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.
The Federal Reserve has kept interest rates at historic lows for the last six years, but eventually rates will return to their long-term averages. That means both policymakers and the public will once again be asking one of the classic questions in monetary economics: What are the impacts of rising interest rates on the real economy? Our recent New York Fed staff report “Interest Rates and the Market for New Light Vehicles,” considers this question for the U.S. market for new cars and light trucks. We find strong evidence that rising rates will dampen activity: Our model predicts that in the short-run a 100-basis-point increase in interest rates will cause light vehicle production to fall at an annual rate of 12 percent and sales to fall at an annual rate of 3.25 percent.
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.
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 (11.9.15): A spreadsheet error in the data analysis has raised doubts about some of the conclusions reached in this blog post. Corrections are forthcoming.
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.
The risk of becoming unemployed varies substantially across different groups within the labor market. Although the “headline” unemployment rate draws the most attention from the news media and policymakers, there is rich heterogeneity underlying this overall measure. We delve into the data to describe how unemployment and job loss risk vary with demographics (gender, age, and race), skill (educational attainment), and job characteristics (occupation and earnings).
How much someone earns is an important determinant of many significant decisions over the course of a lifetime. Therefore, understanding how and why earnings are dispersed across individuals is central to understanding dispersion in a wide range of areas such as durable and non-durable consumption expenditures, debt, hours worked, and even health. Drawing on a recent New York Fed staff report "What Do Data on Millions of U.S. Workers Reveal about Life-Cycle Earnings Risks?", this blog post investigates the nature of earnings inequality over a lifetime. It finds that earnings are subject to significant downside risk and that such risk contributes substantially to overall earnings dispersion.
The Federal Reserve’s statutory mission from Congress is to achieve maximum employment and price stability for the country as a whole. In line with this dual mandate, economists at the New York Fed monitor conditions in the “aggregate” economy on a day-to-day basis. But in addition, they have been doing a substantial amount of work to understand the differences in economic experiences across individuals, households, and regions. This blog series will examine our economists’ findings on how labor, housing, and health outcomes vary for different groups. A brief summary of the posts in the series follows:
The October 2015 Business Leaders Survey of regional service firms, released today, paints a considerably more benign picture of local business conditions than the more troubling October 2015 Empire State Manufacturing Survey, released yesterday. The two surveys point to diverging trends in the regional economy: manufacturing firms report that business activity has weakened, on balance, for the third month in a row, while regional service firms, though far from euphoric, remain slightly positive, on balance, about business trends. One of the reasons for this divergence seems to be the strong dollar, which has had negative effects on far more manufacturers than service firms, according to our surveys.
Our experiment in blogging began four years ago, when we launched Liberty Street Economics. Now, with more than 600 posts published, the blog platform has become a central way for us to share our research with a wide audience. To further expand access to the blog, we’re excited to bring readers a new option for keeping up with our work—the Economic Research Tracker for Apple iPad.
Inflation dynamics are often described by some form of the Phillips curve. Named after A. W. Phillips, the British economist whose study of U.K. wage and unemployment data laid the groundwork, the Phillips curve denotes an inverse relationship between inflation and some measure of economic slack. A much-discussed issue in the literature is how forward-looking this relationship is. In this post, we address this question using a flexible version of the New KeynesianPhillips curve (NKPC) to illustrate the key role that expectations play in inflation dynamics.
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