The Macroeconomics of Uncertainty and Volatility

When uncertainty increases it creates two confounding effects: a realization effect and an anticipation effect. These two effects may have opposing results on current behavior. By using a quasi natural experiment focusing on the pricing behavior of supermarkets during the 2019 riots in Chile we identify the consequences of the anticipation effect: during the 31-day period following the riots supermarkets reduce the frequency of price changes by about 50% and conditional on a price change, the absolute magnitude of price changes is about 50% larger. We attribute these changes to the arrival of news about a future increase in idiosyncratic demand dispersion. We develop a quantitative menu cost model and calibrate it using Chilean product-level data. Only news about future demand dispersion can deliver simultaneously less frequent and conditionally larger price changes. The effectiveness of monetary policy interventions crucially depends on the timing of the intervention relative to the arrival of the news and whether or not the change materializes. In particular, while the realization of uncertainty decreases the effectiveness of monetary policy, monetary policy is more effective when the news about future volatility arrives.

Deviations from a policy rule underpin empirical identification of monetary policy shocks. We cast light on how deviations arise by analyzing internal policy deliberations of the Federal Open Market Committee (FOMC). We show that policymakers’ beliefs about higher-order moments of economic distributions—specifically perceptions of uncertainty and skewness—significantly impact policy stance beyond economic forecasts typically used in rule estimates. To capture those otherwise unobservable decision-making features, we construct text-based proxies for policymakers’ uncertainty, sentiment, and policy stance from the FOMC meeting transcripts over the 1987–2015 period. Heightened uncertainty generally amplifies the policymakers’ response to the macroeconomy. However, while an increased uncertainty about the real economy drives an easier stance, inflation uncertainty leads to more hawkishness. We show that policymakers’ inflation uncertainty is associated with their skewed beliefs about rising inflation, which do not materialize in our sample. The results depart from the certainty equivalence arising in classic monetary models and contrast with the frequently-referenced conservatism in policymaking under uncertainty. Instead, the evidence suggests that policymakers act aggressively to avoid low-probability costly outcomes which are endogenous to their policy actions.

This paper uses a nonlinear vector autoregression and a non-recursive identification strategy to show that an equal-sized uncertainty shock generates a larger contraction in real activity when growth is low (as in recessions) than when growth is high (as in expansions). An estimated New Keynesian model with recursive preferences and approximated to third order around its risky steady state replicates these state-dependent responses. The key mechanism behind this result is that firms display a stronger upward nominal pricing bias in recessions than in expansions, because recessions imply higher inflation volatility and higher marginal utility of consumption than expansions.

 

We introduce information frictions into a tractable quantitative multi-country multi-sector model with global value chains. Producers in a sector do not perfectly observe contemporaneous shocks to other countries and sectors, and their output decisions respond to their idiosyncratic beliefs about worldwide productivity innovations. We discipline agents’ information sets with new quarterly data containing the frequencies of country-industry-specific economic news reports by 11 leading newspapers in the G7 plus Spain. Newspapers in each country publish articles on select events in both domestic and partner-country sectors, and not every event is reported worldwide. We show that (i) greater news coverage is associated with smaller GDP forecast errors by professional forecasters; (ii) the dispersion of forecast errors shrinks with higher news coverage; and (iii) sectors more covered in the news exhibit stronger hours growth synchronization, and more so if they trade more with each other. We use these reduced form facts to discipline the key parameters in the new theory—the precision of the vectors of public and private signals about country-sector productivities. We find that (i) imperfect “news” about economic fundamentals can be a quantitatively important source of international fluctuations and (ii) the effects of information frictions are amplified by the global production network. These information frictions appear as correlated labor wedges in standard models without dispersed information.

