home Printed from https://ideas.repec.org/r/eee/intfor/v7y1991i3p375-384.html
   My bibliography  Save this item

Macroeconomic forecast evaluation techniques

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as


Cited by:

  1. Jos Jansen & Jasper de Winter, 2016. "Improving model-based near-term GDP forecasts by subjective forecasts: A real-time exercise for the G7 countries," DNB Working Papers 507, Netherlands Central Bank, Research Department.
  2. Prem P. Talwar & Edward J. Chambers, 1993. "Forecasting Provincial Business Indicator Variables and Forecast Evaluation," Urban Studies, Urban Studies Journal Limited, vol. 30(10), pages 1763-1773, December.
  3. Grant Allan, 2012. "Evaluating the usefulness of forecasts of relative growth," Working Papers 1214, University of Strathclyde Business School, Department of Economics.
  4. Bespalova, Olga, 2018. "Forecast Evaluation in Macroeconomics and International Finance. Ph.D. thesis, George Washington University, Washington, DC, USA," MPRA Paper 117706, University Library of Munich, Germany.
  5. Norman R. Swanson & Halbert White, 1997. "A Model Selection Approach To Real-Time Macroeconomic Forecasting Using Linear Models And Artificial Neural Networks," The Review of Economics and Statistics, MIT Press, vol. 79(4), pages 540-550, November.
  6. Roy Batchelor, 2001. "How useful are the forecasts of intergovernmental agencies? The IMF and OECD versus the consensus," Applied Economics, Taylor & Francis Journals, vol. 33(2), pages 225-235.
  7. Heilemann Ullrich & Stekler Herman O., 2013. "Has The Accuracy of Macroeconomic Forecasts for Germany Improved?," German Economic Review, De Gruyter, vol. 14(2), pages 235-253, May.
  8. Yousaf Raza, Muhammad & Lin, Boqiang, 2021. "Oil for Pakistan: What are the main factors affecting the oil import?," Energy, Elsevier, vol. 237(C).
  9. Jagric Timotej, 2003. "A Nonlinear Approach to Forecasting with Leading Economic Indicators," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 7(2), pages 1-20, July.
  10. Zidong An & Joao Tovar Jalles, 2020. "On the performance of US fiscal forecasts: government vs. private information," Journal of Economic Studies, Emerald Group Publishing Limited, vol. 48(2), pages 367-391, June.
  11. Hussain, Anwar & Rahman, Muhammad & Memon, Junaid Alam, 2016. "Forecasting electricity consumption in Pakistan: the way forward," Energy Policy, Elsevier, vol. 90(C), pages 73-80.
  12. Jansen, Dennis W. & Kishan, Ruby Pandey, 1996. "An evaluation of federal reserve forecasting," Journal of Macroeconomics, Elsevier, vol. 18(1), pages 89-109.
  13. Clements, Michael P. & Franses, Philip Hans & Swanson, Norman R., 2004. "Forecasting economic and financial time-series with non-linear models," International Journal of Forecasting, Elsevier, vol. 20(2), pages 169-183.
  14. Swanson, Norman R. & White, Halbert, 1997. "Forecasting economic time series using flexible versus fixed specification and linear versus nonlinear econometric models," International Journal of Forecasting, Elsevier, vol. 13(4), pages 439-461, December.
  15. Rodríguez-Vargas, Adolfo, 2020. "Forecasting Costa Rican inflation with machine learning methods," Latin American Journal of Central Banking (previously Monetaria), Elsevier, vol. 1(1).
  16. Döpke, Jörg & Langfeldt, Enno, 1995. "Zur Qualität von Konjunkturprognosen für Westdeutschland 1976-1994," Kiel Discussion Papers 247, Kiel Institute for the World Economy (IfW Kiel).
  17. Wu, Yih-Jiuan, 1998. "Exchange rate forecasting: an application of radial basis function neural networks," ISU General Staff Papers 1998010108000013540, Iowa State University, Department of Economics.
  18. Ullrich Heilemann & Herman Stekler, 2010. "Perspectives on Evaluating Macroeconomic Forecasts," Working Papers 2010-002, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
  19. Lim, Terence & Lo, Andrew W. & Merton, Robert C. & Scholes, Myron S., 2006. "The Derivatives Sourcebook," Foundations and Trends(R) in Finance, now publishers, vol. 1(5–6), pages 365-572, April.
  20. Koning, Alex J. & Franses, Philip Hans & Hibon, Michele & Stekler, H.O., 2005. "The M3 competition: Statistical tests of the results," International Journal of Forecasting, Elsevier, vol. 21(3), pages 397-409.
  21. Timotej Jagric, 2003. "Forecasting with leading economic indicators - a non-linear approach," Prague Economic Papers, Prague University of Economics and Business, vol. 2003(1), pages 68-83.
  22. Jansen, W. Jos & Jin, Xiaowen & de Winter, Jasper M., 2016. "Forecasting and nowcasting real GDP: Comparing statistical models and subjective forecasts," International Journal of Forecasting, Elsevier, vol. 32(2), pages 411-436.
  23. Jef Vuchelen & Maria-Isabel Gutierrez, 2005. "Do the OECD 24 month horizon growth forecasts for the G7-countries contain information?," Applied Economics, Taylor & Francis Journals, vol. 37(8), pages 855-862.
  24. Heilemann, Ullrich & Stekler, H. O., 2003. "Has the accuracy of German macroeconomic forecasts improved?," Technical Reports 2003,31, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
  25. Vuchelen, Jef & Gutierrez, Maria-Isabel, 2005. "A direct test of the information content of the OECD growth forecasts," International Journal of Forecasting, Elsevier, vol. 21(1), pages 103-117.
  26. Mc Cracken, Michael W., 2000. "Robust out-of-sample inference," Journal of Econometrics, Elsevier, vol. 99(2), pages 195-223, December.
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.