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The Consumer Price Index Housing Sample

The Consumer Price Index Housing Sample. An address based sample. Robert Poole Office of Prices and Living Conditions Bureau of Labor Statistics. CPI Housing Sample Overview.

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The Consumer Price Index Housing Sample

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  1. The Consumer Price Index Housing Sample An address based sample Robert Poole Office of Prices and Living Conditions Bureau of Labor Statistics

  2. CPI Housing Sample Overview • Used to estimate inflation for Rent and Owners’ Equivalent Rent – the value of the flow of services one receives from an owned home • One sample of renters is used to move both rent and OER

  3. Some Select Sample Details • Cluster sampling is used • Sample segments (neighborhoods) based on total housing expenditure • Sample households within each segment with equal probability

  4. Ooooh! More Details • Renters are implicitly matched to owners geographically by neighborhood • Assumption that the Rent change in a neighborhood is the same as the unobservable Owners’ Equivalent Rent change • No assumption is made about price levels

  5. Sampling Details: Minutiae • Just kidding!

  6. 1998 Revision Sample • Our segments were census block based • Used a manual address listing process for each segment – very costly • Renters difficult to find in high owner density neighborhoods

  7. “Current” Sample • Our segments are now census block group based • Expect 4.5 times the number of addresses per segment • Generalissimo Francisco Franco is still dead – renters in high owner density areas still hard to find

  8. Cost • Hmmm. How can we make the listing process manageable and cheaper? • ADDRESS LISTS!!!! • But wait …

  9. Address List Issues • Coverage – are all the households in an area on the lists? • Accuracy – are the addresses geocoded accurately?

  10. Coverage • Multi-unit structures can have but one delivery point in the Delivery Sequence File • DSF augmented with marketing lists • Tested for bias in price change associated with “missing” addresses – none found

  11. Geocoding Accuracy • Compared list geocoding with census geocoding • Rob’s bout of swine flu prevented him from digging up numbers about the accuracy in time for this presentation. It was good. Trust him. • Accuracy on par with manual listing

  12. What about them pesky, hard to find renters? • Hey! We’re using marketing lists! Can they help? • Binary renter/owner coding not very helpful • Sliding scale renter/owner coding was very helpful in identifying “certainty” owners – over 98% helpful • Oh yeah! (knock on wood)

  13. Address List Advantages • Cheaper than listing • Owner/Renter information allowed us to effectively double our sample size • Phone Numbers – Too early to tell • Names – A possibility for the future

  14. Questions?

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