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Chapter 13 Forecasting Seasonal Time Series
Ghysels, Eric; Osborn, Denise R.; Rodrigues, Paulo M.M. - 2006
integrated models and deterministic seasonality models. As well as examining how forecasts are computed in each case, the …. Section 3 discusses less traditional models, specifically nonlinear seasonal models and models for seasonality in variance …. Such nonlinear models primarily concentrate on interactions between seasonality and the business cycle, either using a …
Persistent link: https://www.econbiz.de/10014023693
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Ex-post and ex-ante forecasts of spot prices in bulk shipping in a period of economic crisis using simultaneous equation models
Geomelos, Nikolaos D.; Xideas, Evangelos - In: Spoudai : journal of economics and business 64 (2014) 2, pp. 14-39
The paper deals with forecasting of spot prices in bulk shipping using simultaneous equations models (SEMs) during the present economic crisis, emphasizing the importance of such models in empirical applied economics and for decision-makers. The SEMs predictive performance on the spot market is...
Persistent link: https://www.econbiz.de/10010470672
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Financial Variables as Predictors of Real Growth Vulnerability
Reichlin, Lucrezia - 2020
We evaluate the role of financial conditions as predictors of macroeconomic risk first in the quantile regression framework of Adrian et al. (2019b), which allows for non-linearities, and then in a novel linear semi-structural model as proposed by Hasenzagl et al. (2018). We distinguish between...
Persistent link: https://www.econbiz.de/10012839175
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Macroeconomic Stress-Testing of Mortgage Default Rate Using a Vector Error Correction Model and Entropy Pooling
Ardia, David - 2017
We propose a methodology to perform macroeconomic stress-testing on the probability of default of a given borrowers' population (i.e., aggregate probability of default) through simulation from a vector error correction model and entropy pooling (Meucci, 2008)
Persistent link: https://www.econbiz.de/10012968851
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Can Macroeconomists Get Rich Nowcasting Output Gap Turning Points with a Simple Machine-Learning Algorithm?
Raffinot, Thomas - 2017
To nowcast output gap turning points, probabilistic indicators are created from a simple and transparent machine-learning algorithm known as Learning Vector Quantization. The real-time ability of the indicators to quickly and accurately detect economic turning points in the United States and in...
Persistent link: https://www.econbiz.de/10012972314
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Forecasting and Stress Testing with Quantile Vector Autoregression
Chavleishvili, Sulkhan - 2019
We introduce a structural quantile vector autoregressive (VAR) model. Unlike standard VAR which models only the average interaction of the endogenous variables, quantile VAR models their interaction at any quantile. We show how to estimate and forecast multivariate quantiles within a recursive...
Persistent link: https://www.econbiz.de/10012859199
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Large-Dimensional Dynamic Factor Models in Real-Time : A Survey
Luciani, Matteo - 2014
In this paper I review the literature on Large-Dimensional Dynamic Factor Models for real-time applications. I first present the Dynamic Factor model, the implications of using large-dimensional databases, and the challenges of real-time applications. Then, I discuss how the literature has...
Persistent link: https://www.econbiz.de/10013045448
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An Alternative Measure of Economic Slack to Forecast Core Inflation
Sharma, Saurabh - 2021
Assessing macroeconomic demand conditions is critical for monetary policy to gaugeimminent inflationary pressures. Generally, measures of output gap, calculated byapplying statistical filters on GDP data, are used for this purpose. GDP data, however,are released only at quarterly frequency with...
Persistent link: https://www.econbiz.de/10013214672
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Tracking economic activity with alternative high-frequency data
Eckert, Florian; Kronenberg, Philipp; Mikosch, Heiner; … - 2020
Most macroeconomic indicators failed to capture the sharp economic fluctuations during the Corona crisis in a timely manner. Instead, alternative high-frequency data have been used, aiming to monitor the economic situation. However, these data are often only loosely related to the business cycle...
Persistent link: https://www.econbiz.de/10012395297
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Financial variables as predictors of real growth vulnerability
Reichlin, Lucrezia; Ricco, Giovanni; Hasenzagl, Thomas - 2020 - This version: 30th October 2019
We evaluate the role of financial conditions as predictors of macroeconomic risk first in the quantile regression framework of Adrian et al. (2019b), which allows for non-linearities, and then in a novel linear semi-structural model as proposed by Hasenzagl et al. (2018). We distinguish between...
Persistent link: https://www.econbiz.de/10012173525