The Federal Reserve Bank of New York works to promote sound and well-functioning financial systems and markets through its provision of industry and payment services, advancement of infrastructure reform in key markets and training and educational support to international institutions.
The New York Fed engages with individuals, households and businesses in the Second District and maintains an active dialogue in the region. The Bank gathers and shares regional economic intelligence to inform our community and policy makers, and promotes sound financial and economic decisions through community development and education programs.
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.
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.
Olivier Armantier, Giorgio Topa, Wilbert van der Klaauw, and Basit Zafar
Today, the New York Fed is introducing a number of new data series and interactive charts reporting findings from its Survey of Consumer Expectations (SCE). Since January 2014, we have been reporting findings from this monthly survey on U.S. households’ views on inflation, commodity prices, the labor market and household finances. In addition to interactive charts showing national trends (going back to June 2013), as well as trends by demographic groups (age, income, education, numeracy and geography), we also make the underlying micro data (with a nine-month lag) available for download for research purposes.
It always seemed to come down to railroads in the 1800s. Railroads fueled much of the economic growth in the United States at that time, but they required that a great deal of upfront capital be devoted to risky projects. The panics of 1837 and 1857 can both be pinned on railroad investments that went awry, creating enough doubt about the banking system to cause pervasive bank runs. The fatal spark for the Panic of 1873 was also tied to railroad investments—a major bank financing a railroad venture announced that it would suspend withdrawals. As other banks started failing, consumers and businesses pulled back and America entered what is recorded as the country’s longest depression.
The world has gone through a process of financial globalization over the past decades, with countries increasing their holdings of foreign assets and liabilities. At the same time, countries have started to have a more positive foreign currency exposure by reducing their bias toward holding assets in domestic currency instead of foreign currency. One possible reason for these changes is that nations view demand shocks as more likely than supply shocks. That is, a dip in output will be accompanied by lower inflation rather than higher inflation. Monetary policy responds to demand shocks by cutting interest rates and letting the domestic currency depreciate. As a consequence, shifting the currency composition of assets and liabilities to increase net foreign currency holdings is a hedging strategy to protect the country’s income and wealth during downturns.
Olivier Armantier, Wilbert van der Klaauw, Giorgio Topa, and Basit Zafar
Correction: In the right panel of the chart, “Mean Probability of Deflation in the SCE,” we have corrected the labels for the group earning less than $75k, which were initially transposed. We regret the error.
The expectations of U.S. consumers about inflation have declined to record lows over the past several months. That is the finding of two leading surveys, the Federal Reserve Bank of New York’s Survey of Consumer Expectations (SCE) and the University of Michigan’s Survey of Consumers (SoC). In this post, we examine whether this decline is broad-based or whether it is driven by specific demographic groups.
The dollar rose sharply against both the euro and yen in 2014 and 2015 and non-oil import prices subsequently fell. An explanation for this relationship is that a stronger dollar reduces the dollar-denominated cost of producing something in Germany or Japan, giving firms room to lower their dollar prices in order to gain sales against their U.S. competitors. A breakdown by type of good, however, shows that import prices for autos, consumer goods, and capital goods tend not to move much with changes in the dollar as foreign firms choose to keep the prices of their goods stable in the U.S. market. Instead, the connection between import prices and the dollar largely reflects the tendency for commodity prices to fall in dollar terms when the dollar strengthens. As a consequence, the dampening effect of a stronger dollar on U.S. inflation is transmitted much more through falling commodity prices than through cheaper imported cars and consumer goods.
Donghoon Lee, Matt Mazewski, Joelle Scally, and Basit Zafar
Household debt in the United States expanded before the Great Recession, contracted afterward, and has been recovering since 2013. But how has the distribution of debt across different income groups evolved over time? Who has been driving the recovery of household debt over the past two years? To date, there has been little work on how borrowing patterns for high- and low-income individuals have changed over time, although one notable exception is Amromin and McGranahan. Here, using the New York Fed Consumer Credit Panel (CCP), a quarterly panel data set based on Equifax credit reports, we shed further light on these questions.
Update (12.9.15): We revised the chart package linked to in the second paragraph of this post to correct a spreadsheet error. A new note also clarifies our methodology. Please see the addendum below.
We know that different people experience different inflation rates because the bundle of goods and services that they consume is different from that of the "typical" household. This phenomenon is discussed in this publication from the Bureau of Labor Statistics (BLS), and this article from the New York Fed. But did you know that there are substantial differences in inflation experience depending on the level of one's housing costs? In this post, which is based upon our updated staff report on “The Measurement of Rent Inflation,” we present evidence that price changes for rent, which comprises a large share of consumer spending, can vary considerably across households. In particular, we show that rent inflation is consistently higher for lower-cost housing units than it is for higher-cost units. Note that since owners' equivalent rent inflation is estimated from observed changes in rent of rental units, this finding applies to homeowners as well. While we cannot be certain about why this is the case, it appears to be at least partly related to how additional units are supplied to the housing market: in higher-price segments additional units primarily come from new construction, while most of the increase in lower-price segments comes from units that previously were occupied by higher-income households.
Robert DeYoung, Ronald J. Mann, Donald P. Morgan, and Michael R. Strain
Except for the ten to twelve million people who use them every year, just about everybody hates payday loans. Their detractors include many law professors, consumer advocates, members of the clergy, journalists, policymakers, and even the President! But is all the enmity justified? We show that many elements of the payday lending critique—their “unconscionable” and “spiraling” fees and their “targeting” of minorities—don’t hold up under scrutiny and the weight of evidence. After dispensing with those wrong reasons to object to payday lenders, we focus on a possible right reason: the tendency for some borrowers to roll over loans repeatedly. The key question here is whether the borrowers prone to rollovers are systematically overoptimistic about how quickly they will repay their loan. After reviewing the limited and mixed evidence on that point, we conclude that more research on the causes and consequences of rollovers should come before any wholesale reforms of payday credit.
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.
Economic Research Tracker
Liberty Street Economics is now available on the iPhone® and iPad® and can be customized by economic research topic or economist.
We encourage your comments and queries on our posts and will publish them (below the post) subject to the following guidelines:
Please be brief: Comments are limited to 1500 characters.
Please be quick: Comments submitted after COB on Friday will not be published until Monday morning.
Please be aware: Comments submitted shortly before or during the FOMC blackout may not be published until after the blackout.
Please be on-topic and patient: Comments are moderated and will not appear until they have been reviewed to ensure that they are substantive and clearly related to the topic of the post. We reserve the right not to post any comment, and will not post comments that are abusive, harassing, obscene, or commercial in nature. No notice will be given regarding whether a submission will or will not be posted.
The LSE editors ask authors submitting a post to the blog to confirm that they have no conflicts of interest as defined by the American Economic Association in its Disclosure Policy. If an author has sources of financial support or other interests that could be perceived as influencing the research presented in the post, we disclose that fact in a statement prepared by the author and appended to the author information at the end of the post. If the author has no such interests to disclose, no statement is provided. Note, however, that we do indicate in all cases if a data vendor or other party has a right to review a post.