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Course Seasonal Adjustment of Economic Data
  • DATE:
    April 24-28, Mexico City, Mexico.
  • Deadline registration date:
    April 7, 2017.
    CEMLA and Deutsche Bundesbank.
    Introduction: overview, aim of seasonal adjustment, definition of seasonality. X-11 core: basic principle. X-11 core: further issues. Win X-13: structure, data management, installation, configuration, additional tools. Examples: specification file, black box seasonal adjustment, automatic selection of X-11 filters. RegARIMA pre-treatment: basic modelling framework, regression equation, outliers, calendar effects. RegARIMA pre-treatment: time series basics, ARIMA equation. Examples: outliers, calendar effects, automatic ARIMA model identification. Examples: user customisation, time series submitted by participants. Quality control: tests for presence of seasonality, M- and Q-statistics, graphical tools. JDemetra+: a new open source tool for seasonal adjustment. JDemetra+ in practice: mass production, additional tools. Examples: quality control, multi-processing. SEATS core: basic idea. Examples: ARIMA model-based seasonal adjustment. Seasonal adjustment of aggregates: direct vs indirect approach. Examples: aggregate time series, Win X-13 wizard, problematic cases, metafiles. Revision policies.
  • Objective:
    Enable participants to understand the basics of X-13 ARIMA-SEATS and Jdemetra+, work with the programs and interpret the results in economic terms.
    Economists or statisticians who are interested in seasonal adjustment and, in particular, in the application of X-13 ARIMA-SEATS, the successor to X-12 ARIMA, widely used at central banks, statistics institutes, and other related institutions.
    English with simultaneous translation to Spanish.
    René A. Maldonado G.
    Remittances and Financial Inclusion Coordinator
    Phone: +52 (55) 5061-6672 and +52 (55) 5061-6663
    E- mail: rmaldonado@cemla.org, Cc: mramirez@cemla.org








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