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Working Paper
Quantitative Easing and the “New Normal” in Monetary Policy
Kiley, Michael T. (2018-01-17)
Interest rates may remain low and fall to their effective lower bound (ELB) often. As a result, quantitative easing (QE), in which central banks expand their balance sheet to lower long-term interest rates, may complement policy approaches focused on adjustments in short-term interest rates. Simulation results using a large-scale model (FRB/US) suggest that QE does not improve economic performance if the steady-state interest rate is high, confirming that such policies were not advantageous from 1960 to 2007. However, QE can offset a significant portion of the adverse effects of the ELB when ...
Finance and Economics Discussion Series , Paper 2018-004

Working Paper
What's the Story? A New Perspective on the Value of Economic Forecasts
Sinha, Nitish R.; Hollrah, Christopher A.; Sharpe, Steven A. (2017-11-03)
We apply textual analysis tools to measure the degree of optimism versus pessimism of the text that describes Federal Reserve Board forecasts published in the Greenbook. The resulting measure of Greenbook text sentiment, ?Tonality,? is found to be strongly correlated, in the intuitive direction, with the Greenbook point forecast for key economic variables such as unemployment and inflation. We then examine whether Tonality has incremental power for predicting unemployment, GDP growth, and inflation up to four quarters ahead. We find it to have significant and substantive predictive power for ...
Finance and Economics Discussion Series , Paper 2017-107

Journal Article
How Have Shanghai, Saudi Arabia, and Supply Chains Affected U.S. Inflation Dynamics?
Forbes, Kristin J. (2019)
Understanding and forecasting inflation has always been a key focus of macroeconomics and monetary policymaking. Historically, many macroeconomists and central banks have relied on the ?Phillips curve? framework for this purpose. Recently, however, the Phillips curve framework has not been performing well. This article examines a number of possible explanations for the breakdown of the ?Phillips curve? relationship between slack and inflation. These explanations include the possibility that the curve may have flattened or shifted, that standard measures may not be capturing key aspects of the ...
Review , Volume 101 , Issue 1 , Pages 27-44

Working Paper
Do Phillips curves conditionally help to forecast inflation?
Dotsey, Michael; Stark, Tom; Fujita, Shigeru (2015-03-25)
This paper reexamines the forecasting ability of Phillips curves from both an unconditional and conditional perspective by applying the method developed by Giacomini and White (2006). We find that forecasts from our Phillips curve models tend to be unconditionally inferior to those from our univariate forecasting models. We also find, however, that conditioning on the state of the economy sometimes does improve the performance of the Phillips curve model in a statistically significant manner. When we do find improvement, it is asymmetric -- Phillips curve forecasts tend to be more accurate ...
Working Papers , Paper 15-16

Working Paper
Forecast Combination for Euro Area Inflation - A Cure in Times of Crisis?
Hubrich, Kirstin; Skudelny, Frauke (2016-08)
The period of extraordinary volatility in euro area headline inflation starting in 2007 raised the question whether forecast combination methods can be used to hedge against bad forecast performance of single models during such periods and provide more robust forecasts. We investigate this issue for forecasts from a range of short-term forecasting models. Our analysis shows that there is considerable variation of the relative performance of the different models over time. To take that into account we suggest employing performance-based forecast combination methods, in particular one with more ...
Finance and Economics Discussion Series , Paper 2016-104

Working Paper
Assessing Macroeconomic Tail Risks in a Data-Rich Environment
Cook, Thomas R.; Doh, Taeyoung (2019-11-20)
We use a large set of economic and financial indicators to assess tail risks of the three macroeconomic variables: real GDP, unemployment, and inflation. When applied to U.S. data, we find evidence that a dense model using principal components (PC) as predictors might be misspecified by imposing the “common slope” assumption on the set of predictors across multiple quantiles. The common slope assumption ignores the heterogeneous informativeness of individual predictors on different quantiles. However, the parsimony of the PC-based approach improves the accuracy of out-of-sample forecasts ...
Research Working Paper , Paper RWP 19-12

Working Paper
A Nowcasting Model for Canada: Do U.S. Variables Matter?
Bragoli, Daniela; Modugno, Michele (2016-04)
We propose a dynamic factor model for nowcasting the growth rate of quarterly real{{p}}Canadian gross domestic product. We show that the proposed model produces more accurate nowcasts than those produced by institutional forecasters, like the Bank of Canada, the The Organisation for Economic Co-operation and Development (OECD), and the survey collected by Bloomberg, which reflects the median forecast of market participants. We show that including U.S. data in a nowcasting model for Canada dramatically improves its predictive accuracy, mainly because of the absence of timely production data ...
Finance and Economics Discussion Series , Paper 2016-036

Working Paper
The rise and fall of consumption in the '00s
Luengo-Prado, Maria Jose; Demyanyk, Yuliya; Hryshko, Dmytro; Sorensen, Bent E. (2015-10-16)
The major portion of U.S. gross domestic product (GDP) is accounted for by consumer spending, which significantly affects the business cycle. Consumer demand has been extremely volatile since 2000, especially given the booms and busts in housing values and in subprime mortgage lending. While it is well-established that housing net worth, credit availability, and household debt levels help to explain changes in consumer spending, the roles played by other potential determinants of consumption are not well identified or understood. This paper uses county-level data and a multiple-regression ...
Working Papers , Paper 15-12

Report
Online Estimation of DSGE Models
Herbst, Edward; Schorfheide, Frank; Cai, Michael; Matlin, Ethan; Del Negro, Marco; Sarfati, Reca (2019-08-01)
This paper illustrates the usefulness of sequential Monte Carlo (SMC) methods in approximating DSGE model posterior distributions. We show how the tempering schedule can be chosen adaptively, explore the benefits of an SMC variant we call generalized tempering for ?online? estimation, and provide examples of multimodal posteriors that are well captured by SMC methods. We then use the online estimation of the DSGE model to compute pseudo-out-of-sample density forecasts of DSGE models with and without financial frictions and document the benefits of conditioning DSGE model forecasts on nowcasts ...
Staff Reports , Paper 893

Working Paper
High-Dimensional DSGE Models: Pointers on Prior, Estimation, Comparison, and Prediction∗
Shin, Minchul; Tan, Fei; Chib, Siddhartha (2020-09-15)
Working Papers , Paper 20-35

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