![Page 1: Improving the quality of European monthly unemployment statistics Nicola Massarelli, Eurostat Q2014 - European Conference on Quality in Official Statistics](https://reader036.vdocuments.net/reader036/viewer/2022062322/56649ea95503460f94baddab/html5/thumbnails/1.jpg)
Improving the quality of European monthly unemployment statistics
Nicola Massarelli, Eurostat
Q2014 - European Conference on Quality in Official Statistics
Vienna, 3-5 June 2014
![Page 2: Improving the quality of European monthly unemployment statistics Nicola Massarelli, Eurostat Q2014 - European Conference on Quality in Official Statistics](https://reader036.vdocuments.net/reader036/viewer/2022062322/56649ea95503460f94baddab/html5/thumbnails/2.jpg)
KEY WORDS
TIME SERIES
2
QUALITY FRAMEWORK
UNEMPLOYMENT RATES
![Page 3: Improving the quality of European monthly unemployment statistics Nicola Massarelli, Eurostat Q2014 - European Conference on Quality in Official Statistics](https://reader036.vdocuments.net/reader036/viewer/2022062322/56649ea95503460f94baddab/html5/thumbnails/3.jpg)
Main features ILO unemployment rates and levels
Total, plus age and gender breakdown
NSA, SA, TREND
Monthly, quarterly, yearly
T+30 days
EU28, EA18, MS
Levels, M-M and Y-Y changes
3
![Page 4: Improving the quality of European monthly unemployment statistics Nicola Massarelli, Eurostat Q2014 - European Conference on Quality in Official Statistics](https://reader036.vdocuments.net/reader036/viewer/2022062322/56649ea95503460f94baddab/html5/thumbnails/4.jpg)
Current production
Ownership: about 50-50 Eurostat-MS
3 main methods for unadjusted series
Pure monthly LFS
3 month rolling quarters of LFS data
Temporal disaggregation (Quarterly LFS + monthly administrative data)
Publication of adjusted series: SA, but trends for 4 countries
4
![Page 5: Improving the quality of European monthly unemployment statistics Nicola Massarelli, Eurostat Q2014 - European Conference on Quality in Official Statistics](https://reader036.vdocuments.net/reader036/viewer/2022062322/56649ea95503460f94baddab/html5/thumbnails/5.jpg)
How temporal disaggregation works
5
0
50
100
150
200
250
300
350
QLFS Administrative Final Forecast
Bulgaria, number of male unemployed aged 25-74, NSA (thousands)
![Page 6: Improving the quality of European monthly unemployment statistics Nicola Massarelli, Eurostat Q2014 - European Conference on Quality in Official Statistics](https://reader036.vdocuments.net/reader036/viewer/2022062322/56649ea95503460f94baddab/html5/thumbnails/6.jpg)
Quality concerns
Volatility
Revisions
Turning points identification
Timeliness
6
![Page 7: Improving the quality of European monthly unemployment statistics Nicola Massarelli, Eurostat Q2014 - European Conference on Quality in Official Statistics](https://reader036.vdocuments.net/reader036/viewer/2022062322/56649ea95503460f94baddab/html5/thumbnails/7.jpg)
Developing a quality framework
Goal:
Provide acceptance criteria
Compare series
Structure:
Define appropriate indicators for each quality dimension
Synthetic indicator vs. scoreboard
Acceptance thresholds
7
![Page 8: Improving the quality of European monthly unemployment statistics Nicola Massarelli, Eurostat Q2014 - European Conference on Quality in Official Statistics](https://reader036.vdocuments.net/reader036/viewer/2022062322/56649ea95503460f94baddab/html5/thumbnails/8.jpg)
Volatility: big foot effect
8
