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.
Rich Podjasek, Linsey Molloy, Michael Fleming, and Andreas Fuster
Mortgage-backed securities guaranteed by the government-backed entities Fannie Mae, Freddie Mac, and Ginnie Mae, or so-called “agency MBS,” are the primary funding source for U.S. residential housing. A significant deterioration in the liquidity of the MBS market could lead investors to demand a premium for transacting in this important market, ultimately raising borrowing costs for U.S. homeowners. This post looks for evidence of changes in agency MBS market liquidity, complementing similar posts studying liquidity in U.S. Treasury and corporate bond markets.
Income, or wealth, inequality is not something that central bankers generally worry about when setting monetary policy, the goals of which are to maintain price stability and promote full employment. Nevertheless, it is important to understand whether and how monetary policy affects inequality, and this topic has recently generated quite a bit of discussion and academic research, with some arguing that the Federal Reserve’s expansionary policy of recent years has exacerbated inequality (see, for instance, here or here), while others reach the opposite conclusion (see here or here). This disagreement can be attributed in part to the different channels through which expansionary monetary policy can affect inequality: its effect on asset prices would tend to increase inequality, while its effect on labor incomes and employment would likely decrease inequality. In this post, I study one particular channel through which Fed policies may have disparate effects—namely, mortgage refinancing—and I focus on dispersion across locations in the United States.
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.
W. Scott Frame, Andreas Fuster, Joseph Tracy, and James Vickery
In September 2008, the U.S. government engineered a dramatic rescue of Fannie Mae and Freddie Mac, placing the two firms into conservatorship and committing billions of taxpayer dollars to stabilize their financial position. While these actions were characterized at the time as a temporary “time out,” seven years later the firms remain in conservatorship and their ultimate fate is uncertain. In this post, we evaluate the success of the 2008 rescue on several key dimensions, drawing from our recent research article in the Journal of Economic Perspectives.
John Campbell, Andreas Fuster, David Lucca, Stijn Van Nieuwerburgh, and James Vickery
Because mortgages make up the majority of household debt in most developed countries, mortgage design has important implications for macroeconomic policy and household welfare. As one example, most U.S. mortgages have fixed interest rates—if interest rates fall, existing borrowers need to refinance to lower their interest payments. In practice, households are often slow to refinance, or may not be able to do so. As a result, the transmission of U.S. monetary policy is dampened relative to countries like the United Kingdom where mortgage rates on most loans adjust automatically with short-term interest rates. In this post, we discuss some of the key takeaways from a recent conference where policymakers, academics, practitioners, and other experts convened to discuss mortgage design and consider possible mortgage market innovations.
Andrew Haughwout, Donghoon Lee, Joelle Scally, and Wilbert van der Klaauw
Our Consumer Credit Panel, which is based on data from the Equifax credit reporting agency, first arrived at the New York Fed in 2009, and our very first Quarterly Report on Household Debt and Credit was published in August 2010, five years ago this month. We’ve continued to produce the same report, with very few changes, since the report’s initial release. However, with today’s release of the report for the second quarter of 2015, we’re beginning to make some changes, starting with two new charts that provide granularity on mortgage loan originations. These data are identical to the originations data that we’ve released previously, but we now report origination volume by credit score groups. The new charts’ form will be familiar to those who have seen our earlier work on auto loans or the U.S. Economy in a Snapshot, and will leverage some of the detail that we have in our dataset on new extensions of credit and underwriting standards.
My aim in the second post of this series on Thomas Piketty’s Capital in the Twenty-First Century is to talk about the economist’s research accomplishment in reconstructing capital-output ratios for developed countries from the Industrial Revolution to the present and using them to explain why wealth inequality will rise in developed countries. I will then provide a critical discussion of his interpretation of the history of capital in the developed world. Finally, I’ll end by discussing Piketty’s main policy proposal: the global tax on capital.
When a household is looking to buy a home, financial considerations are usually very important. In particular, in deciding “how much house to buy,” a household must ponder how large a down payment it can make at the time of purchase, and also how much it can afford to pay each month. The minimum required down payment and the interest rate on available mortgages (which determines the monthly payment) are key elements in the decision. When these variables change, this likely affects the price a household is willing and able to pay for a home, and thus the housing market overall. However, measuring the strength of these effects is notoriously difficult. In this post, which is based on a recent staff report, we describe a novel approach to measure these effects. We find that a change in down payment requirements tends to have a large effect on housing demand—households’ willingness to pay for a given home—especially for current renters, whereas the effects of a change in the mortgage rate are modest.
The Federal Reserve Bank of New York today released results from its 2015 SCE Housing Survey. The survey, administered to 1,205 U.S. household heads in February, is a follow-up to the one conducted in February 2014. The purpose of the effort is to collect rich and high-quality information on consumers’ experiences and expectations regarding housing. The survey collects data on individuals’ perceptions and expectations of the growth in home prices, intentions regarding moving or buying a new home, and their access to credit, among other things.
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