Academics

Courses Taken at Boston College:

Time Series Econometrics (Econ 8821)- Studied univariate and multivariate models for stationary time series and addressed the issues of unit roots and cointegration.
Cross Section and Panel Econometrics (Econ 8822)- Studied developments in estimating models with limited dependent variables, random and fixed effects models, and duration models.
Applied Econometrics (Econ 8823) - Topics covered include instrumental variables (IV-GMM) estimation and diagnostics, panel data estimators, including dynamic panel data techniques, reduced-form and structural vector autoregressions; ARFIMA (long memory) models, general linear models, limited dependent variable techniques, structural equation modeling, propensity score matching, state-space and dynamic factor models, simulation and bootstrapping.
Topics in Econometric Theory (Econ 8825) - Studied asymptotic theory for econometric estimation and inference, with emphasis on nonlinear, cross section models. Topics include forms of convergence, consistency and limiting distribution theory, maximum likelihood, linear and nonlinear least squares, generalized method of moments, extremum estimators, nonparametric kernel estimators, and semiparametric estimators.
Industrial Organization I (Econ 8853)-Studying imperfect competition between firms and learned how to implement emprirical methods commonly used in Industrial Orgnization. Topics covered include demand estimation, auctions, price discrimination, bundling, asymmetric information and adverse selection, vertical control and contractual arrangements.
Industrial Organization II (Econ 8854)- Topics covered include nonlinear pricing, price discrimination, search, switching costs, obfuscation, insurance markets, present bias, pass-through and consumer protection, collusion, and learning.

BYU Macroeconomics and Computational Laboratory:

The BYU Macroeconomics and Computational Laboratory (BYU MCL) is a mentored student research team at BYU which connects students with economics faculty members with the intention that the students will provide coauthor-level research assistance for projects which will be published in peer-reviewed academic journals. In order to prepare the students for this level of research, the MCL runs an intense 7 week course which starts in April. This course deals with the following topics:

Applied Mathematics
- Dynamic Programming
- Inner Product Spaces
- Spectral Theory
- Convex Analysis
- Unconstrained, Linear Constrained, and Nonlinear Constrained Optimization
Macroeconomic theory
- Overlapping Generation and DSGE Models
- Linearization and Perturbation Methods
- Data Filtering
- Numerical Integration
- Distribution Fitting
- Asset Pricing
- Vector Auto-Regression
- Simulated and Generalized Method of Moments
Computer Programming
- Python
  - A complete list of the labs can be found here.
- Parallel Computing

It is important to note that for most of the macroeconomic topics, and many of the mathematical topics, programming in Python was also used in order to apply the principles and theory learned. After the course is completed, students then work through the summer and the following academic year on their projects. I am currently working with Brigham Frandsen on nonparametric inference which uses much of the computation techniques learned during this class.

Other Courses Taken at Brigham Young University:

Advanced Macroeconomics (Econ 581)- Used Python and Dynare to develop a set of tools for examining dynamic macroeconomic models. Topics included overlapping generations models, infinitely lived agent models, stationarizing and filtering data, spectral analysis, recursive stochastic models, and numerical methods.
Advanced Econometrics (Econ 588)- Theory and practice of formulating, estimating, and analyzing economic models. Topics included matrix theory, quantile regression, univariate and multivariate distributions, ARCH and GARCH models, generalized method of moments, nonlinear models, time series analysis, and VAR/SVAR modeling.
Advanced Price Theory (Econ 580)- Study of advanced mathematical topics and their applications in economics, such as point-set topology, functional analysis, and game theory.
Topics In Mathematical Economics (Econ 582)-More study of advanced mathematical topics and their applications in economics including graduate-level game theory topics such as ambiguity aversion, entropy, and advances in the neuroscientific approach.
Real Analysis (Math 541)- Studied Lebesgue differentiation and integration in Euclidean space, as well as Fourier analysis.
Nonparametric Statistical Methods (Stat 435)- Permutation tests, rank-based methods, analysis of contingency tables, bootstrap methods, and curve fitting.
Statistical Computing 2 (Stat 424)- S plus, statistical graphics, simulation, advanced SAS (macros, Proc IML, and Proc SQL), and database programming.

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