Finance and Economics Discussion Series (FEDS)
Staff working papers in the Finance and Economics Discussion Series (FEDS) investigate a broad range of issues in economics and finance, with a focus on the U.S. economy and domestic financial markets.
The widespread economic damage caused by the ongoing COVID-19 pandemic poses the first major test of the bank regulatory reforms put in place following the global financial crisis. This study assesses this framework, with an emphasis on capital and liquidity requirements. Leading up to the COVID-19 crisis, banks were well-capitalized and held ample liquid assets, reflecting in part heightened requirements. Capital requirements were comparable across major jurisdictions, despite differences in the implementation of the international Basel standards. The overall robust capital and liquidity levels resulted in a resilient banking system, which maintained lending through the early stages of the pandemic. Furthermore, trading activity was a source of strength for banks, reflecting in part a prudent regulatory approach. Areas for potential improvement include addressing the cyclicality of requirements.
This paper explores how to recycle carbon tax revenue back to households to maximize welfare. Using a general equilibrium lifecycle model calibrated to reflect the heterogeneity in the U.S. economy, we find the optimal policy uses two thirds of carbon-tax revenue to reduce the distortionary tax on capital income while the remaining one third is used to increase the progressivity of the labor-income tax. The optimal policy attains higher welfare and more equality than the lump-sum rebate approach preferred by policymakers as well as the approach originally prescribed by economists--which called exclusively for reductions in distortionary taxes.
Keywords: Carbon tax; overlapping generations; revenue recycling
We exploit detailed transaction and position data for a sample of long-short equity hedge funds to study the trading activity of fundamental investors. We find that hedge funds exhibit skill in opening positions, but that they close their positions too early, thereby forgoing about a third of the trades' potential profitability. We explain this behavior with the limits of arbitrage: hedge funds close positions early in order to reallocate their capital to more profitable investments and/or to accommodate tightened financial constraints. Consistent with this view, we document that hedge funds leave more money on the table after opening new positions, negative returns, or increases in funding constraints and volatility.
Keywords: Hedge funds, Short selling, Profitability, Fundamental Trading
We examine the effect of the social networks of bank directors on board gender diversity and compensation using a unique, newly compiled dataset over the 1999-2018 period. We find that within-board social networks are extensive, but there are significant differences in the size and gender composition of social networks of male vs female bank directors. We also find that samegender networks play an important role in determining the gender composition of bank boards. Finally, we show that those connected to male directors receive higher compensation, but we find no evidence that connections to female directors are influential in determining pay and bonuses.
This note explores the potential effects of the widespread adoption of a global stablecoin (GSC) on key aggregate financial sector balance sheets in the United States. To do this, we map out cash flows of GSC transactions among financial sector entities using a stylized set of 't-accounts'. By analyzing these individual transactions, we infer aggregate and compositional effects on U.S. commercial banking sector and Federal Reserve balance sheets. Through this lens, we also consider how these balance sheet changes could affect monetary policy implementation, the demand for central bank reserves, and the market for U.S. dollar safe assets.
I document that less educated workers experience higher and more cyclically sensitive job separation rates. Meanwhile, workers with a bachelor's degree or more exhibit pro-cyclical wages while workers without a high school degree exhibit no statistically discernible cyclical pattern. Differences in the sensitivity are most stark when measurement of labor costs accounts for the value of the persistent effects of current macroeconomic conditions on future remitted wages. These findings suggest optimally differential implementation of self-enforcing implicit wage contracts in which educated workers and their employers leverage relative employment stability to smooth the effects of cyclical fluctuations over longer horizons. This margin of adjustment is less available to the less well educated, who have shorter expected employment durations. Furthermore, failure to account for the heterogeneities documented here leads to substantial underestimation of the welfare costs of business cycles.
Uncertainty surrounding if and when the U.S. government will implement a federal climate policy introduces risk into the decision to invest in capital used in conjunction with fossil fuels. To quantify the macroeconomic impacts of this climate policy risk, we develop a dynamic, general equilibrium model that incorporates beliefs about future climate policy. We find that climate policy risk reduces carbon emissions by causing the capital stock to shrink and become relatively cleaner. Our results reveal, however, that a carbon tax could achieve the same reduction in emissions at less than half the cost.
