Cultural and public services promote the resilience of cities

Cities are more vulnerable to political and economic upheaval than to physical destruction (Glaeser 2021). For example, mass layoffs reduce the local workforce by inducing some of the displaced workers to migrate (Foote et al. 2015), which can have permanent long-term effects on the growth and socio-economic composition of the city. It is unclear how the latter changes following negative economic shocks – and what city-level characteristics promote urban resilience. In a recent study (Behrens et al. 2021), we shed some light on these questions.

The effects of factory closures and mass layoffs on workers and local labor markets

Research on job displacement has shown that workers who lose their jobs due to large factory closures or mass layoffs suffer long-lasting income losses, longer spells of unemployment, and other adverse effects such as lower fertility, higher mortality and lower income for their children when they become adults (eg Jacobson and LaLonde 1993, del Bono and Winter-Ebner 2008, Oreopoulos et al. 2008).

The effects of mass layoffs and large factory closures on local economies are still debated. Some studies show significant negative spillovers to other local businesses, such that the number of locally available jobs declines more than the number of displaced jobs (Gathmann et al. 2020). Other studies show that part of the job losses generated by large factory closures are compensated by new or existing local companies (Jofre-Monseny et al. 2018).

Displacement of jobs triggers emigration, but not all workers react in the same way to local labor demand shocks. Several studies show that highly skilled workers and immigrants are generally more responsive to local shocks (e.g. Albouy et al. 2019). Beyond the different mobility costs, the inelasticity of the housing supply, the existence of social transfers and the selection criteria for immigration can explain this heterogeneous response of workers to local labor demand shocks (eg Notowidigdo 2020).

Closings of large factories, mass layoffs and the age structure of cities

In Behrens et al. (2021), we assess the impact of closures and substantial downsizing of large manufacturing plants on the growth and demographic composition of Canadian cities. About 33% of Canadian manufacturing jobs disappeared between 2003 and 2017 due to the closure or massive downsizing of establishments with more than 50 employees, many of whom were not replaced. However, this job loss rate is quite heterogeneous between Canadian provinces and between cities within provinces, as shown in Figure 1.

Figure 1 Relative rates of job loss due to large plant closures in Canadian urban areas, 2003-2017

To note: Distribution of manufacturing job loss rates due to major plant closures (over 50) in Canadian urban areas. Job loss rates for Canadian urban areas are measured relative to the Canadian average. A value of 1 on the map means that the urban area’s job loss rate is the same as the Canadian average. Cyan outlines delineate cities with at least 300,000 inhabitants.

We can see in Figure 2 that between 2003 and 2017, Canadian cities also experienced very different demographic evolutions. For example, the population of Campbellton in New Brunswick has decreased the most (-18.2% from an initial population of 16,980 in 2001), while the population of Wood Buffalo in Alberta has increased the fastest (+ 72.4% compared to an initial population of 42,475 in 2001). We thus compare the demographic growth of cities hard hit by the closures of large factories and massive layoffs with the demographic evolution of cities where the rate of loss of manufacturing jobs is lower.

Figure 2 Relative population growth rate in Canadian urban areas, 2001-2016

To note: Growth rates are measured relative to the Canadian average. A value of 1 on the map means that the growth rate of the urban area is the same as the Canadian average. Cyan outlines delineate cities with at least 300,000 inhabitants.

To ensure that our analysis is not biased by confounding factors, we take into account the initial size and composition of the cities, as well as various amenities such as average temperatures, distance to the coast and distance to the nearest large town. Additionally, to ensure that we capture the impact of large factory closures on demographic change and not the other way around (since companies could also follow workers and close or downsize in shrinking cities), we let’s use the industry employment growth rate in the United States and the United States. initial composition of manufacturing activity in Canadian cities to construct an instrument of distribution (Bartik).

We find that plant closures lead to lower subsequent population growth, especially among working-age residents (20-59) and very young residents (0-19). Cities badly hit by mass layoffs become aging cities since working-age residents (and their children, if any) are more likely to leave in search of job opportunities elsewhere.

The groups most likely to leave cities affected by negative labor demand shocks are single people and people with an immigrant background. It’s easy to understand: the latter have moved before in their lives, while the former have lower migration costs because they don’t have common location decisions to manage.

We further show that the closure and massive downsizing of large manufacturing plants negatively affects the employment growth of several other sectors of the local economy, particularly in construction, cultural services and finance, l Insurance and Real Estate (FIRE). These negative spillovers could partly explain why negative shocks to employment in the manufacturing sector have such a strong depressive effect on the demographic dynamics of cities.

Cultural and public services as factors of city resilience

When exposed to similar job loss rates, not all cities experience the same demographic decline. More specifically, we identify two factors promoting the resilience of cities. First, cities with the highest initial share of local population employed in education and in health and social services experience less population decline as a result of large manufacturing plant closures and mass layoffs. This mitigating effect is particularly important for migrants, who therefore seem to value (or benefit more from) these services more in the event of negative shocks on the demand for local labour.

We also find that cities with the highest initial share of residents employed in arts and entertainment and recreation are more resilient to the adverse effects of massive job displacements. The effect is particularly concentrated among residents of working age and those with at least a bachelor’s degree, since they are the biggest consumers of cultural services.

Studies on the factors promoting the resilience of local economies are relatively rare (Behrens et al. 2018). We show that public and cultural services promote the resilience of cities in the face of negative labor market shocks. At a time when COVID-19 is putting these services under pressure, our findings are a reminder of how important they are to our economies.

The references

Albouy, D, A Chernoff, C Lutz and C Warman (2019), “Local Labor Markets in Canada and the United States”, Journal of Labor Economics 37(S2): 533–94.

Behrens, K, B Boualam and J Martin (2018), “Plant resilience and clusters: Evidence from the Canadian textile and apparel industry”,, 3 January.

Behrens, K, M Drabo and F Mayneris (2021), “Cultural and public services as factors of city resilience? Evidence of Large Plant Closures and Downsizing”, CEPR Working Paper 16723.

del Bono, E, and R Winter-Ebmer (2008), “The Effect of Job Displacement on Women’s Fertility Decisions”,, 25 February.

Foote, A, M Grosz and AH Stevens (2015), “How workers leave the labor market after local economic downturns”,, 17 November.

Gathmann, C, I Helm and U Schönberg (2020), “Contagion effects of mass layoffs”, Journal of the European Economic Association 18(1): 427–68.

Glaeser, EL (2021), “Urban Resilience”, NBER Working Paper 29261.

Jacobson, LS, and RJ LaLonde (1993), “Displaced Workers’ Income Losses”, American Economic Review 83(4): 685.

Jofre-Monseny, J, M Sánchez-Vidal and E Viladecans-Marsal (2018), “Major factory closures and local employment”, Journal of Economic Geography 18(1): 163–186.

Notowidigdo, MJ (2020), “The Impact of Local Labor Demand Shocks”, Journal of Labor Economics 38(3): 687–725.

Oreopoulos, P, M Page and AH Stevens (2008), “The Intergenerational Effects of Displacing Workers”, Journal of Labor Economics 26(3): 455–83.