Not available at this time

This is a stand-alone independent study designed by the student and faculty sponsor that involves frequent interaction between instructor and student. Qualitative and quantitative enrichment must be evident on the proposed contract before consent is given to undertake the study.

This is a stand-alone independent study designed by the student and faculty sponsor that involves frequent interaction between instructor and student. Qualitative and quantitative enrichment must be evident on the proposed contract before consent is given to undertake the study.

This is a stand-alone independent study designed by the student and faculty sponsor that involves frequent interaction between instructor and student. Qualitative and quantitative enrichment must be evident on the proposed contract before consent is given to undertake the study.

This is a stand-alone independent study designed by the student and faculty sponsor that involves frequent interaction between instructor and student. Qualitative and quantitative enrichment must be evident on the proposed contract before consent is given to undertake the study.

Not available at this time

Topics are divided between forecasting techniques and econometric time-series modeling. Discovering the data generating process of a random variable. Univariate approaches for dealing with a time series: exponential smoothing methods and ARIMA models. Tests for stationarity. Unit roots. Dickey-Fuller tests. Augmented Dickey-Fuller models. Multivariate approaches for modeling. Spurious relationships. Cointegration. Vector autoregression. Error correction models.

This course will introduce you to the building blocks of microeconomic theory. We cover consumer theory, producer theory, partial equilibrium, and public goods and externalities. This will provide you with the tools necessary to both understand and conduct research in economics.

This course introduces advanced econometric theory and tools for estimating and testing models, evaluating policy changes quantitatively, and more generally studying the relation between economic variables. The goal is to learn enough theory and get enough practice to be able to conduct sensible economic analysis. The course covers most contemporary methods on nonlinear estimation, including the Maximum Likelihood Estimator, Nonlinear Least Squares, and General Method of Moments.

This course will focus on probability theory and statistical inference, the foundations of econometric analysis. Probability theory is the building block that will allow you to understand estimation and statistical inference. The first part focuses on univariate distributions and multivariate distributions, with care taken to differentiate discrete and continuous random variables. The second part covers estimation and inference.