13th annual Municipal Finance Conference


13th annual Municipal Finance Conference


Hutchins Roundup: Fed staff projection descriptions, financial networks, and more

Vivien Lee and
Vivien Lee Senior Research Assistant - Hutchins Center on Fiscal & Monetary Policy, The Brookings Institution
Louise Sheiner
Sheiner Headshot Square
Louise Sheiner The Robert S. Kerr Senior Fellow - Economic Studies, Policy Director - The Hutchins Center on Fiscal and Monetary Policy

November 9, 2017

Studies in this week’s Hutchins Roundup find the tone used by the Fed staff in describing its forecast has predictive power for key macroeconomic variables, there was no substantial network fragility buildup in the financial system leading up to the crisis, and more.

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The tone used by the Fed staff in describing its forecast has predictive power for key macroeconomic variables

Prior to every scheduled meeting of the Federal Open Market Committee (FOMC), the staff of the Board of Governors produces a document that describes the staff’s outlook for the U.S. economy. Using these documents from 1973-2009, Steven Sharpe, Nitish Sinha, and Christopher Hollrah of the Federal Reserve Board find that the tonality of those reports—the amount of optimism versus pessimism in the language used to describe the forecasts—has predictive power for monetary policy and for economic variables over and above the numerical forecasts themselves. More optimistic tonality, as measured by a higher balance of positive versus negative words, foreshadows higher than forecasted GDP growth, lower unemployment, and tighter monetary policy up to four quarters in advance.  Tonality also helps explain the response of interest rates and stock prices to FOMC announcements, they find. This suggests that monetary policy makers absorb information from the staff’s description of its forecast beyond the numerical forecasts, and communicate that information to market participants, the authors conclude.

No evidence of substantial network fragility buildup in the financial system leading up to the crisis

The U.S. financial system is interconnected. Financial institutions lend to and borrow from one another, and have assets from and liabilities to outside entities (i.e. households, non-financial firms, the government, etc.). A surprise reduction in the value of an outside asset can cause a domino effect of institutions defaulting on each other, creating network spillovers. Using balance sheet information from 2002-2016 on bank holding companies, broker-dealers, and insurance companies, Fernando Duarte and Collin Jones of the New York Fed estimate the magnitude of network default spillovers, and examine the extent to which they affected the U.S. financial system. Contrary to some narratives of the crisis, they do not find any substantial buildup of network fragility leading up to the crisis. Instead, the events during the crisis made the network fragile between 2008 and 2012, amplifying expected losses by between 5 and 25 percent, they estimate. According to their analysis, network spillovers returned to pre-crisis levels between 2013 and 2016.

Time lags in the implementation and restructuring of new technologies explains discrepancy between productivity expectations and statistics

Although there seem to be transformative new technologies everywhere, statistics suggest that productivity growth over the past decade has slowed significantly. Erik Brynjolfsson and Daniel Rock of MIT and Chad Syverson of the University of Chicago explore various potential explanations for this incongruity. Using historical examples of innovations and productivity trends, the authors argue that time lags in the implementation and restructuring of technologies are the main explanation for the discrepancy. Recent breakthroughs in artificial intelligence (AI), particularly machine learning, have the potential to increase productivity directly and indirectly by spurring other important complementary innovations, they say. However, building the stock of new technology to a sufficient size to have an aggregate effect and discovering, developing, and implementing the complementary innovations necessary to obtain the full benefit of the AI will take substantial time.

Chart of the Week: New firms play a decreasing role in the economy

Chart 11.06.2017

Quote of the week:

“I think that part of the question to ask is where has the risk gone…there is a certain portion of activity, at least, that has been pushed into different portions of the financial sector because of the use of regulation. I do think that…the regulators have tools through the regulated sector, in their interaction with regulated sector, with the unregulated sector, to monitor how risk is developing. But I think we have to be…always careful that are keeping a handle on that part of it,” says new Fed vice chair for supervision Randal Quarles.

“I also think that history, however, has shown us that it’s not just a question of where has the risk…moved, but also what new risks are developing. Because almost certainly the next time there is stress in the financial system, perhaps even a crisis in the financial system, what history would tell us is that it won’t be the risks that we were expecting from the last time. I think that in the regulated area and the industry in general we ought to keep looking at what are the implications of the growth of fintech, how it interacts with the traditionally regulated industry. I think we ought to be looking at cyber, obviously, the industry and the regulators. It’s been a big focus, but I’m not sure that it’s gotten the intellectual attention that it has to have.”