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.
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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