This month, Principal Credit Analyst Eric Espeseth takes a closer look at the Mobility and Engagement Index.
Eric Espeseth, Principal Credit Analyst
Rapidly evolving economic conditions following the onset of the COVID-19 pandemic - and associated stay-at-home orders - drove a need for more timely economic information and placed a greater emphasis on high-frequency data which provide a more up-to-date assessment of economic activity.
The Federal Reserve Bank of Dallas Mobility and Engagement Index (MEI) was created to help address this need. The MEI is a summary of seven different mobility variables measured daily. The Index is intended to give a real-time picture of the impact from the COVID-19 pandemic on economic activity through the deviation from normal mobility behavior. Index variables measure the fraction of devices leaving home in a day, amounts of time devices are away from home at a fixed location, fraction of devices taking trips longer than 10 miles or shorter than 1 mile and an adjusted average of daytime hours spent at home.
The increased importance and appeal of high-frequency data, such as the MEI, is due in large part to the timing of traditional economic indicators. Conventional macroeconomic indicators - including employment, personal spending and Gross Domestic Product (GDP) growth - are typically available on a monthly or quarterly basis and often released with a lag. Through use of the MEI, we are able to see how consumers respond to changing COVID-19 infection levels and government mandated restrictions through deviations in mobility levels. We can make assessments on the impact to economic measures such as employment and consumer spending in a more timely manner than through traditional economic data releases.
The MEI also provides the benefit of assessing current economic conditions on a more granular basis than through other high-frequency data indices which typically rely on national level information. The MEI is constructed using county-level data which is then aggregated to provide different MEIs at the national, state and metro area levels. This additional granularity allows for increased focus on the impact of specific government restrictions, largely levied at the state and local level.
As the COVID-19 pandemic initially had the greatest impact on New York, we can see that mobility in the state was especially restricted throughout the spring and summer and lagged that of the overall country. Lower mobility - and thus reduced economic activity - in key areas such as New York, California and Texas can have an outsized impact on overall U.S. economic activity as these three states account for over 30% of total U.S. GDP. Having this up-to-date, granular information is highly valuable given the ever-changing pandemic and its impact on economic activity.
Bureau of Economic Analysis
Federal Reserve Bank of Dallas