 Using online price data for construction leading macroeconomic indicatorsИспользование онлайн-данных по ценам в качестве опережающих индикаторов динамики макроэкономических показателейDyachkova, Natalya (Дьячкова, Наталья) ()
Working Papers from Russian Presidential Academy of National Economy and Public Administration Abstract: Today big data and online data provide macroeconomists with the advantage to create unique data sets that are conducted to specific research needs, and more than that, it enables some specific capabilities for both measurement and forecasting with the usage of new forms of data. The importance of this work is based on that the online price data has the ability to demonstrate the upcoming dynamics of various economic processes, including inflation, in short term period. The relevance of this work is determined by the ability of high-frequency indicators, including price indices based on online & scanner data, to evaluate the leading dynamics from microlevel and big data. This research is devoted to the issues of assessing and constructing high-frequency indicators, which acquires special significance for macroeconomic forecasting. The main goal of the study is to identify the capabilities of high-frequency indicators and price indices to show leading dynamics in macroeconomics and its capabilities for short-term forecasting (subject of the study). To achieve the stated goal, it is based on reviewing of academic and empirical literature (as the main source of information) to systematize and classify the types of high-frequency leading indicators and their construction methods. Also, it is conducted with the areas of measuring various macroeconomic processes and determined the degree of consistency of the results, which are obtained from low-frequency data comparatively to the results on daily and online data basis (research objectives). In this research were used methods such as descriptive, statistical and graphical analysis, the big data analysis, including the systematic approach and comparative analysis with regression modelling. Based on the empirical results of a study it is shown that the construction and evaluation of high-frequency indicators as leading indicators of macroeconomic processes, can be quite interesting and combat. Finally, the high-frequency indicators show better statistics dynamics for current changes in the economy and demonstrate the greater significance than low-frequency indicators in VAR- & SVAR- models (scientific novelty of the work). The prospects for further research are to show the capabilities of high-frequency indicators in forecasting inflation in the short-term period of time. In the conclusion, the results of the work can be used in the interests of statistical services and macroeconomic departments of the Russian Federation to monitor current price statistics and to obtain advanced information for short-term planning purposes from microlevel data. Keywords: Online price statistics; big data; consumer price index; price aggregation (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:rnp:wpaper:w202321 Access Statistics for this paper More papers in Working Papers from Russian Presidential Academy of National Economy and Public Administration Contact information at EDIRC. |
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