| 1. |
- Brännäs, Kurt, et al.
(författare)
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A new approach to modelling and forecasting monthly guest nights in hotels
- 2002
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Ingår i: International Journal of Forecasting. - : Elsevier. - 0169-2070 .- 1872-8200. ; 18:1, s. 19-30
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Tidskriftsartikel (refereegranskat)abstract
- Starting from a day-to-day model on hotel specific guest nights we obtain an integer-valued moving average model by cross-sectional and temporal aggregation. The two parameters of the aggregate model reflect mean check-in and the check-out probability. Letting the parameters be functions of dummy and economic variables we demonstrate the potential of the approach in terms of interesting interpretations. Empirical results are presented for a series of Norwegian guests in Swedish hotels. The results indicate strong seasonal patterns in both mean check-in and in the check-out probability. Models based on differenced series are preferred in terms of goodness-of-fit. In a forecast comparison the improvements due to economic variables are small. © 2002 International Institute of Forecasters. Published by Elsevier Science B.V.
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| 2. |
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| 3. |
- Öller, Lars-Erik, et al.
(författare)
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The accuracy of European growth and inflation forecasts
- 2000
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Ingår i: International journal of forecasting. - : Elsevier B.V. - 1872-8200 .- 0169-2070. ; 16:3, s. 293-315
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Tidskriftsartikel (refereegranskat)abstract
- One-year-ahead forecasts by the OECD and by national institutes of GDP growth and inflation in 13 European countries are analysed. RMSE was large: 1.9% for growth and 1.6% for inflation. Six (11) OECD and ten (7) institute growth forecast records were significantly better than an average growth forecast (the current year forecast). All full record-length inflation forecasts were significantly better than both naive alternatives. There was no significant difference in accuracy between the forecasts of the OECD and the institutes. Two forecasts were found to be biased and one had autocorrelated errors. Directional forecasts were significantly better than a naive alternative in one-half of the cases. Overall, inflation forecasts were significantly more accurate than growth forecasts, and in contrast to growth forecasts, they generally improved over time. This has implications for economic policy. Positively biased revisions reveal large errors in data.
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| 4. |
- Andersson, Michael K.
(författare)
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Do long-memory models have long memory?
- 2000
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Ingår i: International Journal of Forecasting. - : Elsevier: 24 months. - 0169-2070. ; 16:1, s. 121-124
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- This paper calculates the memory of fractionally integrated ARMA(1,d, 1) processes. It is shown that fractional integration can enhance the memory of common ARMA processes enormously, but also that this is not necessarily the case. Very long memory is found for positively fractionally integrated processes with large positive autoregressive parameters. On the contrary, large negative AR parameters absorb the memory generated by a positive differencing parameter to a great extent. A moving average parameter may also reduce the memory substantially, even if the parameter alone causes virtually no memory.
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| 5. |
- Löf, Mårten, et al.
(författare)
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Forecasting performance of seasonal cointegration models
- 2002
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Ingår i: International Journal of Forecasting. - : Elsevier. - 0169-2070. ; 18:1, s. 31-44
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- Forecasts from two different seasonal cointegration specifications are compared in an empirical forecasting example and in a Monte Carlo study. The two seasonal cointegration specifications are the one proposed by Lee [Journal of Econometrics 54 (1992) 1], with a parameter restriction included at the annual frequency, and the model proposed by Johansen and Schaumburg [Journal of Econometrics 88 (1998) 301], with a general specification for the complex root frequency, respectively. In the empirical forecasting example we also include a standard cointegration model based on first differences and seasonal dummies and analyze the effects of restricting or not restricting seasonal dummies in the seasonal cointegration models. While the Monte Carlo results favor the specification suggested by Johansen and Schaumburg, and definitely so if larger sample sizes are considered, we do not find such clear cut evidence in the empirical example.
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| 6. |
- Löf, Mårten, et al.
(författare)
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On forecasting cointegrated seasonal time series
- 2001
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Ingår i: International Journal of Forecasting. - : Elsevier. - 0169-2070. ; 17:4, s. 607-621
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- We analyze periodic and seasonal cointegration models for bivariate quarterly observed time series in an empirical forecasting study. We include both single equation and multiple equation methods for those two classes of models. A VAR model in first differences, with and without cointegration restrictions, and a VAR model in annual differences are also included in the analysis, where they serve as benchmark models. Our empirical results indicate that the VAR model in first differences without cointegration is best if one-step ahead forecasts are considered. For longer forecast horizons however, the VAR model in annual differences is better. When comparing periodic versus seasonal cointegration models, we find that the seasonal cointegration models tend to yield better forecasts. Finally, there is no clear indication that multiple equations methods improve on single equation methods.
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