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Session 8: Macroeconomics of Uncertainty and Volatility

August 28-30, 2017
Organized by: 
  • Nick Bloom (Stanford University)
  • Steve Davis (University of Chicago)
  • Jesus Fernandez-Villaverde (University of Pennsylvania)

The session will cover recent work on the causes and effects of changes in volatility and uncertainty in the aggregate economy, which remain topical given the recent Brexit and Trump election outcomes. Many observers, including policymakers such as Bernanke, Summers, and Romer, have highlighted that these have been major driving factors in the recent credit-crunch recession and advanced heuristic arguments of why this might have been the case. Unfortunately, our theoretical and empirical understanding of these topics is limited since only recently have macroeconomists started working on these issues from a more systematic basis. Nevertheless, changes in volatility and uncertainty similar to the ones observed for the U.S. economy can be shown to be quantitatively significant factors in business cycle fluctuations and a key element in a successful explanation of aggregate fluctuations. Moreover, the presence of changes in volatility and uncertainty has important implications for the design of optimal policies and for our assessment of the responses of central banks and fiscal authorities to recent developments in the world economy. Therefore, the session will aim to include about 14 recent papers on these topics. Our goal is to have a balanced mix of theoretical and empirical papers and a strong interest in applications to policy.

 

In this Session

Aug 28 | 1:00 pm to 1:40 pm

Uncertainty and the Shadow Banking Crisis: Estimates from a Dynamic Model

Presented by: Xu Tian, University of Toronto
Aug 28 | 1:40 pm to 2:20 pm

Bank lending in uncertain times

Presented by: Piergiorgio Alessandri, Bank of Italy
Co-Author(s): Margherita Bottero, Bank of Italy

We exploit loan-level data from the Italian Credit Register to isolate the impact of aggregate uncertainty on the supply of bank credit. Our dataset includes the loan applications submitted by a sample of 650,000 non-financial firms to all Italian banks between 2003 and 2012. The granularity of the data and the occurrence of multiple bank-firm relations allows us to thoroughly control for both bank and firm characteristics. In particular, following Kwaja and Mian (2008) and Jimenéz et al. (2012, 2014) among others, we can use time-varying firm fixed effects to capture unobserved changes in borrowers’ conditions, including their riskiness and demand for new funds. Our key identification assumption is that banks with low capital ratios, and hence a lower tolerance for non-diversifiable forms of risk, are more likely to reject new borrowers when uncertainty rises. Our analysis shows that banks respond to uncertainty. An increase in uncertainty has three distinct effects on their behavior. First, it reduces banks’ likelihood to accept new credit applications. Second, it lengthens the time firms have to wait for the loans to be released conditional on their applications being successful. Third, it makes banks less responsive to fluctuations in short-term interest rates through a wait-and-see type of effect, weakening the traditional ‘bank lending channel’ of monetary policy. The influence of uncertainty is relatively stronger for poorly capitalized lenders, as one would expect on theoretical grounds. Furthermore, firms that are geographically distant from their perspective lenders are more likely to be rejected in uncertain times, suggesting that proximity facilitates banks’ selection and monitoring processes.

Aug 28 | 2:20 pm to 3:00 pm

Shocks vs. Responsiveness: What Drives Countercyclical Dispersion?

Presented by: Joe Vavra, University of Chicago and NBER
Co-Author(s): David Berger, Northwestern University and NBER

The dispersion of many economic variables is countercyclical. What drives this fact? Greater dispersion could arise from greater volatility of shocks or from agents responding more to shocks of constant size. Without data separately measuring exogenous shocks and endogenous responses, a theoretical debate between these explanations has emerged. In this paper, we provide novel identification using the open-economy environment: using confidential BLS microdata, we document a robust positive relationship between exchange rate pass-through and the dispersion of item-level price changes. We show this relationship arises naturally in models with time-varying responsiveness but is at odds with models featuring volatility shocks.

Aug 28 | 3:30 pm to 4:10 pm

Forward Guidance, Policy Uncertainty, and the Term Premium

Presented by: Brent Bundick, Federal Reserve Bank of Kansas City
Co-Author(s): Trenton Herriford, Federal Reserve Bank of Kansas City A. Lee Smith, Federal Reserve Bank of Kansas City

We examine the macroeconomic and term premia implications of monetary policy uncertainty shocks. Using options on Eurodollar futures, we employ the VIX methodology to measure implied volatility about future short-term interest rates at various horizons. We identify monetary policy uncertainty shocks using the unexpected changes in this term structure of implied volatility around monetary policy announcements. These changes in implied volatility are well described by two principal components, which we interpret as shocks to the level and slope of the term structure for implied interest-rate volatility. Using an event-study approach around FOMC announcements, we find an unexpected decline in the slope of implied volatility leads to a significant decline in term premia for longer-term bond yields. Moreover, a negative slope factor shock leads to an increase in economic activity, higher prices, and a persistent decline in the 10-year term premium. From a policymaking perspective, our results suggest that forward guidance announcements can materially affect term premia in bond markets, even without changes in the central bank's balance sheet.

