Eurostat methodological skills staff survey:

Lessons learned after the 1st wave

Q&A session 9 September 2015 room A2/45 11:00https://ec.europa.eu/eusurvey/runner/MethNet2015

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Eurostat methodological skills staff survey• Why?

To map existing methodological skills within Eurostat

• What for? Understanding better our competencies and how they are grouped

• Who? Open to all staff

• How? Linked with new flexible working conditions in Eurostat

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Background

• Initiative proposed at the end of 2014 by the Eurostat 2020 discussion group B on “Permanent Methodological Development”, chaired by Director of A

• Adopted by the DM seminar in April 2015• Launched in June 2015 by Unit B1 in cooperation with

A2 under new sponsorship of Emanuele Baldacci, Director of B

• First wave during July 2015, open to all ESTAT staff• Still up and running

Aim of this presentation

• Snapshot after the "first wave", network visualisation tools (igraph for R)

• - Respondents• - Dimensions

• methodological areas, statistical domains, tools• training activities, active role

• - Lesson learned • - Next steps

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Competency in R and SAS by methodological areas

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RSAS

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Other

Energy Statistic

Transport

Social Statistics

Science and technology

Prices

National Accounts

International trade

Environmental Statistics

Demography

Business Statistics

Agricultural and Fisheries Statistics

Competency in R and SAS by statistical domains

number of people0 5 10 15

5 1

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3 0

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1 3

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5 8

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RSAS

Other skillsDynamic Factor Analysis

Questionnaire Design

Monte Carlo, sensitivity analysis;

Fuzzy logic

Population size; analytical

hypotheses testing

Regional Statistics/

Geographic information

Land cover and

use

Classifications and metadata standards

Temporal disaggregation

Nowcasting

ArcGIS

Business cycle analysis, S-VARS, G-

VARS

Neural network

Remuneration and Pensions

Cluster analysis

Labour Market

Asylum migratio

n

Fortran, Cobol,Pascal, C

, C++,PHP, Octave

OX-metrics 11

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Active Role

Informed58%

Active40%

No2%

Training delivering experience

No

Yes

Training delivering experience

0 5 10 15 20 25 30 35

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As a trainer elsewhere

As a trainer for in-house courses

As a workshop facilitator

As a ESTP course trainer

As a ESTP course leader

At the university

Training delivering experience

0 5 10 15 20

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Network Visualisation (Areas)

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Network Visualisation (Tools)

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Active role: full networkarea & tools

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Classification of statistical skillsMICROECONOMETRICS MACROECONOMETRICS MULTIDIMENSIONAL

DATA ANALYSISPROCESSES CONCEPTUALISATION

Model based estimation Time series Inferential statistic Statistical confidentiality

Design and optimisation of statistical processes

Econometrics Indicators, composite and synthetic indices

Descriptive statistics Micro-data access

Metadata models and standards

Linear algebra Indices Data analysis Data validation Enterprise architecture

Sampling Seasonal adjustment Big data analytics, Data mining and data science

Data warehousing

Data integration

Survey methodology Administrative data Data processing Information models and standards

Statistical softwareQuality

Data dissemination

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Network of classes

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Class 1MICROECONOMETRICS

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Class 2MACROECONOMETRICS

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Class 3MULTIDIMENSIONAL DATA ANALYSIS

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Class 4PRACTICAL PROCESSES

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Class 5 CONCEPTUALISATION

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Lesson learned

• About half of participants ready to take up an active role

• Strong expertise in Data analysis, Time Series and Econometrics• Most common tools SPSS, SAS and R• More than half have training delivery experience

• Identification of Centre of Competence might be based on a classification

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Next steps

September 2015• Survey link will be kept open, please participate if

you have not done so yet• Eurostat Methodological Network (Yammer Group)

October 2015• New flexible way of working, network layer• DM paper with structured proposal

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…to kick-off the discussion

• Any views and/or interpretation of what you have seen today?

• Do you see gaps in competencies emerging from the survey?