Financial Regulation

The modern financial system features complicated financial intermediation chains, with each layer performing a certain degree of credit/maturity transformation. We develop a dynamic model in which an entrepreneur borrows from overlapping-generation households via layers of funds, forming a credit chain. Each intermediary fund in the chain faces rollover risks from its lenders, and the optimal debt contracts among layers are time invariant and layer independent. The model delivers new insights regarding the benefits of intermediation via layers: the chain structure insulates interim negative fundamental shocks and protects the underlying cash flows from being discounted heavily during bad times, resulting in a greater borrowing capacity. We show that the equilibrium chain length minimizes the run risk for any given contract and find that restricting credit chain length can improve total welfare once the available funding from households has been endogenized.

Real estate values are often under-reported to avoid transaction and property taxes, and to hide wealth built from tax-evaded income. We develop a new method to extract estimates of under-reporting, and employ this measure in the Mumbai real estate market. This approach compares the bunching of reported property values around government-assessed guidance values with a third-party measure of true underlying transactions prices. We estimate that 13 percent of value in Mumbai real estate is under-reported between 2013 and 2018. Measured under-reporting spikes immediately before increases to government-assessed values, and properties with mortgages from public-sector banks and banks with high non-performing assets exhibit more visible evidence of under-reporting.

Privately issued money usually bears devaluation risk that lowers it liquidity and usefulness as a medium of exchange. We evaluate the real economic consequences of eliminating devaluation risk and increasing the safety of private monies in the historical context of the National Banking Act of 1864 in the United States. The Act introduced a new type of federally-regulated bank that supplied safe currency to the local economy as an alternative to the previously existing varieties of unsecured notes. Towns faced a discontinuous cost in accessing these banks, which we leverage as a source of exogenous variation in the change in their monetary transaction costs. We estimate the effects of gaining access to safe private money using a market access approach derived from general equilibrium trade theory, and we find that lowering monetary transaction costs shifted agricultural production to trade-cost sensitive goods, and it increased manufacturing output, the manufacturing output share, and the urban population share. These effects are all consistent with safer money lowering overall trade costs to promote structural transformation and economic development.

We study how financial development affects economic development and wage inequality. We use a large expansion of government-owned banks into Brazilian cities with low bank branch coverage and combine it with data on the universe of employees from 2000–2014. We find that higher financial development fosters firm growth, higher labor demand, and higher average wages, especially for cities initially in banking deserts. However, these gains are not shared equally. Instead, they increase with workers’ productivity, implying a substantial increase in wage inequality. The changes to inequality are concentrated in cities where the initial supply of skilled workers is low, indicating that talent scarcity can drive how financial development affects inequality. Our results are inconsistent with alternative explanations such as differential exposure to Brazil’s economic boom, an overall increase in government lending, and other government or social welfare programs. These results motivate embedding skill heterogeneity into macro-finance development models in order to capture these distributional consequences.

We document substantial racial disparities in consumer bankruptcy and investigate the role of racial bias in contributing to these disparities. Using data on the universe of US bankruptcy cases and deep-learning imputed measures of race, we show that Black filers are more likely to have their bankruptcy cases dismissed without any debt relief. Large disparities persist for Chapter 13 bankruptcy after controlling for a wide array of individual characteristics. We uncover strong evidence for racial bias driven by homophily: Black filer outcomes in Chapter 13 are less favorable when randomly assigned to a white bankruptcy trustee. To interpret our findings, we develop new identification results that characterize when and how homophily can partially identify the share of observable disparities due to bias.

We highlight the role of financial constraints in contributing to persistent disparities in wealth and access to geographic opportunities across demographic groups. We document a racial leverage gap—Black borrowers have substantially higher LTV ratios at mortgage origination, reflecting differences in pre-existing wealth and family transfers. We use a spatial life-cycle model to analyze the impacts of worse initial conditions on the home purchase decisions, spatial allocation, and long-term wealth accumulation of minority borrowers. Wealth and income outcomes for Black borrowers are substantially improved by relaxing LTV constraints and reducing moving frictions.

Defined contribution (DC) plans are a major vehicle for retirement savings in the US, holding almost $10 trillion in assets under management. In recent years, the quality and availability of these plans has been the subject of active policy attention and of several major lawsuits. This paper studies how employers and plan providers (recordkeepers) design these plans. We argue that low plan quality and limited provision can come from two sources. First, employer willingness to pay may be misaligned with that of workers or of regulators. Second, the market for recordkeeping may be imperfectly competitive. We propose a model of plan design and estimate that while both frictions are at play, significant changes to plan quality require modifying employer preferences. Accordingly, we evaluate proposed policies and conclude that only direct quality regulation can lead to significant quality improvements. Recent proposals can increase plan provision but have negligible quality effects.

