Monday, April 27, 2020

Welfare Costs of Travel Reductions within the U.S. due to COVID-19


 

Welfare Costs of Travel Reductions within the U.S. due to COVID-19


One sentence summary: The cumulative welfare costs of reduced travel with respect to January 20th, 2020 is about 11% as of April 19th, 2020 within the U.S., with a range between 7% and 16% across counties.

The corresponding academic paper by Hakan Yilmazkuday has been accepted for publication at Regional Science, Policy and Practice.
 
The corresponding working paper is available here.

 
Abstract
Using daily county-level travel data within the U.S., this paper investigates the welfare costs of travel reductions due to COVID-19 for the period between January 20th and September 5th, 2020. Welfare of individuals (related to their travel) is measured by their inter-county and intra-county travel, where travel costs are measured by the corresponding distance measures. Important transport policy implications follow regarding how policy makers can act to mitigate welfare costs of travel reductions without worsening the COVID-19 spread.


 
Non-technical Summary
After the World Health Organization declared the coronavirus disease 2019 (COVID-19) as a pandemic on March 11th, 2020 and the U.S. federal government declared National Emergency on March 13th, 2020 due to COVID-19, individuals in the U.S. started traveling less due to health concerns, lockdowns or stay-at-home orders. Although these travel reductions are useful to fight against COVID-19, they also result in welfare losses for individuals who get utility out of traveling for leisure, social or recreational purposes.

Using daily county-level travel data from the U.S., this paper investigates the welfare costs of reduced travel during the COVID-19 pandemic. For motivational purposes, a simple model is introduced to measure the welfare of individuals depending on their travel behavior. Travel costs are measured by the distance across (or within) U.S. counties. The implications of the model are estimated by using daily data on inter-county and intra-county travel between January 20th and September 5th, 2020. 
 
The corresponding results show that the negative effects of distance on travel have rapidly increased during the first half of April 2020, after which a gradual recovery has been experienced until June 2020 across U.S. counties.
 

These distance effects are further connected to the welfare of individuals by using the implications of the model. In technical terms, this is achieved by connecting the time-varying effects of distance on travel across (or within) the U.S. counties to the welfare of individuals by taking the total derivative of their utility measured by their travel.


The corresponding results suggest that the cumulative welfare costs of reduced travel with respect to January 20th, 2020 has reached its highest value of about 11% on April 19th, 2020 for the U.S., with a range between 7% and 16% across U.S. counties.
 

When the heterogeneity across U.S. counties on April 19th, 2020 is further investigated, it is shown that initial travel patterns of counties (during the month of January) is correlated with the cumulative welfare costs of reduced travel, suggesting that more-traveling counties in the pre-COVID-19 era have experienced higher welfare costs.
 
When we investigate the political reasons behind the highest cumulative reduction in welfare specifically on April 19th, 2020, we observe that it is the day when the highest portion of U.S. counties have experienced stay-at-home orders. 
 
 
As the estimated welfare losses in this paper (due to traveling less for leisure, social or recreational purposes) are large and significant, there are several implications for policy makers regarding how they can act to mitigate these welfare losses without worsening the COVID-19 spread. Possible policy recommendations include learning from historical experiences and transport policy actions during earlier pandemics, preparing legal and regulatory frameworks as well as supporting guidelines and contingency plans for traveling, providing safety for the health and economic conditions of the transport personnel, sharing information not only with the public but also among different layers of government, adjusting operating times or the travel mode, or hiring contract tracers to detect exposed travelers quickly. Considering these policy recommendations would not only mitigate the spread of COVID-19 but also let individuals travel with fewer concerns, which is essential to reduce the severity of the welfare costs of travel reductions estimated in this paper.


The corresponding academic paper by Hakan Yilmazkuday has been accepted for publication at Regional Science, Policy and Practice.
 
The corresponding working paper is available here.