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Credit conditions tightened considerably in the second half of 2015 and U.S. growth slowed. We estimate the extent to which tighter credit conditions last year were responsible for the slowdown using the FRBNY DSGE model. We find that growth would have slowed substantially more had the Federal Reserve not delayed liftoff in the federal funds rate.
Andrew F. Haughwout, Donghoon Lee, Joelle Scally, and Wilbert van der Klaauw
Today, the New York Fed released the Quarterly Report on Household Debt and Credit for the first quarter of 2016. Overall debt saw one of its larger increases since deleveraging ended, while delinquency rates for the United States continued to improve and remain at very low levels. Although the overall picture of Americans’ liabilities has continued to improve since the financial crisis, we wondered what the variation looks like at local levels. One advantage of our Consumer Credit Panel (CCP), which is based on Equifax credit data, is that we can examine geographic variation in debt and delinquency rates. Here, we use the CCP to examine the borrowing and delinquency in oil-producing geographies in the United States, where the economic trends since the Great Recession have been very different from those in the rest of the country.
Stefano Eusepi, Erica Moszkowski, and Argia Sbordone
The May 2016 forecast of the Federal Reserve Bank of New York’s (FRBNY) dynamic stochastic general equilibrium (DSGE) model remains broadly in line with those of our two previous semiannual reports (see our May 2015 and December 2015 posts). In the past year, the headwinds that contributed to slower growth in the aftermath of the financial crisis finally began to abate. However, the widening of credit spreads associated with swings in financial markets in the second half of 2015 and the first few months of this year have had a negative impact on economic activity. Despite this setback, the model expects a rebound in growth in the second half of the year, so that the medium-term forecast remains, as in the December post, one of steady, gradual economic expansion. The model also continues to predict gradual progress in the inflation rate toward the Federal Open Market Committee’s (FOMC) long-run target of 2 percent.
J.K. Rowling, David Byrne, Eric Idle—In recent years, these captivating figures have delivered commencement addresses at Harvard, Columbia University and Whitman College, respectively. Of course, Federal Reserve chairs give commencement speeches too, and good ones. NPR maintains a list of some standouts, “The Best Commencement Speeches, Ever” (this is a cool interactive website that enables you to search by name, school, year, or by theme—play, inner voice, embrace failure, change the world, make art, etc.). Its roundup of graduation season remarks includes Janet Yellen’s 2014 speech at New York University, and Ben Bernanke’s 2013 speech at Princeton. Another list, “Best Commencement Speeches Of All Time,” includes Alan Greenspan’s 1999 commencement speech at Harvard.
Monitoring the economic and financial landscape is a difficult task. Part of the challenge stems from simply having access to data. Even if this requirement is met, there is the issue of identifying the key economic data releases and financial variables to focus on among the vast number of available series. It is also critical to be able to interpret movements in the data and to know their implications for the economy. Since last June, New York Fed research economists have been helping on this front, by producing U.S. Economy in a Snapshot, a series of charts and commentary capturing important economic and financial developments. At today’s Economic Press Briefing, we took reporters covering the Federal Reserve through the story of how and why the Snapshot is produced, and how it can be helpful in understanding the U.S. economy.
In recent years, policymakers in advanced and emerging economies have employed a variety of macroprudential policy tools—targeted rules or requirements that enhance the stability of the financial system as a whole by addressing the interconnectedness of individual financial institutions and their common exposure to economic risk factors. To examine the foreign experience with these tools, we constructed a novel macroprudential policy (MAPP) index. This index allows us to quantify the effects of these policies on bank credit and house prices, two variables that are often the target of policymakers because of their links to boom-bust leverage cycles. We then used the index in the empirical analysis to measure the effectiveness of these policies in emerging market countries and advanced economies. Our estimates suggest that macroprudential tightening can significantly reduce credit growth and house price appreciation.
Financial regulatory agencies issued guidance intended to curtail leveraged lending—loans to firms perceived to be risky—in March of 2013. In issuing the guidance, the Office of the Comptroller of the Currency, the Board of Governors of the Federal Reserve System, and the Federal Deposit Insurance Corporation highlighted several facts that were reminiscent of the mortgage market in the years preceding the financial crisis: rapid growth in the volume of leveraged lending, increased participation by unregulated investors, and deteriorating underwriting standards. Our post shows that banks, in particular the largest institutions, cut leveraged lending while nonbanks increased such lending after the guidance. During the same period of time, nonbanks increased their borrowing from banks, possibly to finance their growing leveraged lending activity.
In the late 1800s, a surge in silver production made a shift toward a monetary standard based on gold and silver rather than gold alone increasingly attractive to debtors seeking relief through higher prices. The U.S. government made a tentative step in this direction with the Sherman Silver Purchase Act, an 1890 law requiring the Treasury to significantly increase its purchases of silver. Concern about the United States abandoning the gold standard, however, drove up the demand for gold, which drained the Treasury’s holdings and created strains on the financial system’s liquidity. News in April 1893 that the government was running low on gold was followed by the Panic in May and a severe depression involving widespread commercial and bank failures.
Editors’ note: The y-axis labels on the charts in this post have been corrected to read “Share,” rather than “Percent.”
Commonly used metrics of inequality and mobility attempt to capture how household (or individual) income compares to the rest of the population and how persistent that income is over the life cycle. It can be helpful to think of the income distribution as a ladder—each household is a rung, ranked by its level of income. If household income rankings remain constant over time, this could indicate a low level of mobility in a society. However, income only constitutes one aspect of overall well-being. Another crucial, and potentially more appropriate, dimension is consumption expenditures—how much do people spend on goods and services? In many ways, consumption can be thought of as a proxy for quality of life, since what a household buys says a lot about its access to the necessities of life. Therefore, the analysis of consumption expenditures mobility constitutes a crucial dimension of mobility.
China lends to the rest of the world because it saves much more than it needs to fund its high level of physical investment spending. For years, the public sector accounted for this lending through the Chinese central bank’s purchase of foreign assets, but this changed in 2015. The country still had substantial net financial outflows, but unlike in previous years, more private money was pouring out of China than was flowing in. This shift in private sector behavior forced the central bank to sell foreign assets so that the sum of net private and public outflows would equal the saving surplus at prevailing exchange rates. Explanations for this turnaround by private investors include lower returns on domestic investment spending and a less optimistic outlook for China’s currency.
Liberty Street Economics features insight and analysis from New York Fed economists working at the intersection of research and policy. Launched in 2011, the blog takes its name from the Bank’s headquarters at 33 Liberty Street in Manhattan’s Financial District.
The editors are Michael Fleming, Andrew Haughwout, Thomas Klitgaard, and Asani Sarkar, all economists in the Bank’s Research Group.
The views expressed are those of the authors, and do not necessarily reflect the position of the New York Fed or the Federal Reserve System.
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