the three hedonic methods is done on a quarterly basis.
4. GeoStat is aiming at compiling a quarterly RPPI covering new flats and new detached houses for the capital city, Tbilisi . GeoStat is obtaining data on residential dwellings announcements, by webscraping, from the two main websites in Georgia. Data from the National Agency of Public Registry of Ministry of Justice (NAPR) continues being transmitted regularly nonetheless with few variables. The workshop held in Batumi during February built grounds for cooperation among the institutions but a firm
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.
one year of data instead of one quarter, and it is particularly recommended when few observations are available. It is widely used for the RPPI compilation and for the CPI compilation with webscraped data. Extended training was provided on this method accompanied by R codes adapted to the Dubai sample data.
4. The REPI is compiled with data obtained from the Dubai Land Department (DLD) available since 2016. These data cover all types of properties namely residential buildings, commercial buildings, and land (residential and commercial). Regardless of obtaining
-modal with prices being webscraped from the internet or obtained from scanner data, as well as being collected by hand from outlets and by telephone inquiry. Issues of coherence can arise when integrating price data from different sources, with relevant consequences. The internet prices charged by online retailers can differ from the prices charged by traditional outlets. Similarly, the internet prices obtained from a retail chain’s website and the associated sales volume can differ from the corresponding in-store prices. The prices collected from each source should be
obtained are unusable. Mail or electronic questionnaires and collection forms that are only partially filled in, scanner data with missing information concerning specific outlets or Global Trade Item Numbers (GTINs) in the sample, and web-scraped prices where some information is not downloaded from the internet are examples of partial nonresponse. If the price changes of the nonresponding outlets differ from those of the responding outlets, the quality of the price change estimates will be affected.
12.12 Another source of errors is the failure to measure the price
NSOs have been exploring the use of webscraping to observe quality characteristics from retailers’ or manufacturers’ websites to enrich scanner data sets. Scanner data obtained from a market research company may already contain detailed information on item characteristics. One NSO, for example, produces quality-adjusted GEKS price indices for consumer electronics products based on scanner data sets from one market research company that include many item characteristics ( Krsinich 2015 ). All these methods are rather data-intensive as they require prices, turnover
replacing old ones.
6.139 The requirement that data be collected on the prices and specifications of a large sample, if not all models, is not as demanding as it might appear. Extensive data on prices and characteristics of models of consumer goods and services are generally readily available on websites (for example, many comparing prices and salient characteristics), can be copied with relative ease, and automated using webscraping. Such detailed information is also available as scanner data (see Chapter 10 ).
6.140 . Figure 6.2 is a scatter diagram relating