The first of many Krugmans

Below you will see my reply to Princeton Economist Paul Krugman's May 7th post, Phase Two. I'll be commenting a lot on Paul's work; blog posts, New York Times columns (He's a regular columnist every Monday and Friday), popular books, academic books, papers, and other works. I'm a huge admirer of his. I really think he is a great man. He's absolutely brilliant and he's a great person with a big heart and great character. He won the John Bates Clarke Medal, which is Economics second most prestigious prize, and he is likely to eventually win the first, the Nobel. But at the height of his academic career, he diverted what I would guess is much more than half of his time to helping others by writing for the general public about economics and politics in order to educate and encourage people to support policies that make our country and the world a much better place, thus his many popular books, regular New York Times column, and blog, as well as his public and press appearances.

All of this takes huge time away from his academic work, and the vast majority of top academics do little but work huge hours on their academic work. Thus, he has seriously risked his chance of winning a Nobel prize, and of being recognized as one of the great economists in history. This huge amount of time could also have been spent on his personal life, which, with all he does, I doubt he has much time for. So he's truly a caring man who has sacrificed much to help others.

O.k., a moment to dry our eyes...Now to my comments on Paul's recent post:

Some key things to keep in mind:

1) The graph has average (real - I checked the book) income growth of those employed. It doesn't factor in the unemployment rate, and this could and should be factored in. That's why even in recession years like 1992 we see about 2% growth in incomes - it's growth in incomes of those who have an income.

2) It doesn't factor in how skewed the average income growth is, which can be very important this year, where a huge percentage had their incomes decrease or stagnate, and a small minority had giant gains. This also can, and should be factored in.

A quick idea (very technical) - try catagorizing the data. For example:

Define the parameters a1 through a7 as follows;

-a1 = Unemployed person

-a2 = Decrease in earnings greater than 10%

-a3 = Decrease in earnings between 5% and 10%

-a4 = Decrease in earnings between 1% and 5%

a5 = Increase in earnings between 1% and 5%

a6 = Increase in earnings between 5% and 10%

a7 = Increase in earnings greater than 10%

Then, come up with numbers for the parameters a1 through a7 by calibrating to the historic data before 2008 (finding the values for the a1 through a7 that will make this model best fit the historic data).

So, you might find a1 = 5, a2 = 3.7, a3 = 1.4, etc.

Then, plug in 2008's numbers and see what comes out for the probability of the incumbent party losing.

The idea behind catagorizing is that it stops false linearity. What do I mean by that? The way the model is now, if a person's income increases by 50%, it's saying it's 10 times more likely that he will vote for the incumbent party than if his income increased by only 5% (this is approximately true, technically due to a non-zero intercept -- sorry to the laypeople). This is probably very unrealistic. In reality it's probably something like there's typically a 60% chance of a person voting for the incumbent party if he has a 5% increase in income and an 80% chance if he has a 50% increase in income. So the probability increase from 60% to 80%, a 33% increase, not a 10 fold, or 1,000%, increase.

Any source