Session 12: The Macroeconomics of Uncertainty and Volatility

Using the 2018-2019 U.S.-China trade war as a laboratory, we establish the casual relation that policy uncertainty shocks significantly lower stock prices. In addition, we find that the usage of bank debt in firms’ debt structure can significantly mitigate the negative impact, while the mitigating effect does not exist for non-bank debt. We further demonstrate the source of the mitigating effect by showing that it is concentrated among zombie firms — mature firms that persistently do not have enough earnings to cover their interest expenses. A zombie firm that derives half of its capital from bank debt can offset the negative impact of uncertainty entirely due to the mitigating effect. Our findings provide evidence that bank debt can provide insurance and flexibility for shareholders of distressed firms, especially during turbulent times.

This paper uses U.S. loan-level credit register data and the 2018–2019 Trade War to test for the effects of international trade uncertainty on domestic credit supply. We exploit cross-sectional heterogeneity in banks’ ex-ante exposure to trade uncertainty and find that an increase in trade uncertainty is associated with a contraction in bank lending to all firms irrespective of the uncertainty that the firms face. This baseline result holds for lending at the intensive and extensive margins. We identify two channels underlying the estimated credit supply effect: a wait-and-see channel by which exposed banks assess their borrowers as riskier and reduce the maturity of their loans, and a financial frictions channel by which exposed banks facing greater balance sheet constraints contract lending more. The decline in credit supply has real economic effects: firms that borrow from more exposed banks experience lower asset and investment growth. These effects are stronger for firms that are more reliant on bank finance.

We use a comprehensive Swedish credit register to document that firms throughout the size distribution have access to fairly large and reasonably priced credit lines, but borrow relatively little from them. We rationalize this using a theoretical framework in which the expected cost of financial distress increases with current borrowing, and lower credit-line utilization reflects tighter ‘dynamic’ credit constraints. Consistently with the predictions of the model, firm-level uncertainty is negatively related to credit-line utilization in the data. We also find that firms increase borrowing in response to credit-limit increases, even when their current debt is far from the limit.

The COVID-19 pandemic has raised concerns about the future of work. The pandemic may become recurrent, necessitating repeated adoptions of social distancing measures (voluntary or mandatory), creating substantial uncertainty about worker productivity. But robots are not susceptible to the virus. Thus, pandemic-induced job uncertainty may boost the incentive for automation. However, elevated uncertainty also reduces aggregate demand and reduces the value of new investment in automation. We assess the importance of automation in driving business cycle dynamics following an increase in job uncertainty in a quantitative New Keynesian DSGE framework. We find that, all else being equal, job uncertainty does stimulate automation, and increased automation helps mitigate the negative impact of uncertainty on aggregate demand.

We identify and study two mechanisms that can overturn the stabilizing effects of unemployment insurance policies. First, households in economies with more generous unemployment insurance reduce precautionary savings and borrow more in the mortgage market. Second, the share of mortgages among bank assets, as well as the fraction of mortgages with higher loan-to-income ratios, increases on bank balance sheets. As a result, both bank and household balance sheets become vulnerable to adverse shocks, which deepens recessions. Furthermore, booms are also amplified, as smaller income risk enables households to increase their mortgage debt, consumption, and housing demand in response to expansionary shocks. We use a quantitative general equilibrium model that features interactions between household, bank, and firm balance sheets, and a border discontinuity design from the U.S. mortgage and housing markets to demonstrate the importance of these channels.

Voting seats at FOMC meetings rotate between Reserve Bank presidents on a yearly basis. Using detailed data on 488 FOMC meetings that took place between 1969 and 2021 and predetermined rotations of voting rights, we show that economic conditions in Reserve Bank presidents’ districts affect Federal funds target rates only when those presidents hold voting seats at FOMC meetings. Federal funds futures reflect this effect of local economic conditions on FOMC decisions. Supporting the voting mechanism, we show that voting presidents dissent based on economic conditions in their districts. Reserve Bank presidents’ districts are more likely to be mentioned in FOMC transcripts than are the districts of non-voting presidents. Finally, we show that the path of the target rate would have been different if economic conditions in all districts affected FOMC decisions.

We study how the Fed’s communication of its forward-looking policy stance affects risk premia in financial markets. We analyze private deliberations of the Federal Open Market Committee (FOMC) to elicit policy stance beyond the current announcement. We show that more hawkish (dovish) policymakers’ views expressed in the FOMC meeting predict economically significant reductions (increases) in risk premia during the subsequent intermeeting period. The risk premium reaction unfolds gradually in the days after the FOMC announcement. The effect is not subsumed by the content of the FOMC statements and is distinct from the “on impact” risk-premium reduction caused by surprise rate cuts at the FOMC announcements, documented in the literature. To understand the predictive power of the Fed’s private deliberations, we trace out how the stance emerging from the meeting is revealed to the public via speeches and minutes, and tie the movements in risk premia to the granular communication events over the intermeeting period. The results highlight the role of communication in managing public risk perceptions.

