Timely statistical information for monetary

policy purposes

Werner Bier Deputy Director-General

Statistics, European Central Bank

International Seminar on Timeliness, Methodology and Comparability of Rapid Estimates of Economic Trends

Ottawa, 27-29 May 2009

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Content

• Monetary policy data needs - the example of the European Central Bank

• Timeliness of data for the euro area

• Assessing a wide range of data in a short period of time – consistency and accessibility of data

• The challenges for statistics of a global economy

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The ECB’s monetary policy framework

Full set of information (monetary, financial and economic statistics, euro area accounts, macro-economic projections, opinion surveys, market

data, ...)

Analysis of monetary trends

Analysis of economic

dynamics and shocks

Monetary policy decisions based

on a unified overall assessment

of the risks to price stability

Primary objective: price stability

Economicanalysis

Cross-checking

Monetaryanalysis

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Timeline of euro area statistical data

2009

FEBRUARY MARCH APRIL MAY

GOVERNING

COUNCIL

ANNOUNCES ITS

DECISION

UNEMPLOYMENT MARCH 2009, CONSUMER/ BUSINESS OPINION SURVEYS APRIL 2009, FLASH ESTIMATES INFLATION APRIL 2009 & QUARTERLY EAA Q4 2008

30 APRIL

BANK LENDING SURVEY APRIL 2009 MFI BALANCE SHEET STATISTICS MARCH 2009

7 MAY29 APRIL

MFI INTEREST RATE STATISTICS FEBRUARY 2009

6 APRILMARKET DATAREAL TIME

FLASH ESTIMATES GDP Q4 2008

13 FEBRUARY 31 MARCH

GERMANY UNEMPLOYMENT MARCH 2009

QNA Q4 2008

5 MARCH

HICP GERMANY APRIL 2009

PMI (MF) & PMI SURVEY APRIL 2009

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Timeliness of data for the euro area

• Forecasts (‘broad’ and ‘narrow’ projection exercises)

• Opinion surveys (e.g. bank lending survey, business and consumer surveys, purchasing managers surveys): at least monthly with a high timeliness

• Market data (e.g. stock market data, exchange rates, yields): at least daily, frequently “tick-by-tick”

• Monetary and financial statistics (e.g. MFI (bank) balance sheets & interest rates, securities, balance of payments): monthly

• Short-term statistics (e.g. Harmonised CPI (HICP), unemployment rate, leading indicators): monthly

• National accounts (e.g. GDP, sector accounts): quarterly with a timeliness between 45 - 90 days

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Coherence among the information sets - I

• Assessing huge data sets in a very timely fashion

• Coherence in the concepts applied between e.g.

- forecasts and national accounts (SNA 2008)

- national accounts by sector including (financial) balance sheets and monetary & financial statistics, balance of payments statistics & international investment positions (BPM6)

- national accounts and short-term statistics

- short-term statistics and opinion surveys

- micro market data (e.g. individual securities) and financial statistics

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Coherence among the information sets - II

• Coherence among different data sets also requires - acceptance of main statistical standards such

as SNA 2008 / BPM6 or the statistical classification of economic activities- close cooperation among data providers on the

detailed methodology applied, the compilation timetable, revision policies, underlying

registers, the seasonal adjustment, etc.- exchange of (confidential) data, where needed- organisational measures (partly including legal

provisions) involving also senior management

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Accessibility of data

• Assessing huge data sets in a very timely fashion

• Application of Statistical Data Warehouses that

- provide access to different data sets simultaneously (e.g. market data, opinion surveys,

national accounts and related forecasts)

- allow dedicated access rights, where needed

• Networks of Statistical Data Warehouses among producers and users of data

• Statistical Data and Metadata eXchange (SDMX)

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The challenges for statistics of a global economy

• Globalisation requires global statistics:

- agreed international statistical standards such as the SNA 2008 and the BPM6

- comparable statistics at least among systemic relevant countries

- relevant timely world-aggregates such as a quarterly global GDP at day t+60

- a central and publicly accessible database for the Principal Global Economic Indicators (PGEIs)

- Inter-Agency Group on Economic and Financial Statistics (Principal Global Indicators Website)

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A few conclusions

• Monetary policy decisions are evidence based and forward looking, and rely on a wide range of data

• The relevance of statistics is enhanced by a higher degree of coherence, timeliness and reliability

• In the short-term, there is a trade-off between coherence, timeliness and reliability

• In the medium-term, one cannot only move on the production function for statistics, but one can move the production function

• Globalisation requires global statistics with appropriate regional breakdowns