Network analysis has demonstrated that interconnectedness among market participants results in spillovers, amplifies or absorbs shocks, and creates other nonlinear effects that ultimately affect market health. In this paper, we propose a new directed network construct, the liquidity network, to capture the urgency to trade by connecting the initiating party in a trade to the passive party. Alongside the conventional trading network connecting sellers to buyers, we show both network types complement each other: Liquidity networks reveal valuable information, particularly when information asymmetry in the market is high, and provide a more comprehensive characterization of interconnectivity in the overnight-lending market.
We study new transaction-level data of discount window borrowing in the U.S. between 2010 and 2017, merged with quarterly data on bank financial con- ditions (balance sheet and revenue). The objective is to improve our under- standing of the reasons for why banks use the discount window during periods outside financial crises. We also provide a model of the decision of banks to borrow at the window, which is helpful for interpreting the data. We find that decisions to gain access and to borrow at the discount window are meaning- fully correlated with some relevant banks' characteristics and the composition of banks' balance sheets. Banks choose simultaneously to obtain access to the discount window and hold more cash-like liquidity as a proportion of assets. Yet, conditional on access, larger and less liquid banks tend to borrow more from the discount window. In general, our findings suggest that banks could, in principle, adapt their operations to modulate, and possibly reduce, their use of the discount window in "normal" times.
I analyze the implications of allowing consumers to make mistakes on the risk-return relationships predicted by consumption-based asset pricing models. I allow for consumption mistakes using a model in which a portfolio manager selects investments on a consumer's behalf. The consumer has an arbitrary consumption policy that could reflect a wide range of mistakes. For power utility, expected returns do not generally depend on exposure to single-period consumption shocks, but robustly depend on exposure to both long-run consumption and expected return shocks. I empirically show that separately accounting for both types of shocks helps explain the equity premium and cross section of stock returns.
We perform a real-time forecasting exercise for US inflation, investigating whether and how additional information--additional macroeconomic variables, expert judgment, or forecast combination--can improve forecast accuracy and robustness. In our analysis we consider the pre-pandemic period including the Global Financial Crisis and the following expansion--the longest on record--featuring unemployment that fell to a rate not seen for nearly sixty years. Distinguishing features of our study include the use of published Federal Reserve Board staff forecasts contained in Tealbooks and a focus on forecasting performance before, during, and after the Global Financial Crisis, with relevance also for the current crisis and beyond. We find that while simple models remain hard to beat, the additional information that we consider can improve forecasts, especially in the post-crisis period. Our results show that (1) forecast combination approaches improve forecast accuracy over simpler models and robustify against bad forecasts, a particularly relevant feature in the current environment; (2) aggregating forecasts of inflation components can improve performance compared to forecasting the aggregate directly; (3) judgmental forecasts, which likely incorporate larger and more timely datasets, provide improved forecasts at short horizons.
Keywords: Inflation, Survey forecasts, Forecast combination
We show that the effectiveness of redistribution policy in stimulating the economy and improving welfare is directly tied to how much inflation it generates, which in turn hinges on monetary-fiscal adjustments that ultimately finance the transfers. We compare two distinct types of monetary-fiscal adjustments: In the monetary regime, the government eventually raises taxes to finance transfers, while in the fiscal regime, inflation rises, effectively imposing inflation taxes on public debt holders. We show analytically in a simple model how the fiscal regime generates larger and more persistent inflation than the monetary regime. In a quantitative application, we use a two-sector, two-agent New Keynesian model, situate the model economy in a COVID-19 recession, and quantify the effects of the transfer components of the Coronavirus Aid, Relief, and Economic Security (CARES) Act. We find that the transfer multipliers are significantly larger under the fiscal regime—which results in a milder contraction—than under the monetary regime, primarily because inflationary pressures of this regime counteract the deflationary forces during the recession. Moreover, redistribution produces a Pareto improvement under the fiscal regime.
Keywords: Household heterogeneity, Redistribution, Monetary-fiscal policy mix, Transfer multiplier, Welfare evaluation, COVID-19, CARES Act
We exploit institutional features of the U.S. banking stress tests to disentangle different types of information garnered by market participants when the stress test results are released. By examining the reaction of different asset prices, we find evidence that market participants value the stress test announcements not only for the information on possible future capital distributions but also for the signals about bank resilience. These results back the use of stress tests by central banks to inform the broader public about the soundness of the banking system.
