United Arab Emirates:Technical Assistance Report-Hedonic Methods for Price Indices Mission

Author: International Monetary Fund. Statistics Dept.

Technical Assistance Report-Hedonic Methods for Price Indices Mission: United Arab Emirates: Technical Assistance Report-Hedonic Methods for Price Indices Mission

Volume/Issue: Volume 2022 Issue 303

Publication date: September 2022

ISBN: 9798400221736

$20.00

Add to Cart by clicking price of the language and format you'd like to purchase

Available Languages and Formats


English

Prices in red indicate formats that are not yet available but are forthcoming.

Topics covered in this book

This title contains information about the following subjects. Click on a subject if you would like to see other titles with the same subjects.

Economics- Macroeconomics , Money and Monetary Policy , International - Economics , Ta recipient , REPI CPI , DSC Management evaluation , transaction data , real estate price index , Dubai land department , Consumer price indexes , Price indexes , Data collection

Also of interest

Nepal

Republic of Congo : 2001 Article IV

Peru

Summary

A technical assistance (TA) mission was conducted remotely during January 16-20, 2022 to assist the Dubai Statistics Center (DSC) in introducing hedonic methods for quality adjustments in the consumer price index (CPI) and the real estate price index (REPI). Currently the REPI is compiled by DSC using stratification with simple averages. Moving from simple averages to hedonic regressions will improve the accuracy of the indicator since it will take into account the quality mix of properties within each stratum. The mission recommended the hedonics time dummy method with a rolling window of 12 months for compiling the REPI. This method provides more stable results, i.e., less volatile indices, since it pools one year of data instead of one quarter, and it is particularly recommended when few observations are available. It is widely used for Residential Property Price Index compilation and for CPI compilation with web scraped data. The TA mission provided extensive training on using this method accompanied by R codes adapted to the Dubai sample data.