The Future of Prediction: How Google Searches Foreshadow Housing Prices and Quantities

To make effective decisions, consumers, executives and policymakers must make predictions. However, most data sources, whether from the government or businesses, are available only after a substantial lag, at a high level of aggregation, and for a small set of variables that were defined in advance. This hampers real-time prediction. A critical advance in IT research has been the development of powerful search engines and the underlying Internet infrastructure. We demonstrate a highly accurate but simple way to predict future business activities by using data from such search engines. Applying our methodology to predict housing trends, we find that our index of housing search terms can predict future quantities and prices in the housing market. During our sample period, each percentage rise in our housing search index predicts sales of 121,400 additional houses in the next quarter. This approach can be applied to other markets, transforming the future of prediction

What the GDP Gets Wrong (Why Managers Should Care)

We see the influence of the information age ever ywhere, except in the GDP statistics. More people than ever are using Wikipedia, Facebook, Craigslist, Pandora, Hulu and Google. Thousands of new information goods and services are introduced each year. Yet, according to the official GDP statistics, the information sector (software, publishing, motion picture and sound recording, broadcasting, telecom, and information and data processing services) is about the same share of the economy as it was 25 years ago - about 4%. How is this possible? Don’t we have access to more information than ever before? The answer isn’t about quantity, it’s about price. The bits that comprise today’s information goods are supplanting the atoms that formed yesterday’s encyclopedias, movie theaters, music CDs and newspapers. Online information may be updated every minute of the day and accessible almost anywhere in the world, but its price is usually radically lower than that of its physical counterpart, if there even is a price

Moneyball for Academics: network analysis methods for predicting the future success of papers and researchers.

Drawing from a combination of network analysis measurements, Erik Brynjolfsson and Shachar Reichman present methods from their research on predicting the future success of researchers. The overall vision for this project is to create an academic dashboard that will include a suite of measures and prediction methods that could supplement the current subjective tools used in decision-making processes in academia