Is Lending Distance Really Changing? Distance Dynamics and Loan Composition in Small Business Lending
Has information technology improved small businesses' access to credit by hardening the information used in loan underwriting and reducing the importance of proximity to lenders? Previous research, pointing to increasing average lending distances, suggests that it has. But this conclusion can obscure differences across loans and lenders. Using over 20 years of Community Reinvestment Act data on small business lending, we find that while average distances have increased substantially, distances at individual banks remain unchanged. Instead, average distance has increased because a small group of lenders specializing in high-volume, small-loan lending nationwide have increased their share of small business lending by 10 percentage points. Our findings imply that small businesses continue to depend on local banks.
Does expansionary monetary policy drive up prices of risky assets? Or, do investors interpret monetary policy easing as a signal that economic fundamentals are weaker than they previously believed, prompting riskier asset prices to fall? We test these competing hypotheses within the U.S. corporate bond market and find evidence strongly in favor of the second explanation—known as the "Fed information effect". Following an unanticipated monetary policy tightening (easing), returns on corporate bonds with higher credit risk outperform (underperform). We conclude that monetary policy surprises are predominantly interpreted by market participants as signaling information about the state of the economy.
Focusing on some key metrics of bank performance, such as revenues and loan charge-off rates, we estimate the fraction of the observed variation in these metrics that can be attributed to changes in economic conditions. Macroeconomic factors can explain the preponderance of the fluctuations in charge-off rates. By contrast, bank-specific, idiosyncratic factors account for a sizable share of the variation in bank revenues. These results point to importance of bank-specific business models as a driver of performance.
We use credit card data from the Federal Reserve Board's FR Y-14M reports to study the impact of the COVID-19 shock on the use and availability of consumer credit across borrower types from March through August 2020. We document an initial sharp decrease in credit card transactions and outstanding balances in March and April. While spending starts to recover by May, especially for risky borrowers, balances remain depressed overall. We find a strong negative impact of local pandemic severity on credit use, which becomes smaller over time, consistent with pandemic fatigue. Restrictive public health interventions also negatively affect credit use, but the pandemic itself is the main driver. We further document a large reduction in credit card originations, especially to risky borrowers. Consistent with a tightening of credit supply and a flight-to-safety response of banks, we find an increase in interest rates of newly issued credit cards to less creditworthy borrowers.
This paper estimates the impact of reducing export and import tariffs on firm input choices. In presence of borrowing constraints, lower export tariffs facilitate the reallocation of capital and labor inputs across firms, while a decline in import tariffs either tightens import competition or increases the availability of imported inputs; all three mechanisms suggest that a higher degree of openness should be associated with lower misallocation. To analyze the empirical relationship between openness and input misallocation, we draw on the annual surveys conducted by the Chinese National Bureau of Statistics (NBS) between 1998 and 2007. From the surveys, we con- struct firm-level measures of input misallocation that control for firm heterogeneity; we identify shocks to openness using industry tariff levels and firm trade shares. We find that firm facing higher tariffs in either import or export markets make less optimal input choices. We further decompose our analysis between input and output tariffs: our results suggest that the labor reallocation mainly occurs because of lower input tariffs, while the selection effect induced by changes in output tariffs does not necessarily cause more distorted firms to exit and, therefore, tends to have an insignificant effect on input allocation. Finally, we calculate the contribution of tariff changes towards aggregate misallocation and productivity: our results indicate that the impact of firm-level tariff reductions on aggregate misallocation and productivity was marginal in our sample period, but the presence of sizeable interactions between trade shocks and mis- allocation at the sector level suggests that our result should be interpreted as a lower bound of the overall effect.
A continuous distribution of agents that face a piecewise-linear schedule of incentives results in a distribution of responses with mass points located where the slope (kink) or intercept (notch) of the schedule changes. Bunching methods use these mass points to estimate an elasticity parameter, which summarizes agents' responses to incentives. This article introduces the command bunching, which implements new non-parametric and semi-parametric identification methods for estimating elasticities developed by Bertanha et al. (2021). These methods rely on weaker assumptions than currently made in the literature and result in meaningfully different estimates of the elasticity in various contexts.
