2. 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’

3. 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
Developed using MarketMap/TimeIQ (Java toolkit) to load and download MarketMap objects from/into databases

4. 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

5. 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.

6. 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: [ ]
General specification:
RSA0
Predefined OUTLIERS
LS , LS , LS , LS , LS
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)

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

8. 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_ 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

9. 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: [ ]
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)

10. SOME PRODUCTION EXAMPLES OF ($Fme2JDp) in “FACTORY” MODE
Industrial Production Index for Spain (PI): General index and by branch of activity
seriesSpan=between( / ),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)= f,phi(2)= f,Phi(3)= f,th(1)= f,bth(1)= f

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

12. 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

13. 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

14. THANK YOU FOR YOUR ATTENTION