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Safety, liquidity, and the natural rate of interest
Del Negro, Marco; Giannone, Domenico; Giannoni, Marc; Tambalotti, Andrea (2017-05-11)
Why are interest rates so low in the Unites States? We find that they are low primarily because the premium for safety and liquidity has increased since the late 1990s, and to a lesser extent because economic growth has slowed. We reach this conclusion using two complementary perspectives: a flexible time-series model of trends in Treasury and corporate yields, inflation, and long-term survey expectations, and a medium-scale dynamic stochastic general equilibrium (DSGE) model. We discuss the implications of this finding for the natural rate of interest.
Staff Reports , Paper 812

Working Paper
Monetary policy, trend inflation, and the Great Moderation: an alternative interpretation: comment based on system estimation
Kurozumi, Takushi; Hirose, Yasuo; Van Zandweghe, Willem (2015-12-01)
What caused the U.S. economy's shift from the Great Inflation era to the Great Moderation era? {{p}} A large literature shows that the shift was achieved by the change in monetary policy from a passive to an active response to inflation. However, Coibion and Gorodnichenko (2011) attribute the shift to a fall in trend inflation along with the policy change, based on a solely estimated Taylor rule and a calibrated staggered-price model. We estimate the Taylor rule and the staggered-price model jointly and demonstrate that the change in monetary policy responses to inflation and other variables ...
Research Working Paper , Paper RWP 15-17

Working Paper
Forecasting US Inflation Using Bayesian Nonparametric Models
Clark, Todd E.; Huber, Florian; Koop, Gary; Marcellino, Massimiliano (2022-03-02)
The relationship between inflation and predictors such as unemployment is potentially nonlinear with a strength that varies over time, and prediction errors error may be subject to large, asymmetric shocks. Inspired by these concerns, we develop a model for inflation forecasting that is nonparametric both in the conditional mean and in the error using Gaussian and Dirichlet processes, respectively. We discuss how both these features may be important in producing accurate forecasts of inflation. In a forecasting exercise involving CPI inflation, we find that our approach has substantial ...
Working Papers , Paper 22-05

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Time-Varying Structural Vector Autoregressions and Monetary Policy: a Corrigendum
Primiceri, Giorgio E.; Del Negro, Marco (2013)
This note corrects a mistake in the estimation algorithm of the time-varying structural vector autoregression model of Primiceri (2005) and shows how to correctly apply the procedure of Kim, Shephard, and Chib (1998) to the estimation of VAR, DSGE, factor, and unobserved components models with stochastic volatility. Relative to Primiceri (2005), the main difference in the new algorithm is the ordering of the various Markov Chain Monte Carlo steps, with each individual step remaining the same.
Staff Reports , Paper 619

Working Paper
Can Forecast Errors Predict Financial Crises? Exploring the Properties of a New Multivariate Credit Gap
Afanasyeva, Elena (2020-06-12)
Yes, they can. I propose a new method to detect credit booms and busts from multivariate systems -- monetary Bayesian vector autoregressions. When observed credit is systematically higher than credit forecasts justified by real economic activity variables, a positive credit gap emerges. The methodology is tested for 31 advanced and emerging market economies. The resulting credit gaps fit historical evidence well and detect turning points earlier, outperforming the credit-to-GDP gaps in signaling financial crises, especially at longer horizons. The results survive in real time and can shed ...
Finance and Economics Discussion Series , Paper 2020-045

Working Paper
Sequential Bayesian Inference for Vector Autoregressions with Stochastic Volatility
Zito, John; Bognanni, Mark (2019-12-16)
We develop a sequential Monte Carlo (SMC) algorithm for Bayesian inference in vector autoregressions with stochastic volatility (VAR-SV). The algorithm builds particle approximations to the sequence of the model’s posteriors, adapting the particles from one approximation to the next as the window of available data expands. The parallelizability of the algorithm’s computations allows the adaptations to occur rapidly. Our particular algorithm exploits the ability to marginalize many parameters from the posterior analytically and embeds a known Markov chain Monte Carlo (MCMC) algorithm for ...
Working Papers , Paper 19-29

Working Paper
Clustered Housing Cycles
Rubio, Margarita; Owyang, Michael T.; Hernandez-Murillo, Ruben (2015-10-22)
Using a panel of U.S. city-level building permits data, we estimate a Markov-switching model of housing cycles that allows for idiosyncratic departures from a national housing cycle. These departures occur for clusters of cities that experience simultaneous housing contractions. We find that cities do not form housing regions in the traditional geographic sense. Instead, similarities in factors affecting the demand for housing (such as average winter temperature and the unemployment rate) appear to be more important determinants of cyclical comovements than similarities in factors affecting ...
Working Papers (Old Series) , Paper 1524

Report
Which bank is the \\"central\\" bank? an application of Markov theory to the Canadian Large Value Transfer System
Garratt, Rod; Chapman, James T. E.; Bech, Morten L. (2008-11-01)
Recently, economists have argued that a bank's importance within the financial system depends not only on its individual characteristics but also on its position within the banking network. A bank is deemed to be "central" if, based on our network analysis, it is predicted to hold the most liquidity. In this paper, we use a method similar to Google's PageRank procedure to rank banks in the Canadian Large Value Transfer System (LVTS). In doing so, we obtain estimates of the payment processing speeds for the individual banks. These differences in processing speeds are essential for ...
Staff Reports , Paper 356

Working Paper
Regionalization vs. globalization
Otrok, Christopher; Kose, M. Ayhan; Hirata, Hideaki (2013-01-01)
Both global and regional economic linkages have strengthened substantially over the past quarter century. We employ a dynamic factor model to analyze the implications of these linkages for the evolution of global and regional business cycles. Our model allows us to assess the roles played by the global, regional, and country-specific factors in explaining business cycles in a large sample of countries and regions over the period 1960?2010. We find that, since the mid-1980s, the importance of regional factors has increased markedly in explaining business cycles especially in regions that ...
Working Papers , Paper 2013-002

Working Paper
Government Loan Guarantees during a Crisis: The Effect of the PPP on Bank Lending and Profitability
Marsh, W. Blake; Sharma, Padma (2021-07-14)
We study bank responses to the Paycheck Protection Program (PPP) and its effects on lender balance sheets and profitability. To address the endogeneity between bank decisions and balance sheet effects, we develop a Bayesian joint model that examines the decision to participate, the intensity of participation, and ultimate balance sheet outcomes. Overall, lenders were driven by risk-aversion and funding capacity rather than profitability in their decision to participate and the intensity of their participation. Indeed, with greater participation intensity, banks experienced sizable growth in ...
Research Working Paper , Paper RWP 21-03

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