I show that the precautionary savings motive can account for the high-frequency variation in the stock-bond covariance. An increase in the price of risk lowers risky asset prices on account of an increase in risk premia; it lowers bond yields on account of the precautionary savings component. Consequently, times when the price of risk is volatile see a more negative stock-bond covariance. I demonstrate that a model of time-varying price of risk, calibrated to fit equity moments, matches well the evidence regarding both the nominal and real stock-bond covariance, even in the absence of inflation news. Empirically, I show that the stock-bond covariance co-moves with credit spreads and can predict excess returns on corporate bonds and on bond-like stocks. The calibrated model underlines the systematic nature of high-frequency changes in the stock-bond covariance and the first-order effect of risk compensation on safe rates

We propose a proxy for the inflation expectations of firms based on aggregating own-firm probabilistic unit cost expectations. Unlike other surveys of firms or households that elicit “aggregate” expectations, we focus on idiosyncratic costs that firms are well-aware of, plan for, and matter for price setting. We document five key findings. First, once aggregated, firms’ unit cost realizations closely comove with U.S. inflation statistics. Second, in aggregate, firms’ unit cost expectations significantly outperform households’ inflation expectations and are at least as accurate as the expectations of professional forecasters in out-of-sample forecasting exercises. Third, utilizing a novel, flexible technique to parametrically estimate firms’ unit cost uncertainty, we find that up until early 2020, the evolution of firms’ views was similar to other survey and market-based measures of inflation uncertainty. Fourth, utilizing special questions, we find evidence that information treatments about aggregate inflation and policymakers’ forecasts do little to alter firms’ unit cost expectations. And, lastly, we show that unit costs, at the firm level, are an important determinant of their own price setting behavior.

Using a long-panel data set of Japanese  rms that contains  rm-level sales forecasts, we provide evidence on  rm-level uncertainty and imperfect information over their life cycles. We find that firms make non-negligible and positively auto-correlated forecast errors. However, they make more precise forecasts and less auto-correlated forecast errors when they become more experienced. We then build a model of heterogeneous firms with endogenous entry and exit where  rms gradually learn about their demand by using a noisy signal. We present our novel approach to cleanly isolate the learning mechanism from other mechanisms by using expectations data over time. We combine the model with our data to perform a non-parametric decomposition of forecast errors and find that learning accounts for between 20% to 40% of the overall decline in forecast errors over the life cycle. Our model shows that, within the context of our cross-regional data, productivity gains from removing information frictions ranges from 3% to 12%. We find a prominent role of  rm entry and exit in generating high productivity gains.

Supply chain disturbances can lead to substantial increases in production costs. To mitigate these risks, firms may take steps to reduce their reliance on volatile suppliers. We construct a model of endogenous network formation to investigate how these decisions affect the structure of the production network and the level and volatility of macroeconomic aggregates. When uncertainty increases in the model, producers prefer to purchase from more stable suppliers, even though they might sell at higher prices. The resulting reorganization of the network leads to less macroeconomic volatility, but at the cost of a decline in aggregate output. The model also predicts that more productive and stable firms have higher Domar weights—a measure of their importance as suppliers—in the equilibrium network. We calibrate the model to U.S. data and find that the mechanism can account for a sizable decline in expected GDP during periods of high uncertainty like the Great Recession.

Existing studies on uncertainty shocks focus on economy-wide shocks that affect all sectors symmetrically and simultaneously. However, as the recent COVID-19 pandemic underscores, a rise in uncertainty often appears to be concentrated in several specific sectors. In this paper, I study how these sector-specific volatility shocks propagate and affect aggregate outcomes. First, using novel sector-level data, I estimate sectoral TFP and demand processes allowing for stochastic volatility. I show that sectoral TFP and demand display nontrivial fluctuations in volatility even after controlling for economy-wide variations. During recessions, the number of sectors experiencing an increase in volatility sharply increases. Second, I use the estimated sectoral TFP and demand processes to simulate the impact of sector-specific volatility shocks  in a calibrated multi-sector New Keynesian model that features input-output networks. I find that sectoral volatility shocks generate contractions in macro variables such as the aggregate GDP and that the quantitative impact heavily depend on the sectoral origin of the shock. The key transmission mechanism is the precautionary pricing motive that propagates to other sectors.

This paper measures option-implied skewness for individual firms and the overall stock market between 1980 and 2020 giving a real-time measure of conditional micro skewness. There are three key results for firm-level skewness: 1. It is significantly procyclical, while market skewness is acyclical; 2. It leads the business cycle, and it is strongly linked to credit spreads, suggesting one potential causal channel; 3. It is significantly, and not mechanically, correlated with aggregate volatility, implying that there is a common shock driving them both, which is also linked to the business cycle.