We introduce a new measure of own-price inflation uncertainty using firm-level data from a large and representative survey of UK businesses. Inflation uncertainty increased significantly from the start of 2021 and reached a peak in the second half of 2022, even as a similar measure of sales uncertainty declined. We also find large cross-sectional differences in inflation uncertainty, with uncertainty particularly elevated for smaller firms and those in the goods sector. Finally, we show that firms which are more uncertain about their own price expectations experience higher forecast errors 12 months later. These findings suggest that studying inflation uncertainty at the firm level may be an important new dimension to understanding firm performance.

We use data from a large panel survey of UK firms to analyze the economic drivers of price setting since the start of the Covid pandemic. Inflation responded asymmetrically to movements in demand. This helps to explain why inflation did not fall much during the negative initial pandemic demand shock. Energy prices and shortages of labor and materials account for most of the rise during the rebound. Inflation rates across firms have become more dispersed and skewed since the start of the pandemic. We find that average price inflation is positively correlated with the dispersion and skewness of the distribution. Finally, we also introduce a novel measure of subjective inflation uncertainty within firms and show how this has increased during the pandemic, continuing to rise in 2022 even as sales uncertainty dropped back.

This paper shows the importance of technological synergies among heterogeneous firms for aggregate fluctuations. First, we document five novel empirical facts using microdata that suggest the existence of important technological synergies between trading partners, the presence of positive assortative matching among firms, and their evolution during the business cycle. Next, we embed technological synergies in a general equilibrium model calibrated on firm-level data and show that frictions in forming trading relationships and separation costs explain imperfect sorting between firms in equilibrium. In particular, an increase in the volatility of idiosyncratic productivity shocks significantly decreases aggregate output without resorting to non-convex adjustment costs.

This paper studies the dynamic effects of an uncertainty shock on firm expectations. We conduct a survey that confronts managers from a representative firm sample with a model-consistent uncertainty shock scenario. An exogenous increase in uncertainty significantly reduces managers’ expected investment, employment, and production in the short and mid-run. We collect novel direct firm-level measures for different types of capital and labor adjustment costs. Adjustment costs vary strongly across types and sectors. They help explain firms’ reactions to the shock, which provides evidence for the relevance of real-options channels. We compare the findings to DSGE and VAR results.

Using recently available daily S&P 500 index option expirations, we examine the ex ante pricing of uncertainty surrounding key economic releases and the determinants of risk premia associated with these releases. The cost of insurance against price, variance, and downside risk is higher for options that span U.S. CPI, FOMC, Nonfarm Payroll, and GDP releases compared to neighboring expirations. We calculate release-driven forward equity and variance risk premia and find that premia vary considerably across economic releases and increase with risk aversion as well as with monetary policy and real economic uncertainty. The empirical framework presented in this paper can be used to examine the ex ante pricing of a wide variety of events.

The historical returns on equity index options are well-known to be strikingly negative. That is typically explained either by investors having convex marginal utility over stock returns (e.g., crash/variance aversion) or by intermediaries demanding a premium for hedging risk. This paper examines the consistency of those explanations with returns on dynamically replicated, or synthetic, options. Theoretically, it derives conditions under which convex marginal utility leads synthetic options to also have negative excess returns. Empirically, synthetic options have never earned significantly negative CAPM alphas, in stark contrast to exchange-traded options. Over the last 15 years, returns on true options have converged to those on synthetic options while various drivers of the cost and risk of hedging options exposures have shrunk, consistent with a model in which intermediaries drive option prices.

We study the transmission of uncertainty shocks in production networks and find that their impact on economic activity depends on their source in supply chains. A real-option framework with time-to-build predicts that only upstream uncertainty suppresses investment, since upstream (downstream) uncertainty from suppliers (customers) affects the shorter-run (longer-run). Consistently, production-network data show that upstream uncertainty propagates downstream, affecting firm-level outcomes negatively. Conversely, downstream uncertainty propagates upstream more weakly but affects firm-level outcomes positively. At the macro-level, these two uncertainties oppositely predict aggregate growth and asset prices. Overall, downstream uncertainty has an expansionary effect, in contrast to other facets of uncertainty.

