DETECTION OF OUTLIERS IN THE CANADIAN CONSUMER PRICE INDEX (CPI) DETECTION OF OUTLIERS IN THE CANADIAN CONSUMER PRICE INDEX (CPI) ABDELNASSER SAÏDI AND.

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Presentation transcript:

DETECTION OF OUTLIERS IN THE CANADIAN CONSUMER PRICE INDEX (CPI) DETECTION OF OUTLIERS IN THE CANADIAN CONSUMER PRICE INDEX (CPI) ABDELNASSER SAÏDI AND SUSANA RUBIN BLEUER STATISTICS CANADA STATISTICS CANADA

What is the CPI ?  Is a weighted arithmetic average of price indexes over all basic classes. The weights are obtained from the survey of households spending.  the price index at the basic class is in turn a weighted sum of the micro indexes over all the items in the class.  The micro index is a geometric mean of the price relatives of n outlets surveyed.

CURRENT EVALUATION PROCEDURES  Large amount of resources used to correct a small number of errors.  verifications made manually: –Verification of all records with status ‘special’. –Verification of all records with a relative price increased or decreased by 15%.  Editing procedures related to missing values, missing outlets and quality changes (see Allard-Saulnier and Beyrouti (2003)).

PROPOSED EVALUATION PROCEDURES  Performed on an editing group –All observations pertaining to a particular item – and in a particular geographical area ( 4 possible levels) –and having the same status code if the percentage of “SP’s” > 15%.  status code “ SP’s ” ( regular → special or special→ regular).

PROPOSED EVALUATION PROCEDURES  Methods considered :  ILO Tukey and variants,  MAD (Median Absolute Deviation),  Quartile method and HB (Hidiroglou-Berthelot)  RFM (Resistant Fence Method)  Detection method with higher breakdown point than Tukey’s method and taking into account the skewness of the distribution and the small size of the CPI sample are favoured  Quartile method with asymmetric fences applied to the log of the price relatives was recommended

INFLUENCE IN THE BASIC CLASS  Contribution of each outlier on the basic class index  Analysis of the percentage of contribution  How to define a cut-off to identify influent observations ?