Using American Recovery and Reinvestment Act (ARRA) data, we show that firms lever their political connections to win stimulus grants and public expenditure channeled through politically connected firms hinders job creation. We build a unique database that links campaign contributions and state legislative election outcomes to ARRA grant allocation. Using exogenous variation in political connections based on ex-post close elections held before ARRA, we causally show that politically connected firms are 64 percent more likely to secure a grant. Based on an instrumental variable approach, we also establish that state-level employment creation associated with grants channeled through politically connected firms is nil. Therefore, the impact of fiscal stimulus is not only determined by how much is spent, but also by how the expenditure is allocated across recipients.
We use new annual data on gasoline taxes and corporate income taxes from U.S. states to analyze whether politicians avoid tax increases in election years. These data contain 3 useful attributes: (1) when state politicians enact tax laws, (2) when state politicians implement tax laws on consumers and firms, and (3) the size of tax changes. Using a pre-analysis research plan that includes regressions of tax rate changes and tax enactment years on time-to-gubernatorial election year indicators, we find that elections decrease the probability of politicians enacting increases in taxes and reduce the size of implemented tax changes relative to non-election years. We find some evidence that politicians are most likely to enact tax increases right after an election. These election effects are stronger for gasoline taxes than for corporate income taxes and depend on no other political, demographic, or macroeconomic conditions. Supplemental analysis supports political salience over legislative e ort in generating this difference in electoral effects.
Ten Days Late and Billions of Dollars Short: The Employment Effects of Delays in Paycheck Protection Program Financing
Delay in the provision of Paycheck Protection Program (PPP) loans due to insufficient initial funding under the CARES Act substantially and persistently reduced employment. Delayed loans increased job losses in May and persistently reduced recalls throughout the summer. The magnitude and heterogeneity of effects suggest significant barriers to obtaining external financing, particularly among small firms. Effects are inequitably distributed: larger among the self-employed, less well paid, less well educated and--importantly for the design of future programs--in very small firms. Our estimates imply the PPP saved millions of jobs but larger initial funding could have saved millions more, particularly if it had been directed toward the smallest firms. About half of the jobs lost to insufficient PPP funding are lost in firms with fewer than 10 employees, despite such firms accounting for less than 20 percent of employment.
Keywords: Paycheck Protection Program, CARES Act, Countercyclical Fiscal Policy, Covid-19, Kurzarbeit, Income Support, Small Business Lending, Small and Medium Enterprises (SMEs), Financial Frictions
We study the bunching identification strategy for an elasticity parameter that summarizes agents' response to changes in slope (kink) or intercept (notch) of a schedule of incentives. A notch identifies the elasticity but a kink does not, when the distribution of agents is fully flexible. We propose new non-parametric and semi-parametric identification assumptions on the distribution of agents that are weaker than assumptions currently made in the literature. We revisit the original empirical application of the bunching estimator and find that our weaker identification assumptions result in meaningfully different estimates. We provide the Stata package bunching to implement our procedures.
Keywords: partial identification, censored regression, bunching, notching
This paper investigates spillovers from foreign economies to the U.S. through changes in longterm Treasury yields. We document a decline in the contribution of U.S. domestic news to the variance of long-term Treasury yields and an increased importance of overnight yield changes—a rough proxy for the contribution of foreign shocks to U.S. yields—over the past decades. Using a model that identifies U.S., Euro area, and U.K. shocks that move global yields, we estimate that foreign (non-U.S.) shocks account for at least 20 percent of the daily variation in long-term U.S. yields in recent years. We argue that spillovers occur in large part through bond term premia by showing that a low level of foreign yields relative to U.S. yields predicts a decline in distant forward U.S. yields and higher returns on a strategy that is long on a long-term Treasury security and short on a long-term foreign bond.
Keywords: Bond risk premia, foreign spillovers, event study, identification by heteroskedasticity, predictability.
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The Board values having a staff that conducts research on a wide range of economic topics and that explores a diverse array of perspectives on those topics. The resulting conversations in academia, the economic policy community, and the broader public are important to sharpening our collective thinking.