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Should forecasters use real-time data to evaluate leading indicator models for GDP prediction? : German evidence
Heinisch, Katja; Scheufele, Rolf - 2017
-time and final data releases differ, we also observe minimal impacts on the relative forecasting performance of indicator …
Persistent link: https://www.econbiz.de/10011595370
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Factor models for non-stationary series : estimates of monthly U.S. GDP
Hengge, Martina; Leonard, Seton - 2017
This paper presents a novel dynamic factor model for non-stationary data. We begin by constructing a simple dynamic stochastic general equilibrium growth model and show that we can represent and estimate the model using a simple linear-Gaussian (Kalman) filter. Crucially, consistent estimation...
Persistent link: https://www.econbiz.de/10011669132
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Anticipating business-cycle turning points in real time using density forecasts from a VAR
Schreiber, Sven - 2014 - This version: January 2014
For the timely detection of business-cycle turning points we suggest to use mediumsized linear systems (subset VARs with automated zero restrictions) to forecast the relevant underlying variables, and to derive the probability of the turning point from the forecast density as the probability...
Persistent link: https://www.econbiz.de/10010233998
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Forecasting business-cycle turning points with (relatively large) linear systems in real time : conference paper
Schreiber, Sven - 2013 - This preliminary version: March 2013
The detection of business-cycle turning points is usually performed with non-linear discrete-regime models such as binary dependent variable (e.g., probit or logit) or Markov-switching methods. The probit model has the drawback that the continuous underlying target variable is discretized, with...
Persistent link: https://www.econbiz.de/10010344635
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Combined density nowcasting in an uncertain economic environment
Aastveit, Knut Are; Ravazzolo, Francesco; Dijk, Herman … - 2014
We introduce a Combined Density Nowcasting (CDN) approach to Dynamic Factor Models (DFM) that in a coherent way accounts for time-varying uncertainty of several model and data features in order to provide more accurate and complete density nowcasts. The combination weights are latent random...
Persistent link: https://www.econbiz.de/10010465155
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Business cycle dating and forecasting with real-time Swiss GDP data
Glocker, Christian; Wegmüller, Philipp - 2017
proposed model demonstrates a remarkable performance in short-term and medium-term forecasting. Using real-time GDP data since …
Persistent link: https://www.econbiz.de/10011732586
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Would DSGE models have predicted the Great Recession in Austria?
Breuss, Fritz - 2016
story-telling and policy analysis were in the forefront of applications since its inception, the forecasting perspective of … models are inferior in ex-ante forecasting a crisis. Surprisingly however, it turned out that not all but those models which … only detect the turning point of the Austrian business cycle early in 2008 but they also succeeded in forecasting the …
Persistent link: https://www.econbiz.de/10011561187
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A daily fever curve for the Swiss economy
Burri, Marc; Kaufmann, Daniel - 2020
Because macroeconomic data is published with a substantial delay, assessing the health of the economy during the rapidly evolving Covid-19 crisis is challenging. We develop a fever curve for the Swiss economy using publicly available daily financial market and news data. The indicator can be...
Persistent link: https://www.econbiz.de/10012225774
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Does the Phillips curve help to forecast euro area inflation?
Bańbura, Marta; Bobeica, Elena - 2020
; (iv) newer generation Phillips curve models with several timevarying features are a promising avenue for forecasting …
Persistent link: https://www.econbiz.de/10012299084
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Forecasting Macedonian GDP : evaluation of different models for short-term forecastin
Jovanovic, Branimir; Petrovska, Magdalena - Narodna Banka na Republika Makedonija - 2010
We evaluate the forecasting performance of six different models for short-term forecasting of Macedonian GDP: 1) ARIMA …
Persistent link: https://www.econbiz.de/10011623268