TYPES of seasonal adjustment processes in banco de españa Use for several relevant economic indicators. Fine-tuning of model specification, taking care of calendar-effects estimation, outliers, etc. Using JD+ Graphical User Interface Seasonal adjustment ‘laboratory’ Use for regular mass and automated production of thousands of time series. Use in production of relevant indicators previously analysed in the ‘laboratory’ Using the MarketMap-JD+ interface ($Fme2JDp) as a MarketMap native command. Seasonal adjustment ‘factory’

Interface for seasonal adjustment ‘laboratory’ Characteristics of THE INTERFACE BETWEEN MarketMap AND DEMETRA+ ($Fme2JDp) Interface for seasonal adjustment ‘laboratory’ $genSDMX is a MarketMap(Fame/4GL application) Interface for seasonal adjustment ‘factory’ $Fme2JDp is a Java application Encapsulating JDemetra+ statistical algorithms (following the approach of the examples of jdemetra-hello. See https://github.com/nbbrd/jdemetra-hello) Developed using MarketMap/TimeIQ (Java toolkit) to load and download MarketMap objects from/into databases

seasonal adjustment ‘laboratory’ using JD+ GUI. Interface: $genSDMX The time series are downloaded from MarketMap databases to a SDMX-ML format file This file is loaded in JD+ (GUI) using the SDMX data providers The users test several models and choose the best one

seasonal adjustment ‘factory’ using MarketMap-JD+. Interface: $Fme2JDp The analysts, using MarketMap scripting language, automated the SA of a large amount of series stored in several MarketMap databases. The series signal extraction process is performed and the components and effects are recovered as time series in an output MarketMap database. The validation test and some graphics are written in a Windows folder as an HTML document. All the calculations and processes between MarketMap and JD+ are done on the fly. There are no files involved.

SOME PRODUCTION EXAMPLES OF ($Fme2JDp) in “FACTORY” MODE Spanish Harmonized Index of Consumer Prices (HICP): Indices of subclasses. Main features Monthly Process Concurrent SA and forecasts process integrated in a more general analysis of the monitoring of inflation evolution. (including reports in MarketMap (Fame) ) Loaded directly from BIE database (Short-term ESCB-wide information database) 99 Time series Estimation span: [1-2010 - 2-2019] General specification: RSA0 Predefined OUTLIERS LS.2010-07-01, LS.2010-08-01, LS.2010-09-01, LS.2012-09-01, LS.2012-10-01 Performance of the interface $Fme2JDp (time processing 99 TS) BdE internal network: 5 minutes (3 seconds per series) Remote connection to BdE-net : 13 minutes. (8 seconds per series)

SOME PRODUCTION EXAMPLES OF ($Fme2JDp) in “FACTORY” MODE Spanish Harmonized Index of Consumer Prices (HICP): Indices of subclasses MarketMap (Fame) Script. (JD+ block)

SOME PRODUCTION EXAMPLES OF ($Fme2JDp) in “FACTORY” MODE Spanish Harmonized Index of Consumer Prices (HICP): Indices of subclasses Main results Detailed OUPUT in a HTML format in a local directory Fme2JD_RH_M.ES.N.FOODUN.4.INX_20190303115041.html One HTML file per time series processed Per each original 31 derived time series are generated with the different output transformations and components (calendars and outliers effects, etc.) RH_M.ES.N.FOOD00.4.IN.Y Original series and forecast of the original series RH_M.ES.N.FOOD00.4.INX.TTrend/cycle and forecasts of the trend/cycle RH_M.ES.N.FOOD00.4.INX.SASeasonally adjusted series (including deterministic effects) and forecasts of the seasonally adjusted series RH_M.ES.N.FOOD00.4.INX.SSeasonal component (including deterministic effects) and forecasts of the seasonal component … 9 scalars variables generated with the ARIMA model specification Whole output saved in MarketMap (Fame) database All results are generated on the fly Not files involved for the different components and scalars

SOME PRODUCTION EXAMPLES OF ($Fme2JDp) in “FACTORY” MODE Industrial Production Index for Spain (PI): General index and by branch of activity Main features 13 Time Series Estimation span: [1-1992 - 12-2018] One specific model per TS, including predefined specific calendar effects Under revision and implementation in a monthly regular analysis (SA and forecasts) and monitoring report process. Calendar effects particularized by component. Weighted by Gross Value Added. Loaded from MarketMap (Fame) (user database) Input Specification in a TXT File “scanned” by MarketMap (Fame)

SOME PRODUCTION EXAMPLES OF ($Fme2JDp) in “FACTORY” MODE Industrial Production Index for Spain (PI): General index and by branch of activity seriesSpan=between(1995-01-01/2018-12-31),USERVARS={(DIAS=dias.lab.m)/(FJUE=f.gen_jue)/(HSS=HSS)}, TSREGRESIONVARS={(DIAS[0:0]SERIES)/(FJUE[0:0]SERIES)/(HSS[0:0]SERIES)},npred=24,P=3,D=1,Q=1,BP=0,BD=1,BQ=1,phi(1)=-0.4274f,phi(2)=-0.3437f,Phi(3)=-0.1414f,th(1)=-0.9424f,bth(1)=-0.3103f

SOME PRODUCTION EXAMPLES OF ($Fme2JDp) in “FACTORY” MODE Industrial Production Index for Spain (PI): General index and by branch of activity MarketMap (Fame) SCRIPT

SOME EXAMPLES OF use of ($Fme2JDp) in FACTORY MODE Industrial Production Index for Spain (PI): SA General index and by branch of activity MarketMap (Fame) SCRIPT

SOME EXAMPLES OF use of ($Fme2JDp) in FACTORY MODE Industrial Production Index for Spain (PI): General index and by branch of activity GENERAL INDEX OUTPUT

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