JDemetra+ (1.2.1)Luxembourg, 16/4/2013

Data providers IT improvements Methodological improvements

What's new ?

SDMX◦ .STAT (OECD) compatible

Automatic change of frequency ◦ Excel, ODBC...

Optimization◦ Caching...

Plug-ins ◦ Access databases

File-based (Access not needed)◦ Random Arima◦ SAS

Data providers

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)

IT improvements

X11◦ Diagnostics

Calendars◦ Documentation

Arima estimation◦ Stdev of parameters ( + scores)◦ Optimisation procedure

Methodological improvements

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

Optimisation procedure

Comparison between: JD+ / TS JD+ / X12 TS / X12

Model: Arima [+calendar effects]

JD+ better

TSbetter = JD+

betterX12 better = TS

betterX12 better =

(0,1,1)(0,1,1)+TD7 0% 0% 100% 0% 0% 100% 0% 0% 100%

(1,1,1)(1,1,1)+TD7 3% 0% 97% 2% 0% 98% 0% 2% 98%

(2,1,1)(0,1,1)+TD7 4% 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] "Better" means significantly higher likelihood (and thus different estimates).

Regular polynomials Seasonal polynomial

Log-LikelihoodAuto-regressive Moving

averageMoving average

φ(1) φ(2) φ(3) θ(1) Θ(1)

X12 -0.449 0.124 -0.079 -0.715 -0.733 -706.27

Tramo 1.089 0.424 0.136 0.931 -0.746 -703.31

JD+ 0.761 0.326 -0.031 0.622 -0.779 -702.57

Estimation for a (3 1 1)(0 1 1) model

01/0

1/19

91

01/1

0/19

91

01/0

7/19

92

01/0

4/19

93

01/0

1/19

94

01/1

0/19

94

01/0

7/19

95

01/0

4/19

96

01/0

1/19

97

01/1

0/19

97

01/0

7/19

98

01/0

4/19

99

01/0

1/20

00

01/1

0/20

00

01/0

7/20

01

01/0

4/20

02

01/0

1/20

03

01/1

0/20

03

01/0

7/20

04

01/0

4/20

05

01/0

1/20

06

01/1

0/20

06

01/0

7/20

07

01/0

4/20

08

01/0

1/20

09

01/1

0/20

0980

90

100

110

120

130

140

TramoJD+

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

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

Consequences

Tramo-Seats◦ Integration of the last modifications of the core

engine. ?

Next steps