Economic crises like the Covid-19 pandemic affect individual firms in different ways (Barrero et al, 2020; 2021). Policies also have variable impacts across sectors (Ramey and Shapiro, 1998; Galindo-Rueda et al, 2020; Farhi et al, 2021). So, to assess whether particular policy actions soften or amplify the uneven effects of macroeconomic shocks, we need to understand how and why firms differ in their responses.
In our research, we show that observable differences in business characteristics are a key part of why, in the event of a macroeconomic shock, there is increased dispersion in firms’ revenue growth, employment growth, investment rates and earnings surprises (Davis et al, 2025).
Macroeconomic shocks and firm-level risk exposure
Our study considers various types of macroeconomic shocks that hit the US economy between 2020 and 2022. To identify these shocks, we focus on ‘jump’ days when the US stock market rose or fell by more than 2.5%. By this measure, there were 67 daily stock market jumps during the exceptionally volatile period of 2020-22.
Following earlier work (Baker et al, 2025), we categorise the jump dates based on the nature of ‘jump-triggering’ news. This approach reveals several types of shocks, which include news about the pandemic, inflation data, monetary policy decisions and fiscal policy announcements.
To quantify firm-level exposures to each category of macroeconomic shock, we use two types of information: stock returns; and prior discussions of business risk factors in mandatory corporate filings. A firm’s average stock return across jumps with a common trigger offers an initial measure of its exposure to the associated news shock.
Our analysis reveals wide cross-firm return variation on jump days, suggesting that financial markets expect the underlying shocks to affect firms in very different ways.
Common observables of a firm – such as its industry, size and financial characteristics – explain only a modest share of the variation in firm-level returns. This is because differences in shock exposure reflect granular, harder-to-measure business characteristics.
To take one example, consider two firms in the computer equipment manufacturing sector: NetApp, which provides cloud services to various clients, and Scientific Games, which specialises in serving casinos. Their distinct customer bases meant that they faced radically different challenges during Covid-19, despite them having a common industry classification. Similarly, Domino’s Pizza and Ruth’s Hospitality Group both operate restaurants, but pizza delivery outlets and fine-dining establishments had vastly different exposures to the sudden shift to a stay-at-home world.
To account for the wide array of relevant business characteristics, we tap each firm’s ‘risk factor’ disclosures, which form part of its annual 10-K filing. These mandatory documents are publicly available and provide a comprehensive written description of any business risks identified by the firm’s senior management. They comment on the firm’s customer base, supply chains, technology adoption, competitive concerns, operational risks, policy-related risks and other aspects of the business. The filings are distinct from quarterly earnings calls, which tend to focus on the most salient current issues that affect earnings rather than the full range of business characteristics.
Analysis of the risk disclosures reveals several notable patterns. For example, during pandemic-driven downward jumps, firms discussing travel, leisure, property and energy tend to experience negative returns, while those mentioning remote services, drug trials and information technology see positive relative returns. Inflation-driven jumps produce different patterns related to language about property, debt, healthcare and energy.
Real effects of shock exposure
We also explore the relationship between a variety of firm-level outcomes and exposure measures. First, we focus on exposures to pandemic and inflation news shocks given their salience during the period. Exposures to these shocks are nearly uncorrelated in the cross section, which means that they play out very differently at the firm level. In this sense, macroeconomic shocks are not all alike.
Figure 1 shows the effect of a one standard-deviation increase in pandemic and inflation shock exposures, respectively, on quarterly revenue growth (also in standard deviation units). Pandemic-related news shocks have large and persistent effects on the variation of revenue growth for up to two years beyond the first quarter of 2020. Independently, inflation news shocks have significant effects on revenue growth variation that closely track the evolution of inflation expectations across firms.
Figure 1: Revenue growth effects of increased pandemic (left-hand side) and inflation (right-hand side) exposure.
Source: Davis et al, 2025
Remarkably, we also find that variation in jump day abnormal returns that text cannot explain beyond standard controls has no effect on revenue growth. That is, our method isolates the fundamental variation in returns that helps to predict future firm-level outcomes.
One implication is that using raw returns as an exposure measure – which is common in previous research – substantially understates the extent to which exposure and responses to macroeconomic shocks can vary. Across other real outcomes – employment growth, investment rates and earnings surprises – we again find significant predictive effects of our text-based shock exposures.
Figure 2: Dispersion in firm-level revenue growth in data (black curve) and dispersion
Source: Davis et al, 2025
Finally, we return to the central question of quantifying the effect of shocks on the dispersion in real firm-level outcomes. The black curve in Figure 2 shows the standard deviation of revenue growth by quarter. As expected, this rises sharply at the onset of the pandemic recession and again, in milder form, during the burst of inflation in 2022.
We then plot the standard deviation in the predicted revenue growth distribution from regressions that include all other exposure types (including the pandemic and inflation). Collectively, macroeconomic exposures account for most of the rise in cross-firm performance variation in the 2020 recession.
While risk factors in their current form don’t have long historical coverage, research suggests that this mechanism operates beyond the pandemic period. Since 1900, stock market jumps have been three times more frequent during recessions than expansions, and tend to be more extreme during downturns. The relationship between jump magnitude and firm-level return dispersion also holds consistently since 2000, suggesting that financial markets systematically expect firms to respond to shocks in a varied way.
Using jump-date returns as exposure measures over the period 1995-2022, we find that macroeconomic shock exposures explain similar amounts of the increased dispersion in firm-level outcomes during other recessions. Importantly, firm exposures differ dramatically across recessions and the shocks that drive them. For example, companies highly exposed to the dot-com crash showed little correlation with exposures to financial crisis or pandemic shocks, reflecting each downturn’s distinct character.
Implications
Our findings challenge conventional explanations for countercyclical variation in firm performance. Rather than attributing variability to higher uncertainty or greater sensitivity to shocks, our evidence points to differing exposures to common shocks driven by observable business characteristics.
For monetary and fiscal policy, the results highlight the importance of understanding transmission. Different types of shocks create different effects across firms and sectors. A financial crisis, for example, affects firms differently than an inflation shock or a supply chain disruption or a trade dispute. Because different shocks produce distinct patterns of responses across firms, they may also require distinct and tailored policy actions if the aim is to moderate the uneven effects or facilitate adjustments to them.
