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In this paper we study what professional forecasters actually explain. We use spectral analysis and state space modeling to decompose economic time series into a trend, a business-cycle, and an irregular component. To examine which components are captured by professional forecasters we regress...
Persistent link: https://www.econbiz.de/10011305773
We introduce a Combined Density Nowcasting (CDN) approach to Dynamic Factor Models (DFM) that in a coherent way … nowcasts. The combination weights are latent random variables that depend on past nowcasting performance and other learning …
Persistent link: https://www.econbiz.de/10010465155
We explore a periodic analysis in the context of unobserved components time series models that decompose time series into components of interest such as trend and seasonal. Periodic time series models allow dynamic characteristics to depend on the period of the year, month, week or day. In the...
Persistent link: https://www.econbiz.de/10011342560
been satisfactorily answered. We focus on out-of-sample nowcasting, and extend the Bayesian Structural Time Series model …
Persistent link: https://www.econbiz.de/10011987495
Persistent link: https://www.econbiz.de/10009765842
This paper investigates the feasibility of using earlier provisional data to improve the now- and forecasting accuracy of final and official statistics. We propose the use of a multivariate structural time series model which includes common trends and seasonal components to combine official...
Persistent link: https://www.econbiz.de/10015062979
We assess the predictive ability of 15 economic uncertainty measures in a real-time out-of-sample forecasting exercise for the quantiles of The Conference Board's coincident economic index and its components (industrial production, employment, personal income, and manufacturing and trade sales)....
Persistent link: https://www.econbiz.de/10013375365
This paper proposes a new model-based method to obtain a coincident indicator for the business cycle. A dynamic factor model with trend components and a common cycle component is considered which can be estimated using standard maximum likelihood methods. The multivariate unobserved components...
Persistent link: https://www.econbiz.de/10011334364
We develop a vector autoregressive model with time variation in the mean and the variance. The unobserved time-varying mean is assumed to follow a random walk and we also link it to long-term Consensus forecasts, similar in spirit to so called democratic priors. The changes in variance are...
Persistent link: https://www.econbiz.de/10011809970
estimation accuracy. Modestly increasing the noise level also accelerates convergence. A nowcasting exercise of euro area GDP …This paper addresses the poor performance of the Expectation-Maximization (EM) algorithm in the estimation of low …-noise dynamic factor models, commonly used in macroeconomic forecasting and nowcasting. We show analytically and in Monte Carlo …
Persistent link: https://www.econbiz.de/10014249849