Please use this identifier to cite or link to this item: https://repository.iimb.ac.in/handle/2074/13491
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dc.contributor.authorGhosh, Pulak
dc.contributor.authorGhosh, Soumya Kanti
dc.date.accessioned2020-07-20T14:37:33Z-
dc.date.available2020-07-20T14:37:33Z-
dc.date.issued2015-05-27
dc.identifier.urihttps://repository.iimb.ac.in/handle/2074/13491-
dc.descriptionThe Economic Times, 27-05-2015
dc.description.abstractPick up the analyst interaction (even the Technical Advisory Committee minutes) with the Reserve Bank of India governor and you will find that after every policy announcement, there is at least one question regarding consumer inflationary expectations. Herein lies the role of ‘Big Data’ to unravel the mystery of correctly deciphering such expectations. Technically, Big Data refers to large volumes of structured and unstructured data and can be a combination of digital information of both, derived from the consumer interaction in the digital world, like web applications, social networks, sensors, etc, that can be used in facilitating policy decisions for banks (central banks included). The Billion Prices Project (BPP) at the Massachusetts Institute of Technology, led by professor Alberto Cavallo, actually took the internet’s help to gather inflation data from online stores. Cavallo wrote a computer programme that scanned websites’ HTML codes, and found out all the prices of online goods. The estimates through the internet very closely matched the ones produced by statistical offices of the US. The project now gives prices of about half-a-million products per day and while the Government Bureau in the US comes out with monthly inflation numbers, the BPP gives the daily inflation rate. Imagine the RBI using similar algorithms to scan retail inflation data on a daily basis (published by the ministry of consumer affairs) as well as weekly (Directorate of Economics & Statistics) and juxtaposing it with data from even supermarkets to generate an inflationary expectation index on a daily basis in advance. Such online price data will be of very high frequency, available almost in real time. It will have detailed information on product consumption and will thereby give greatly improved forecasting abilities to the RBI. Read more at: https://economictimes.indiatimes.com/blogs/et-commentary/how-big-data-can-help-central-banks-with-real-time-policy-analytics/
dc.language.isoen_US
dc.publisherBennett, Coleman & Co. Ltd.
dc.subjectBanking
dc.subjectFinancial management
dc.subjectMonetary policy
dc.subjectEconomic policy
dc.titleHow big data can help central banks with real-time policy analytics
dc.typeMagazine and Newspaper Article
dc.identifier.urlhttps://economictimes.indiatimes.com/blogs/et-commentary/how-big-data-can-help-central-banks-with-real-time-policy-analytics/
dc.journal.nameThe Economic Times
Appears in Collections:2010-2019
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