NATIONAL BUREAU OF ECONOMIC RESEARCH
NATIONAL BUREAU OF ECONOMIC RESEARCH
loading...

Monetary Economics Program Meeting

November 4, 2011
Julio Rotemberg of Harvard Business School and Yuriy Gorodnichenko of the University of California, Berkeley, Organizers

Bartosz Mackowiak, European Central Bank, and Mirko Wiederholt, Northwestern University
Inattention to Rare Events

Why were people so unprepared for the global financial crisis, the European debt crisis, and the Fukushima nuclear accident? To address this question, Mackowiak and Wiederholt study a model in which agents make state-contingent plans - they think about actions in different contingencies - subject to the constraint that agents can process only a limited amount of information. The model predicts that agents are unprepared in a state when the state has a low probability, the optimal action in that state is uncorrelated with the optimal action in normal times, and actions are strategic complements. The authors then compare the equilibrium allocation of attention to the efficient allocation of attention. They then characterize the conditions under which society would be better off if agents thought more carefully about optimal actions in rare events.


Ivan Werning, MIT and NBER
Managing a Liquidity Trap: Monetary and Fiscal Policy

Werning studies monetary and fiscal policy in liquidity-trap scenarios, where the zero bound on the nominal interest rate is binding. He works with a continuous-time version of the standard New Keynesian model. Without commitment, the economy suffers from deflation and depressed output --surprisingly, both are exacerbated with greater price flexibility. Werning examines monetary and fiscal policies that maximize utility for the agent in the model and refers to these as optimal. He finds that the optimal interest rate is set to zero past the liquidity trap and jumps up discretely upon exit. Inflation may be positive throughout, so the absence of deflation is not evidence against a liquidity trap. On the other hand, output always starts below its efficient level and rises above it. Werning then studies fiscal policy and show that, regardless of parameters that govern the value of "fiscal multipliers" during normal or liquidity trap times, optimal spending is above its natural level at the start of a liquidity trap. However, it declines over time and goes below its natural level. He proposes a decomposition of spending according to "opportunistic" and "stimulus" motives. The former is defined as the level of government purchases that is optimal from a static, cost-benefit standpoint, taking into account that, due to slack resources, shadow costs may be lower during a slump; the latter measures deviations from the former. He shows that stimulus spending may be zero throughout, or switch signs, depending on parameters. Finally, he considers the hybrid where monetary policy is discretionary, but fiscal policy has commitment. In this case, stimulus spending is typically positive and increasing throughout the trap.


Eric M. Leeper, Indiana University and NBER; Nora Traum, North Carolina State University; and Todd B. Walker, Indiana University
Clearing Up the Fiscal Multiplier Morass

Leeper, Traum, and Walker note that Bayesian prior predictive analysis of five nested DSGE models suggests that model specifications and prior distributions tightly circumscribe the range of possible government spending multipliers. Multipliers are decomposed into wealth and substitution effects, yielding uniform comparisons across models. By constraining the multiplier to tight ranges, model and prior selections bias results, revealing less about fiscal effects in data than about the lenses through which researchers choose to interpret data. When monetary policy actively targets inflation, output multipliers can exceed one, but investment multipliers are likely to be negative. Passive monetary policy produces consistently strong multipliers for output, consumption, and investment. Keywords: government spending; monetary-fiscal interactions; prior predictive analysis

Ruediger Bachmann, University of Michigan and NBER; Tim Berg, Ifo Institute; and Eric R. Sims, University of Notre Dame and NBER
Inflation Expectations and Readiness to Spend: Cross-Sectional Evidence

There have recently been numerous suggestions for monetary policy to engineer higher inflation expectations so as to stimulate spending. But what is the empirical relationship between inflation expectations and spending? Bachmann, Berg, and Sims use the underlying micro data from the Michigan Survey of Consumers to test whether increased inflation expectations are indeed associated with greater reported readiness to spend. Cross-sectional data deliver the necessary variation to test whether the relationship between inflation expectations and spending changes in the recent zero lower bound regime compared to normal times, as suggested by many standard models. The authors find that the impact of inflation expectations on the reported readiness to spend on durable goods is small in absolute value when compared to other variables, such as household income or expected business conditions. Moreover, it appears that higher expected price changes have an adverse impact on the reported readiness to spend. A one percent increase in expected inflation reduces the probability that households have a positive attitude towards spending by 0.15 percentage points. At the zero lower bound, this small adverse effect remains, and is, if anything, exacerbated. The researchers also extend their analysis to the reported readiness to spend on cars and houses and obtain similar results. Altogether the results tell a cautionary tale for monetary (or fiscal) policy designed to engineer inflation expectations in order to generate greater readiness to spend.


Susanto Basu, Boston College and NBER, and Brent Bundick, Boston College
Uncertainty Shocks in a Model of Effective Demand

Basu and Bundick examine the role of uncertainty shocks in a one-sector, representative-agent dynamic stochastic general-equilibrium model. When prices are flexible, uncertainty shocks are not capable of producing business-cycle comovements among key macro variables. With countercyclical markups through sticky prices, however, uncertainty shocks can generate fluctuations that are consistent with business cycles. Monetary policy usually plays a key role in offsetting the negative impact of uncertainty shocks. If the central bank is constrained by the zero lower bound, then monetary policy can no longer perform its usual stabilizing function and higher uncertainty has even more negative effects on the economy. Calibrating the size of uncertainty shocks using fluctuations in the VIX, the authors find that increased uncertainty about the future may indeed have played a significant role in worsening the Great Recession, which is consistent with statements by policymakers, economists, and the financial press.


Atif Mian, University of California, Berkeley and NBER, and Amir Sufi, University of Chicago and NBER
What Explains High Unemployment?The Aggregate Demand Channel

A drop in aggregate demand driven by shocks to household balance sheets is responsible for a large fraction of the decline in U.S. employment from 2007 to 2009. The aggregate demand channel for unemployment predicts that employment losses in the non-tradable sector will be higher in high leverage U.S. counties that are most severely impacted by the balance sheet shock, while losses in the tradable sector will be distributed uniformly across all counties. Mian and Sufi find exactly this pattern from 2007 to 2009. Alternative hypotheses for job losses based on uncertainty shocks or structural unemployment related to construction do not explain these results. Using the relation between non-tradable sector job losses and demand shocks, and assuming Cobb-Douglas preferences over tradable and non-tradable goods, they quantify the effect of aggregate demand channel on total employment. Their estimates suggest that the decline in aggregate demand driven by household balance sheet shocks accounts for almost 4 million of the lost jobs from 2007 to 2009, or 65 percent of the lost jobs in their data.


 
Publications
Activities
Meetings
NBER Videos
Themes
Data
People
About

National Bureau of Economic Research, 1050 Massachusetts Ave., Cambridge, MA 02138; 617-868-3900; email: info@nber.org

Contact Us