A comparison of linear forecasting models and neural networks: an application to Euro inflation and Euro Divisia
AbstractLinear models reach their limitations in applications with nonlinearities in the data. In this paper new empirical evidence is provided on the relative Euro inflation forecasting performance of linear and non-linear models. The well established and widely used univariate ARIMA and multivariate VAR models are used as linear forecasting models whereas neural networks (NN) are used as non-linear forecasting models. It is endeavoured to keep the level of subjectivity in the NN building process to a minimum in an attempt to exploit the full potentials of the NN. It is also investigated whether the historically poor performance of the theoretically superior measure of the monetary services flow, Divisia, relative to the traditional Simple Sum measure could be attributed to a certain extent to the evaluation of these indices within a linear framework. Results obtained suggest that non-linear models provide better within-sample and out-of-sample forecasts and linear models are simply a subset of them. The Divisia index also outperforms the Simple Sum index when evaluated in a non-linear framework.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoArticle provided by Taylor & Francis Journals in its journal Applied Economics.
Volume (Year): 37 (2005)
Issue (Month): 6 ()
Contact details of provider:
Web page: http://www.tandfonline.com/RAEC20
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Perman, Roger & Scouller, John, 1999. "Business Economics," OUP Catalogue, Oxford University Press, number 9780198775249.
- Drake, L. & Mullineux, A., 1995. "One Divisa Money for Europe?," Discussion Papers 95-04, Department of Economics, University of Birmingham.
- James H. Stock & Mark W. Watson, 1999.
NBER Working Papers
7023, National Bureau of Economic Research, Inc.
- Church, Keith B. & Curram, Stephen P., 1996. "Forecasting consumers' expenditure: A comparison between econometric and neural network models," International Journal of Forecasting, Elsevier, vol. 12(2), pages 255-267, June.
- Hendry, David F & Doornik, Jurgen A, 1994. "Modelling Linear Dynamic Econometric Systems," Scottish Journal of Political Economy, Scottish Economic Society, vol. 41(1), pages 1-33, February.
- Gorr, Wilpen L. & Nagin, Daniel & Szczypula, Janusz, 1994. "Comparative study of artificial neural network and statistical models for predicting student grade point averages," International Journal of Forecasting, Elsevier, vol. 10(1), pages 17-34, June.
- Gordon de Brouwer & Neil R. Ericsson, 1995.
"Modelling Inflation in Australia,"
RBA Research Discussion Papers
rdp9510, Reserve Bank of Australia.
- Luca Stanca, 1999. "Asymmetries and nonlinearities in Italian macroeconomic fluctuations," Applied Economics, Taylor & Francis Journals, vol. 31(4), pages 483-491.
- Zhang, Guoqiang & Eddy Patuwo, B. & Y. Hu, Michael, 1998. "Forecasting with artificial neural networks:: The state of the art," International Journal of Forecasting, Elsevier, vol. 14(1), pages 35-62, March.
- LeSage, James P, 1990. "A Comparison of the Forecasting Ability of ECM and VAR Models," The Review of Economics and Statistics, MIT Press, vol. 72(4), pages 664-71, November.
- Nag, Ashok K & Mitra, Amit, 2002. "Forecasting Daily Foreign Exchange Rates Using Genetically Optimized Neural Networks," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 21(7), pages 501-11, November.
- Geraint Johnes, 2000. "Up Around the Bend: Linear and nonlinear models of the UK economy compared," International Review of Applied Economics, Taylor & Francis Journals, vol. 14(4), pages 485-493.
- Johansen, Soren, 1995. "Likelihood-Based Inference in Cointegrated Vector Autoregressive Models," OUP Catalogue, Oxford University Press, number 9780198774501.
- Tkacz, Greg, 2001. "Neural network forecasting of Canadian GDP growth," International Journal of Forecasting, Elsevier, vol. 17(1), pages 57-69.
- Johansen, Soren & Juselius, Katarina, 1990. "Maximum Likelihood Estimation and Inference on Cointegration--With Applications to the Demand for Money," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 52(2), pages 169-210, May.
- Fair, Ray C & Shiller, Robert J, 1990. "Comparing Information in Forecasts from Econometric Models," American Economic Review, American Economic Association, vol. 80(3), pages 375-89, June.
- Granger, C. W. J., 1981. "Some properties of time series data and their use in econometric model specification," Journal of Econometrics, Elsevier, vol. 16(1), pages 121-130, May.
- Doornik, Jurgen A & Hendry, David F & Nielsen, Bent, 1998.
" Inference in Cointegrating Models: UK M1 Revisited,"
Journal of Economic Surveys,
Wiley Blackwell, vol. 12(5), pages 533-72, December.
- Jurgen A. Doornik & David F. Hendry & Bent Nielsen, 1998. "Inference in Cointegrating Models: UK M1 Revisited," Journal of Economic Surveys, Wiley Blackwell, vol. 12(5), pages 533-572, December.
- Johansen, Soren, 1988. "Statistical analysis of cointegration vectors," Journal of Economic Dynamics and Control, Elsevier, vol. 12(2-3), pages 231-254.
- William Barnett, 2005.
WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS
200510, University of Kansas, Department of Economics, revised Mar 2005.
- Stracca, Livio, 2001. "Does liquidity matter? Properties of a synthetic divisia monetary aggregate in the euro area," Working Paper Series 0079, European Central Bank.
- Joseph Plasmans & William Verkooijen & Hennie Daniels, 1998. "Estimating structural exchange rate models by artificial neural networks," Applied Financial Economics, Taylor & Francis Journals, vol. 8(5), pages 541-551.
- Pantula, Sastry G., 1989. "Testing for Unit Roots in Time Series Data," Econometric Theory, Cambridge University Press, vol. 5(02), pages 256-271, August.
- Monterola, Christopher, et al, 2002. "Accurate Forecasting of the Undecided Population in a Public Opinion Poll," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 21(6), pages 435-49, September.
- Johansen, Soren, 1992.
"Determination of Cointegration Rank in the Presence of a Linear Trend,"
Oxford Bulletin of Economics and Statistics,
Department of Economics, University of Oxford, vol. 54(3), pages 383-97, August.
- Johansen, S., 1991. "Determination of Cointegration Rank in the Presence of a Linear Trend," Papers 76a, Helsinki - Department of Economics.
- Barnett, William A., 1980. "Economic monetary aggregates an application of index number and aggregation theory," Journal of Econometrics, Elsevier, vol. 14(1), pages 11-48, September.
- JØrgen Wolters & Helmut LØtkepohl, 1998. "A money demand system for German M3," Empirical Economics, Springer, vol. 23(3), pages 371-386.
- A. M. Gazely & J. M. Binner, 2000. "The application of neural networks to the Divisia index debate: evidence from three countries," Applied Economics, Taylor & Francis Journals, vol. 32(12), pages 1607-1615.
- Balkin, Sandy D. & Ord, J. Keith, 2000. "Automatic neural network modeling for univariate time series," International Journal of Forecasting, Elsevier, vol. 16(4), pages 509-515.
- Jane M. Binner & Alicia M. Gazely & Shu-Heng Chen & Bin-Tzong Chie, 2004. "Financial Innovation and Divisia Money in Taiwan: Comparative Evidence from Neural Network and Vector Error-Correction Forecasting Models," Contemporary Economic Policy, Western Economic Association International, vol. 22(2), pages 213-224, 04.
- Hendry, David F, 1980. "Econometrics-Alchemy or Science?," Economica, London School of Economics and Political Science, vol. 47(188), pages 387-406, November.
- Pejman Bahramian & Mehmet Balcilar & Rangan Gupta & Patrick T. kanda, 2014. "Forecasting South African Inflation Using Non-Linear Models: A Weighted Loss-Based Evaluation," Working Papers 201416, University of Pretoria, Department of Economics.
- A. Malliaris & Mary Malliaris, 2013.
"Are oil, gold and the euro inter-related? Time series and neural network analysis,"
Review of Quantitative Finance and Accounting,
Springer, vol. 40(1), pages 1-14, January.
- Malliaris, A.G. & Malliaris, Mary, 2011. "Are oil, gold and the euro inter-related? time series and neural network analysis," MPRA Paper 35266, University Library of Munich, Germany.
- Jane Binner & Rakesh Bissoondeeal & Andrew Mullineux, 2004.
"A Composite Leading Indicator of the Inflation Cycle for the Euro Area,"
Money Macro and Finance (MMF) Research Group Conference 2004
24, Money Macro and Finance Research Group.
- J. M. Binner & R. K. Bissoondeeal & A. W. Mullineux, 2005. "A composite leading indicator of the inflation cycle for the Euro area," Applied Economics, Taylor & Francis Journals, vol. 37(11), pages 1257-1266.
- Oscar Claveria & Enric Monte & Salvador Torra, 2014.
"“A multivariate neural network approach to tourism demand forecasting”,"
AQR Working Papers
201410, University of Barcelona, Regional Quantitative Analysis Group, revised May 2014.
- Oscar Claveria & Enric Monte & Salvador Torra, 2014. "“A multivariate neural network approach to tourism demand forecasting”," IREA Working Papers 201417, University of Barcelona, Research Institute of Applied Economics, revised May 2014.
- Farzan Aminian & E. Suarez & Mehran Aminian & Daniel Walz, 2006. "Forecasting Economic Data with Neural Networks," Computational Economics, Society for Computational Economics, vol. 28(1), pages 71-88, August.
- Tseng, Chih-Hsiung & Cheng, Sheng-Tzong & Wang, Yi-Hsien & Peng, Jin-Tang, 2008. "Artificial neural network model of the hybrid EGARCH volatility of the Taiwan stock index option prices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(13), pages 3192-3200.
- Ryadh M. Alkhareif & William Barnett, 2012.
"Divisia Monetary Aggregates for the GCC Countries,"
WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS
201209, University of Kansas, Department of Economics, revised Aug 2012.
- S. DeVicerte & P. Alvarez & J. Perez & C. Caso, 2008. "Does currency crisis identification matter?," Applied Financial Economics, Taylor & Francis Journals, vol. 18(5), pages 387-395.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Michael McNulty).
If references are entirely missing, you can add them using this form.