Econ 439 Spring 2021 Applied Econometrics: Macroeconomic and Finance Forecasting Ray C. Fair |
Description
This course has an applied econometrics focus.
The focus is on forecasting macroeconomic and financial variables.
The requirements are three empirical papers. The first, worth 20 percent
of the grade, is an extension of an existing article,
where some of the results are duplicated and then extended. An example
is provided if a student wants to use it. The second, worth 30 percent
of the grade, is more of the same but with no example provided. The third,
worth 50 percent of the grade, is a more original paper within the
range of topics covered in the course, where data are collected
and analyzed using whatever econometric techniques are relevant.
This paper can possibly be the beginning of a senior essay.
The aim of the course is to get students doing original empirical
research using econometric tools. It is also to prepare students to
read empirical papers in economics and finance.
Macroeconomic forecasting concerns forecasting variables like GDP, components of GDP like consumption, investment, and imports, inflation, the unemployment rate, interest rates, the government deficit, and exchange rates. There are various forecasting methods, some purely statistical time series techniques and some using economic theory. We will consider both. Financial forecasting is more problematic, since changes in asset prices may be roughly unpredictable. We will examine topics like momentum forecasting to see if some asset prices are predictable. There will also be some lectures on time series econometrics, which is usually not covered extensively in the core economertrics courses. Prerequisites: Two semesters of econometrics or statistics and intermediate macroeconomics. Special permission from the instructor is needed if the student has had only one semester of econometrics or statistics. Attendance Class attendance is required, and there will be considerable class participation. Statistical Software Many students use R, but any software is fine. A package focused on time series econometrics would be ideal, but not necessary. One possibility is the Fair-Parke program: FP Program. Class time will not be taken going over software. Readings The main reference for much of the macroeconomics part of the course is Macroeconometric Modeling: 2018, denoted MM below. Most of the other readings will be journal articles. The following are some of the readings. More readings will be added later.
February 1, 3, 8, 10: Econometric Methodology and Tools
February 15, 17, 24: Autoregressive (AR) and
Vector Autoregressive (VAR)
Forecasting; Quasi Ex Ante Forecasting
First paper due Monday, March 1
March 1, 3, 8, 10, 15, 17:
Structural Macro Modeling; Macro Financial
Effects
March 22: Reports by Students on the Second Paper Second paper due Monday, March 29
March 29: Nowcasting
One page discussion of your SP500 regression due noon, Sunday, April 4
March 31, April 5, 7: Shiller and the Stock Market, Discussion of SP500
Regression
April 12, 14: Momentum Forecasting
Outline of your third paper and a pdf file of your lead article due Noon, Sunday, April 18
April 19, 21: Student presentations of the lead article
# Goolsbee, Austan, and Chad Syverson,
Fear, Lockdown, and Diversion: Comparing Drivers of Pandemic Economic
Decline: 2020, NBER Working Paper 27432, June 2020.
April 26, 28: Announcement Effects, Open Economy Macro
# Fair, Ray C., Shock Effects on Stocks,
Bonds, and Exchange Rates, Journal of International Money and
Finance, 2003.
May 3, 5: Student presentations of the third paper Third paper due midnight, Wednesday, May 12. Dean's excuse needed for an extension.
Data, News Items, Miscellaneous
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