For now, the class will be fully online. M212 is currently not open for teaching. We will reconsider in a month or so if the department allows for the use of M212.
TA: Xavier Bautista.     Xavier is available by appt. most days
TA Session will be online Friday 1pm-3pm.
No class: TBA if needed
Make-up classes: TBA if needed or desired
Exam Wednesday December 2nd 10-12pm. (This can be changed if someone has a good reason, but it should be done soon.Syllabus
Two midterms, Monday September 28th and Monday October 26th.
2019 Midterm 1
2019 Midterm 2
NOTE: There will be computer exercises using Matlab as part of the homeworks. NOTE: the computer exercises are at the heart of this course.
Material Covered 2019
Review of Maximum Likelihood (updated a little 2020) .
Short Introduction to Time Series. (How to work with time series model, unchanged from Macro II notes.)
Estimation of AR and MA models (revised 2020).
Truncation, censoring and selection.
(Similar to the coverage in the Davidson-MacKinnon book, but updated with more details 2020.)
My 1992 JBES article on credit rationing. (Example of an ordered-sequential logit model.)
After covering the selectivity model, I will talk about my 2000 Journal of Econometrics article on portfolio demand. (Example of an multinomial discrete-continuous logit model.)
The following notes may be adjusted during the semester.
Note on Panel Data (small corrections 2020)
Literature on clustered standard errors:
Bertrand, Dufflo and Mullainathan
Cameron and Miller: Guide to Cluster Robust Inference
(link to Cameron's WEB page which has the paper as well as Stata code and datasets)
Class Notes on Weak Instruments (summarizes some of the surveys below, small corrections 2020)
Know the striking example in Nelson-Starz Journal of Business (1990)
Michael Murray's survey in Journal of Economic Perspectives 2006, (you should know the formulas on pp. 123-124 and the Stock- Yogo (2005) rule of thumb in footnote 8)
Most up-to-date survey on weak instruments Andrews, Stock, Sun (2018)
Local Average Treatment Effects (LATE) if we get to it (not 2019):
Derivation of simplest case in my paper in Quantitative Economics
GMM Notes part 1
GMM Notes part 2
GMM Notes part 3 (The first two pages are the most important. The theory is not going to be on exam.)
Statistics Notes     Aug 24
Newton Algorithm     Aug 26
Information Matrix Identity     Aug 26
Likelihood Dependent Variables     Sep 2
Short intro to duration models     Sep 30
Short intro to SURE estimation     Oct 10
Short intro to Multivariate, Multinomial, Ordered and Sequential Probit/Logit Models     Oct 8
Short intro to identification in multivariate linear model     Oct 10
Short intro to bootstrapping of critical values     Oct 28
Homework # Matlab Code Due
Homework 1     Pdf Code Wed September 2
Homework 2     Wed September 9
Homework 3       MatlabAR-MA    Wed September 16
Homework 4       Program code    Wed September 23
Homework 5       Program code    Wed October 7
Homework 6       Program code    Wed October 14
Homework 7       Program code for 2SLS, LIML..    Wed October 21
Program code panel estimation
Homework 8       Program code for bootstrapping    Wed November 4
Program code for clustering
Homework 9       Program code for weak IV         Wed November 11
Homework 10          Program code     Wed November 18