We investigate how macro prudential policies intended to dampen rises in debt and house prices are influenced by segmentation in the mortgage market. We develop a modeling framework with two mortgage submarkets: a government-insured sector with loose LTV limits and tight PTI limits, and an uninsured sector displaying the reverse pattern. This form of heterogeneity is modeled after the Canadian mortgage system, but is common in countries around the world, including the United States. This multi-market structure implies that house prices are much more responsive to increases in latent demand, allowing for larger booms. While tightening payment-to income (PTI) limits is highly effective at dampening a housing boom in a one-sector system, tightening these limits in the insured sector only is much weaker, due to substitutions into the uninsured sector. In contrast, the effect of tightening loan-to-value (LTV) limits in the uninsured sector is strengthened by market segmentation, causing price-rent ratios to fall, while the same tightening in the insured sector would counterproductively cause price-rent ratios to rise.

Standard theory implies that the discount rates used by firms in investment decisions play a key role in determining investment and in transmitting shocks to asset prices and interest rates to the real economy. However, there exists little evidence on how corporate discount rates change over time and affect investment. We construct a new global database of firms’ discount rates based on manual entry from earnings conference calls. We show that corporate discount rates move with the cost of capital, but the relationship is less than one-to-one, leading to time-varying wedges between discount rates and the cost of capital. The average discount rate wedge has increased substantially over the last decades as the cost of capital has dropped. Discount rate wedges are negatively related to future investment, with a magnitude close to that predicted by theory. Moreover, the large and growing discount rate wedges can account for low investment (relative to high asset prices) in recent decades. We find important roles for risk and market power in explaining levels and trends in discount rate wedges.

We document new patterns in investment behavior using a comprehensive dataset of 401(k) plans from 2009 through 2019. We show that there is substantial heterogeneity in asset allocation across plans, and that these differences are systematically predictable by sector of employment and demographic characteristics. For example, higher income and education is associated with more exposure to equities, while a greater share of minorities and retirees is associated with less equity exposure. These patterns cannot be rationalized by differences in investment options or plan participation. To understand observed investment behavior, we use a revealed preference approach that allows us to recover heterogeneity in investors’ (subjective) expectations and risk preferences. We find that differences in expectations play an important role in explaining portfolios. Further, we show that investors appear to form expectations based on local sources of information such as county-level GDP growth, home prices, and employer past performance. Overall, our findings are consistent with a model in which heterogeneity in investor expectations reflects idiosyncratic experiences and local environments.

This paper examines the impact of dynamic pricing regulation on market outcomes and social welfare in the U.S. long-term care insurance (LTCI) market. We first provide descriptive evidence that the introduction of rate stability regulation, which limits insurers’ ability to increase premiums over the lifetime of a contract, improved rate stability while reducing product variety. To quantify this trade-off, we develop and estimate a dynamic equilibrium model of LTCI where insurers have market power and cannot commit to future premiums. Our estimates suggest that consumers’ demand for LTCI is relatively price inelastic. However, insurers do not charge a high markup due to various pricing regulations. Using the estimated model, we conduct counterfactual experiments to assess the welfare effect of dynamic pricing regulation. We find that a stricter rate stability regulation lowers social welfare as the benefit from improved rate stability is outweighed by the cost from reduced product variety.

This papers studies how banks compete amid digital disruption and resulting distributional effects on financial inclusion. Using survey data, we document that digital consumers (younger, more-educated and higher-income) have adapted to mobile banking, whereas non-digital consumers still heavily rely on brick-and-mortar branches. We build a model of bank competition with endogenous branching and entry decisions to show that the shift of digital consumers’ preference from branch to digital services affects how banks compete which results in negative spillovers to non-digital consumers. We empirically test the model predictions by exploiting the staggered expansion of 3G networks across the U.S., and our identification strategies rely on difference-in-differences and instrumental-variable (the frequency of lightning strikes) analyses. We find that (1) banks close costly branches, especially in regions with more young people; (2) banks enter new markets with fewer branches which intensifies local competition; and (3) branching banks increase their prices, whereas non-branching banks lower prices. Consequently, non-digital consumers pay a higher cost to access financial services and thus face the risk of financial exclusion. Approximately, this channel causes 2.5 million previously banked individuals to lose banking access. Overall, the evidence highlights the role of banks’ endogenous responses to digital disruption in widening digital inequality.

This paper tests for the presence of asymmetric information in the originate-to-distribute mortgage supply chain. In this supply chain, a mortgage specialist originates a loan that she sells to a bank which securitizes the loan into a mortgage-backed security(MBS) that he sells to investors. Using a novel data set on auctions through which mortgage specialists sell loans to banks, we show that the mortgage specialists have private information about loan quality. Using data on mortgage securitization, we show that banks have more information about loan quality than the MBS investors and that the banks use this to their advantage. The presence of asymmetric information should put downward pressure on the resale price of mortgages in the supply chain, and thus raise the costs to consumers seeking mortgages.