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Working Papers

Working Papers

  • WP 20-28 | On the Importance of Household versus Firm Credit Frictions in the Great Recession


    Patrick Kehoe Pierlauro Lopez Virgiliu Midrigan Elena Pastorino

    Abstract

    Although a credit tightening is commonly recognized as a key determinant of the Great Recession, to date, it is unclear whether a worsening of credit conditions faced by households or by firms was most responsible for the downturn. Some studies have suggested that the household-side credit channel is quantitatively the most important one. Many others contend that the firm-side channel played a crucial role. We propose a model in which both channels are present and explicitly formalized. Our analysis indicates that the household-side credit channel is quantitatively more relevant than the firm-side credit channel. We then evaluate the relative benefits of a fixed-sized transfer to households and to firms that improves each group’s access to credit. We find that the effects of such a transfer on employment are substantially larger when the transfer targets households rather than firms. Hence, we provide theoretical and quantitative support to the view that the employment decline during the Great Recession would have been less severe if instead of focusing on easing firms’ access to credit, the government had expended an equal amount of resources to alleviate households’ credit constraints. This paper has been published: https://doi.org/10.1016/j.red.2020.06.006.   Read More

  • WP 20-13R2 | Nowcasting Tail Risks to Economic Activity with Many Indicators


    Andrea Carriero Todd E. Clark Massimiliano Marcellino

    Original Paper: WP 20-13R

    Abstract

    This paper focuses on nowcasts of tail risk to GDP growth, with a potentially wide array of monthly and weekly information. We consider different models (Bayesian mixed frequency regressions with stochastic volatility, as well as classical and Bayesian quantile regressions) and also different methods for data reduction (either forecasts from models that incorporate data reduction or the combination of forecasts from smaller models). Our results show that, within some limits, more information helps the accuracy of nowcasts of tail risk to GDP growth. Accuracy typically improves as time moves forward within a quarter, making additional data available, with monthly data more important to accuracy than weekly data. Accuracy also typically improves with the use of financial indicators in addition to a base set of macroeconomic indicators. The better-performing models or methods include the Bayesian regression model with stochastic volatility, Bayesian quantile regression, some approaches to data reduction that make use of factors, and forecast averaging. In contrast, simple quantile regression performs relatively poorly.   Read More

  • WP 20-02R | Capturing Macroeconomic Tail Risks with Bayesian Vector Autoregressions


    Andrea Carriero Todd E. Clark Massimiliano Marcellino

    Original Paper: WP 20-02

    Abstract

    A rapidly growing body of research has examined tail risks in macroeconomic outcomes. Most of this work has focused on the risks of significant declines in GDP, and it has relied on quantile regression methods to estimate tail risks. Although much of this work discusses asymmetries in conditional predictive distributions, the analysis often focuses on evidence of downside risk varying more than upside risk. We note that this pattern in risk estimates over time could obtain with conditional distributions that are symmetric but subject to simultaneous shifts in conditional means (down) and variances (up). Building on that insight, we examine the ability of Bayesian VARs with stochastic volatility to capture tail risks in macroeconomic forecast distributions and outcomes. We consider both a conventional stochastic volatility specification and a specification with a common factor in volatility that enters the VAR’s conditional mean. Even though the one-step-ahead conditional predictive distributions from the conventional stochastic volatility specification are symmetric, the model estimates yield more time variation in downside risk as compared to upside risk. Results from the model that includes a volatility factor in the conditional mean and thereby allows for asymmetries in conditional distributions are very similar. Our paper also extends the recent literature by formally evaluating the accuracy of tail risk forecasts and assessing the performance of Bayesian quantile regression, as well as our Bayesian VARs, in this context. Overall, the BVAR models perform comparably to quantile regression for estimating and forecasting tail risks, complementing BVARs’ established performance for forecasting and structural analysis.   Read More

  • WP 20-27 | No-Arbitrage Priors, Drifting Volatilities, and the Term Structure of Interest Rates


