Comparison of Variance Estimation Methods Using PPI Data

• Activity Number: 471
• Type: Contributed
• Date/Time: Wednesday, August 4, 2010 : 8:30 AM to 10:20 AM
• Sponsor: Section on Government Statistics
• Author(s): Andy Sadler*+ and Helen Chen
• Companies: Bureau of Labor Statistics and Bureau of Labor Statistics
• Keywords: NAICS ; Balanced Repeated Replication ; Fay's Method ; Stratified Jackknife ; Bootstrap

Abstract

The Producer Price Index (PPI) collects price data from domestic producers of commodities and publishes monthly indexes on average price changes received by those producers at all stages of processing. PPI samples employ a two-stage design where establishments are selected in the first stage and unique items are selected in the second stage. In this paper we review the research results from the PPI variance estimation study. The objective of the study was to determine the best method of variance estimation appropriate for PPI data. Historical data from eleven NAICS industries were used to create simulation frames, from which simulation samples were drawn and estimated variances calculated. The replication methods compared were the Balanced Repeated Replication (BRR), Fay's BRR, Jackknife and the Bootstrap. The Bootstrap method was recommended for the PPI program by the study.