Intangible Assets: How the Interaction of Computers and Organizational Structure Affects Stock Market Valuations

macroeconomics, Intangible Assets, Interaction, Computers, Organizational Structure, Stock Market Valuations

The Rapid Adoption of Data-Driven Decision-Making

We provide a systematic empirical study of the diffusion and adoption patterns of data-driven decision making (DDD) in the U.S. Using data collected by the Census Bureau for a large representative sample of manufacturing plants, we find that DDD rates nearly tripled (11%-30%) between 2005 and 2010. This rapid diffusion, along with results from a companion paper, are consistent with case-based evidence that DDD tends to be productivity-enhancing. Yet certain plants are significantly more likely to adopt than others. Key correlates of adoption are size, presence of potential complements such as information technology and educated workers, and firm learning

Information Technology as a Factor of Production : The Role of Differences Among Firms

Despite evidence that information technology (IT) has recently become a productive investment for a large cross-section of firms, a number of questions remain. Some of these issues can be addressed by extending the basic production function approach that was applied in earlier work. Specifically, in this short paper we 1) control for individual firm differences in productivity by employing a firm effects specification, 2) consider the more flexible translog specification instead of only the Cobb-Douglas specification, and 3) allow all parameters to vary between various subsectors of the economy. We find that while firm effects may account for as much as half of the productivity benefits imputed to IT in earlier studies, the elasticity of IT remains positive and statistically significant. We also find that the estimates of IT elasticity and marginal product are little-changed when the less restrictive translog production function is employed. Finally, we find only limited evidence of differences in IT\u27s marginal product between manufacturing and services and between the measurable and unmeasurable sectors of the economy. Surprisingly, we find that the marginal product of IT is at least as high in firms that did not grow during 1988-1992 sample period as it is in firms that grew

The Attention Economy: Measuring the Value of Free Digital Services on the Internet

Over the past decade, there has been an explosion of digital services on the Internet, from Google and Wikipedia to Facebook and YouTube. However, the value of these innovations is difficult to quantify, because consumers pay nothing to use them. We develop a new framework to measure the value of free services using the insight that even when people do not pay cash, they must still pay “attention,” or time. Using our model, we estimate the increase in consumer surplus created by free internet services to be over $100 billion per year in the U.S. alone. Our analysis implies that most of welfare gain from digital services on the Internet would be overlooked by traditional approaches that rely only on the direct expenditures of money. Considering the time spent on consumption, as we do, makes it possible to assess the full value of these digital innovations

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