    Andrea Carriero Todd E. Clark Massimiliano Marcellino

    Abstract

    We derive a Bayesian prior from a no-arbitrage affine term structure model and use it to estimate the coefficients of a vector autoregression of a panel of government bond yields, specifying a common time-varying volatility for the disturbances. Results based on US data show that this method improves the precision of both point and density forecasts of the term structure of government bond yields, compared to a fully fledged term structure model with time-varying volatility and to a no-change random walk forecast. Further analysis reveals that the approach might work better than an exact term structure model because it relaxes the requirements that yields obey a strict factor structure and that the factors follow a Markov process. Instead, the cross-equation no-arbitrage restrictions on the factor loadings play a marginal role in producing forecasting gains.   Read More

  • WP 20-26 | Average Inflation Targeting and Household Expectations


    Olivier Coibion Yuriy Gorodnichenko Edward S. Knotek II Raphael Schoenle

    Abstract

    Using a daily survey of U.S. households, we study how the Federal Reserve’s announcement of its new strategy of average inflation targeting affected households’ expectations. Starting with the day of the announcement, there is a very small uptick in the minority of households reporting that they had heard news about monetary policy relative to prior to the announcement, but this effect fades within a few days. Those hearing news about the announcement do not seem to have understood the announcement: they are no more likely to correctly identify the Fed’s new strategy than others, nor are their expectations different. When we provide randomly selected households with pertinent information about average inflation targeting, their expectations still do not change in a different way than when households are provided with information about traditional inflation targeting.   Read More

  • WP 20-25 | Information and Inequality in the Time of a Pandemic


    Allan Dizioli Roberto Pinheiro

    Abstract

    We introduce two types of agent heterogeneity in a calibrated epidemiological search model. First, some agents cannot afford to stay home to minimize virus exposure. Our results show that poor agents bear most of the epidemic’s health costs. Furthermore, we show that when a larger share of agents fail to change their behavior during the epidemic, a deeper recession is possible. Second, agents develop symptoms heterogeneously. We show that for diseases with a higher share of asymptomatic cases, even when less lethal, health and economic outcomes are worse. Public policies such as testing, quarantining, and lockdowns are particularly beneficial in economies with larger shares of poor agents. However, lockdowns lose effectiveness when a larger share of the agents take voluntary precautions to minimize virus exposure independent of the lockdown.   Read More

  • WP 20-24 | Low Interest Rates, Policy, and the Predictive Content of the Yield Curve


    Michael Bordo Joseph G. Haubrich

    Abstract

    Does the yield curve’s ability to predict future output and recessions differ when interest rates are low, as in the current global environment? In this paper we build on recent econometric work by Shi, Phillips, and Hurn that detects changes in the causal impact of the yield curve and relate that to the level of interest rates. We explore the issue using historical data going back to the 19th century for the United States and more recent data for the United Kingdom, Germany, and Japan. This paper is similar in spirit to Ramey and Zubairy (2018), who look at the government spending multiplier in times of low interest rates.   Read More

  • WP 20-23 | Government Debt Limits and Stabilization Policy


    Daniel Murphy Eric Young

    Abstract

    We evaluate alternative public debt management policies in light of constraints imposed by the effective lower bound on interest rates. Replacing the current limit on gross debt issued by the fiscal authority with a limit on consolidated debt of the government can ensure that output always reaches its potential, but it may permit excess government spending when the economy is away from the effective lower bound. The welfare-maximizing policy sets the gross debt limit to the level implied by Samuelson (1954), while the central bank finances government spending with money when the economy is at the effective lower bound.   Read More

  • WP 20-21 | Evaluating the Benefits of a Streamlined Refinance Program


    Kristopher Gerardi Lara Loewenstein Paul Willen

    Abstract

    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.   Read More

  • WP 20-22 Removed | Will COVID-19-Induced Rental Nonpayment Drive Large Reductions in Shelter Inflation? Hints from the Great Recession


    Wesley Janson Randal J. Verbrugge

    Abstract

    Working paper 20-22 was reviewed by staff at the BLS prior to its posting. After its posting, subsequent discussions with staff at the BLS revealed that the BLS treatment of nonpayment is different from the treatment assumed in the working paper. As a result, the authors have removed the old version of the working paper in order to incorporate this new information.   Read More