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15.013  Industrial Economics for Strategic Decisions

Fall 2010

Instructor: Robert S Pindyck

TAs: David Jacobs, Dagmar Trantinova, Fatma Yalcin

Section A Lecture:  MW 10:00-11:30  (E51-315)
Section B Lecture:  MW 1:00-2:30  (E51-315)      

Information: 

 

Announcements

Informational Cascade Clarification

Class,

 

There have been several questions regarding informational cascades. The key to understanding this topic is that when each firm makes the decision to invest, they do so after doing their own research and calculating the probability of success and the probability weighted net present value. If you run through the example from class and the calculations presented in the course pack you will see that if person A gets a strong positive signal and person B invests (either from a positive signal or a coin flip), the probability of success for person C and onward is going to be above 0.5. As people are investing in positive NPV opportunities, it is therefore rational in the long run to do so. The note below is from Professor Pindyck explaining the topic with a real world example.

 

                Here is the basic idea.  The model I presented was very basic and just designed to make a point, which is that if people based their decisions on information they get (the “signal” they receive) as well as the actions of other people, and if they know the other people are doing the same thing (and have also received a “signal”), then it can be rational (in terms of an expected NPV > 0) to act even with a negative signal.  This simple model assumes that people make their decisions (e.g. to invest in real estate) one at a time, and it doesn’t say anything about how the cascade ends.

 

                To apply this in practice, let’s consider real estate in Florida 3 or 4 years ago.  Real estate developers looked at Florida housing markets and got “signals,” many (but certainly not all) of which were positive.  Perhaps their studies showed that more retired people wanted to move to Florida, that the tourism industry in Florida was growing, that more businesses were moving to Florida, etc.  And some of these developers might have even learned about the positive signals of a few other developers (which was not in our simple model, but that’s OK).  And they see something else – lots of developers are buying land and building houses and condos.  So they rationally concluded that they should buy land and build houses.  Then individuals who don’t know much at all about real estate see prices going up year after year, conclude (rationally) that the developers are professionals who must have studied the market carefully, and based on what the developers are doing decide (rationally) to buy several houses themselves as “investments.”

 

                How did this housing cascade end?  First there are public research studies (e.g., by economists like Robert Shiller and others) that make a strong case that increases in housing prices (in Florida and elsewhere) are not consistent with fundamentals of supply and demand.  Next homeowners in Florida start defaulting on their mortgages, and developers start having trouble selling newly completed condos.  Soon there are enough negative “signals” that people start to conclude that Florida real estate is not such a good investment after all.  Then more and more people start to sell, and prices fall. 

 

                Note that at the early stages it was rational for developers and individuals to invest in Florida real estate.  And in the end it was rational for them to sell as soon as they started to realize what was going on.

Announced on 03 December 2010  6:17  p.m. by David Jacobs

Google Form for Game Submissions

Please use this google form to play the strategic oligopoly game each week. If you want to change your submission until Monday, 5pm, simply re-submit the form and we will use your latest submission.

https://spreadsheets.google.com/viewform?formkey=dHBtb2tlNmRDZ2RfcGhFYnkzc1FySWc6MQ

Thanks,

Dave and Fatma

Announced on 24 September 2010  1:35  p.m. by Fatma Yalcin