Working Papers

Description: Building upon Robert Moffit’s work on income volatility, this work seeks to track Volatility in Income Subsets.

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Description: Unpacking subsets of income, disaggregated by race to look for recent trends in disparities.

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Description: Analysis of California Small Claims Courts, and expansion upon a previous thesis which shows an increase in filing fees with lower courts results in a reduction in filings, with different claims showing different elasticities.

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This project explores the Sahm Rule through a racially disaggregated lens, calibrating it for Black and Hispanic unemployment to assess its effectiveness in highlighting economic disparities. While it reveals significant inequities, its noisiness due to higher unemployment volatility suggests it is better suited as an alarm for disparities rather than a standalone policy trigger, prompting further analysis across other unemployment subcategories and state-level data.

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This code replicates basic figures found in Scott Baker, Steven Davis and Jeff Levy Journal of Monetary Economics 2022, and visualizes the EPU Index with structural breaks.

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Description: Evaluates Piketty, Saez, & Zucman and Auten & Splinter post-tax income estimates relative to tax data, and visualizes various structural breaks. The code uses both Python and R, and imports data from host websites.

This project is complemented by a visual site.

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The line graph of wealth inequality in the U.S. from the GC Wealth Project, as depicted by various authors, presents a striking visual representation of the increasing inequality over several decades. This project is possible because of data compiled by the GC Wealth Project.

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This project visualizes polling data for the 2024 U.S. presidential election, focusing on key "tipping point" states critical to the election outcome. It integrates various predictive factors, including incumbency effects, economic conditions, and external events, to create a nuanced view of each candidate's standing over time. Using a custom-styled ggplot, the visualization includes trend lines and confidence intervals for each state, allowing viewers to see shifts in polling data with contextual annotations. An online legend image is overlaid on the plot, providing a seamless reference without altering the plot’s dimensions, making this a comprehensive and interactive analysis tool for election forecasting.

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This project analyzes trends in U.S. economic policy uncertainty from 1984 to the present, highlighting periods around key election dates. It combines the Policy Uncertainty Index with a scaled visualization of consumer sentiment, averaged from the University of Michigan Consumer Sentiment Index and The Conference Board Consumer Confidence Index, to provide a comprehensive view of public economic perception. The analysis uses LOESS smoothing and linear regression to capture both short-term fluctuations and overall trends, offering insights into how policy uncertainty and consumer confidence evolve in response to economic and political events.

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This project visualizes the Sahm Recession Indicator, disaggregated by racial demographics, to illustrate economic recessions' disparate impacts across racial groups in the United States from 1975 to the present. By incorporating recession shading and external legend information, the analysis highlights how Black and Hispanic communities are disproportionately affected by prolonged economic downturns.

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This project visualizes core and headline inflation measures, including moving averages and Kalman filter outputs, from 2010 to the present, with recession periods highlighted and the Federal Reserve's 2% inflation target indicated. It provides a clear, data-driven analysis of inflation trends using percent change metrics for enhanced economic insights.

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