Google Inc. turns 10 years today and I think a part of all of us should celebrate with them.
As almost everyone knows, this internet giant was started by two Standford University students with little more than a couple of CPUs and a desire to create something better. The secret to their success is also just as well known: amazing working conditions for their staff, a motto to "do no evil", they think big, and never settle for the status quo. They never stand still. (Yesterday's Globe and Mail had a great story on Google's contributions with a cool timeline of the company.)
Hats off to Google Inc.! Thank you for keep blogger, gmail, google analytics, and the new and improved search engine free. Free! Amazing!
4 comments:
I can't believe Google's been around for 10 years. I still kind of think of it as the "new" search engine...
You know what other ten year anniversary this month marks??? Yes! Our ten year anniversary of starting at King's! Yay to having been friends for ten years!
Jenny! It is hard to believe that a decade has flew by since we landed in the quad! I feel like I have missed a chance to have a great party! Friends for 10 years: sounds like a facebook group waiting to happen. Wait! We can start a group, and parties will rage! At King's: The Watch turns 20 and the Wardroom turns 30 (err, like some other people I know) this year!
A quick question off topic. In any large cross section of firms/plants there exists a range of firm/plant sizes. Some have higher productivity levels than others, either through better utilization or through reaching something close to minimum efficiency scale. If one estimates a cost function for these firms/plants, the current fasion is to use a flexible functional form - often the trans-logarithmic form.
In the cross-section, the coefficients on the second order derivatives capture curvature related to the trade off between inputs (note: you must have at least three inputs to estimate the trans-logarithmic function). The results from the cross section estimation fit data reasonably well.
I am curious if you think the same arguement can be made using time series data, particularly aggregate data for somthing like a business sector. Is it possible to capture the curvature associated with differing productivity levels across plants using changes in economic aggregates over time?
(sorry for the randomness of this, I just had it on my mind)
Hi Anonymous,
Yes, your question is rather random and asking such question on a blog unfortunately leaves little room to discuss for motivation (the most important part of any research). Before getting to the choice of how to model something, you should clearly state your research question. Otherwise, this just feels like a exam question (that I forgot to study for) and of little interest to my readers.
A cross-section, measures a point in time. In this case, a snapshot of the trade-off between different inputs across the business sector production to understand how different input mixes can be used to produce goods (if I understand you). I am actually surprised that it fits the data well (send me a paper?). Whether one could attempt to measure the trade-off overtime is not any harder practically speaking, but without knowing your motivation, it is hard to say whether it is appropriate. I am sure there is a deep literature that could provide you with much more direction than I can here.
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