Course web page:
Instructor:
Teaching assistant:
Books available at UCSD bookstore:
Fumio Hayashi, Econometrics, Princeton University Press, 2001. This is the main text for the course. Click here for the home page for Hayashi's text.
James D. Hamilton, Time Series Analysis, Princeton University Press, 1994. This book is used as an optional supplementary text for the course and is also used in other courses at UCSD.
Journal articles:
Arnold Zellner, "Bayesian and non-Bayesian analysis of the regression model with multivariate Student-t error terms", Journal of the American Statistical Association, 71, June 1976, pp. 400-405.
M.L. King, "Robust tests for spherical symmetry and their application to least squares regression", Annals of Statistics1980, pp. 1265-1271.
N. Gregory Mankiw, David Romer, and David Weil, "A Contribution to the Empirics of Economic Growth," Quarterly Journal of Economics,107, May 1992, pp. 407-437.
Howard J. Wall, "Using the Gravity Model to Estimate the Costs of Protection," Federal Reserve Bank of St. Louis Review, Jan/Feb 1999, pp. 33-40.
Stephen V. Cameron and James J. Heckman, "The Nonequivalence of High School Equivalents," Journal of Labor Economics, Vol. 11, part 1, Jan 1993, pp. 1-47.
Joshua D. Angrist and Jorn-Steffen Pischke, "The Credibility Revolution in Empirical Economics: How Better Research Design is Taking the Con out of Econometrics," Journal of Economic Perspectives, 24, Spring 2010, pp. 3-30.
Douglas Staiger and James H. Stock, "Instrumental Variables Regression with Weak Instruments," Econometrica 65, May 1997, pp. 557-586.
The articles above can be downloaded online. The syllabus you are now reading can also be viewed as an HTML document at http://dss.ucsd.edu/~jhamilto/Econ220B_syllabus.html. If you are viewing this as an HTML document, clicking on any active link above will take you immediately to the source where the article can be viewed online or downloaded.
Grades for Econ 220B will be determined as follows:
| Tues Jan 10 | Review of linear algebra (Hamilton, Section A.4, pp. 721-739) | |
| Thurs Jan 12 | The algebra of least squares (Hayashi, Section 1.2) | |
| Tues Jan 17 | The classical regression model (Hayashi, Sections 1.1 and 1.3; Hamilton, Section 8.1) | |
| Thurs Jan 19 | Hypothesis testing (Hayashi, Sections 1.4, 1.5, and 1.7; references: Zellner, 1976 and King, 1980) | |
| Tues Jan 24 | Generalized least squares (Hayashi, Section 1.6) | |
| Thurs Jan 26 | Asymptotic distribution theory (Hayashi, Sections 2.1-2.2; Hamilton, Section 7.1) | |
| Tues Jan 31 | Large sample properties of OLS (Hayashi, Sections 2.3 and 2.9; Hamilton, Section 8.2) | |
| Thurs Feb 2 | Hypothesis testing-- asymptotic results (Hayashi, Sections 2.4-2.6; Hamilton, Section 8.2) | |
| Tues Feb 7 | Maximum likelihood estimation (Hayashi, Section 1.5; Hamilton, Section 5.7) | |
| Thurs Feb 9 | Midterm exam | |
| Tues Feb 14 | Heteroskedasticity and serial correlation (Hayashi, Sections 2.7, 2.8, 2.10, 2.11; Hamilton, Section 8.3) | |
| Thurs Feb 16 | Simultaneous equations bias (Hayashi, Sections 3.1-3.2; Hamilton, Section 9.1) | |
| Tues Feb 21 | Applied econometrics (Mankiw, Romer, and Weil; Wall) | |
| Thurs Feb 23 | Applied econometrics (Cameron and Heckman; Angrist and Pischke) | |
| Tues Feb 28 | General formulation (Hayashi, Section 3.3; Hamilton, Section 9.2) | |
| Thurs Mar 1 | No scheduled class | |
| Tues Mar 6 | Weak instruments (Staiger and Stock) | |
| Thurs Mar 8 | Generalized method of moments (Hayashi, Sections 3.4-3.6; Hamilton, Section 14.1) | |
| Tues Mar 13 | Uses of GMM (Hayashi, Sections 3.8-3.9; Hamilton, Section 14.2) | |
| Thurs Mar 15 | GMM and Maximum likelihood estimation (Hamilton, Section 14.4) | |
| Thurs Mar 22 | Final exam (8-11 a.m.) |