We study the properties of business expectations and uncertainty in 27 developing and emerging economies. Our evidence comes from 14,000 businesses responding to the World Bank Group Business Pulse and Enterprise Surveys. Each survey elicits three-point subjective probability distributions about future own-firm sales. We measure expectations and uncertainty using the first and second moments of those distributions and verify they predict future sales growth outcomes and absolute forecast errors. Our analysis reveals two new facts about business uncertainty across countries. (1) Uncertainty is higher in our sample than in advanced economies, and it declines with GDP per capita even after accounting for firm size, sector, and other firm- and country-level predictors of uncertainty. (2) Absolute forecast errors are larger than our survey-based measures of business uncertainty imply; namely, managerial beliefs are overprecise (understate sales volatility) and particularly so in lower-income countries.

We present a framework to identify market responses to uncertainty faced by firms regarding both the potential incidence of extreme weather events and subsequent economic impact. Stock options of firms with establishments in forecast and realized hurricane landfall regions exhibit large increases in implied volatility, reflecting significant incidence uncertainty and long-lasting impact uncertainty. Comparing ex ante expected volatility to ex post realized volatility by analyzing volatility risk premia changes shows that investors significantly underestimate extreme weather uncertainty. After Hurricane Sandy, this underreaction diminishes and, consistent with Merton (1987), these increases in idiosyncratic volatility are associated with positive expected stock returns.

We construct a quantitative indicator of tension between the U.S. and China using news-based textual analysis, and examine its economic transmission. Our baseline U.S.-China Tension index (UCT) is constructed from eight major U.S. newspapers. We also construct indexes using four newspapers from Canada, three from the United Kingdom, and four from China. This allows us to document differences in perspectives on issues that give rise to bilateral tension between the U.S. and China. According to all of our western-based indexes, U.S.-China tensions rise around the Tibet unrest and China military buildup in 2008, arrest of a Huawei executive in 2018, the sustained trade disputes in 2018-2019, onset of the global pandemic and mutual blaming over the spread of coronavirus, and most recently war in Ukraine. Our China-based index often exhibits noticeably different patterns, including around the Belgrade embassy bombing (May 1999),Hainan Island spy plane standoff in 2001, and during the pandemic. This is suggestive of “media slant” driven by domestic economic and political factors. In all countries, our index is quiescent throughout late 2000, following the U.S. Congress passing a bill in October granting permanent normal trade relations (PNTR) status to China. We validate our baseline (U.S.-based) measure by showing that it closely tracks the share of related discussions in U.S. firms’ earnings conference calls and that it correlates with firm actions in ways that are highly indicative of firm concerns about bilateral tensions. Elevated tension is associated with protracted declines in U.S. corporate investment, especially among firms that are expected to be exposed to the bilateral tensions. We also find adverse economic effects in the aggregate, even after accounting for a large number of factors traditionally used to explain such effects. Impulse responses from medium-sized VARs show that positive shocks to the U.S.-based UCT index lead to protracted output declines, increased credit spreads, and reduced bilateral trade. These effects are milder and less persistent in the Chinese data than the United States.

We present a novel finding that higher macroeconomic uncertainty is surprisingly associated with greater accumulation of physical capital, despite a contemporaneous reduction in investment. To reconcile this evidence, we show that high uncertainty predicts a persistent decrease in the utilization and depreciation of existing capital, which dominates the investment slowdown. We construct and estimate a general-equilibrium model to explain our novel findings alongside the existing evidence on the relationship between uncertainty, economic growth, and asset prices. In the model, precautionary saving is achieved by lowering utilization, instead of increasing investment. Lower utilization persistently decreases depreciation, conserving capital for the future, and simultaneously discourages new investment. The mechanism changes the sign of uncertainty risk-premium in general-equilibrium, and microfounds firms’ exposures to uncertainty risks. We further demonstrate the quantitative importance of our mechanism to generate a negative impact of uncertainty shocks in an extended New-Keynesian framework.

