The course covers topics related to financial economics, including
investors attitudes toward risk, capital allocation, portfolio
selection, asset pricing models (Capital Asset Pricing Model and
Arbitrage Pricing Theory), the efficient market hypothesis, fixed income
markets, equity valuation, and options and futures markets.
Link
to syllabus (Spring 2013)
This course provides an introduction to multiple regression methods
for analyzing data in economics and related disciplines. Starting from
the linear regression method, the course will extend to regression with
discrete random variables, instrumental variables regression, analysis
of random experiments and quasi-experiments, and regression with time
series data. The objective of the course is twofold: (i) understand the
logic and the key intuitions behind the various econometric procedures,
and (ii) learn how to conduct and how to critique empirical studies in
economics and related fields. Accordingly, the course will devote
significant space to empirical applications. Through the use of
econometric software and a variety of empirical data sets, you will have
the opportunity to gain hands-on experience on how to conduct empirical
work in econometrics.
Link to syllabus
(Spring 2014)
This course aims at introducing econometric models and empirical
techniques that are useful to conduct economic research with data. The
course covers linear regression models, discrete choice models, time
series models, and panel data models. We will devote significant space
to empirical applications, and give the students the opportunity to gain
hands-on experience on how to conduct empirical work in econometrics
using the R programming language.
Link to syllabus
(Fall 2018)
This course examines the models and statistical techniques used to
study time series data. Topics include linear and non-linear univariate
as well as multivariate econometric models. The first goal of the course
is to provide students with a good understanding of econometric models
for time series data. These models are widely used in the empirical
macroecomic and financial literature, and a good understanding of these
models is crucial for the second goal of the course, provide students
with the tools to understand and evaluate empirical studies. The third
goal of the course is to develop empirical skills, which are necessary
to perform independent research using real world data. A theme
throughout the course is the use of computational methods for analyzing
the material covered in class, and throughout the course we will rely
heavily on examples and applications using the software MatLab.
Link to syllabus
(Spring 2014)