Is TRAMO-SEATS automatic identification of Reg-ARIMA ... - Cemfi

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But what about REAL SERIES?Generating process is unknown. Is a reg-ARIMA model a reasonableapproximation?(Real world is always harder than simulated one.)Mixed set of monthly seriesApprox. # of seriesFTI European countries (Eurostat) 6500US series (BLS, USBC) 3300Spanish series (INE) 1500Other (multiple sources) 2000Dominant groups: FTI, employment US (1800)Rest: smaller groups All categoriesBesides FTI and unemployment, national accounts,manufacturing, housing and construction, monetary series,industrial production, price indices, sales and inventories,public finance, tourism and travel, agriculture and food,energy, health, survey data, among other.Also: SA, MO. Many countries (Africa, Asia, Australia, Europe, North andSouth America)Length: [60 – 600] observations.31
Table 11: GeneralGroup# observ-Average# of% logs Average #Average #% withper-serielengthseriesparameters/outliers/sercalendarsereffect1 60 – 110 92 3479 82.5 2.1 0.8 23.22 111 – 160 126 3885 91.1 2.2 1.3 70.83 161 – 210 173 2945 91.3 2.3 1.6 72.64 211 – 260 229 1817 80.7 2.2 2.5 28.75 261 – 360 290 1038 84.8 2.4 2.8 60.7TOTAL (1 to 5) 155 13164 87.0 2.2 1.5 52.06 361 – 600 496 527 71.4 3.0 5.9 42.1TOTAL (1 to 6): 13691 Longer series highly unfrequent.Only 527.Besides: results deteriorate considerably.Mostly to illustrate which problems arise with longer series.TOTALS AVERAGES do not include Group 6. They refer to the 13164series that are not longer than 30 years. FTI in groups 1, 2 and 3.US series in all, mostly 1 and 4 (also 3).Spanish series in all, mostly 4 and 5.Other series in 2, 5, 1. Mixed set, with much variation in series behavior. Not an easy set!32
Page 1: April 2012Is TRAMO-SEATS automatici
Page 5 and 6: (2) Components in STSM approach: al
Page 8 and 9: REG-ARIMA model:
Page 10 and 11: AUTOMATIC MODEL IDENTIFICATION (TRA
Page 12 and 13: Models:A. AIRLINE-TYPE MODELS (8500
Page 14 and 15: . Non-stationary Orders 1 0.7
Page 16 and 17: 1 0.3 B x 1 0.6 B 1 0.3 B
Page 18 and 19: 16% are stationary (40% of them are
Page 20 and 21: Table 2:Errors in the detection-of-
Page 22 and 23: Next:AODCTable 3:Average number of
Page 24 and 25: Results: For the 25000 series with
Page 26 and 27: Errors in orders of differencing Gr
Page 28 and 29: All tests are carried at the 1% (ap
Page 30 and 31: Table 10:Correct Identification of
Page 34 and 35: Next:Results from TSW+ purely autom
Page 36 and 37: Table 14: % Reduction in residual S
Page 38 and 39: SEATS will reduce it further (throu
Page 40 and 41: Table 17: ARMA parametersGroup (by
Page 42 and 43: Table 19:Real series: Model-diagnos
Page 44 and 45: :- For all groups 99%. and con
Page 46 and 47: OutliersResidual Autocorrelation116
Page 48 and 49: OutliersResidual Autocorrelation%38
Page 50 and 51: %2625242322212019181716151413121110
Page 52 and 53: SEASONALITY AND SEASONAL ADJUSTMENT
Page 54 and 55: SEATS decomposes the series into co
Page 56 and 57: Computational failure: 0%.Misspecif

Is TRAMO-SEATS automatic identification of Reg-ARIMA ... - Cemfi

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