Aug 28 | 4:10 pm to 5:00 pm

Policy Uncertainty, Political Capital, and Firm Risk-Taking

Presented by: Pat Akey, University of Toronto
Co-Author(s): Stefan Lewellen, London Business School
Aug 29 | 9:30 am to 10:00 am

Waiting on the Courts: Effects of Policy Uncertainty on Pollution and Investment

Presented by: Jackson Dorsey, University of Arizona

Legal challenges and transitions of political power cause the future of regulatory policies to be uncertain. In this article, I investigate how uncertainty about environmental policy affects investment and emissions at coal-fired power plants. I exploit a legal challenge to the Clean Air Interstate Rule (CAIR) that created variation in the probability that individual plants would need to comply with the new policy. I use a difference-in-differences approach to compare pollution reductions at power plants located in states subject to more uncertainty to plants in states that that were not. I find that plants with a lower probability of being regulated invested in fewer capital-intensive pollution controls and reduced pollution by less overall. Many of these plants did switch to capital-intensive pollution controls after the court upheld CAIR. Regulatory uncertainty increased compliance costs by $252 million by delaying efficient investments.

Aug 29 | 10:00 am to 10:30 am

Policy Uncertainty in Japan

Presented by: Steven J. Davis, University of Chicago
Co-Author(s): Elif C. Arbatli, International Monetary Fund, Arata Ito, Research Institute of Economy, Trade and Industry, Naoko Miake, International Monetary Fund, Ikuo Saito, International Monetary Fund
Aug 29 | 10:30 am to 11:00 am

Components of Uncertainty

Presented by: Vegard Høghaug Larsen Norges Bank (Central bank of Norway)

Uncertainty is acknowledged to be a source of economic fluctuations. But, does the type of uncertainty matter for the economy’s response to an uncertainty shock? This paper offers a novel identification strategy to disentangle different types of uncertainty. It uses machine learning techniques to classify different types of news instead of specifying a set of keywords. It is found that, depending on its source, the effects of uncertainty on macroeconomic variable may differ. I find that both good (expansionary effect) and bad (contractionary effect) types of uncertainty exist.

Aug 29 | 11:30 am to 12:00 pm

Firm-Level Political Risk: Measurement and Effects

Presented by: Tarek A. Hassan, University of Chicago
Co-Author(s): Stephan Hollander, Tilburg University, Laurence van Lent, Tilburg University, Ahmed Tahoun, London Business School
Aug 29 | 12:00 pm to 12:30 pm

Uncertainty-Induced Reallocations and Growth

Presented by: Max Croce, University of North Carolina at Chapel Hill
Co-Author(s): Ravi Bansal, Duke University, Wenxi Liao, Duke University, Sam Rosen, University of North Carolina at Chapel Hill
Aug 29 | 1:30 pm to 2:00 pm

Uncertainty and Hyperinflation: European Inflation Dynamics after World War I

Presented by: Kris James Mitchener, Santa Clara University & NBER
Co-Author(s): Jose A. Lopez, Federal Reserve Bank of San Francisco

Fiscal deficits, high debt-to-GDP ratios, and inflation rates suggest hyperinflation could have potentially emerged in many European countries after World War I. We demonstrate that policy uncertainty was instrumental in pushing a subset of European countries into hyperinflation shortly after the end of the war. Germany, Austria, Poland, and Hungary (GAPH) suffered from pronounced levels of uncertainty caused by protracted political negotiations over reparations payments, the apportionment of the Austro-Hungarian debt, and border disputes. In contrast, other European countries exhibited lower levels of measured uncertainty between 1919 and 1925, and thus had more capacity with which to implement credible commitments to their fiscal and monetary policies. Impulse response functions from a small, reduced-form macroeconomic model suggest that increased uncertainty caused a rise in inflation contemporaneously and for a few months afterward in the GAPH countries, which contributed to their elevated monthly inflation rates. For the other European countries in our sample, this effect was absent or much more limited. In line with recent literature, our results suggest that elevated economic uncertainty affects macroeconomic dynamics generally and inflation dynamics in particular during the interwar period.

