Hal Varian, Google Chief Economist

Google_logo Throughout this blog, I have focused on identifying emerging elements of new voice, web, mobile and social business models based on data centric analytics, network effects, the power of communities and the creation of markets.  Emerging webware and traditional software application providers are embracing these models to generate new value for users, new revenue growth and as a source of competitive advantage.   With Google leading the charge in many of these new elements and models, I found a few of the questions in the New York Times Q&A interview with Google Chief Economist Hal Varian interesting:

Q: How does Google measure the market value and determine pricing for its ad placements on search results?

A: We determine a market value by making a market. No kidding. Google auctions off placement for ads on results pages. The high bidder gets the most prominent position, the second highest bidder gets the second most prominent position, and so on. See my paper on “Position Auctions” for more details.

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Q: How would you rate the future of experimental economics?

A: I’m a big fan of experimental economics. In fact, we’re using it at Google to study various sorts of market designs. The goal in economic experiments, as in all experiments, is to make the results reproducible.

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Q: Aside from auctions, what have been some of the applications of game theory to the Internet or Internet-related businesses? What role, if any, has game theory played in the area of computer/Internet security?

A: This is a good place for me to plug Ross Anderson’s page on “The Economics of Information Security.” I think that there are a lot of opportunities to apply game theoretic reasoning here. It is certainly an area where thinking strategically is important.

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Q: Your job sounds extremely interesting. What jobs would you recommend to a young person with an interest, and maybe a bachelors degree, in economics?

A: If you are looking for a career where your services will be in high demand, you should find something where you provide a scarce, complementary service to something that is getting ubiquitous and cheap. So what’s getting ubiquitous and cheap? Data. And what is complementary to data? Analysis. So my recommendation is to take lots of courses about how to manipulate and analyze data: databases, machine learning, econometrics, statistics, visualization, and so on.

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Q: You once said that “marketing is the new finance,” because of the data and tools that are now available. In your opinion, what are the three most useful quantitative techniques for analyzing this kind of data? To what extent does Google use this type of analysis?

A: The three most important techniques, in my opinion, are: 1) experimental design and analysis; 2) regression; and 3) Bayesian methods. We use the first two extensively, and are beginning to use Bayesian techniques more.

Comments

  1. It is very difficult to study Bayesian Analysis topic. Not many good reference textbooks to study Markov chain.
    I use Statistical Decision Theory and Bayesian Analysis, 2nd Edition to study. This is good reference textbook.
    Do you have any other good Bayesian Analysis related textbooks recommend?
    Regards,
    Andy ^_^
    Cocomartini Discount Online Bookstore

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