Liberty Street Economics

November 27, 2023

The Nonbank Shadow of Banks

Nicola Cetorelli and Saketh Prazad

Decorative image: Aerial view of money transfer icon over cityscape

Financial and technological innovation and changes in the macroeconomic environment have led to the growth of nonbank financial institutions (NBFIs), and to the possible displacement of banks in the provision of traditional financial intermediation services (deposit taking, loan making, and facilitation of payments). In this post, we look at the joint evolution of banks—referred to as depository institutions from here on—and nonbanks inside the organizational structure of bank holding companies (BHCs). Using a unique database of the organizational structure of all BHCs ever in existence since the 1970s, we document the evolution of NBFI activities within BHCs. Our evidence suggests that there exist important conglomeration synergies to having both banks and NBFIs under the same organizational umbrella.

Posted at 7:00 am in Banks, Nonbank (NBFI) | Permalink

November 21, 2023

The New York Fed DSGE Model Perspective on the Lagged Effect of Monetary Policy

Richard Crump, Marco Del Negro, Keshav Dogra, Pranay Gundam, Donggyu Lee, Ramya Nallamotu, and Brian Pacula

Decorative image: Factory workers on an assembly line with baseball caps on.

This post uses the New York Fed DSGE model to ask the question: What would have happened to interest rates, output, and inflation had the Federal Reserve been following an average inflation targeting (AIT)-type reaction function since 2021:Q2, when inflation began to rise—as opposed to keeping the federal funds rate at the zero lower bound (ZLB) until March 2022, and then raising it aggressively thereafter? We show that actual policy was more accommodative in 2021 than implied by the AIT reaction function and then more contractionary in 2022 and beyond. On net, the lagged effect of monetary policy on the level of GDP, when measured relative to the counterfactual, has been positive throughout the forecast horizon, due to the initial boost associated with keeping the fed funds rate near zero in 2021.

Posted at 7:01 am in DSGE, Monetary Policy | Permalink

A Bayesian VAR Model Perspective on the Lagged Effect of Monetary Policy

Richard Crump, Marco Del Negro, Keshav Dogra, Pranay Gundam, Donggyu Lee, Ramya Nallamotu, and Brian Pacula

Over the last few years, the U.S. economy has experienced unusually high inflation and an unprecedented pace of monetary policy tightening. While inflation has fallen recently, it remains above target, and the economy continues to expand at a robust pace. Does the resilience of the U.S. economy imply that monetary policy has been ineffectual? Or does it reflect that policy acts with “long and variable lags” and so we haven’t yet observed the full effect of the monetary tightening that has already taken place? Using a Bayesian vector autoregressive (BVAR) model, we show that economic activity has, indeed, been substantially stronger than would have been anticipated considering the rapid policy tightening. Still, the model expects a significant slowdown in 2024-25, even though short-term interest rates are forecasted to fall.

Posted at 7:00 am in Forecasting, Macroeconomics, Monetary Policy | Permalink | Comments (1)

November 20, 2023

Banks versus Hurricanes

Peter Anagnostakos, Jason Bram, Benjamin Chan, Natalia Fischl-Lanzoni, Hasan Latif, James M. Mahoney, Don Morgan, Ladd Morgan, and Ivelisse Suarez

Woman looking over the debris left by hurricane of her home in Puerto Rico.

The impacts of hurricanes analyzed in the previous post in this series may be far-reaching in the Second District. In a new Staff Report, we study how banks in Puerto Rico fared after Hurricane Maria struck the island on September 17, 2017. Maria makes a worst case in some respects because the economy and banks there were vulnerable beforehand, and because Maria struck just two weeks after Hurricane Irma flooded the island. Despite the immense destruction and disruption Maria caused, we find that the island’s economy and banks recovered surprisingly quickly. We discuss the various protections—including homeowners’ insurance, federal aid, and mortgage guarantees—that helped buttress the island’s economy and banks.

Posted at 7:00 am in Banks, Climate Change | Permalink

November 17, 2023

Flood‑Prone Basement Housing in New York City and the Impact on Low‑ and Moderate‑Income Renters

Claire Kramer Mills, Ambika Nair, and Julian di Giovanni

Decorative image: Man in front of a house with belongings from flood damage.

Hurricane Ida, which struck New York in early September 2021, exposed the region’s vulnerability to extreme rainfall and inland flooding. The storm created massive damage to the housing stock, particularly low-lying units. This post measures the storm’s impact on basement housing stock and, following the focus on more-at-risk populations from the two previous entries in this series, analyzes the attendant impact on low-income and immigrant populations. We find that basements in select census tracts are at high risk of flooding, affecting an estimated 10 percent of low-income and immigrant New Yorkers.

Posted at 7:00 am in Climate Change, Inequality, New York | Permalink

November 16, 2023

Small Business Recovery after Natural Disasters in the Fed’s Second District

Asani Sarkar

A previous Liberty Street Economics post found that minority-owned small businesses in the Federal Reserve’s Second District have been particularly vulnerable to natural disasters. Here we focus on the aftermath of disasters (such as hurricanes, floods, wildfires, droughts, and winter storms) and examine disparities in the ability of these firms to reopen their businesses and access disaster relief. Our results indicate that while white- and minority-owned firms remain closed for similar durations, the latter are more reliant on external funding from government and private sources to cope with disaster losses.

