TUFTS UNIVERSITY Department of Economics Economics 207: Graduate Applied Econometrics Professors Marcelo Bianconi and Jeffrey Zabel Syllabus - Fall Semester
Office: E-Mail:
Prof. M. Bianconi 111 Braker Hall
[email protected]
Prof. J. Zabel 221 Braker Hall
[email protected]
Software: STATA Course Requirements for Part 1: Homework (10% total) (to be handed in at a prearranged date) One Exam (20%) on October 14 One Final Project (20%) that includes a class presentation on October 19 or October 21 and a related paper, due on October 28 (More information about the final project will be distributed) Course Requirements for Part 2: Homework (10% total) (to be handed in at a prearranged date) One Exam (20%) W, November 18; in the evening 8:00-9:00PM or TBD One Final Project (20%) that includes a class presentation on December 7 or December 9 and a related paper, due on December 14 (More information about the final project will be distributed) LATE HOMEWORK ASSIGNMENT/PROJECT POLICY: 10% of the total homework/project score will be deducted per day for each late homework/project with the exception that the weekend will count 15% off the total score. Homework will not be accepted after 10:30 am of the following class after the homework is due. For example, if homework is due on Wednesday, September 10 at 3:00 pm then it will not be accepted after 3:00 pm on Monday, September 15.
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Part 1: Estimating Causal Impacts in Micro-Economics: Theory and Practice COURSE DESCRIPTION This course focuses on the recent literature and methodology used to estimate causal impacts in microeconomics. We will start by establishing the basic framework for analyzing causal impacts – called the Rubin Causal Model. Next, we will consider 5 frameworks for data generation used to evaluate causal impacts: Randomized Controlled Trials (RCTs), Quasi-Experiments, Natural Experiments, Regression Discontinuity, and Observational Data. In the process we will also consider different estimators: Instrumental Variables, Matching Estimators, and difference-in-difference estimators. The focus is on applying these different data generation frameworks and estimators to a broad scope of economic questions and issues.
TEXTBOOKS:
Mostly Harmless Econometrics: An Empiricist’s Companion by Joshua Angrist and Stephen Pischke Princeton: Princeton University Press, 2009.
REFERENCES:
Introductory Econometrics, A Modern Approach, 4th edition by Jeffrey M. Wooldridge South-Western Publishing Company, 2008.
Important Articles: Imbens, Guido and Jeffrey Wooldridge (2009) “Recent Developments in the Econometrics of Program Evaluation,” Journal of Economic Literature 47:1 5-86. Lee, David S. and Thomas Lemieux (2010) “Regression Discontinuity Designs in Economics,” Journal of Economic Literature 48:1 281-355.
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Part 2: TIME SERIES ANALYSIS COURSE DESCRIPTION This course focuses on the modeling of economic time series, with particular attention to financial time series. Time series analysis has become one of the most important tools for the understanding and interpretation of dynamic economic processes, in particular, the ones concerning macroeconomic variables such as real output, interest rates, inflation rates, exchange rates, and so on. An important advantage of applying these methods is that, with a basic understanding of the dynamic process that underlies a certain economic time series, one is able to construct forecasts within a certain range of confidence. Several references to specific papers will be provided. Some Textbooks: Yacine Aït-Sahalia & Jean Jacod (2014) High-Frequency Financial Econometrics. Princeton University Press, NJ. The treatise on financial trading for small and potentially unevenly spaced data and the econometric methods for it. Badi H. Baltagi (2013) Econometric Analysis of Panel Data, 5th Edition, September 2013, Wiley. A thorough review of theory and method of panel data including the dynamic case. Campbell, John Y., Andrew W. Lo and A. Craig MacKinlay (1997) The Econometrics of Financial Markets. Princeton University Press, Princeton, NJ. This is a competent survey of applied theory and econometric practice with financial markets. It is advanced, but Chapter 1 is a very useful reading. Enders, Walter (1995, 2009, 3rd Edition) Applied Econometric Time Series. John Wiley & Sons Inc.: New York, NY. This is a good undergraduate textbook on time series econometrics; I shall refer to it often and will make some of the material available. Granger, Clive W. J. (1989) Forecasting in Business and Economics. Second Edition. Academic Press, Inc., Boston. This is a low-level textbook that discusses time series econometrics with emphasis on forecasting techniques. Granger, Clive W. J. and Paul Newbold (1986) Forecasting Economic Time Series, Second Edition. Academic Press, New York. Classic graduate textbook on time series econometrics. Hamilton, James (1994) Time Series Analysis. Princeton University Press, Princeton, NJ. The main graduate textbook on the subject. The ultimate treatise. Andrew Harvey (2013) Dynamic models for Volatility and Heavy Tails. Econometric Society Monograph. Cambridge University Press. June. Time series models for volatility and heavy tails data. Holden, K., D. A. Peel, and J. L. Thompson (1990) Economic Forecasting: An Introduction. Cambridge University Press, Cambridge. Survey of time series econometrics applications. Intriligator, Michael D., Ronald G. Bodkin, and Cheng Hsiao (1996) Econometric Models, Techniques, and Applications. Prentice Hall, NJ. General econometrics textbook at the undergraduate level; presents a nice chapter on econometric projects. 3
Lütkepohl, Helmut (2007) New Introduction to Multiple Time Series Analysis. Springer-Verlag. Mills, Terence C. and R. N. Markellos (2008) The Econometric Modelling of Financial Time Series Cambridge University Press. 3rd edition. I shall make some parts of it available to the class. Mills, Terence C. (1999) The Econometric Modelling of Financial Time Series, Second Edition. Cambridge University Press, Cambridge, UK. This is a text that presents some of the developments in time series econometrics applied to financial data. Mills, Terence C. (1990) Time Series Techniques for Economists. Cambridge University Press, Cambridge. It is comparable to Enders (1995), and I shall make some parts of it available to the class. Newbold, Paul and Theodore Bos (1994) Introductory Business and Economic Forecasting, Second Edition. South-Western Publishing Co., Cincinatti, OH. Another undergraduate textbook that discusses time series econometrics from the point of view of forecasting techniques. Pindyck, Robert S. and D. L. Rubinfeld (1998) Econometric Models and Economic Forecasts. Fourth Edition. McGraw Hill Book Co., New York. A very good undergraduate econometrics textbook with very valuable and accessible material in time series techniques; I shall make some parts available. Ramanathan, Ramu (1998) Introductory Econometrics with Applications, Fourth Edition. The Dreyden Press, HBJ, New York. Solid undergraduate econometrics textbook with good time series material as well. Tsay, Ruey S. (2010) Analysis of Financial Time Series (Wiley Series in Probability and Statistics, 3rd Edition). This is an excellent textbook that covers many new important topics. Wooldridge, Jeffrey (2008) Introductory Econometrics: A Modern Approach. South-Western College Pub; 4th Edition. Advanced undergraduate/masters level textbook, very detailed and useful. Wooldridge, Jeffrey (2010 )Econometric Analysis of Cross Section and Panel Data. MIT Press. The classic on modern panel data analysis.