This paper studies the macroeconomic consequences of asymmetric interest rate shocks at which small open economies borrow in international financial markets. Empirically, we document that borrowing spreads have two distinct regimes. The first one features stable borrowing rates, i.e. low risk. In contrast, the second phase displays large spreads with significant volatility and asymmetry – high risk. We fit the spreads to a rich statistical process that allows for changes in the level, volatility, skewness, and kurtosis of the spread’s distribution. Each of the spread regimes is estimated to be highly persistent. When we embed the estimated spreads in a standard small-open economy model, we find that 1) Spread shocks alone explain a large fraction of the volatility in consumption and investment in the data 2) Interest shocks of similar magnitude have stronger contractionary effects in an economy where only low risk exists than in one with changes between high and low risk. 3) The transition from an economy with only low-risk interest rate shocks to one like in the data results in a significant and persistent contraction. The welfare cost of this transition equals 2.4% of consumption. Finally, an unexpected increase in skewness pushes the economy into a recession with output, consumption, and investment dropping by as much as 1%, 2%, and 5%, respectively. This contraction resembles those experienced by developing countries during sudden stop episodes.

We identify a shock that explains the bulk of fluctuations in the equity risk premium, and show that the shock also explains a large fraction of the business-cycle comovements of output, consumption, employment, and investment. Recessions induced by the shock are associated with reallocation away from full-time labor positions, and towards part-time and flexible contract workers. We develop a novel real model with labor market frictions and fluctuations in risk appetite, where a "flight-to-safety" reallocation from riskier to safer factors of production precipitates a recession that can explain the data, since the safer factors offer lower marginal products in equilibrium.

We use novel data covering 2 billion daily employee-article interactions across approximately 2 million firms to characterize firms’ exposures to uncertainty in almost real-time. We find that, in the cross-section, firms that more intensely read about financial versus other uncertainty-related topics are those most exposed to changes in aggregate measures of economic uncertainty. Consistent with exposure to uncertainty being priced, public firms that spend more time reading these topics have a 2% higher cost of capital, translating into relatively low investment rates. Higher attention to financial uncertainty relates to a 7% lower investment and a 5% lower hiring rate on an annual basis.

Uncertain times are often challenging, and distinguishing between volatility shocks and large negative level shocks can be problematic. We use the Base Realignment and Closure process in the United States in the 1990s and 2000s to address this question. In this case, the level shock is announced after a significant period of uncertainty and is implemented after an even greater period of time, allowing us to distinctly separate first-moment from second-moment shocks and directly estimate the impact of uncertainty. Employing a difference-in-difference approach, as well as a panel regression in which we explicitly control for the level effect of spending, we demonstrate that uncertainty had a significant impact independently of level effects.

We capture economic policy uncertainty from mainstream TV cable networks and link it to expected market volatility. The novelty of our method is that we can identify who is on TV and when the news is delivered. At the daily level, our measure is correlated with print-based proxies of policy uncertainty, but contains significant complementary information. Importantly, it is also correlated with expected market volatility when measured at more granular time intervals, such as at the hourly level. Politician airtime is not related to market volatility, but it is when they discuss policy-related matters. The news network, political party, and party control are also related to the expected volatility reaction. Finally, aggregated firm state-level volatility is correlated with the home state Governor’s discussion of policy uncertainty.

Beyond its environmental damage, climate change is predicted to produce significant economic costs for many countries around the world. Indeed, several studies have shown that increasing temperature levels, temperature anomalies, and natural disasters are associated with sizeable declines in economic activity, especially among developing economies. This article examines another potentially important channel through which global warming can lead to economic costs: the increase in temperature volatility. To this end, it suggests a new empirical approach based on granular local weather and firm-level panel data to quantify the causal impact of climate change on economic activity. Using novel high-frequency granular geospatial temperature data from satellites with measures of economic activity for the universe of US-listed firms, the results show that increases in temperature volatility—by increasing economic uncertainty—persistently reduce the level of firms’ investment. The estimates suggest that the increase in temperature volatility observed in the US in the past 20 years may have resulted in a decline of firms’ investment of about 1.6 percent—that is, about $20 billion for the entire US economy. This effect varies across firms, with firms characterized by tighter financial constraints, such as younger and smaller firms, disproportionately more affected. Our empirical evidence shows that increasing temperature volatility is associated with higher firms’ economic uncertainty and is an additional contributing factor to the economic costs of climate change.

This paper measures the impact of information quality on the success of firms' investment decisions using the U.S. census as an empirical context. Over the course of a decade, information from the decennial census snapshot likely deviates from the evolving market condition, thereby making the data less relevant. I find that on average, outdated census information increases establishment failure rate by 1.6% per year. The effects are stronger for geographic areas that experience large changes in demographics, for industries that rely on precise information in small trade areas, and for independent retailers that lack alternative sources of demographic information.