The official statistics framework is based on internationally agreed standards, taking into account the core principles of impartiality, objectivity, professional independence, cost effectiveness, statistical confidentiality, minimisation of the reporting burden and high output quality. Since the latest 2007 global economic crisis, a growing demand for more, better and timelier data under limited resources for compilers and reporting agents has been observed. The concept of experimental statistics becomes more relevant, despite the lower quality in terms of coverage, data sources and harmonised definitions. The main aim of this paper is to present the methodological development of the residential property price index in Croatia from experimental to official statistics, as well as to show corresponding changes in time, which occurred due to the changes in methodological framework, institutional responsibility for compilation, coverage and data sources. A general conclusion of the paper is that publication of non-harmonized experimental statistics results, together with explanatory metadata, is better from the point of view of users than having nothing produced by official statistics.
This article describes the estimation of quality-adjusted price indexes from ‘big data’ such as scanner and online data when there is no available information on product characteristics for explicit quality adjustment using hedonic regression. The longitudinal information can be exploited to implicitly quality-adjust the price indexes. The fixed-effects (or ‘time-product dummy’) index is shown to be equivalent to a fully interacted time-dummy hedonic index based on all price-determining characteristics of the products, despite those characteristics not being observed. In production, this can be combined with a modified approach to splicing that incorporates the price movement across the full estimation window to reflect new products with one period’s lag without requiring revision. Empirical results for this fixed-effects window-splice (FEWS) index are presented for different data sources: three years of New Zealand consumer electronics scanner data from market-research company GfK; six years of United States supermarket scanner data from market-research company IRI; and 15 months of New Zealand consumer electronics daily online data from MIT’s Billion Prices Project.
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