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TOPICS (Tentative) Univariate Time Series: Dynamic Stochastic Processes: The Stationary Case Applied Time Series Analysis and the Identification-Estimation-Diagnostic Checking Approach Structural Breaks; Trend and Cycle Decomposition ARCH, GARCH and Volatility Dynamic Stochastic Processes: The Nonstationary Case [Integrated Processes and the Unit Root Problem] Cointegration and Error Correction Models Markov Switching Models Multivariate Time Series: VAR Models; Structural VAR Models Dynamic Factors Models (Dynamic Principal Components) VEC (Vector Error Correction) Multivariate ARCH-GARCH Dynamic Panel and Panel Unit Roots Instrumental Variables (IV) – Generalized Methods of Moments (GMM)
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CLASS SCHEDULE Monday
Wednesday PART 1 9/09 CLASS 1 (JZ): Introduction
9/14 CLASS 2 (JZ): Economic Significance
Homework 1 Assigned 9/16 CLASS 3 (JZ): RCM Framework
9/21 CLASS 4 (JZ): Regression Fundamentals
Homework 1 Due Homework 2 Assigned 9/23 CLASS 5 (JZ): Matching Estimators
9/28 CLASS 6 (JZ): Instrumental Variables
Homework 2 Due Homework 3 Assigned 9/30 CLASS 7 (JZ): Instrumental Variables
10/05 CLASS 8 (JZ): Natural Experiments
10/07 October CLASS 9 (JZ): Regression Discontinuity
10/12 CLASS 10 (JZ): Difference-in-Difference Estimator
Homework 3 Due 10/14 CLASS 11 (JZ): Panel Data
10/19 CLASS 12 (JZ) Student Presentations
Exam 10/21 CLASS 13 (JZ): Student Presentations
PART 2
10/28
10/26
CLASS 14 (MB):
Univariate Time Series Dynamic Stochastic Processes: The Stationary Case
CLASS 15 (MB):
Univariate Time Series Identification-Estimation-Diagnostic Checking Approach Forecasting, Trend and Cycle Decomposition
Homework 1 Assigned
Final Project Paper for Part 1 Due
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November 11/02 CLASS 16 (MB):
11/04 CLASS 17 (MB): Univariate Time Series
Dynamic Stochastic Processes: The Nonstationary Case [Integrated Processes and the Unit Root Problem]
Univariate Time Series
Homework 1 Due Homework 2 Assigned
Dynamic Stochastic Processes: The Nonstationary Case [Integrated Processes and the Unit Root Problem] Structural Breaks; Rethinking Trend and Cycle Decomposition Cointegration and Error Correction
11/09
CLASS18 (MB):
11/10 CLASS 19 (MB): Wednesday’s Schedule on Tuesday
Univariate Time Series Univariate Time Series Dynamic Stochastic Processes: The Non Stationary Case Cointegration and Error Correction
Dynamic Stochastic Processes: ARCH, GARCH, Volatility
ARCH, GARCH, Volatility
Introduction to Markov Switching Models
Homework 2 Due Homework 3 Assigned 11/16 CLASS 20 (MB):
11/18
CLASS 21 (MB):
Univariate Time Series Multivariate Time Series Dynamic Stochastic Processes: VAR, Structural VARs Introduction to Markov Switching Models Multivariate Time Series VAR, Structural VARs
One-Hour Exam: In the evening, 8:009:00PM or TBD
Homework 3 Due 11/23 CLASS 22 (MB):
11/25 NO CLASSES: THANKSGIVING
Multivariate Time Series VAR, Structural VARs Dynamic Factors Models (Dynamic Principal Components)
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11/30 CLASS 23 (MB):
December 12/02 CLASS 24 (MB):
Multivariate Time Series: Multivariate Time Series: Dynamic Panel and Panel Unit Roots VEC (Vector Error Correction)
Multivariate ARCH-GARCH Dynamics: IV – GMM
Student Report Due 12/07 December CLASS 25 (MB):
12/09
Student Discussions-Presentations
Student Discussions- Presentations
CLASS 26 (MB): LAST CLASS
12/14
Final Project Paper for Part 2 Due By 5:00PM
MB/JZ October 2015
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