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U-Midas: Midas Regressions with Unrestricted Lag Polynomials · Study

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PreprintU-Midas: Midas Regressions with Unrestricted Lag Polynomials

Claudia Foroni2016

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Preprintgreen2016

U-Midas: Midas Regressions with Unrestricted Lag Polynomials

Claudia Foroni · Massimiliano Giuseppe Marcellino · Christian Schumacher

71 citations·0/0 files stored·SSRN Electronic Journal

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Forecasting Techniques and Applications Monetary Policy and Economic Impact Statistical and numerical algorithms

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References

2007MIDAS Regressions: Further Results and New Directions 2005Predicting volatility: getting the most out of return data sampled at different frequencies 2005A comparison of direct and iterated multistep AR methods for forecasting macroeconomic time series 2002A new coincident index of business cycles based on monthly and quarterly series 2008Macroeconomic Forecasting With Mixed-Frequency Data 2010Factor MIDAS for Nowcasting and Forecasting with Ragged-Edge Data: A Model Comparison for German GDP*1999Some Consequences of Temporal Aggregation in Empirical Analysis 2009Forecasting US output growth using leading indicators: an appraisal using MIDAS models

Cited by

2018Do high-frequency stock market data help forecast crude oil prices? Evidence from the MIDAS models 2014Variable Selection in Predictive MIDAS Models 2014Forecasting GDP growth using mixed-frequency models with switching regimes 2016A mixed frequency approach to the forecasting of private consumption with ATM/POS data 2021A comparison of monthly global indicators for forecasting growth

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2013A Survey of Econometric Methods for Mixed-Frequency Datapreprint · 8 shared references 2013Unrestricted Mixed Data Sampling (MIDAS): MIDAS Regressions with Unrestricted Lag Polynomialsarticle · 7 shared references 2016A comparison of MIDAS and bridge equationsarticle · 7 shared references 2012Forecasting with Mixed-Frequency Datachapter · 6 shared references 2018Using low frequency information for predicting high frequency variablesarticle · 6 shared references 2014Central Bank Macroeconomic Forecasting During the Global Financial Crisis: The European Central Bank and Federal Reserve Bank of New York Experiencesarticle · 6 shared references

Details

Year2016

Typepreprint

Published2016-01-01

VenueSSRN Electronic Journal

ISSN-L1556-5068

Languageen

Citations71

Files0 public / 0

ShelfForecasting Techniques and Applications

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doi10.2139/ssrn.2785452

openalex_workW1501780088

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2013Mixed-Frequency Vector Autoregressive Models

2016The estimation of continuous time models with mixed frequency data

2013Nowcasting causality in mixed frequency vector autoregressive models