Pandemic: Additional Considerations when Modeling the Coronavirus

Candi Clouse, PhD

June 02, 2020 19:47

INTRODUCTION

As the world continues to see changes stemming from the COVID-19 pandemic, more questions arise on best practices for how to look at the economic impact of the latest developments in IMPLAN. Here are some considerations to think through when analyzing your impacts.

ASSUMPTIONS

The assumptions inherent in Input-Output analysis remain the same. However, two specifically come into play.

The Constant Make Matrix assumption states that an Industry will always produce the same mix of Commodities regardless of the level of production. In other words, an Industry will not increase the Output of one product without proportionately increasing the Output of all its other products. Given the increased production of items like personal protective equipment, this assumption could be called into question when manufacturing firms like Ford have pivoted to make respirators and masks; not a usual Commodity coming from automobile manufacturers.

On the flip side, another assumption states that there are No Supply Constraints. This means there are no restrictions to raw materials and employment to produce an unlimited amount of product. During this pandemic, there is excess capacity as plants are operating at reduced capacity and there are a lot of unemployed people. Because of this, businesses are willing to accept lower prices and also not increase prices, so increases in demand (i.e., the changes analyzed in Input-Output) are less likely to change prices and Input-Output is therefore more reasonable.

PURCHASING CHANGES

Peoples' and businesses' normal purchasing patterns have changed. Industries may be spending less on payroll and travel, while spending more on technology. These changes will affect how the multipliers react.

Additionally, household purchases are changing. There are fewer trips to restaurants and far less travel and entertainment. So, the multipliers for household spending are also affected.

The government issued stimulus checks to people that are working and those that are not. This money will likely be saved by those working and spent by those who are currently not employed.

Finally, while some people have been furloughed or lost their jobs entirely, unemployment benefits are being collected. In some cases, people are actually earning more with the expanded unemployment benefits. This money may be spent or saved.

INDUSTRY CHANGES

Industries are changing, too. Trade across the U.S. and the world has changed. Also, the relative sizes of Industries have changed. Some tech and manufacturing industries, for example, have grown, whereas in-person service industries (e.g., restaurants, sporting events, other personal services) have declined. Some businesses have been completely shuttered while some are booming and employing additional staff and shifts. The Paycheck Protection Program (PPP) has given out loans to small businesses to pay their employees during the pandemic in order to ensure that Employee Compensation levels are maintained, benefits retained, rent is paid, and utilities are continued. These forgivable loans might make the difference between a business staying open or closing for good.

ANALYZING THIS IN IMPLAN

Some of the changes to the economy are easily modeled in IMPLAN like adding 100 new jobs at a manufacturing plant with an Industry Employment Event. However, given the systemic nature of many of the current changes, the Industry Impact Analysis (Detailed) Event Type is the best approach.

You can further edit the Indirect and Induced Effects to move spending that was going to restaurants to spending at grocery stores in Excel or a similar program. Also, an assumption could be made that people are saving more money than normal because they cannot go anywhere, therefore less disposable income is expended. On the other hand, many people have lost income and are probably spending a higher percentage of income than in the model. In these cases, you can export the SAM, rearrange and rebalance it, and recalculate your own multipliers that more accurately reflect what you want to show.

Governments have also been reporting large losses in sales tax revenues. Most of this stems from reduced overall economic activity, not from changes in effective tax rates. By adjusting your inputs and results, you should not have to do much editing to the tax impact report. However, effective personal income tax rates are based on labor income and capital income; reduced capital income (e.g., from dividends and rent) might require adjustments to personal income taxes. Corporate income taxes likely also would need to be edited. In this case, we recommend supplementing the direct tax impacts with your own estimates.

DATA RESOURCES

The following lists some data sources on how the economy has changed to help inform how to edit direct effects, the model, and/or results.

Several news outlets, research organizations, banks, and consultancies have identified particular industries and occupations affected by changes related to COVID-19.

Brookings: The places a COVID-19 recession will likely hit hardest

JP Morgan: COVID impact on markets: stimulus and valuations

New York Times: The Workers Who Face the Greatest Coronavirus Risk

Moody’s: Coronavirus impact on sectors

Government sources have some timely information as well.

BEA: Aggregate preliminary data on components of GDP and Value Added

BLS CES: Changes in Industry Employment and Compensation

BLS Labor Productivity: Changes in Productivity

Census: Small Business Pulse Survey Data

CONCLUSION

Until all of the dust settles from the economic changes spurred by the pandemic, we will not know the full extent of the impact. Be cautious not to overstate the effects in your analysis. Consider taking additional care in analyzing the Results by Industry and Type of Effect. As there are likely to be winners and losers, consider both sides of the equation by using a Net Analysis.

Pandemic: Analyzing the Economic Impacts of the Coronavirus

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Evolving Economy - COVID 2020 Q2 Data Details