Northern Economist 2.0

Thursday, 5 November 2020

Why Makings Things Matters in the Age of COVID: A Tale of Three Cities

 

The Covid-19 pandemic has come with a huge cost in terms of employment loss with the retail, food and accommodation, and travel sectors exceptionally hard hit.  The employment impact in Ontario has been substantial also with total employment falling about 13 percent from February 2020 to June of 2020.  The rebound since June has been insufficient to make up all the employment losses and as of September total employment in Ontario was still about 6 percent lower than February 2020.  The impact has also varied across major cities in Ontario with Kitchener-Waterloo, Thunder Bay and Peterborough and Hamilton hit the hardest whereas Guelph, Brantford, Oshawa and London experienced softer blows.

 

The composition of employment seems to be a factor and this post drills down a bit into the employment composition by broad industry sector – goods and services. The goods sector consists of employment in agriculture, resources, utilities and oil and gas, construction and manufacturing. Everything else ranging from wholesale and retail trade and transport, finance and real estate, health and education to food and accommodation and public administration are the services. 

 

 


 

Figure 1 plots the composition of employment across these two industry sectors for three cities in Ontario: Hamilton, Thunder Bay and Guelph. What is quite interesting is despite their industrial, agricultural and resource extraction histories, Hamilton, Guelph, and Thunder Bay, are now all remarkably service intensive - part of the trend everywhere in high income economies. Hamilton’s goods production sector accounts for 21 percent of employment whereas Thunder Bay is the lowest of the three cities at 17 percent.  However, Guelph on the other hand still has a relatively large share of employment in goods production at 27 percent. 

 

 


 

Figures 2 and 3 plot the percentage change in employment for total, goods, and service sector employment for the three cities for two periods: the onset of the pandemic between January 2020 to May 2020 and the period of employment recovery as the first wave was brought under control from May 2020 to September 2020.  The data is non-seasonally adjusted three-month average monthly employment data from Statistics Canada.  

 


 

 

From January to May, all three cities saw a drop in monthly employment, but Guelph was hit half as hard with a drop of about 6 percent compared to more than twice that for both Hamilton and Thunder Bay.  What is also interesting is the employment hit was harder in Guelph for the goods sector with a 25 percent employment drop compared to 17 percent for Thunder Bay and 13 percent for Hamilton.  However, service employment dropped about 13 percent in both Hamilton and Thunder Bay during the first wave of the pandemic, but Guelph’s was essentially stable.

 

As for the recovery period from the first wave from May to September, all three cities saw employment grow: 4 percent for Hamilton, 9 percent for Thunder Bay and 8 percent for Guelph.  The performance across sectors is more interesting.  Employment in Guelph’s goods sector rebounded robustly growing 57 percent compared to only 21 percent in Hamilton and 26 percent in Thunder Bay.  Construction was the major source of the rebound in all three cities but manufacturing reinforced the rebound in Guelph whereas in Thunder Bay manufacturing employment continued to decline even from May to September.  Services did not recover as well as goods production in all three cities with Guelph actually seeing some service sector employment losses from May to September.  For whatever reason, the service sector job losses in Guelph were delayed compared to the other two cities.

 

What explains this?  Good question but one cannot help but wonder if the CERB played a role.  On average, foods sector jobs are higher paying than service sector ones though where the service jobs are is important- for example, retail and food and accommodation versus health and education.  The CERB kicks in during the pandemic and millions took advantage of it over the summer and into the early fall.  The CERB and its income support may have provided more of a disincentive to return. Having a large goods production sector relative to service sector did not insulate against employment loss in the first wave of the pandemic but may have slowed the rebound in the presence of the CERB.