1. New Techniques and Technologies for Statistics Brussels, March 2017
Satellite session on Multi-indicator systems and partially ordered sets Views from Official Statistics
Emanuele Baldacci *, European Commission, Eurostat
@emibaldacci
Dario Buono*, European Commission, Eurostat
@darbuo
*The views expressed are the author’s alone and do not necessarily correspond to those of the corresponding organisations of affiliation

2. Triggers for Socio-economic evaluation
Data-users call for condensed information
Allow multidimensional phenomena to be synthesized.
Need to ensure time and regional comparisons

3. Dashboards proliferation
Pro: Separation of Statistics from Economic Reading
Cons: not always straightforward

4. Dimensionality Reduction
Indicator systems might leads to the need of computing composite indicators and introduce some degree of arbitrariness concerning:
The analytical approach
The choice of the weights
The aggregation technique

5.
This is a non-parametric approach for ranking multi-indicator data sets
Poset theory can help to overcome the conceptual and computational drawbacks of the standard aggregative procedures by exploiting the relational structure of the data, so as to compute evaluation scores in purely ordinal terms.

6. Features for Official Statistics
Based on some Eurostat pilot projects
Poset permits to deal with complex multi-dimensional systems of indicators
Poset allows to derive rankings and synthetic indicators, without variable aggregations
Poset have already been applied in a variety of areas (Refugees' relocation in the EU, European opinions on services, Formal Concept Analysis, Fiscal policies)

7. Drawbacks for Official Statistics
Based on some Eurostat pilot projects
Poset does not have a temporal dimension (all variables refer to a fixed point in time)
Poset is computationally complex and tools are currently under development

8. (1)
Paper on "Complementing scoreboards with composite indicators: the new
business cycle clock", by Mazzi (Eurona 2015).
4 possible applications of POSET to the PEEIs (with mixed results)
detect the presence of cross-sectional effects in financial markets ()
explain the economic phases ()
explain the country ranking with another variable (V)
measure the diffusion of a crisis (?)
The results obtained until now are still preliminary and not very conclusive. What has emerged is that the third application is the easiest to implement, even if the results could be quite obvious, so that its added value will be relatively low. By contrast, the first, second and fourth applications appear to be more challenging due to the fact that some quite complex hypotheses have to be formulated but their informational content from analysts' point of view is expected to be relatively high.

9. POSET@Eurostat (2) Applications of POSETs in macro-economics,
by Ruggeri,Mazzi,Fattore(NTTS 2017)
Case of Regional Competitiveness Index in IT
set of triples; regions are ranked; use of "benchmarking profiles"
The interesting point: no synthetic indicators, incomparability remains but the “distance” between two elements could be quantified
Use of the R package, PARSEC (Partial Orders in Socio-Economics), for implementing the procedure for multidimensional evaluation.

10. Lessons learned The effectiveness of the partial order approach
is particularly evident in the way the weighting and the aggregation problem is addressed and solved with an objective approach.

11. Challenges ahead Computational issues
New skills with deep learning curve
Communication and dissemination of methods and approach

12. Next Steps
Call for scaled-up partnership between official statisticians, researchers and analysts
Further research, in order to improve the efficiency of algorithms to avoid too heavy numerical computations
Education of users about the possibilities and limitations of using indicators including communication of detailed information on the underlying assumption and selection method Lisbon Memorandum, (DGINS Sept 2015)

13. Thanks!