Working paper
OA Policy
English

High Frequency House Price Indexes with Scarce Data

PublisherSFI
Collection
  • Swiss Finance Institute Research Paper; 16-27
Publication date2016
Abstract

We show how a method that has been applied to commercial real estate markets can be used to produce high frequency house price indexes for a city and for submarkets within a city. Our application of this method involves estimating a set of annual robust repeat sales regressions staggered by start date and then undertaking an annual-to-monthly (ATM) transformation with a generalized inverse estimator. Using transactions data for Louisville, Kentucky, we show that the method substantially reduces the volatility of high frequency indexes at the city and submarket levels. We demonstrate that both volatility and the benefits from using the ATM method are related to sample size.

Keywords
  • House Prices
  • High-Frequency Price Indexes
  • Repeat Sales Method
  • Scarce Data
Classification
  • JEL : R31
Citation (ISO format)
HOESLI, Martin E., BOURASSA, Steven. High Frequency House Price Indexes with Scarce Data. 2016
Main files (1)
Working paper
accessLevelPublic
Identifiers
  • PID : unige:84700
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Technical informations

Creation20/06/2016 16:43:00
First validation20/06/2016 16:43:00
Update time15/03/2023 00:28:35
Status update15/03/2023 00:28:35
Last indexation31/10/2024 03:44:12
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