Aug 29 | 2:00 pm to 2:30 pm

Redistribution and Fiscal Uncertainty Shocks

Presented by: Hikaru Saijo, University of California, Santa Cruz

This paper revisits the macroeconomic impact of an uncertainty shock about fiscal policy in a New Keynesian framework. Motivated by the observation that many fiscal policies are redistributive and that many U.S. households do not own capital, I introduce household heterogeneity in the form of limited capital market participation. I show that household heterogeneity significantly magnifies the aggregate effect and restores co-movement of macroeconomic variables in a contraction that is generated by a fiscal uncertainty shock. This is because the heterogeneous household model captures individual uncertainty about redistribution that cancels out in representative agent models. Importantly, the impact of fiscal uncertainty shocks becomes larger as wealth becomes more concentrated.

Aug 29 | 3:00 pm to 3:30 pm

Global Spillover Effects of US Uncertainty

Presented by: Saroj Bhattarai, University of Texas at Austin
Co-Author(s): Arpita Chatterjee, University of New South Wales, Woong Yong Park, Seoul National University and CAMA
Aug 29 | 3:30 pm to 4:00 pm

The Impact of Uncertainty Shocks in the U.K.

Presented by: Chris Redl, Bank of England

Abstract This paper uses a data rich environment to produce direct econometric estimates of macroeconomic and financial uncertainty in the United Kingdom for the period 1991-2016. These indices exhibit significant independent variation from popular proxies for macroeconomic and financial uncertainty. We identify the impact of uncertainty shocks using narrative sign restrictions which allows us to exploit individual historic events to separate the impact of macroeconomic, financial and credit shocks on real variables. Using only traditional sign restrictions, we find that real effects of macroeconomic uncertainty shocks is generally weaker than proxies suggest and that the effect depends on an subsequent rises in financial uncertainty and credit spreads to have a negative impact on GDP. Exploiting narrative events such as the disorderly exit from the Exchange Rate Mechanism, dot-com recession and financial crisis support this finding. However, conditioning on narrative events more closely associated with political uncertainty, i.e. tight general elections, suggests a stronger impact response of GDP to macro uncertainty shocks. We find these results are robust to controlling for both financial and global uncertainty. (I should have a full year of post-Brexit data by the time of the conference and will update results accordingly).

Aug 29 | 4:00 pm to 4:30 pm

Risk Aversion and the Response of the Macroeconomy to Uncertainty Shocks

Presented by: Andrea Tamoni, LSE
Co-Author(s): Lorenzo Bretscher, LSE Alex Hsu, Georgia Institute of Technology
Aug 30 | 8:30 am to 9:10 am

Embrace or Fear Uncertainty: Growth Options, Limited Risk Sharing, and Asset Prices

Presented by: Winston Dou, The Wharton School

The impact of uncertainty shocks on asset prices and macroeconomic dynamics depends on the degree of risk sharing in the economy and the origin of uncertainty. We develop a general equilibrium model with imperfect risk sharing and two sources of uncertainty shocks: (i) productivity uncertainty shocks, which affect the idiosyncratic volatility of firms’ productivity, and (ii) investment uncertainty shocks, which affect the idiosyncratic variability of firms’ investment opportunities. My model deviates from the neoclassical setting in two respects: first, firms’ investment policies are set by the managers who are subject to a moral hazard problem and thus must maintain an undiversified ownership stake in the firm; and second, costly hedging can be obtained through intermediaries. As a result, risk sharing capacity between managers and other investors is limited, which is governed by the intermediary condition. Limited risk sharing distorts equilibrium investment choices, firm valuation, and prices of risk in equilibrium relative to the frictionless benchmark. In the calibrated model, the risk premium on investment uncertainty shocks is negative when risk sharing capacity is low and positive otherwise. Moreover, the cross-sectional spread in valuations between value and growth stocks loads positively on the investment uncertainty shocks under poor risk sharing conditions and negatively otherwise. The calibrated model provides quantitative implications that help understand empirical patterns. Empirical tests also support the predictions of the model.

