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We theoretically and empirically investigate how climate risks affect collateralized debt markets. First, we develop a debt model where agents have different beliefs over a long-run risk. In contrast with existing two-period competitiveequilibrium models, our infinite-horizon competitive-search model predicts more pessimistic agents are more likely to make leveraged investments on risky collateral assets. They also tend to use longer maturity debt contracts, which are more exposed to the long-run risk. Second, employing large data on real estate and mortgage transactions, combined with high resolution sea-level-rise maps, we find robust evidence for these findings. We also show how monetary and securitization policies affect mortgage climate risk exposure. Our results highlight the importance of heterogeneous beliefs in understanding the effects of climate change on the financial system. [ABSTRACT FROM AUTHOR]

One of the main channels through which monetary policy stimulus affects the real economy is mortgage borrowing. This channel, however, is weakened by frictions in the mortgage market. The rapid growth of financial technology-based (FinTech) lending tends to ease these frictions, given the higher quality services provided under this new lending model. This paper establishes that the role of FinTech lending in the monetary policy transmission is further amplified by consumers' social networks. I provide empirical evidence for this network effect using county-level data and novel identification strategies. A 1 pp increase in the FinTech market share in a county's socially connected markets raises the county's FinTech market share by 0.23-0.26 pps. Moreover, I find that in counties where FinTech market penetration is high, the pass-through of market interest rates to borrowers is more complete. To quantify the role of FinTech lending and its network propagation in the transmission of monetary policy shocks, I build a multi-region heterogeneous-agent model with social learning that embodies key features of FinTech lending. The model shows that the responses of consumption and refinancing to a monetary stimulus are 13% higher in the presence of FinTech lending. Almost half of this improvement is accounted for by FinTech propagation through social networks. [ABSTRACT FROM AUTHOR]

We study the role of mortgage servicers in implementing the CARES Act mortgage forbearance program during the COVID-19 pandemic. Despite universal eligibility, around one-third of the nonperforming federally-backed loans in our sample fail to enter into forbearance. The relative frequency of these "missing" forbearances varies significantly across servicers for observably similar loans, with small servicers and nonbanks, and especially nonbanks with small liquidity buffers, having a lower propensity to provide forbearance. The incidence of forbearance-related complaints by borrowers is also higher for these servicers. We also use servicer-level variation to estimate the causal effect of forbearance on borrower outcomes. Assignment to a "high-forbearance" servicer translates to a significant increase in the probability of nonpayment, which moves essentially 1:1 with the forbearance probability. Part of this additional household liquidity is used to pay down high-cost credit card debt. [ABSTRACT FROM AUTHOR]

We study the evolution of USmortgage credit supply during the COVID-19 pandemic. Although the mortgage market experienced a historic boom in 2020, we show there was also a large and sustained increase in intermediation markups that limited the pass-through of lowrates to borrowers. Markups typically rise during periods of peak demand, but this historical relationship explains only part of the large increase during the pandemic. We present evidence that pandemic-related labor market frictions and operational bottlenecks contributed to unusually inelastic credit supply, and that technology-based lenders, likely less constrained by these frictions, gained market share. Rising forbearance and default risk did not significantly affect rates on "plainvanilla" conforming mortgages, but it did lead to higher spreads on mortgages without government guarantees and loans to the riskiest borrowers. Mortgage-backed securities purchases by the Federal Reserve also supported the flow of credit in the conforming segment. [ABSTRACT FROM AUTHOR]

The goal of this paper is to show that household-level financial distress (FD) varies greatly, meaning there is unequal exposure to macroeconomic risk, and that FD can increase macroeconomic vulnerability. To do this, we first establish three facts: (i) regions in the U.S. vary significantly in their "FD-intensity," measured either by how much additional credit households therein can access, or in how delinquent they typically are on debts, (ii) shocks that are typically viewed as "aggregate" in nature hit geographic areas quite differently, and (iii) FD is an economic "pre-existing condition": the share of an aggregate shock borne by a region is positively correlated with the level of FD present at the time of the shock. Using an empirically disciplined and institutionally rich model of consumer debt and default, we show that in the shocks dealt by the Great Recession and in the initial months in the COVID-19 pandemic, FD mattered. Our model implies that the uneven distribution of FD creates widely varying consumption responses to shocks. This is true even when subjecting regions (with differing levels of FD) to the same shocks, which highlights the importance of FD independently of its correlation with shocks. [ABSTRACT FROM AUTHOR]

