C-19: Observing the US economy under the pandemic


In this article we continue exploring spending, employment, and store revenue collection and opening data from the US economy; and tie the evolution of these factors to mobility as reported by Google's Community Mobility Reports.


Previous articles that touch on this topic can be found here and here.


#US #COVID19 #Economy


A. Aggregated data sources & key observations

  • During lockdown mobility across critical activities such as retail, transit and workplaces dropped dramatically as expected, and so too did spending activity, store opening and employment.

  • As such spending and store opening generally correlated with declining mobility at lockdown; interestingly however, decline in employment distinctly lagged behind. In fact, employment recovery post lock-down has struggled to recover despite increases in mobility, particularly at the low income end.

  • While aggregate spending levels have increased over the course of recovery, and in fact risen beyond pre-lockdown levels since reopening and through the Christmas and New Year period, store opening and revenue collection are far from previous levels.

  • More recently, spending has begun to show an opposite trend vs. store opening and store revenues since Christmas up to present day. While spending is above baseline levels, store opening and spending hovers at -40% from baseline levels.

  • Note: refer to section C for reference legend for data sources used.



B. Detailed analysis across four phases


Phase 1: initial lockdown

  • Start: 9 March 2020

  • End: 29 March 2020

Time series data
Cross-correlation analysis

Phase 2: post lockdown

  • Start: 3 April 2020

  • End: 17 June 2020

Time series data
Cross-correlation analysis

Phase 3: Slow recovery

  • Start: 7 July 2020

  • End: 14 November 2020

Time series data
Cross-correlation analysis

Phase 4: Christmas & New Year

  • Start: 24 November 2020

  • End: 23 January 2021

Time series data
Cross-correlation analysis

C. Reference legend

  • Spend_: spend data from Affinity Solutions. Legend: acf-accom. & food service; aer-arts, entertainment & recreation; apg-general merchandise & apparel; grf-groceries & foods; hcs-healthcare & social; tws-transport & warehousing; inc_ prefix indicates zip code distribution by income levels*.

  • GPS_: mobility data sourced from Google.

  • Merchants_*: small business openings/closings sourced from Womply.

  • Revenue_*: small business revenues sourced from Womply.

  • Emp_*: employment level for low income workers sourced from Earnin and Homebase.

  • Pay_*: earnings by low-income workers sourced from Earnin and Homebase.

  • by_posts: average level of job postings relative to baseline sourced from Burnglass.

  • _ss30: manufacturing sector (NAICS)

  • _ss40: transportation sector (NAICS)

  • _ss60: professional and business services

  • _ss70: leisure and hospitality

  • _pay/emp44_45: pay or employment in accommodation and food services

  • _pay/emp48_49: pay or employment in transportation and warehousing

  • _pay/emp72: pay or employment in accommodation and food services

  • Note (*): inc_ indicates location of store by US zip code, i.e. high income indicates high income zip code.

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