1. Making Statistics Talk 2 – Identifying the key message PPT2
CONTRACTOR IS ACTING UNDER A FRAMEWORK CONTRACT CONCLUDED WITH THE COMMISSION

2. Summary Identifying the data changes to be covered
Identifying and communicating the key message
Identifying contributions to aggregate changes
The identification of trends / turning points in data
Identifying a key message in a data set

3. Aggregate data changes to cover
Direction, size of aggregate change over year
(or other reasonably long period)
Identify change in data since last period
Place data in context of at least a year’s observations

4. Short-term changes
Look at observation to observation (month to month) data changes
Identify impact on most recent & baseline observations
Large, symmetrical changes may be ephemeral

5. The more that data is disaggregated, the less accurate it becomes

6. Disaggregated data changes
Identify main sector contribution(s) to change
i.e. not the largest change in magnitude but, for example, the largest (sector share) x (change)
Ranking of Member States is often structural
May not be of interest in Main statistical findings
Absolute values of outliers of interest
Martin Wolf: ‘only three countries have negative inflation and only a fifth of items in the consumer price index have fallen in price.’ 
Changes in ranking can be of interest

7. Trends and changes
Fitting trend lines & moving averages to data helps understanding of data
One observation does not usually mean an end to a trend
Even if a new secular trend is established, cycles (seasonal, business cycle) will often overwhelm
Basically, very unlikely to identify a new cycle without applying auto-regression methods

9. Exercise 3
Identify the main aggregate and disaggregated data changes of interest in HCPI data, either the series we have been discussing or at Member State level
Data provided (EU, Euro-zone, Member States):
m/m-12, m/m-1 aggregate and
m/m-12, m/m-1 at COICOP top level (12 groups)
20 minutes, 20 minutes discussion

10. Identifying the main story
Two possibilities:
Biggest effect Versus Biggest surprise
HICP example:
‘Headline’ (all items) inflation rate unchanged
Versus
Increase in ‘core inflation’ (ex. energy, food, alcohol, tobacco)

11. My choice: ‘unchanged inflation’
I am more certain about the behaviour of the aggregate data
Based on the aggregate figure, I can develop a narrative that includes the (apparently conflicting) disaggregated data effects:
‘Core’ inflation increase; fall in month to month inflation; clothing price fall (potentially aberrant data); number of member states with falling price levels; price stability of these countries
Result: a cohesive narrative that incorporates conflicting data changes

12. Summary of main story selection
Main effect v. main surprise
Focus on aggregate data
Incorporate disaggregated data effects within this narrative
Ensure uncertainty about disaggregated effects is appropriately identified
Avoid reference to external causes / analysis
Can use analysts concerns to identify areas of interest

13. Exercise 4 Identify the main story for a Member State’s HICP data
Note how you would incorporate other data developments within the narrative
10 minutes
10 minutes discussion

14. Thank you
CONTRACTOR IS ACTING UNDER A FRAMEWORK CONTRACT CONCLUDED WITH THE COMMISSION