The goal of this paper is to show that household-level financial distress (FD) varies greatly, meaning there is unequal exposure to macroeconomic risk, and that FD can increase macroeconomic vulnerability. To do this, we first establish three facts: (i) regions in the U.S. vary significantly in their "FD-intensity," measured either by how much additional credit households therein can access, or in how delinquent they typically are on debts, (ii) shocks that are typically viewed as "aggregate" in nature hit geographic areas quite differently, and (iii) FD is an economic "pre-existing condition": the share of an aggregate shock borne by a region is positively correlated with the level of FD present at the time of the shock. Using an empirically disciplined and institutionally rich model of consumer debt and default, we show that in the shocks dealt by the Great Recession and in the initial months in the COVID-19 pandemic, FD mattered. Our model implies that the uneven distribution of FD creates widely varying consumption responses to shocks. This is true even when subjecting regions (with differing levels of FD) to the same shocks, which highlights the importance of FD independently of its correlation with shocks. [ABSTRACT FROM AUTHOR]

During the Great Recession, the collapse of consumption across the U.S. varied greatly but systematically with house-price declines. We find that financial distress among U.S. households amplified the sensitivity of consumption to house-price shocks. We uncover two essential facts: (1) the decline in house prices led to an increase in household financial distress prior to the decline in income during the recession, and (2) at the zip-code level, the prevalence of financial dis- tress prior to the recession was positively correlated with house-price declines at the onset of the recession. Using a rich-estimated-dynamic model to measure the financial distress channel, we find that these two facts amplify the aggregate drop in consumption by 7 percent and 45 percent respectively. [ABSTRACT FROM AUTHOR]

Does advertising help consumers to find the products they need or push them to buy products they don't need? In this paper, we study the effects of advertising on consumer mistakes and quantify the resulting effect on consumer welfare in the market for mortgage refinancing. Mortgage borrowers frequently make costly refinancing mistakes by either refinancing when they should wait, or by waiting when they should refinance. We assemble a novel data set that combines a borrower's exposure to direct mail refinance advertising and their subsequent refinancing decisions. Even though on average borrowers would lose approximately $500 by refinancing, the average monthly exposure of 0.23 refinancing advertisements reduces the expected net present value of mortgage payments on average by $13, because borrowers who should refinance are targeted by advertisers and more responsive to advertising. A counterfactual advertising policy that redirects all advertising to borrowers who should refinance would increase the gain in borrower welfare to $45. [ABSTRACT FROM AUTHOR]

In this paper, we document that mortgage-backed securities (MBS) held by the Federal Reserve exhibit faster principal prepayment rates than MBS held by the rest of the market. Next, we show that this stylized fact persists even when controlling for factors that affect prepayment behavior, and thus determine the MBS that are delivered to the Federal Reserve. After ruling out several potential explanations for this result, we provide evidence that points to an agency problem in the secondary market for MBS, which has not previously been documented, as the most likely explanation for the abnormal prepayment behavior of Federal Reserve-held MBS. This agency problem—a key feature of the MBS market—arises when originators of mortgages that underlie the MBS no longer share in the prepayment risk of the securities, thereby increasing incentives to solicit refinancing activity. Therefore, Federal Reserve MBS holdings acquired from originators as a result of large-scale asset purchases can help stimulate economic activity through a so-called "solicited refinancing channel." Finally, we provide an estimate of the additional refinancing activity resulting from the solicited refinancing channel in the years after the Federal Reserve's first MBS purchase program, demonstrating that this channel conveyed savings on monthly mortgage payments to homeowners. [ABSTRACT FROM AUTHOR]

We incorporate house price risk and mortgages into a standard incomplete market (SIM) model. We calibrate the model to match U.S. data, and we show that the model also accounts for non-targeted features of the data such as the distribution of down payments, the life-cycle profile of homeownership, and the mortgage default rate. In addition, we show that the average coefficients that measure the agents' ability to self-insure against income shocks are similar to those of a SIM model without housing (as presented by Kaplan and Violante, 2010). However, incorporating housing increases the values of these coefficients for younger agents, which narrows the gap between the SIM model's implications and the data. The response of consumption to house price shocks is minimal. We also study the e ects of default prevention policies. Introducing a minimum down payment requirement of 15 percent reduces defaults on mortgages by 30 percent, reduces the homeownership rate up to only 0.2 percentage points (if the aggregate house price level does not adjust), and may cause house prices to decline up to 0.7 percent (if homeownership does not adjust). Garnishing defaulters' income in excess of 43 percent of median consumption for one year produces a similar decline in defaults; but, since it reduces the median equilibrium down payment from 19 percent to 9 percent, it boosts homeownership up to 4.3 percentage points (if the aggregate house price level does not adjust) and may increase house prices up to 16.1 percent (if homeownership does not adjust). The introduction of minimum down payments or income garnishment benefit a majority of the population. [ABSTRACT FROM AUTHOR]