ECN 240A ECONOMETRIC Winter 2014 METHODS

ARE/ECN 240A ECONOMETRIC METHODS ... Some of the material in my notes borrows from the textbook that Bruce Hansen ... Examples of assignments and solu...

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ARE/ECN 240A Department of Economics

University of California, Davis Professor Òscar Jordà

ARE/ECN 240A Instructor:

ECONOMETRIC METHODS

Winter 2014

Professor Òscar Jordà 1150 Social Sciences and Humanities Bldg. (SSH) Phone: (530) 554 9392 e-mail: [email protected] CLASS URL: http://www.econ.ucdavis.edu/faculty/jorda/class/240a/240a.html

Class Meets:

M-W, 10 – 11:20/50am. Room: KERR 293

Office Hours:

Mondays, 1 – 2pm; Tuesdays 10-12am, or by appointment

Teaching Assistant

Felipe Avilés Lucero Room: SSH 117 e-mail: [email protected] Fridays 1-3pm, or by appointment

Office Hours:

Textbook: I do not follow a particular textbook. Instead, I constructed my own notes from different sources. I have specific views as to what and how to teach the material. However, professor Dalia Ghanem, the 240B instructor, will use Econometric Analysis of Cross Section and Panel Data (2nd Edition) by Jeffrey M. Wooldridge. Below I provide the correspondence between some of the chapters in Wooldridge and my notes. Other textbooks you may find helpful are: Econometric Theory and Methods by Davidson and McKinnon (Oxford University Press); Econometrics by Fumio Hayashi (Princeton University Press); and Econometric Analysis by William Greene. Some of the material in my notes borrows from the textbook that Bruce Hansen makes available in his website: http://www.ssc.wisc.edu/~bhansen/econometrics/. I like his approach on a number of topics although for some others, the level may be too high for this course. Assignments: I plan to have regular assignments, hopefully involving some computer work as well. Examples of assignments and solutions posted on my website. The software program I plan to use is STATA. In the past I have also assigned problems in GAUSS but a) perhaps this is too much and b) Matlab is now more prevalent than GAUSS. My understanding is that STATA is widely available to students in both departments. Grading: There will be three components to your grade, assignments (10%), midterm (40%) and final (50%).

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ARE/ECN 240A Department of Economics

University of California, Davis Professor Òscar Jordà

Important Dates: January 20 February 10 February 17 March 20: 6-8pm

Martin Luther King’s Day Midterm President’s Day FINAL

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Topic 0. Review of Basic Concepts. Quick review of bivariate regression, estimation, inference and evaluation. Statistical foundations. Basic statistical concepts you should know from 239. Basic matrix algebra you should know. o Wooldridge chapter 1 Topic 1. Multivariate Regression: Part I. Statement of the objective of regression analysis. Basic assumptions. Three approaches: method of moments (MM); ordinary least squares (OLS); and maximum likelihood (MLE). Basic derivations for each of these methods. o Wooldridge chapters 2 and 4. Topic 2. Multivariate Regression Part II. Properties of MM/OLS/MLE estimators – finite and large sample properties. Basic theory for extremum estimators. o Wooldridge chapters 3, 4, 12 and 14. Topic 3. Inference I. Elements of a test. Wald, likelihood ratio (LR) and Lagrange multiplier (LM) tests; single and multiple hypothesis testing; asymptotic distribution of common tests. Topic 4. Inference II. Confidence regions and simultaneous testing procedures. Simulation-based testing. Assessing the size and power of a test with Monte Carlo techniques. The bootstrap. o Wooldridge chapters 12 and 14 Topic 5. Extensions to the basic framework I. Heteroskedasticity and autocorrelation – testing and generalized least-squares. o Wooldridge chapter 6 Topic 6. Instrumental Variable Regression. Causation versus correlation. Basic ideas. Two stage least squares. Generalized Method of Moments. o Wooldridge chapters 5 and 14 Topic 7. Extensions to the basic framework II. Nonlinear regression. Limited dependent variable regression and applications of MLE. o Wooldridge chapters 13, 14 and 15 Topic 8. Introduction to Time Series Data. Introduction to basic concepts. Stationarity. ARMA models. o Wooldridge does not cover this material. Alternatives are Hamilton’s Time Series Analysis (Princeton University Press) which is the textbook for 240C; Hayashi, chapter 6; or Hansen chapter 17.

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