![Page 9: Improving the quality of European monthly unemployment statistics Nicola Massarelli, Eurostat Q2014 - European Conference on Quality in Official Statistics](https://reader036.vdocuments.net/reader036/viewer/2022062322/56649ea95503460f94baddab/html5/thumbnails/9.jpg)
Volatility: pitching & roller coaster effects
9
![Page 10: Improving the quality of European monthly unemployment statistics Nicola Massarelli, Eurostat Q2014 - European Conference on Quality in Official Statistics](https://reader036.vdocuments.net/reader036/viewer/2022062322/56649ea95503460f94baddab/html5/thumbnails/10.jpg)
Measuring volatility
Big foot effect: STDev of M-M and Q-Q changes
Thresholds: 0.25 / 0.63
Pitching effect:% sign inversions
Threshold: 20%
Roller coaster effect: % double large inversions
Large: ≥0.2 p.p. for M, ≥ 0.3 p.p. for Q
Threshold: 0%
10
![Page 11: Improving the quality of European monthly unemployment statistics Nicola Massarelli, Eurostat Q2014 - European Conference on Quality in Official Statistics](https://reader036.vdocuments.net/reader036/viewer/2022062322/56649ea95503460f94baddab/html5/thumbnails/11.jpg)
Measuring revisions
Focus on last data point (headline)
Average absolute revision of the level
Max absolute revision of the level
STDev revision M-M change
% sign inconsistency of M-M changes
Which thresholds?11
![Page 12: Improving the quality of European monthly unemployment statistics Nicola Massarelli, Eurostat Q2014 - European Conference on Quality in Official Statistics](https://reader036.vdocuments.net/reader036/viewer/2022062322/56649ea95503460f94baddab/html5/thumbnails/12.jpg)
Turning point identification
12
![Page 13: Improving the quality of European monthly unemployment statistics Nicola Massarelli, Eurostat Q2014 - European Conference on Quality in Official Statistics](https://reader036.vdocuments.net/reader036/viewer/2022062322/56649ea95503460f94baddab/html5/thumbnails/13.jpg)
Unemployment rate: delay in the identification of turning points (monthly vintages)
13
SEASONALLY ADJUSTED TRENDS
Monthly LFS 3MMA
Mixed sources
Monthly LFS 3MMA
Mixed sources
AT 0 0 -
4 1 -
CZ 0 0 5
1 0 5
DE 3 9 -
3 10 -
DK - 0 5
- 4 9
EL 0 0 -
0 1 -
FI 0 0 -
3 5 -
HU - 0 0
- 0 0
IT 1 14 -
13 10 -
NL 2 1 -
7 1 -
RO 0 1 -
3 1 -
SE 0 0 -
0 0 -
![Page 14: Improving the quality of European monthly unemployment statistics Nicola Massarelli, Eurostat Q2014 - European Conference on Quality in Official Statistics](https://reader036.vdocuments.net/reader036/viewer/2022062322/56649ea95503460f94baddab/html5/thumbnails/14.jpg)
Summary: no perfect approach
14
Volatility RevisionsTurning points identification
Timeliness
UNADJUSTED SERIESPure monthly LFS - + + +3-month moving averages of LFS data + + + -Mixed sources + - ? +
ADJUSTMENTSeasonally-adjusted series = = + NATrends + = - NA
![Page 15: Improving the quality of European monthly unemployment statistics Nicola Massarelli, Eurostat Q2014 - European Conference on Quality in Official Statistics](https://reader036.vdocuments.net/reader036/viewer/2022062322/56649ea95503460f94baddab/html5/thumbnails/15.jpg)
How to discriminate?
Do we focus on the right quality concerns?
Synthetic indicator or scoreboard?
Which indicators?
Which thresholds for acceptance?
Which weights for indicators and quality dimensions?
15
![Page 16: Improving the quality of European monthly unemployment statistics Nicola Massarelli, Eurostat Q2014 - European Conference on Quality in Official Statistics](https://reader036.vdocuments.net/reader036/viewer/2022062322/56649ea95503460f94baddab/html5/thumbnails/16.jpg)
Possible synthetic indicator: RMSE volatility + revisions
16