The New York Fed DSGE Model Forecast—May 2017

Ozge Akinci, Marco Del Negro, Abhi Gupta, Pearl Li, and Erica Moszkowski

This post presents our quarterly update of the economic forecasts generated by the Federal Reserve Bank of New York’s dynamic stochastic general equilibrium (DSGE) model. We describe very briefly our forecast and its change since February 2017. As usual, we wish to remind our readers that the DSGE model forecast is not an official New York Fed forecast, but only an input to the Research staff’s overall forecasting process. For more information about the model and variables discussed here, see our DSGE Model Q & A.

Dealer Balance Sheets and Corporate Bond Liquidity Provision

Tobias Adrian, Nina Boyarchenko, and Or Shachar



Regulatory reforms since the financial crisis have sought to make the financial system safer and severe financial crises less likely. But by limiting the ability of regulated institutions to increase their balance sheet size, reforms—such as the Dodd-Frank Act in the United States and the Basel Committee's Basel III bank regulations internationally—might reduce the total intermediation capacity of the financial system during normal times. Decreases in intermediation capacity may then lead to decreased liquidity in markets in which the regulated institutions intermediate significant trading activity. While recent commentary by market participants claims that this is indeed the case—a Wall Street Journal article [subscription required] notes that “three-quarters of institutional bond investors say that liquidity provided by bond dealers has declined in the past year...”—empirical studies have struggled to find evidence supporting this narrative. In this post, we summarize the findings of our recent article in the Journal of Monetary Economics that addresses the apparent disconnect between the market-participant commentary and the empirical evidence by focusing on the relationship between bond-level liquidity and financial institutions’ balance sheet constraints.

Measuring Trend Inflation with the Underlying Inflation Gauge

Marlene Amstad, Simon Potter, and Robert Rich



Consumers, financial market participants, and policymakers are particularly interested in the trend, or persistent, component of inflation. But this variable is not observed, which has resulted in a variety of proposed proxy measures. Because each measure has its own strengths and weaknesses, a consensus about a preferred candidate has not emerged. Here, we introduce the Underlying Inflation Gauge (UIG) as a measure of trend inflation. Among its attractive features, the UIG is derived from a large data set that extends beyond price variables and displays greater forecast accuracy than various measures of core inflation.

Hey, Economist! Is Now a Good Time to Be Graduating from College?

A Conversation with Jaison R. Abel and Richard Deitz



With the 2017 college graduation season in full swing, we thought it would be helpful to take stock of the job prospects for recent college graduates. Is now a good time to be graduating from college? Publications editor Trevor Delaney caught up with Jaison Abel and Richard Deitz, two economists in our Research and Statistics Group, to discuss some of their work on the labor market for recent college graduates.

Household Borrowing in Historical Perspective

Andrew Haughwout, Donghoon Lee, Joelle Scally, and Wilbert van der Klaauw



Today, the New York Fed’s Center for Microeconomic Data released its Quarterly Report on Household Debt and Credit for the first quarter of 2017. The report shows a rise in household debt balances in the quarter of $149 billion, the eleventh consecutive quarterly increase since the long period of deleveraging following the Great Recession. As of March 31, 2017, household debt balances stood at $12.73 trillion, surpassing the previous 2008 peak and hitting a level 14 percent above the trough seen in the second quarter of 2013. With this report’s release, we’re adding two new charts which show both early and severe delinquency trends by loan product type. The report and the analyses presented here are based on the New York Fed’s Consumer Credit Panel (CCP), which is sourced from Equifax credit report data.

Do Credit Markets Watch the Waving Flag of Bankruptcy?

Paul Goldsmith-Pinkham

Personal bankruptcy is surprisingly common in the United States. Almost 15 percent of the U.S. population has filed for bankruptcy sometime over the past twenty-five years, based on my calculations using the New York Fed Consumer Credit Panel/Equifax (CCP). In 2015, roughly 800,000 debtors filed for bankruptcy, according to court records, representing 0.64 percent of U.S. households. One of the consequences for filers is a mark on their credit report—a bankruptcy “flag”—which indicates that the consumer has filed for bankruptcy.

At the N.Y. Fed: The Evolution of OTC Derivatives Markets

Nina Boyarchenko, Or Shachar, and Jacqueline Yen



The 2007-09 financial crisis highlighted weaknesses in the over‑the‑counter (OTC) derivatives markets and the increased risk of contagion due to the interconnectedness of market participants in these markets. As a response, the global regulatory community introduced a number of reforms to both the market structure and the regulatory environment. The intent of these innovations was to improve the functioning of OTC markets but some market participants have suggested that some of the new regulations may have had unintended consequences. In this post, we discuss some key takeaways from a recent two-day conference on “Over‑the‑Counter Derivatives and Recent Regulatory Changes,” where policymakers, academics, practitioners, and other experts convened to discuss the evolution of OTC derivatives markets after the crisis.

Just Released: 2017 SCE Housing Survey Finds Increased Optimism about Home Price Growth

Andreas Fuster, Basit Zafar, and Nima Dahir



The Federal Reserve Bank of New York’s 2017 SCE Housing Survey indicates that expected home price growth over the next year has increased compared with twelve months earlier, and is at its highest level since the survey’s inception in 2014. Five-year growth expectations have also risen, albeit more modestly. In line with these findings, the majority of households continue to view housing as a good investment. Respondents expect slightly larger increases in mortgage rates than they did in last year’s survey. Renters’ perceived access to mortgage credit continued to ease.

Which Dealers Borrowed from the Fed’s Lender-of-Last-Resort Facilities?

Viral V. Acharya, Michael J. Fleming, Warren B. Hrung, and Asani Sarkar



During the 2007-08 financial crisis, the Fed established lending facilities designed to improve market functioning by providing liquidity to nondepository financial institutions—the first lending targeted to this group since the 1930s. What was the financial condition of the dealers that borrowed from these facilities? Were they healthy institutions behaving opportunistically or were they genuinely distressed? In published research, we find that dealers in a weaker financial condition were more likely to participate than healthier ones and tended to borrow more. Our findings reinforce the importance of Bagehot’s principle that the lender-of-last resort should lend only against high-quality collateral and at a penalty rate so as to discourage unneeded or opportunistic borrowing.

Forecasting with Julia

Abhi Gupta, Pearl Li, Erica Moszkowski, Marco Del Negro, and Marc Giannoni

A little more than a year ago, in this post, we announced DSGE.jl—a package for working with dynamic stochastic general equilibrium (DSGE) models using Julia, the open-source computing language. At that time, DSGE.jl contained only the code required to specify, solve, and estimate such models using Bayesian methods. Now, we have extended the package to provide the additional code needed to produce economic forecasts, counterfactual simulations, and inference on unobservable variables, such as the natural rate of interest or the output gap. The old, pre-Julia version of the code, which was written in MATLAB and is posted here on Github, a public repository hosting service, also performed some of these functions, but not quite as fast.