- The OFR Financial Stress Index (OFR FSI) is a daily market-based snapshot of stress in global financial markets that is constructed from 33 financial market variables. As of the time of writing, seven of these variables rely on obsolete reference rates. Since its inception, the OFR FSI was intended to allow for the periodic replacement of obsolete variables as the need arises. In this paper, I introduce replacements for these seven obsolete variables, and I make explicit the procedure with which the OFR FSI incorporates these new variables. Furthermore, I demonstrate generally that this replacement procedure produces an index with the following desirable properties: (1) the index is a weighted sum of the presently included variables; (2) removed variables no longer directly affect the index, and newly included variables do not modify historical values of the index; (3) the index uses all available historical data on the newly included variables to train the model; and (4) the volatility of the index is roughly comparable before and after the replacement.

- I characterize the relationship between dividend dynamics and the term structure of equity risk premia. Within a class of log-linear asset pricing models, I show that the risk exposure associated with dividend futures is equal to the impulse response function of dividends and that the average slope of the term structure depends on the relationship between the permanent and transitory components of dividends. Going beyond the class of log-linear models, I then explore the consequences of adding a transitory, mean-reverting component to dividend dynamics within several classic asset pricing models, such as the extended consumption capital asset pricing model and an external habits model. Recent empirical evidence suggests that the term structure of equity may be downward sloping on average, which is at odds with the traditional specification of many common asset pricing models. I show that this potential discrepancy can be reconciled by adjusting cash flow growth dynamics in the proposed way.

- I argue that the term structure of equity as characterized by expected holding period returns on dividend strips can be used as a diagnostic to evaluate the quantity dynamics that arise in a macroeconomic model. For instance, as shown in the first chapter, the risk exposures associated with dividend futures are equal to the impulse responses of aggregate consumption with respect to the underlying shocks. As an application, I derive the asset pricing implications of a multi-sector production network model and use this to shed light on relative importance of idiosyncratic and aggregate total factor productivity (TFP) shocks. Though aggregate TFP in the U.S. over the last 60 years has grown approximately 1.4 percent annually, these gains have been dispersed across individual sectors, with some sectors even seeing substantial declines. This dispersion is either the result of idiosyncratic sectoral shocks or aggregate shocks that shift the composition of the economy without necessarily affecting long-run aggregate output. Decomposing the contribution of each shock to this term structure of equity, I show that the shift shocks contribute to a downward sloping term structure of equity while others contribute to an upward sloping term structure. Thus, imposing a downward sloping term structure in this model amounts to putting a lower bound on the contribution of aggregate shifts relative to other shocks.

- ECON 21410: Computational Methods in Economics (Spring 2019)

This course introduces the basic programming and computational techniques necessary for solving and estimating economic models. The course covers topics in numerical methods, such as optimization, function approximation, and Monte Carlo techniques, as well as topics in data exploration... (Click here for course evaluations) - ECON 21410: Computational Methods in Economics (Spring 2018)
- Parallel Programming with Python and MPI: BYU 2013

This is the material, including a short text I wrote and video tutorials, for a workshop on parallel programming with MPI and Python that I taught as part of a summer bootcamp on computational economics in 2013. It may be quite out of date by now.

- Interactive Plot and Widget Demo. Here I present examples of the kinds of interactive plots and widgets that can be easily embedded into a website using tools that work well with or are based in the Python/R ecosystem.
- Jupyter Notebook: Fixed and Random Effects Models in Python, R, and Stata . This should be updated, but some have found this useful. It's a Jupyter notebook in which I replicate some examples from Wooldridge's panel data book. It provides side-by-side code showing how to implement fixed and random effects models in Python (using the statsmodels and linearmodels packages), R, and Stata.