Lara Loewenstein

A significant share of commercial real estate (CRE) investment properties—about half by our estimates—are purchased without a mortgage. Using comprehensive microdata on transactions in the US CRE market, we analyze which types of properties are purchased without a mortgage, highlighting the important role of renovation or redevelopment options. We show that mortgage-financed properties are less likely to be subsequently redeveloped, and that owners anticipate these redevelopment frictions and avoid mortgage financing for properties with greater redevelopment options. These effects were even stronger during the COVID-19 pandemic, when uncertainty increased redevelopment option values.

We use microdata on the phases of commercial construction projects to document three facts regarding time-to-plan lags: (1) plan times are long—about 1.5 years—and highly variable, (2) roughly 40 percent of projects are abandoned in planning, and (3) property price appreciation reduces the likelihood of abandonment. We construct a model with endogenous planning starts and abandonment that matches these facts. The model has the testable implication that supply is more elastic when there are more "shovel ready" projects available to advance to construction. We use local projections to validate that this prediction holds in the cross-section for US cities.

Rent measurement determines 32 percent of the CPI. Accurate rent measurement is therefore essential for accurate inflation measurement, but the CPI rent index often differs from alternative measures of rent inflation. Using repeat-rent inflation measures created from CPI microdata, we show that this discrepancy is largely explained by differences in rent growth for new tenants relative to all tenants. New-tenant rent inflation provides information about future all-tenant rent inflation, but the use of new-tenant rents is contraindicated in a cost-of-living index such as the CPI. Nevertheless, policymakers should integrate new-tenant inflation into inflation forecasts and monetary policy decisions.

We study the joint evolution of prices and rents of residential property. We construct indices for both rents and prices of renter-occupied properties and for prices of owner-occupied properties. We then decompose the change in the price of occupant-owned property into three components: (1) changes in rent, (2) changes in the relative prices of investor- and occupant-owned properties, and (3) changes in the price-rent ratio. We use a simple model to link our decomposition to different sources of variation in house prices. We argue that while the 2000s boom was plausibly driven by exuberant expectations, the boom of the 2020s more likely resulted from a preference shock.

Prominent rent growth indices often give strikingly different measurements of rent inflation. We create new indices from Bureau of Labor Statistics (BLS) rent microdata using a repeat-rent index methodology and show that this discrepancy is almost entirely explained by differences in rent growth for new tenants relative to the average rent growth for all tenants. Rent inflation for new tenants leads the official BLS rent inflation by four quarters. As rent is the largest component of the consumer price index, this has implications for our understanding of aggregate inflation dynamics and guiding monetary policy.

Banks modify more CRE loans than CMBS, contributing to better loan performance when property incomes decline. However, banks have higher delinquency rates for less-stressed loans, consistent with modification policies encouraging strategic default. Motivated by these facts, we develop a tradeoff theory model in which lenders vary in their modification technologies. Modification frictions discourage strategic renegotiation, enabling CMBS to offer higher LTV loans and attract borrowers seeking higher leverage. The model produces cross-lender differences in LTVs and spreads consistent with the data. Reducing modification frictions at CMBS decreases welfare by restricting debt capacity for the borrowers that value it most.

We study the role that recourse plays in the commercial real estate loan contracts of the largest U.S. banks. We find that recourse is valued by lenders and is treated as a substitute for conventional equity. At origination, recourse loans have rate spreads that are at least 20 basis points lower and loan-to-value ratios that are around 3 percentage points higher than non-recourse loans. Dynamically, recourse affects loan modification negotiations by providing additional bargaining power to the lender. Recourse loans were half as likely to receive accommodation during the COVID-19 pandemic, and the modifications that did occur entailed a relatively smaller reduction in payments.

Mortgage borrowers who have experienced employment disruptions as a result of the COVID-19 pandemic are unable to refinance their loans to take advantage of historically low market rates. In this article, we analyze the effects of a streamlined refinance (“refi”) program for government-insured loans that would allow borrowers to refinance without needing to document employment or income. In addition, we consider a cash-out component that would allow borrowers to extract some of the substantial housing equity that many have accumulated in recent years.

In this paper, we use two comprehensive micro datasets to study the evolution of the distribution of mortgage debt during the 2000s housing boom. We show that the allocation of mortgage debt remained stable, as did the distribution of real estate assets. We propose that any theory of the boom must replicate this fact. Using a general equilibrium model, we show that this requires two elements: (1) an exogenous shock to the economy that increases expected house price growth or, alternatively, reduces interest rates and (2) financial markets that endogenously relax constraints in response to the shock. The role played by subprime mortgage debt provides additional empirical evidence that this narrative mirrors reality.

The application of information technology to finance, or “fintech,” is expected to revolutionize many aspects of borrowing and lending in the future, but technology has been reshaping consumer and mortgage lending for many years. During the 1990s computerization allowed mortgage lenders to reduce loan-processing times and largely replace human-based assessment of credit risk with default predictions generated by sophisticated empirical models. Debt-to-income ratios at origination add little to the predictive power of these models, so the new automated underwriting systems allowed higher debt-to-income ratios than previous underwriting guidelines would have typically accepted. In this way, technology brought about an exogenous change in lending standards, which helped raise the homeownership rate and encourage the conversion of rental properties to owner-occupied ones, but did not have large effects on housing prices. Technological innovation in mortgage underwriting may have allowed the 2000s housing boom to grow, however, because it enhanced the ability of both borrowers and lenders to act on optimistic beliefs about future house-price growth.

We compare the current US house-price boom to the 2000–2006 house-price boom, highlighting important similarities and differences in housing and mortgage market conditions.

Women’s labor force participation in the US is persistently below that of men’s. This Commentary describes three contributors to this divide.

The guarantee of mortgage forbearance provided in the CARES Act is an unprecedented provision of flexibility for government-insured mortgage borrowers and has been successful thus far at limiting delinquencies during the COVID-19 pandemic. The terms of this forbearance are favorable to borrowers, and there is little required in terms of documentation of hardship, making requesting forbearance an attractive option even if borrowers are not facing hardship and do not need forbearance to remain current on a mortgage. Despite this, evidence indicates that so far CARES Act forbearance has largely been used by borrowers who did actually need it. The success of forbearance in providing households liquidity and in reducing mortgage delinquencies, and its many potential benefits relative to foreclosure in terms of aligning incentives among the borrower, lender, and neighboring homeowners, raises questions for how policymakers should approach mortgage policy during the next economic downturn and about how mortgage contracts are designed.

In March 2020, in the early days of the COVID-19 pandemic, many were concerned about the liquidity of nonbank mortgage servicers. As it turned out, the vast majority of these servicers did not face a liquidity crisis. In this Commentary I detail the reasons why, including lower than expected take up rates of forbearance, the role played by mortgage origination income, and the actions taken by the government-sponsored enterprises, Ginnie Mae, and housing agencies.

During the 2000s housing bust, Cleveland’s Slavic Village was dubbed “ground zero of the foreclosure crisis” by the national media. Despite this, during the preceding housing boom Cleveland had stable house price growth and relatively low mortgage debt growth, a stark contrast to circumstances in areas such as California that had exceptionally high house price and mortgage debt growth. What explains the relatively minor housing boom and perceived sharp downturn in Cleveland? In this Commentary I show that while subprime debt was a prominent source of debt in Cleveland and especially in its Slavic Village neighborhood during the 2000s, it is difficult to peg subprime debt as playing a causal role in the subsequent foreclosure crisis.