1. Luxembourg, 16/4/2013

2.  Data providers  IT improvements  Methodological improvements

3.  SDMX ◦.STAT (OECD) compatible  Automatic change of frequency ◦ Excel, ODBC...  Optimization ◦ Caching...  Plug-ins ◦ Access databases  File-based (Access not needed) ◦ Random Arima ◦ SAS

4.  Correction of bugs, improvements of many features ◦ Workspaces (storage...) ◦ Graphical components (charts, grids...) ◦ Properties Window ◦...  Calendars and user-defined variables (graphical interface) ◦ Demetra+ (not yet in the cruncher)

5.  X11 ◦ Diagnostics  Calendars ◦ Documentation  Arima estimation ◦ Stdev of parameters ( + scores) ◦ Optimisation procedure

6.  Problem: ◦ The likelihood function of complex models (AR and MA parameters) have often several local maxima. ◦ Tramo, X12 and JD+(1.1.0) can lead to different solutions ◦ No "best" solution (with acceptable performances) ◦ The solution is more dependant on the starting point than on the Levenberg-Marquardt variant.  Solution in 1.2.1 ◦ Several starting points

7. Comparison between:JD+ / TSJD+ / X12TS / X12 Model: Arima [+calendar effects] JD+ better TS better = JD+ better X12 better = TS better X12 better = (0,1,1)(0,1,1)+TD70% 100%0% 100%0% 100% (1,1,1)(1,1,1)+TD73%0%97%2%0%98%0%2%98% (2,1,1)(0,1,1)+TD74%1%95%7%0%93%4%1%95% (3,1,1)(0,1,1)18%2%80%11%1%88%6%11%83% (1,1,3)(0,1,1)19%1%80%14%1%85%5%11%83% [1] [1] "Better" means significantly higher likelihood (and thus different estimates).

8. Regular polynomials Seasonal polynomial Log- Likelihood Auto-regressive Moving average Moving average φ(1)φ(2)φ(3)θ(1)Θ(1) X12-0.4490.124-0.079-0.715-0.733-706.27 Tramo1.0890.4240.1360.931-0.746-703.31 JD+0.7610.326-0.0310.622-0.779-702.57 Estimation for a (3 1 1)(0 1 1) model

10. Tramo-Seats and JD+. SA series based on the same model (different parameters estimation)

11.  Comparison is not so simple  Impact of the estimation problem on the whole AMI ◦ Differencing: (1 x 1)(1 x 1) ◦ Arma identification ◦ Last resort model (3 1 1)(0 1 1)  Comparability depends on the set of series: ◦ Simple models (airline...) -> Highly comparable results ◦ Complex models -> Many different results

12.  Tramo-Seats ◦ Integration of the last modifications of the core engine.  ?