Data%20requirements%20and%20summary%20statistics%20for%20revisions%20analysis

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Data requirements and summary statistics for
revisions analysis

• Performing revisions analysis for sub-annual
  economic statistics
• Michela Gamba, Statistics Directorate - OECD
• OECD Short-Term Economic Statistics Working Party
• ______________________________
• Paris 23-24 June 2008

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Scope of revisions analysis

• WHY USEFUL?
• Allow users and providers to better understand
  quality of published sub-annual statistics and to
  study magnitude of revisions
• WHAT IS NEEDED?
• A Real-time database to perform Revision analysis
• A dataset containing a separate time series for
  the variable as appeared in each official past
  release

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OECD input to Task Force on revisions analysis

• 1. DATA METADATA KEY ELEMENTS
• Guidelines for data and metadata requirements
• 2. INVENTORY OF DATA SOURCES
• List of existing sources available publicly
• 3. SUMMARY STATISTICS
• Review summary statistics used
• Include relevant statistics- how much the story
  has changed
• Selected statistics to be included in the toolkit
• Provide description and purpose of statistics

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DATA METADATA KEY ELEMENTS 8 requirements to
build a RT database

• 1 COUNTRY/REGION DESCRIPTION
• -gt identify country/region/ zone aggregate
• 2 VARIABLE DESCRIPTION
• -gtFull description of variable (classification
  system, value/volume, ref years) with links to
  current revision policy associated requires well
  detailed METADATA
• 3 VARIABLE MEASURES
• -gt gross/ SA/ trend/ provided as published
  (index or level) GR

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DATA METADATA KEY ELEMENTS 8 requirements to
build a RT database (cont.)

• 4 IDENTIFICATION OF VINTAGE
• -gt data and metadata snapshot for each variable,
  for each official release
• -gt Field providing the date of release (one new
  data point for each vintage, forming a triangle)
• 5 LENGTH OF VINTAGE
• -gt going back as far as possible

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DATA METADATA KEY ELEMENTS 8 requirements to
build a RT database (cont.)

• 6 LENGTH OF TIME SERIES
• -gt ideally the full time series available for
  each official release..general rule of at least
  one year before the starting point of vintages to
  allow y_o_y growth rates
• 7 ONGOING UPDATING
• -gt store all new vintages with regular
  achieving
• 8 DATA ACCESSING
• -gt different formats available but..it is
  important to be able to extract data in the right
  format ( i.e. triangle table)

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Summary statistics

• 3 levels of analysis
• BASIC/ CORE MEASURES
• Targeting users that require quick, easy to
  understand information
• Additional/ advanced measures
• Targeting users that require more in-depth
  analysis
• Sophisticated / special user measures
• Information for detailed research purposes
  references to formula only

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Summary statistics (cont.)Default dataset
information

• Period of analysis
• reference data points of the time series being
  analysed (e.g. from 1994Q1 2007Q3)
• Revision Interval L_P
• revision interval being analysed for the
  vintages of the sampled time points
• n
• number of observations

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Summary statistics (cont.)Drop-down boxes

• USUAL SIZE AND RANGE OF REVISIONS
• Basic measures
• Mean absolute revision
• Range that 90 of revisions lie within
• Advanced/additional measures
• Median absolute revision
• ASSESSMENT OF POSSIBLE DIRECTIONAL TENDENCY IN
  REVISIONS
• Basic measures
• Mean
• Statistical significance of the mean
• Advanced/additional measures
• Median
• positive/ negative/ zero revisions
• HAC standard deviation
• Adjusted t-stat of mean revision
• Critical value of t-stat for significance of
  mean

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Summary statistics (cont.) Drop-down boxes

• VARIABILTY OF REVISIONS
• Basic measures
• Standard deviation
• Advanced/additional measures
• Root mean square revision
• Quartile deviation
• Min/ max/ range
• Sophisticated/ special user measures
• Skewness
• IMPACT OF REVISIONS ON SIGN OF GROWTH RATES
• Basic measures
• sign(later) sign(earlier)
• Advanced/additional measures
• Acceleration/ deceleration test

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Summary statistics (cont.) Drop-down boxes

• EFFICIENCY ASSESSMENT
• Advanced/additional measures
• Correlation between revision and earlier/ later
  estimate
• Test if revisions are noise/ news
• Sophisticated/ special user measures
• Mean squared revision
• Mean squared revision Decomposition UM
• Mean squared revision Decomposition UR
• Mean squared revision Decomposition UD

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The tool kit