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.

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.

Attendance Class attendance is required, and there will be considerable class participation. Students will be required to present some of the readings in class. Smartphones, tablets, and laptops may not be used in class.

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.

General Remarks 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.

Readings The main reference for much of the macroeconomics part of the course is Macroeconometric Modeling: 2018, denoted MM below. Most of the readings will be journal articles. The following are some of the readings. More readings will be added later.

January 13, 15, 17, 22: Econometric Methodology and Tools
# Your econometrics text---use this for review throughout the course.
# Case, Fair, and Oster, Chapter 21, "Critical Thinking About Research."
# Fair, Ray C., Predicting Presidential Elections and Other Things, Second Edition, Chapters 1 and 2.
# MM, Sections 2.1 and 2.3.

January 27, 29, February 3, 5: Autoregressive (AR) and Vector Autoregressive (VAR) Forecasting; Quasi Ex Ante Forecasting
# Your econometrics text on time series modeling.
# Fair, Ray C., and Robert J. Shiller, "Comparing Information in Forecasts from Econometric Models," The American Economic Review, June 1990, 375-389.
# Fair, Ray C., and Robert J. Shiller, "The Informational Content of Ex Ante Forecasts," The Review of Economics and Statistics, May 1989, 325-331.
# Fair, Ray C., "Information Content of DSGE Forecasts," Journal of Forecasting, 2019.
# Begin the first paper. Get whatever software you are going to use in control. A topic will be given if you want to use it for the first paper. If you want to use the FP program, there will be a review session on it.

First paper due Monday, February 10, before class

February 10, 12, 17, 19, 24, 26, March 2, 5: Structural Macro Modeling; Macro Financial Effects
# S&P 500 data, S&P 500 data
# S&P 500 regression, S&P 500 regression
# Lecture 9, Lecture 9
# Lecture 14, Lecture 14
# MM, Sections 1.1, 1.2, Macroeconometric Modeling: 2018.
# US Model, US Model
# Wealth effects: MM, Sections 4.2, 5.7. (Optional)
# Begin second paper by February 20.
# Nowcasting, Nowcasting

Second paper due Monday, March 23, before class. (This is after the break)

March 23, 24: Are Asset Price Changes Predictable?
# Articles on efficient markets.
# Shiller, Robert J., Narrative Economics, American Economic Review, 2017.
# Shiller, Robert J., Bubbles, Human Judgment, and Expert Opinion, Financial Analysts Journal, 2002.
# Begin third paper. It can be an extension of the second paper, depending on how original the second paper was.

March 30, April 1: Momentum Forecasting
# Articles on possible momentum in the stock market.
# Moskowitz, Tobias J., Yao Hua Ooi, and Lasse Heje Pedersen, Time Series Momentum, Journal of Financial Economics, 2011.
# Hurst, Brian, Yao Hua Ooi, and Lasse Heje Pedersen, A Century of Evidence on Trend-Following Investing, The Journal of Portfolio Management, Fall 2017.

Outline of third paper due Wednesday, April 7, before class

April 6, 7: Back to Macro Forecasting: True Ex Ante Forecasts
# Fair, Ray C., Ex ante forecasts from the US model and its forecasting record.

April 13, 15, 20, 22: Student presentations of the third paper

Third paper due the last day of final exams, Wednesday, May 6, at 5pm.

Data, News Items, Miscellaneous
# Macro data, data
# Data descriptions, Table A.2, pdf file
# Fed equation, Fed equation
# FP program, FP program
# Example of data mining, Gary Smith, Data Mining