Aug 30 | 9:10 am to 9:50 am

Pricing Macroeconomic Uncertainty

Presented by: Francesco Bianchi, Duke University
Co-Author(s): Howard Kungy, London Business School, Mikhail Tirskikh, London Business School
Aug 30 | 9:50 am to 10:30 am

Volatility Risk Pass-Through

Presented by: Mariano Croce, University of North Carolina–Chapel Hill
Co-Author(s): Riccardo Colacito, University of North Carolina–Chapel Hill, Yang Liu, University of Pennsylvania, Ivan Shaliastovich, The Wharton School

We show novel empirical evidence on the significance of output volatility (vol) shocks for both currency and international quantity dynamics. Focusing on G-17 countries, we document that: (1) consumption and output vols are imperfectly correlated within countries; (2) across countries, consumption vol is more correlated than output vol; (3) the pass-through of relative output vol shocks onto relative consumption vol is significant, especially for small countries; and (4) consumption differentials vol and exchange rate vol are disconnected. We rationalize these findings in a frictionless model with multiple goods and recursive preferences featuring a novel and rich risk-sharing of vol shocks.

Aug 30 | 10:50 am to 11:20 am

Trade Collapses: The role of Economic and Trade Policy Uncertainty in the Great Recession

Presented by: Kyle Handley, University of Michigan
Co-Author(s): Nuno Limão, University of Maryland Jeronimo Carballo, University of Colorado

We are submitting an extended abstract with a link in the abstract to a set of slides. We are awaiting additional disclosure of a large set of new results from the Census. Therefore, we have not consolidated our latest model new results into a complete draft. However, I can assure you a draft exists and the paper is more mature than it may appear from our submission. EXTENDED ABSTRACT The sharp economic downturn in 2008 triggered the "great trade collapse" (GTC)--- the largest worldwide trade contraction since WWII. Standard models are unable to fully account for either the depth of the collapse or its relatively fast reversal. The crisis also generated widespread fear of a global trade war. We examine if the resulting increase in policy uncertainty initially deepened the collapse and then helped reverse it, when the worst fears of protection were not realized. More generally, we use this episode to examine the role of institutions such as preferential trade agreements (PTAs) as insurance mechanisms for policy uncertainty. We do so in three steps. First, we characterize the trade dynamics of U.S. trade at the firm level before, during and after the crisis. Among other things we find a sharp initial decline in the number of exporting firm-product destinations (varieties) that took two years to recover to the pre-crisis level. We show this net exit accounts for about 40% of the aggregate drop in U.S. export value during the collapse. The corresponding contribution of net exit is smaller for the subset of exports to PTA destinations. Second, we develop a dynamic model with sunk costs of entry and exit into foreign markets where heterogeneous firms face demand uncertainty in both policy and economic conditions. The model predicts that the impact of economic uncertainty shocks on firm entry and exit is amplified if lower income is associated with higher trade protection, as was the case in the Great Depression and until recently. For example, the possibility of trade wars or rising protectionism were widely discussed at the start of the GTC. Agreements where countries credibly fix their trade barriers may reduce both the direct impact of trade policy uncertainty and dampen the effect of economic uncertainty, as suggested by the lower contribution of net exit to PTA destinations in the GTC. Third, we construct measures of economic and policy uncertainty and estimate their impact on firms' entry and exit decisions. We find that uncertainty has a negative impact on the number of firm-product varieties exported by the US and that its effect increased during the GTC compared to the baseline period of 2002-2008. The negative impact of economic and policy uncertainty during the GTC is weaker for firms exporting to countries with which the US has preferential trade agreements (PTAs); this differential effect disappears by 2011. The impact of uncertainty for non-PTA destinations is stronger in industries where the importer has higher potential tariffs at the start of the crisis and then recedes. The findings are consistent with several of the models' predictions and indicate that (i) the Great Recession increased not just economic but trade policy uncertainty in non-PTA markets and both contributed to the GTC; (ii) PTAs insured against the negative effects of potential protectionism and (iii) the reversal in the expectation of a trade war contributed to the recovery.

Aug 30 | 11:20 am to 12:00 pm

Rare Events and the Persistence of Uncertainty

Presented by: Savitar Sundaresan, Business School, Imperial College London

I present a novel methodology to deliver persistence in risk perceptions. Unlike long-term Bayesian learning, all of the parameters of the economy are known, and agents only collect information about shocks to narrow the variance of perceived signals. Collecting information affects not only period-by-period utility but affects the perceived distribution of future shocks, thus \emph{changing how information is collected in future periods}. This dynamic spillover leads to persistence in the variance of perceived distributions. After solving the model in a simple, but general, setting, I applying the mechanism to a more complex model of a financial market to generate implications for the dynamics of financial risk, volatility, asset demand, dispersion of beliefs, and bid-ask spreads. This mechanism provides one way to endogenize auto-regressive outcome variables, such as ARCH or GARCH-style patterns, while assuming i.i.d. underlying processes.