Meyler, Aidan and Kenny, Geoff and Quinn, Terry (1998): Forecasting irish inflation using ARIMA models. Published in: Central Bank and Financial Services Authority of Ireland Technical Paper Series , Vol. 1998, No. 3/RT/98 (December 1998): pp. 1-48.
Download (165kB) | Preview
This paper outlines the practical steps which need to be undertaken to use autoregressive integrated moving average (ARIMA) time series models for forecasting Irish inflation. A framework for ARIMA forecasting is drawn up. It considers two alternative approaches to the issue of identifying ARIMA models - the Box Jenkins approach and the objective penalty function methods. The emphasis is on forecast performance which suggests more focus on minimising out-of-sample forecast errors than on maximising in-sample ‘goodness of fit’. Thus, the approach followed is unashamedly one of ‘model mining’ with the aim of optimising forecast performance. Practical issues in ARIMA time series forecasting are illustrated with reference to the harmonised index of consumer prices (HICP) and some of its major sub-components.
|Item Type:||MPRA Paper|
|Original Title:||Forecasting irish inflation using ARIMA models|
|Keywords:||NAIRU; inflation; unobserved components; kalman filter|
|Subjects:||C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C53 - Forecasting and Prediction Methods; Simulation Methods
C - Mathematical and Quantitative Methods > C6 - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling > C61 - Optimization Techniques; Programming Models; Dynamic Analysis
C - Mathematical and Quantitative Methods > C2 - Single Equation Models; Single Variables > C22 - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models
E - Macroeconomics and Monetary Economics > E0 - General > E00 - General
E - Macroeconomics and Monetary Economics > E3 - Prices, Business Fluctuations, and Cycles > E37 - Forecasting and Simulation: Models and Applications
C - Mathematical and Quantitative Methods > C6 - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling > C62 - Existence and Stability Conditions of Equilibrium
|Depositing User:||Aidan Meyler|
|Date Deposited:||03. Nov 2008 14:34|
|Last Modified:||11. Feb 2013 17:33|
Akaike, H., 1974. “A New Look at Statistical Model Identification”, IEEE Transactions on Automatic Control, AC-19, pp. 716-723.
Anderson, O., 1976. Time Series Analysis and Forecasting, London: Butterworths
Banerjee, A., J. Dolado, J. Galbraith and D. Hendry, 1993. Co-integration, Error Correction and the Econometric Analysis of Non-Stationary Data, Advanced Texts in Econometrics, Oxford University Press: Oxford.
Beguin, J-M., C. Gourieroux and A. Monfort, 1980. “Identification of a Mixed Autoregressive Moving Average Process: The Corner Method”, in O.D. Anderson (ed.) Time Series, North-Holland: Amsterdam.
Box, G. and G. Jenkins, 1976. Time Series Analysis: Forecasting and Control, Holden Day: San Francisco.
Bryan, M., and S. Cecchetti, 1993. “Measuring Core Inflation”, NBER Working Paper Series No. 4303, March.
Cecchetti, S., 1995. “Inflation Indicators and Inflation Policy”, in B. Bernanke and J. Rotemberg (eds.), NBER Macroeconomic Annual 1995, MIT Press: London.
Chatfield, C., 1979. “Inverse Autocorrelations”, Journal of the Royal Statistical Society, Series A, Vol. 142, pp. 363-377.
Dotsey, M. and P. Ireland, 1996. “The Welfare Cost of Inflation in General Equilibrium”, Journal of Monetary Economics, Vol. 37, pp. 29-47.
European Central Bank (ECB), 1998. “A Stability-Oriented Monetary Policy Strategy for the ESCB”, Press Release, 13 October.
Feldstein, M., 1996. “The costs and benefits of going from low inflation to price stability”, NBER Working Paper No. 5469, February.
Frain, J., 1995. “Econometrics and Truth”, Central Bank of Ireland Technical Paper 2/RT/95.
Gómez, V. and A. Maravall, 1998. “Automatic Modelling Methods for Univariate Series”, Banco de España Working Paper No. 9808.
Gray, H., G. Kelley and D. McIntire, 1978. “A New Approach to ARMA Modelling”, Communications in Statistics, B7(1), pp. 1-77.
Hamilton, J., 1994. Time Series Analysis, Princeton University Press: Princeton. 46
Hannan, E., 1980. “The Estimation of the Order of ARMA Process”, Annals of Statistics, Vol. 8, pp. 1071-1081.
Harris, R., 1995. Using Cointegration Analysis in Econometric Modelling, Prentice Hall: London.
Kenny, G., A. Meyler and T. Quinn, 1998. “Bayesian VAR Models for Forecasting Irish Inflation”, Central Bank of Ireland Technical Paper 4/RT/98.
Litterman, R., 1986. “Forecasting with Bayesian Vector Autoregressions - Five Years of Experience”, Journal of Business and Economic Statistics, January, No. 1, Vol. 4, pp. 25-38.
Ljung, G. and G. Box, 1978. “On a Measure of Lack of Fit in Time Series Models”, Biometrika, Vol. 66, pp. 67-72.
Meyler, A., G. Kenny and T. Quinn, 1998. “A Note on the Construction of an Historical (November 1975 - May 1998) HICP Series for Ireland”, Central Bank of Ireland Research Department Memorandum, 1/RDM/98.
Mills, T., 1993. The Econometric Modelling of Financial Time Series, Cambridge University Press: Cambridge.
Mills, T., 1990. Time Series Techniques for Economists, Cambridge University Press: Cambridge.
Perron, P., 1989. "The Great Crash, the Oil Price Shock, and the Unit Root Hypothesis", Econometrica, Vol. 57, No 6, pp. 1361-1401.
Poskitt, D. and A. Tremayne, 1987. “Determining a Portfolio of Linear Time Series Models”, Biometrika, 74, pp. 125-137.
Schwarz, G., 1978. “Estimating the Dimension of a Model”, Annal of Statistics, Vol. 6, pp. 461-464.
Stockton, D., and J. Glassman, 1987. “An Evaluation of the Forecast Performance of Alternative Models of Inflation”, Review of Economics and Statistics, Vol. 69, No. 1, February, pp. 108-117.
Tsay, R. and G. Tiao, 1985. “Use of Canonical Analysis in Time Series Model Identification”, Biometrika, Vol. 72, No. 2, pp. 299-315.