Working Papers:

On the Drivers of U.S. Breakeven Inflation
This paper examines the drivers, specifically economic and financial variables, that explain movements in the breakeven inflation rate at different time horizons. To do this, I evaluated a selection of potential explanatory variables using LASSO regressions and Bayesian Model Averaging. Variables that were deemed likely to explain movements in inflation were inputted in a VAR and had their shocks analyzed via a Cholesky Decomposition. The results indicate that longer term breakeven rates are more persistent and require fewer explanatory variables than short term breakeven rates. Moreover, it also implies that the output gap variables, prices and exchange rates variables, and financial variables are important in examining breakeven inflation at all time horizons. However, the relative importance of the prices and exchange rates variables decrease as the time horizon increases. On the other hand, the financial variables were more significant for longer time horizons than shorter. The output gap was relatively less significant for middle time horizons and was instead more significant for long- and short-term horizons.
Replication Files

The impact of the US Economy and Consumer Behavior on Cryptocurrencies

Published Works:

Accounting for Leverage in Intangible and Tangible Investments Across the Business Cycle (Undergraduate Economic Review)
In this paper, I study the role of the leverage ratio and its impact on investing in tangible and intangible goods. The results confirm the hypotheses outlined in the introduction. Specifically, the results show that when accounting for differences in the leverage ratio between firms, investment is cyclical. However, when looking only at firms with low leverages, intangible investing becomes countercyclical. Moreover, during recessions, firms with lower leverages tend to invest more than firms with higher leverages. Finally, the results argue for the existence of financial frictions between investing in tangibles and intangibles

The Application of Global Factors in Inflation Forecasting Models (Internal Fidelity Research Database)
In this paper, I show that the inclusion of global factors in macroeconomic inflation forecasting models helps prediction error and can help us reexamine the Phillip’s Curve relationship in a new context.  This global factors model was then used to create a Time Varying Dimension (TVD) model, which used both an Unobserved Components Model with Stochastic Volatility (UCSV) as well as an Autoregressive Distributed Lag (ADL) Model with global factors. This new model, which followed a stochastic process for the trend inflation and a macroeconomic informed stochastic process for the cyclical component, outperformed many other similar models.