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Today, the Federal Reserve Bank of New York is hosting the spring meeting of its Economic Advisory Panel (EAP). As has become the custom at this meeting, the New York Fed’s Research staff is presenting its forecast for U.S. growth, inflation, and the unemployment rate. Following the presentation, members of the EAP, which consists of leading economists in academia and the private sector, are asked to critique the staff forecast. Such feedback helps the staff evaluate the assumptions and reasoning underlying its forecast as well as the forecast’s key risks. The feedback is also an important part of the forecasting process because it informs the staff’s discussions with New York Fed President William Dudley about economic conditions. In that same spirit, we are sharing a short summary of the staff forecast in this post; for more detail, see the New York Fed Staff Outlook Presentation from the EAP meeting on our website.
President Trump announced a new tariff of 25 percent on steel imports and 10 percent on aluminum imports on March 8, 2018. One objective of these tariffs is to protect jobs in the U.S. steel industry. They were introduced under a rarely used 1962 Act, which allows the government to impose trade barriers for national security reasons. Although the tariffs were initially to apply to all trading partners, Canada and Mexico are currently exempt subject to NAFTA negotiations, and implementation of the tariffs for the European Union, Argentina, Australia, and Brazil has been paused. South Korea has received a permanent exemption from the steel tariffs and will instead be subject to a quota of 70 percent of its current average steel exports to the United States. In this post, we consider how the steel tariffs could affect U.S. trade and employment. We focus on steel since the steel industry employs about three times as many workers as the aluminum industry, although qualitatively our conclusions apply to both. We argue that the new tariffs are likely to lead to a net loss in U.S. employment, at least in the short to medium run.
Andreas Fuster, Andrew F. Haughwout, Nima Dahir, and Michael Neubauer
Home price growth expectations remained stable relative to last year, according to the Federal Reserve Bank of New York’s 2018 SCE Housing Survey. Respondents expect mortgage rates to rise over the next year, and perhaps as a result, the share of owners who expect to refinance their mortgages over the next year declined slightly. In addition, homeowners view themselves as more likely to make investments in their homes, and renters’ perceived access to mortgage credit has tightened somewhat. Although the majority of households continue to view housing as a good financial investment, there are some persistent and large differences across regions in the pervasiveness of this view, as this post will discuss.
The European Central Bank (ECB)’s marginal lending facility has been used by banks to borrow funds both in normal times and during the crisis that started in 2007. In this post, we argue that how a central bank communicates the purpose of a facility is important in determining how users of the facility are perceived. In particular, the ECB never refers to the marginal lending facility as a back-up source of funds. The ECB’s neutral approach may be a key factor in explaining why financial institutions are less reluctant to use the marginal lending facility than the Fed’s discount window.
Editor's note: This post has been corrected to reflect that the limit on itemized deductions of state and local taxes for individuals is now $10,000 (not $5,000, as originally stated) and the limit on the mortgage interest deduction for individuals is now $750,000 (not $375,000). These errors did not affect the authors’ conclusions since their analysis concerns the impact of the new tax code with respect to a married couple.
The Tax Cuts and Jobs Act of 2017 (TCJA) introduces significant changes to the federal income tax code for individuals and businesses. Several provisions of the new tax law are particularly significant for the owner‑occupied housing market. In this blog post, we compare the federal tax liability and the marginal after-tax cost of mortgage interest and property taxes under the old and new tax codes for a wide range of hypothetical recent home buyers in a high tax state. We find that impacts vary substantially along the income/home price distribution.
Tobias Adrian, Nina Boyarchenko, and Domenico Giannone
Traditional GDP forecasts potentially present an overly optimistic (or pessimistic) view of the state of the economy: by focusing on the point estimate for the conditional mean of growth, such forecasts ignore risks around the central forecast. Yet, policymakers around the world increasingly focus on risks to the central forecast in policy debates. For example, in the United States the Federal Open Market Committee (FOMC) commonly discusses the balance of risks in the economy, with the relative prominence of this discussion fluctuating with the state of the economy. In a recent paper, we propose a method for constructing the full conditional distribution of GDP projected growth as a function of current economic and financial conditions. This blog post reviews some of the findings from that paper and the implications for macroeconomic theory and for policymakers.
R. Jason Faberman, Thomas Haasl, Andreas I. Mueller, Ayşegül Şahin, and Giorgio Topa
In a previous post, we examined the job search behavior of workers, both on the job and while unemployed. We found that job seeking is pervasive among employed workers, and that searching while employed is more effective than searching while unemployed in producing employer contacts and job offers. But how do the offers received through “on the job” searches compare to those received while unemployed? What do their wages look like, how do they compare in terms of nonwage benefits, and how much bargaining between employers and job applicants is involved? In this post, we shed some light on how job offers may vary depending on the employment status of the job seeker.
The recent U.S. housing crisis featured explosive growth and collapse of house prices at the national level, with substantial boom-bust pattern variation at the local level. What is less commonly known in the housing market is the behavior of housing quantities. While measures of supply and inventory play an important role in understanding markets, quantity data in housing is traditionally limited to national aggregates. Using a rich new data set of homes listed for sale across a wide range of U.S. housing markets, this post explores whether the collapse in prices from 2006 to 2009 owed more to a flood of houses on the market (higher supply) or a dearth of sales (lower demand).
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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