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A price index aggregates various combinations of base period prices (), later period prices (), base period quantities (), and later period quantities (). Price index numbers are usually defined either in terms of (actual or hypothetical) expenditures (expenditure = price * quantity) or as different weighted averages of price relatives ( p t ...
A CPI is a statistical estimate constructed using the prices of a sample of representative items whose prices are collected periodically. Sub-indices and sub-sub-indices can be computed for different categories and sub-categories of goods and services, which are combined to produce the overall index with weights reflecting their shares in the total of the consumer expenditures covered by the ...
Neural Turing machines (NTMs) are a method of extending recurrent neural networks by coupling them to external memory resources with which they interact. The combined system is analogous to a Turing machine or Von Neumann architecture but is differentiable end-to-end, allowing it to be efficiently trained with gradient descent .
Consumer Price Index for Americans 62 years of age and older (R-CPI-E): This index re-weights prices from the CPI-U data to track spending for households with at least one consumer age 62 or older.
The Consumer Price Index was initiated during World War I, when rapid increases in prices, particularly in shipbuilding centers, made an index essential for calculating cost-of-living adjustments in wages. To provide appropriate weighting patterns for the index, it reflected the relative importance of goods and services purchased in 92 ...
A hedonic index is any price index which uses information from hedonic regression, which describes how product price could be explained by the product's characteristics.. Hedonic price indexes have proved to be very useful when applied to calculate price indices for information and communication products (e.g. personal computers) and housing, [1] because they can successfully mitigate problems ...
Predictive analytics statistical techniques include data modeling, machine learning, AI, deep learning algorithms and data mining. Often the unknown event of interest is in the future, but predictive analytics can be applied to any type of unknown whether it be in the past, present or future.
The Billion Prices Project (BPP) was an academic initiative at MIT Sloan and Harvard Business School that uses prices collected from hundreds of online retailers around the world on a daily basis to conduct research in macro and international economics and compute real-time inflation metrics. [1]