Last modified: Wednesday, 9 April 2008 at 20:08 UTC.

1.A Fetch and plot US quarterly GDP Employment, Total hours worked, Hours per worker, Hours per adult of working age and Hourse per person not in jail over 18 years of age both from CPS and from the firm survey (see Cooley chapter 1, page 30). Store it in pdf, eps, and emf or wmf formats.
1.B HP filter and plot US quarterly (log) GDP and the series in 1.A. Store it in postcript or pdf. Compute the same table as in the Cooley book for those 4 variables using data up to 2003:4 or later.
1.C Calculate a linear trend and decompose log GDP in the linear trend the hp trend and the hp residual.
1.D Plot the growth rates together with the hp residual and comment the differences.
1.E Compute a VAR of GDP, Total Hours and Labor Productivity and plot the impulse responses. Make sure that you explicitly state what are the identifying assumptions that you make.
Write a routine that linearly interpolates. Apply it by storing the value of exp (x) between 0 and 1. in intervals of .1 and assessing the value by interpolation in intervals of .05. Plot the function and what results from using approximation.
(Parts of Homework 1 of Chapter 5 of Judd's book.) Solve sin 2 p x 2x=0 using bisection between x _{ 0 } =5 and x _{ 1 } =5 (If this interval is a bad one change it).
Compute labor factor shares with a CES production function
Y=[ q K ^{ r } +(1 q )N ^{ r } )] ^{ 1/ r }
when K=N=1, and K=2, N=1. Are they the same?
What about with CobbDouglas ( r =1).
Note that Labor share = w*N/Y, and that under competition w=(dY/dN).
The tools that we will be developing beyond those already covered in the first year can be grouped into:
This is a Ph.D. course not a Masters course. As such students are not expected to learn what other people have discovered, but the tools that are needed in order to discover things by themselves. Because of this reason the active work of the students is crucial to achieve the objective of mastering the tools that are described above. This is a course to learn to do things, and, therefore, it requires to do some things.
Every class except the first one we will devote the first twenty minutes or so to students presentations of homeworks. I expect professional competence in this regard.
There are various types of requirements that are a necessary part of the course, all of which have to be fulfilled.
This course believes drastically in Learning by Doing. To learn the material that we cover requires that students do all the homeworks in a timely manner. Given the way to collect the homeworks, timeliness is automatically recorded. I will look at what is done weekly.
This is not a course in computer languages so students are responsible to learn to write computer programs. Students are also responsible for learning their way around McNeil computational facilities. I do not expect anybody to have a computer at home or anything like that. It is better to work in McNeill's computer room because you can talk to each other.
There are three general classes of computer languages.
Students should be able to write code in F90 in addition to matlab or gauss and to stata. Most students tell me in later years that I should have enforced harder the learning of F90, but I am willing to consider exceptions. If somebody has a serious reason not to use F90, please come and talk to me. At least one homework should be answered in f90.
Look at Tips for Doing Computational Work in Economics by Tony Smith for insights.For those that do not register but take the course, I recommend that they do the homeworks. We learn to solve problems by facing them. Learning jointly with others greatly speeds the process. The deadline for the Empirical Requirement is the last day of class.