Econ 439: Spring 2023


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.


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.


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.


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.

January 18, 20, 23, 25: Econometric Methodology and Tools

January 30, February 1, 6, 8: Autoregressive (AR) and Vector Autoregressive (VAR) Forecasting; Quasi Ex Ante Forecasting

First paper due Monday, February 13, before class

February 13, 15, 20, 22, 27, March 1: Structural Macro Modeling; Macro Financial Effects

March 6: Reports by Students on the Second Paper

March 8: Nowcasting

Second paper due Friday, March 10, at midnight

March 27, 29: Shiller and the Stock Market, Discussion of SP500 Regression

April 3, 5: Momentum Forecasting

Outline of your third paper and a pdf file of your lead article due Noon, Sunday, April 9

April 10, 12: Student presentations of ther lead article

  • Goolsbee, Austan, and Chad Syverson, Fear, Lockdown, and Diversion: Comparing Drivers of Pandemic Economic Decline: 2020, NBER Working Paper 27432, June 2020.
  • Jacks, David S., and Martin Stuermer, What Drives Commodity Price Booms and Busts?, Dallas Fed Working Paper 1614, November 2016.
  • Lansing, Kevin J., Improving the Phillips Curve with an Interaction Variable, FRBSF Economic Letter, May 6, 2019.
  • Xu, Xiaoqing Eleanor, and Hung-Gay Fung, What Moves the Mortgage-Backed Securities Market?, Real Estate Economics, 2005.

    April 17, 19: Announcement Effects, Open Economy Macro

    April 24, 26:: Student presentations of the third paper

    Third paper due midnight, Wednesday, May 3. Dean's excuse needed for an extension.

    Data, News Items, Miscellaneous