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Billion Prices Proj ect: Avoiding the Big Data Small Info S yndrome Roberto Rigobon MIT S loan, NBER, CS AC Big distance between Data and Information! The world is not lacking of data, its lacking of information Need a question


  1. Billion Prices Proj ect: Avoiding the Big Data – Small Info S yndrome Roberto Rigobon MIT S loan, NBER, CS AC

  2. Big distance between Data and Information!  The world is not lacking of data, it’s lacking of information  Need a question before collection  Data without purpose, produces problems not information  Great Data is not a licenses for Bad Econometrics  Need to understand phenomena  Measuring is not Predicting  Correlations are hardly Causal

  3. Inflation and Price Indexes  Albert o Cavallo  We want t o produce alt ernat ive measures of inflat ion  We need prices  We need methodology to weight those prices  We need to understand product introductions and discontinuations  We need to understand store behavior  How to collect prices of products not sold on the internet? S ervices?

  4. Online Information and Indexes Our Approach to Daily Inflation S tatistics 1 2 3 4 5 Use scraping Connect t o Find individual S t ore and Develop daily t echnology t housands of it ems process key it em inflat ion online ret ailers informat ion in a st at ist ics for ~20 every day dat abase count ries • Dat e • It em • Price • Descript ion

  5. How do we collect data?  Our prices are collected from public online sources, using a technique called “ web scraping ”  A software downloads a webpage, analyses the html code, “ scrapes ” price data, and stores it in a database

  6. Countries covered

  7. Properties of Inflation Indexes  Congruence  S tores keep markups between online and offline prices relatively constant in the medium run  Anticipation  Online Price Indexes trends anticipate official inflation shifts.  Online prices are easier to change, retailers are more competitive, and consumers have less memory.  Demand trends  Changes in inflation trends by retailers reflect changes in the demand they are facing

  8. Argentina

  9. US A

  10. US Recession S ep 16 2008

  11. US 2012

  12. Annual Inflation Rates China – S upermarket Index Argentina Australia Colombia Germany Ireland Venezuela UK Russia

  13. Other Indexes  Nat ural Disast er’s Measurement  Employment  Real Est at e Inflat ion and Capit al Gains  GDP and Economic Act ivit y

  14. Thailand: When Help S hould Be Deployed? Product Availability In Online Retailers 120 100 80 60 40 20 0 10/ 1 10/ 2 10/ 3 10/ 4 10/ 5 10/ 6 10/ 7 10/ 8 10/ 9 10/ 10 10/ 11 10/ 12 10/ 13 10/ 14 10/ 15 10/ 16 10/ 17 10/ 18 10/ 19 10/ 20 10/ 21 10/ 22 10/ 23 10/ 24 10/ 25 10/ 26 10/ 27 10/ 28 10/ 29 10/ 30 10/ 31 Not es: Product Availabilit y normalized t o 100 on 10/ 1/ 2011

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