When Initial Jobless Claims (IJC) are higher than expected, investors may expect more generous Federal Government support and drive up the aggregate stock prices through the expected cash flow channel, leading to a novel "Main Street pain, Wall Street gain'' phenomenon. This phenomenon emerges when news articles on IJC announcements mention fiscal policy keywords more. During the Covid period, firms/industries that are expected to suffer more in fundamentals, get mentioned more in legal stimulus bills, or have higher obligated funding amounts show higher individual stock returns when bad IJC news arrives. Our results suggest that investors form fiscal policy expectations.

In this paper, we study household consumption-saving and portfolio choices in a heterogeneousagent economy with sticky prices and time-varying total factor productivity and idiosyncratic stochastic volatility. Agents can save through liquid bonds and illiquid capital and shares. With rich heterogeneity at the household level, we are able to quantify the impact of uncertainty across the income and wealth distribution. Our results help us in identifying who wins and who loses when during periods of heightened individual and aggregate uncertainty. To study the importance of heterogeneity in understanding the transmission of economic shocks, we use a deep learning algorithm. Our method preserves non-linearities, which is essential for understanding the pricing decisions for illiquid assets.

Using a new survey of European households, we study how exogenous variation in the macroeconomic uncertainty perceived by households affects their spending decisions. We use randomized information treatments that provide different types of information about the first and/or second moments of future economic growth to generate exogenous changes in the perceived macroeconomic uncertainty of some households. The effects on their spending decisions relative to an untreated control group are measured in follow-up surveys. Higher macroeconomic uncertainty induces households to reduce their spending on non-durable goods and services in subsequent months as well as to engage in fewer purchases of larger items such as package holidays or luxury goods. Moreover, uncertainty reduces household propensity to invest in mutual funds. These results support the notion that macroeconomic uncertainty can impact household decisions and have large negative effects on economic outcomes.

Recessions are associated with sharp increases in turbulence that reshuffle firms’ productivity rankings. To study the business cycle implications of turbulence shocks, we use Compustat data to construct a measure of turbulence based on the (inverse of) Spearman correlations of firms’ productivity rankings between adjacent years. We document evidence that turbulence rises in recessions, reallocating labor and capital from high- to low-productivity firms and reducing aggregate TFP and the stock market value of firms.A real business cycle model with heterogeneous firms and financial frictions can generate the observed macroeconomic and reallocation effects of turbulence. In the model, increased turbulence makes high-productivity firms less likely to remain productive, reducing their expected equity values and tightening their borrowing constraints relative to low-productivity firms. This leads to a reallocation that reduces aggregate TFP. Unlike uncertainty, turbulence changes both the conditional mean and the conditional variance of the firm productivity distribution, enabling a turbulence shock to generate a recession with synchronized declines in aggregate activities.

Foreign investors’ changing appetite for risk-taking have been shown to be a key determinant of the global financial cycle. Such fluctuations in risk sentiment also correlate with the dynamics of UIP premia, capital flows, and exchange rates. To understand how these risk sentiment changes transmit across borders, we propose a two-country macroeconomic framework. Our model features cross-border holdings of risky assets by U.S. financial intermediaries who operate under financial frictions, and who act as global intermediaries in that they take on foreign asset risk. In this setup, an exogenous increase in U.S.-specific uncertainty, modeled as higher volatility in U.S. assets, leads to higher risk premia in both countries. This occurs because higher uncertainty leads to deleveraging pressure on U.S. intermediaries, triggering higher global risk premia and lower global asset values. Moreover, when U.S. uncertainty rises, the exchange rate in the foreign country vis-à-vis the dollar depreciates, capital flows out of the foreign country, and the UIP premium increases in the foreign country and decreases in the U.S., as in the data.

This paper studies the role of uncertainty in a search-and-matching framework with riskaverse households. Heightened uncertainty about future productivity reduces current economic activity even in the absence of nominal rigidities, although the effect is reinforced by the latter. The reason behind the former result is that future asset prices become more volatile and covary positively with aggregate consumption, which increases the risk premium in the present, putting negative pressure on current asset values, and contracts supply. With nominal rigidities, a more uncertain future increases households’ precautionary behavior, which causes demand to contract. Compared to negative demand shocks, uncertainty shocks are less deflationary and render a flatter Phillips curve.