Reproduction Package for "The COVID-19 Pandemic and the $16 Trillion Virus"

This is a reproduction package for "The COVID-19 Pandemic and the $16 Trillion Virus" by Cutler and Summers (2020). The effort followed the Guide for Accelerating Computational Reproducibility (ACRE) from the Berkeley Initiative for Transparency in the Social Sciences (BITSS). The reproduction attempt is logged here on the Social Science Reproduction Platform (SSRP). For interested reproducers, this record also includes suggestions for potential improvements.

The data and calculations were based on the Appendix and a provided replication model, which are available in the resources folder.

Description

An installation of R will be required to run the analysis and cleaning scripts.

The following is a diagram of all inputs and outputs, where "manual" indicates a manual transcription:

  Table 1
  └── analysis.R
      ├── projections.csv
      │   └── cleaning.R
      │       ├── cbo-2020-01-economicprojections.xlsx
      │       └── cbo-2020-07-economicprojections.xlsx
      ├── impairments.csv
      │   └── cleaning.R
      │       ├── covid_by_age.csv
      │       │   └── manual
      │       │       └── covid_by_age_snapshot.pdf
      │       └── covasim.csv
      │           └── manual
      │               └── covasim.pdf
      ├── covid_deaths.csv
      │   └── cleaning.R
      │       └── covid19-death-counts.csv
      └── mental_health.csv
          └── cleaning.R
              ├── 2019nchsmentalhealth.csv
              │   └── manual
              │       └── 2019mentalhealth.pdf
              ├── 2019gender_table1.xlsx
              └── 2020pulsementalhealth.csv

The reproduction is based on the following data sources, which are available in the data/raw subfolder:

• Weekly COVID-19 death counts from the CDC.
• A September snapshot of COVID-19 deaths counts by age and gender from the CDC.
• Results from the NCHS Pulse mental health survey.
• 2019 mental health estimates from the NCHS.
• January and July 2020 10-year GDP projections from the CBO.
• The 2019 American Community Survey (ACS).
• Results from the Covasim model of COVID-19 dynamics.

The raw data are processed by the cleaning.R script, which outputs the following analysis datasets to the data/analysis subfolder:

• covid_deaths.csv - CDC COVID-19 deaths estimates.
• impairments.csv - impairment data from COVID-19 deaths by age and Covasim model.
• mental_health.csv - Compiled results from 2019 and 2020 mental health surveys.
• projections.csv - Pre- and post-COVID 10-year GDP projections.

The analysis.R script accepts these datasets as inputs, as well as other estimates outlined in the Appendix. It produces both figures from the appendix, gdp_fig.png and deaths_fig.png, and saves them to the results folder. The script then uses the authors' methodology to estimate the cost of the COVID pandemic.

Robustness Checks

After verifying the authors' estimate, it adopts the following alternative parameters:

1. Change Future Ratio - The ratio of total (current + future) deaths to current deaths, used to project future impairments. The authors estimate the value to be "625,000/250,000", which appears unjustified by their own estimates. The value is recomputed using the deaths estimates.
2. Update COVID-19 Deaths - The new COVID-19 death counts by the CDC yield a greater estimate of deaths by September 25th. The updated value is added to the model.
3. Change Adult Population - The authors use a value of 263,000,000 for the number of American adults, which is then used to compute mental health impairments. The ACS indicates that the number of adults is 250,563,000.

Results

The table of results, for both the author's specifications and the three alternatives, is stored as results_fig.png and is displayed below.