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An estimation of the Euro Area potential output with a semi-structural multivariate Hodrick-Prescott filter. (2004). Lemoine, Matthieu ; Chagny, Odile .
In: Working Papers.
RePEc:hal:wpaper:hal-00972840.

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  1. Real Time Estimation of Potential Output and Output Gap for the Euro-Area : Comparing Production Function with Unobserved Components and SVAR Approaches. (2008). Lemoine, Matthieu ; Veroni, Paola ; Reynes, Frederic ; Mazzi, Gian Luigi .
    In: Working Papers.
    RePEc:hal:wpaper:hal-01027422.

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  2. The (Ir)relevance of the NRU for Policy Making: The Case of Denmark. (2006). Sala, Hector ; Salvador, Pablo ; Karanassou, Marika.
    In: IZA Discussion Papers.
    RePEc:iza:izadps:dp2397.

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  1. 10Diebold and Mariano (1995) initially proposed an estimate of ˆ V (d) that was not always positive semi-definite.
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  2. An estimation of the euro area potential output with a semi-structural HPMV filter Appendices A Description of the dataset The database is quarterly. The sample covers the period extending from the first quarter of 1978 to the fourth quarter of 2002. Countries covered are Germany, France, Italy, the Netherlands and Spain. As far as possible, data have been taken from the Eurostat national accounts. When necessary, data have been back-calculated or are taken from the national sets of accounts. Specific attention has been paid to using the same concepts and definitions for each country. EU5 data are calculated as the aggregation of the five national data. German data have been retropolated for the years preceding the reunification (first quarter of 1978 to fourth quarter of 1990) using the data set published by the Statistisches Bundesamt, where national accounts aggregates for west Germany have been harmonized with the ESA95 concepts and definitions.
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  6. Both sources of uncertainty are also characterised. Orphanides and Van Norden (1999), Cayen and Van Norden (2002) proposed a battery of descriptive statistics but no formal testing in order to evaluate the estimates of the output gap using real time data, final data or quasi-real time data.
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  7. BOURDIN J. and P. MARINI, 2003, “Une d ecennie de r eformes fiscales en Europe : la France ` a la traˆ ine”, Rapport du S enat No 343.
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  11. Capital stock in the business sector: capital stock in constant prices (converted into billions of ECUs of 1995) of the total economy excluding government and housing taken from the national accounts for Germany, and France. OECD time series converted into billions of 1995 ECUs for Italy, the Netherlands, and Spain. Annual data interpolated to quarterly data. B Measures of forecasting performance We test the forecasting performance of the different measures of the output gap by the root mean squared error (RMSE) for multi-step ahead inflation forecasts.7 All models have hence been 7Other criteria can be used, as for instance the mean absolute error. Results are robust to alternative measures of forecasting performances. O. Chagny and M. Lemoine recursively estimated from 1978Q1 to i=1996Q4...2002Q3, and out-of-samples forecasts from 1 to 10 quarters ahead have been computed over the period 1997Q1-2002Q4.
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  27. Harvey et al. (1997), Clark and McCracken (2001) show that this modified test statistic performs better than the DM test statistic even if it still performs poorly in finite samples (Clark and McCracken, 2001). They also show that the power of the test is improved, when p-values are computed with a Student distribution. 8In the case of SVAR models, we use an AR(3) in first differences in order to be consistent. 9It is to to be noted that the significance of the relative mean squared error (RRMSE) is not directly tested. Indeed, the one-sided test H0 :RRMSE=1 againt H0 :RRMSE < 1 can be used and the corresponding p-values measure type-I error associated with the test.
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  30. In this paper, a consistent estimate of the standard deviation is constructed from a weighted sum of the available sample autocovariances of the loss differential vector - the difference between the squared forecast error of the models and that of the reference model. Chosen weights insure that the matrix ˆ V (d) is positive semi-definite (Newey and West, 1987).
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  37. ORPHANIDES A. and S. VAN NORDEN, 2003, “The reliability of inflation forecasts based on output gap estimates in real time”, CIRANO working paper.

  38. P t=k+1 (dt − d)(dt−k − d).10 However, as is noted by Diebold and Mariano (1995), simulation evidence suggests that their test could be seriously over-sized in the case of two-steps ahead prediction and the problem become more acute as the forecasting horizon increases. In this respect, Harvey, Leybourne and Newbold (1997) proposed employing an approximately unbiased estimator of the variance of d, which leads to a modified Diebold-Mariano test statistic: S∗ = T + 1 − 2h + T−1 h(h − 1) T SDM .
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  39. PESARAN M.H. and A. TIMMERMANN, 1992, “A simple nonparametric test of predictive performance”, Journal of Business and Economic Statistics, Vol. 10, pp561-56.

  40. PROIETTI T., A. MUSSO and T. WESTERMANN, 2002, “Estimating potential output and the output gap for the euro area: a Model-Based Production Function Approach”, ECB Working paper.

  41. Specifically, Orphanides and Van Norden (2003) find large discrepancies between the sequentially estimated measures of the output gap when compared with final estimates. The disparities are explained by the unreliability of the models in estimating end of sample values and to a lower extent by data revisions. However, Orphanides and Van Norden (2003) mainly compare univariate methods. Camba-Mendez and Rodriguez-Palenzuela (2003) assess the consistency of output gap estimates by implementing the Pesaran and Timmermann (1992) test of directional change and a Fisher test to compare the variances of recursively estimated output gap sequence and the finally estimated sequence. Camba-Mendez and Rodriguez-Palenzuela (2003) show that the concern of reliability of estimates may be to some extent overdone in the Euro-area. However, Van Norden (2003) casts some doubts on their conclusion. O. Chagny and M. Lemoine D Tables and graphs
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  42. St AMANT P. and S. VAN NORDEN, 1997, “Measurement of the output-gap: a discussion of recent research at the Bank of Canada”, Bank of Canada Technical Report No 79.

  43. UNSTLER G., 2002, “The information content of real-time output gap estimates. An application to the euro area”, ECB Working Paper.
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