The COVID-19 pandemic led to unprecedented federal transfers to state and local governments. Did this funding benefit incumbent politicians electorally? The conditions that triggered this funding influx might also affect incumbents for other reasons. We therefore develop an instrument to predict allocations to states based on variation in congressional representation. Using over a decade of election data, we find that incumbents in state-wide races performed significantly better in 2020 and beyond in states that received more relief funding due to their overrepresentation in Congress. These results are robust across specifications and after adjusting for a variety of economic and political controls. We uncover larger effects for governors and other statewide executive office holders than for legislators, providing suggestive evidence on underlying mechanisms. This paper contributes to our understanding of economic voting during times of crisis, the downstream electoral consequences of the COVID-19 pandemic, and the effects of unequal political representation.

Overview and Contents
This replication package was assembled in January of 2025. Thecode in this repository generates the 13 figures and content of the 3 tablesfor the paper “All Forecasters Are Not the Same: Systematic Patterns inPredictive Performance”. It also generates the 2 figures and content of the 5tables in the appendix to this paper. The main contents of the repository arethe following: Code/: folder of scripts to prepare and clean data as well as generate tables and figures. Functions/: folder of subroutines for use with MATLAB scripts. Data/: data folder. Raw/: ECB SPF forecast data, realizations of target variables, and start and end bins for density forecasts. Intermediate/: Data used at intermediate steps in the cleaning process. These datasets are generated with x01_Raw_Data_Shell.do, x02a_Individual_Uncertainty_GDP.do, x02b_Individual_Uncertainty_HICP.do, x02c_Individual_Uncertainty_Urate.do, x03_Pull_Data.do, x04_Data_Clean_And_Merge, and x05_Drop_Low_Counts.do in the Code/ folder. Ready/: Data used to conduct regressions, statistical tests, and generate figures. Output/: folder of results. Figures/: .jpg files for each figure used in the paper and its appendix. HL Results/: Results from applying the Hounyo and Lahiri (2023) testing procedure for equal predictive performance to ECB SPF forecast data. This folder contains the material for Tables 1A-4A. Regressions/: Regression results, as well as material for Tables 3 and 5A. Simulations/: Results from simulation exercise as well as the datasets used to create Figures 9-12. Statistical Tests/: Results displayed in Tables 1 and 2. The repository also contains the manuscript, appendix, andthis read-me file.

Disclaimer
This replication package was produced by the authors and is not an official product of the Federal Reserve Bank of Cleveland. The analysis and conclusions set forth are those of the authors and do not indicate concurrence by the Federal Reserve Bank of Cleveland or the Federal Reserve System.

Overview and Contents
This replication package was assembled in January of 2025. Thecode in this repository generates the 13 figures and content of the 3 tablesfor the paper “All Forecasters Are Not the Same: Systematic Patterns inPredictive Performance”. It also generates the 2 figures and content of the 5tables in the appendix to this paper. The main contents of the repository arethe following: Code/: folder of scripts to prepare and clean data as well as generate tables and figures. Functions/: folder of subroutines for use with MATLAB scripts. Data/: data folder. Raw/: ECB SPF forecast data, realizations of target variables, and start and end bins for density forecasts. Intermediate/: Data used at intermediate steps in the cleaning process. These datasets are generated with x01_Raw_Data_Shell.do, x02a_Individual_Uncertainty_GDP.do, x02b_Individual_Uncertainty_HICP.do, x02c_Individual_Uncertainty_Urate.do, x03_Pull_Data.do, x04_Data_Clean_And_Merge, and x05_Drop_Low_Counts.do in the Code/ folder. Ready/: Data used to conduct regressions, statistical tests, and generate figures. Output/: folder of results. Figures/: .jpg files for each figure used in the paper and its appendix. HL Results/: Results from applying the Hounyo and Lahiri (2023) testing procedure for equal predictive performance to ECB SPF forecast data. This folder contains the material for Tables 1A-4A. Regressions/: Regression results, as well as material for Tables 3 and 5A. Simulations/: Results from simulation exercise as well as the datasets used to create Figures 9-12. Statistical Tests/: Results displayed in Tables 1 and 2. The repository also contains the manuscript, appendix, andthis read-me file.

Disclaimer
This replication package was produced by the authors and is not an official product of the Federal Reserve Bank of Cleveland. The analysis and conclusions set forth are those of the authors and do not indicate concurrence by the Federal Reserve Bank of Cleveland or the Federal Reserve System.

This is the replication package for "The Heterogeneous Effects of Large and Small Minimum Wage Changes: Evidence Using a Partially Pre-Committed Analysis Plan," accepted in 2024 by the Journal of Labor Economics.

We study Opportunity Zones, giving an overview of how the legislation was passed and the eligibility requirements. Using data from the 2013-17 American Community Survey, we show to what extent selected tracts were targeted towards the most disadvantaged (as measured by median income).

We study Opportunity Zones, giving an overview of how the legislation was passed and the eligibility requirements. Using data from the 2013-17 American Community Survey, we show to what extent selected tracts were targeted towards the most disadvantaged (as measured by median income).

This project contains the data and code needed to replicate the findings for Brummund and Strain's article published in the Journal of Human Resources, entitled "Does Employment Respond Differently to Minimum Wage Increases in the Presence of Inflation Indexing?". doi:10.3368/jhr.55.2.1216.8404R2

This project contains the data and code needed to replicate the findings for Brummund and Strain's article published in the Journal of Human Resources, entitled "Does Employment Respond Differently to Minimum Wage Increases in the Presence of Inflation Indexing?". doi:10.3368/jhr.55.2.1216.8404R2

This project contains the data and code needed to replicate the findings for Brummund and Strain's article published in the Journal of Human Resources, entitled "Does Employment Respond Differently to Minimum Wage Increases in the Presence of Inflation Indexing?". doi:10.3368/jhr.55.2.1216.8404R2

Data set for construction of compactness measures.