Please use this identifier to cite or link to this item: https://repository.iimb.ac.in/handle/2074/20168
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dc.contributor.advisorSubramanian, Chetan
dc.contributor.authorSingh, Meenakshi
dc.contributor.authorSinghal, Nished
dc.date.accessioned2021-06-30T12:01:22Z-
dc.date.available2021-06-30T12:01:22Z-
dc.date.issued2015
dc.identifier.urihttps://repository.iimb.ac.in/handle/2074/20168-
dc.description.abstractInflation is one of the most important parameter on which major decisions are made in an economy. The monetary policy set by the Reserve Bank of India is driven by the existing & expected inflation. Given the importance of inflation numbers, especially in a developing country like India, it is important that the inflation data is accurate as well as provides an early signal of changes. In this context, emerges the importance of tracking inflation online. An online index can remove the 12 day lag in the existing inflation computation using offline prices, detect inflation changes early as online prices tend to be less sticky and also lessen the manpower costs involved in the collection of offline prices. Through this project, a broad framework has been developed using which the existing Urban Consumer Price Index (CPI) can be tracked in real time by using APIs/web scraping technology. Online substitutes have been cited for the major groups in the inflation basket. However, mapping a few items such as those related to Housing Index, Clothing, etc. posed additional challenges which can make the index less reliable. Hence, the model developed has been restricted to compute inflation only for ‘Food & Beverages’ group. The prices of the food basket will give much more reliable results as compared to tracking the overall inflation online. The National Sample Survey Report on Household Expenditureiv was the basis for creating the list of items & their weights for Karnataka’s urban food basket. The most suitable substitute(s) available at the Bigbasket website was listed for each of the items for which off-line price data is collected. The inputs from the visit to the National Sample Survey Office (NSSO), Bangalore on the detailed item specifications have been used, wherever applicable. Currently, the sample model has been built for Bangalore for which Bigbasket will provide prices weekly. Similar model will be built for other cities such as Delhi and the online index inflation trend will be compared with offline CPI food inflation numbers to get more insights. Though there exists multiple challenges of computing online inflation in India, the online food basket developed is a step towards improved inflation measurement, especially with the ability to cover all major urban centres owing to the rapid expansion of e-commerce in India.
dc.publisherIndian Institute of Management Bangalore
dc.relation.ispartofseriesPGP_CCS_P15_089
dc.subjectEconomics
dc.subjectInflation
dc.subjectMonetary policy
dc.titleReal time tracking of inflation in India
dc.typeCCS Project Report-PGP
dc.pages12p.
Appears in Collections:2015
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