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ARIMA Forecasting of COVID-19 incidence in Italy, Russia, and the USA
Perone, Gaetano - 2020
economic emergencies. This paper aims to forecast the short to medium-term incidence of COVID-19 epidemic through the medium of …
Persistent link: https://www.econbiz.de/10014096892
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Reverse Kalman Filtering US Inflation with Sticky Professional Forecasts
Nason, James M. - 2013
forecasters is consistent with evidence on mean forecast errors. We find considerable evidence of inflation-gap persistence and …We provide a new way to filter US inflation into trend and cycle components, based on extracting long-run forecasts …, then estimating parameters, and then extracting the stochastic trend in inflation. The trend-cycle model with unobserved …
Persistent link: https://www.econbiz.de/10013076654
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A large Bayesian VAR of the United States Economy
Crump, Richard K.; Eusepi, Stefano; Giannone, Domenico; … - 2021
We model the United States macroeconomic and financial sectors using a formal and unified econometric model. Through shrinkage, our Bayesian VAR provides a flexible framework for modeling the dynamics of thirty-one variables, many of which are tracked by the Federal Reserve. We show how the...
Persistent link: https://www.econbiz.de/10012613922
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Real-time datasets really do make a difference : definitional change, data release, and forecasting
Fernández, Andrés; Swanson, Norman R. - 2011 - Rev.
square forecast error (MSFE) "best" predictions. On the other hand, models estimated and implemented using "latest available …
Persistent link: https://www.econbiz.de/10009130680
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The role of commodity prices in forecasting U.S. core inflation
Gospodinov, Nikolaj - 2016
This note documents a curious finding about the substantial forecast ability of a simple aggregator of three commodity … futures prices for U.S. core inflation. The proposed aggregator reduces the out-of-sample root mean squared error for 12-month …-ahead inflation forecasts of the benchmark AR(1) model by 28 percent (20 percent) for the PCE (CPI) measure of core inflation. To …
Persistent link: https://www.econbiz.de/10011428084
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The Informational Content of the Term-Spread in Forecasting the U.S. Inflation Rate : A Nonlinear Approach
Gogas, Periklis - 2017
The difficulty in modelling inflation and the significance in discovering the underlying data generating process of … inflation is expressed in an ample literature regarding inflation forecasting. In this paper we evaluate nonlinear machine … learning and econometric methodologies in forecasting the U.S. inflation based on autoregressive and structural models of the …
Persistent link: https://www.econbiz.de/10012953784
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The Role of Commodity Prices in Forecasting U.S. Core Inflation
Gospodinov, Nikolay - 2017
This note documents a curious finding about the substantial forecast ability of a simple aggregator of three commodity … futures prices for U.S. core inflation. The proposed aggregator reduces the out-of-sample root mean squared error for 12-month …-ahead inflation forecasts of the benchmark AR(1) model by 28 percent (20 percent) for the PCE (CPI) measure of core inflation. To …
Persistent link: https://www.econbiz.de/10012970034
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Neuronale Netze zur Prognose von Warenterminpreisen
Stolzke, Ulf A. - 2000
Persistent link: https://www.econbiz.de/10001421515
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Unobserved components with stochastic volatility in U.S. inflation : estimation and signal extraction
Li, Mengheng; Koopman, Siem Jan - 2018
applied to quarterly and monthly US inflation in an empirical study. We find that the persistence of quarterly inflation has … and density forecasts for monthly US inflation. …
Persistent link: https://www.econbiz.de/10011809984
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A first look on the new halle economic projection model
Giesen, Sebastian; Holtemöller, Oliver; Scharff, Juliane; … - 2010
In this paper we develop a small open economy model explaining the joint determination of output, inflation, interest … Zeitpunkten werden präsentiert und diskutiert. -- Mehrländermodell ; Prognose ; Bayesianische Ökonometrie …
Persistent link: https://www.econbiz.de/10003950731