Posted at 7:00 am in Climate Change, Inequality, New Jersey, New York | Permalink

November 15, 2023

How Do Natural Disasters Affect Small Business Owners in the Fed’s Second District?

Asani Sarkar

Decorative image: Woman walking in flood water to go shopping.

In this post, we follow up on the previous Liberty Street Economics post in this series by studying other impacts of extreme weather on the real sector. Data from the Federal Reserve’s Small Business Credit Survey (SBCS) shed light on how small businesses in the Second District are impacted by natural disasters (such as hurricanes, floods, wildfires, droughts, and winter storms). Among our findings are that increasing shares of small business firms in the region sustain losses from natural disasters, with minority-owned firms suffering losses at a disproportionately higher rate than white-owned firms. For many minority-owned firms, these losses make up a larger portion of their total revenues. In a companion post, we will explore the post-disaster recovery of small firms in the Second District: how long do they remain closed and what are their sources of disaster relief?

Posted at 7:00 am in Climate Change, Demographics, New Jersey, New York | Permalink | Comments (1)

November 14, 2023

Flood Risk and Firm Location Decisions in the Fed’s Second District

Oliver Zain Hannaoui, Hyeyoon Jung, João A.C. Santos, and Lee Seltzer

Photo of long island restaurant near the ocean and bay with people having food and cocktails.

The intensity, duration, and frequency of flooding have increased over the past few decades. According to the Federal Emergency Management Agency (FEMA), 99 percent of U.S. counties have been impacted by a flooding event since 1999. As the frequency of flood events continues to increase, the number of people, buildings, and agriculture exposed to flood risk is only likely to grow. As a previous post points out, measuring the geographical accuracy of such risk is important and may impact bank lending. In this post, we focus on the distribution of flood risk within the Federal Reserve’s Second District and examine its effect on establishment location decisions over the last two decades.

Posted at 7:00 am in Climate Change | Permalink

November 13, 2023

How Do Banks Lend in Inaccurate Flood Zones in the Fed’s Second District?

Kristian S. Blickle, Katherine Engelman, Theo Linnemann, and João A. C. Santos

Photo of blue house in pine woods area flooded with muddy water up to its front door.

In our previous post, we identified the degree to which flood maps in the Federal Reserve’s Second District are inaccurate. In this post, we use our data on the accuracy of flood maps to examine how banks lend in “inaccurately mapped” areas, again focusing on the Second District in particular. We find that banks are seemingly aware of poor-quality flood maps and are generally less likely to lend in such regions, thereby demonstrating a degree of flood risk management or risk aversion. This propensity to avoid lending in inaccurately mapped areas can be seen in jumbo as well as non-jumbo loans, once we account for a series of confounding effects. The results for the Second District largely mirror those for the rest of the nation, with inaccuracies leading to similar reductions in lending, especially among non-jumbo loans.

Posted at 7:00 am in Banks, Climate Change, Credit, Housing, Regional Analysis | Permalink

November 10, 2023

Potential Flood Map Inaccuracies in the Fed’s Second District

Kristian Blickle, Katherine Engelman, Theo Linnemann, and João A.C. Santos

The National Flood Insurance Program (NFIP) flood maps, which designate areas at risk of flooding, are updated periodically through the Federal Emergency Management Agency (FEMA) and community efforts. Even so, many maps are several years old. As the previous two posts in the Extreme Weather series show, climate-related risks vary geographically. It is therefore important to produce accurate maps of such risks, like flooding. In this post we use detailed data on the flood risk faced by individual dwellings as well as digitized FEMA flood maps to tease out the degree to which flood maps in the Second District are inaccurate. Since inaccurate maps may leave households or banks exposed to the risk of uninsured flood damage, understanding map inaccuracies is key. We show that, when aggregated to the census tract level, a large number of maps do not fully capture flood risk. However, we are also able to show that updates do in fact improve map quality.

Posted at 7:00 am in Climate Change, New York, Regional Analysis | Permalink

Markets & Policy Implementation

Liberty Street Economics

The Nonbank Shadow of Banks

The New York Fed DSGE Model Perspective on the Lagged Effect of Monetary Policy

A Bayesian VAR Model Perspective on the Lagged Effect of Monetary Policy

Banks versus Hurricanes

Flood‑Prone Basement Housing in New York City and the Impact on Low‑ and Moderate‑Income Renters

Small Business Recovery after Natural Disasters in the Fed’s Second District

How Do Natural Disasters Affect Small Business Owners in the Fed’s Second District?

Flood Risk and Firm Location Decisions in the Fed’s Second District

How Do Banks Lend in Inaccurate Flood Zones in the Fed’s Second District?

Potential Flood Map Inaccuracies in the Fed’s Second District

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