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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Mixed-Frequency Vector Autoregressive Models
Claudia Foroni, Éric Ghysels, Massimiliano Marcellino
Advances in econometrics (2013), pp. 247-272
Closed Access | Times Cited: 45

Showing 1-25 of 45 citing articles:

Do high-frequency financial data help forecast oil prices? The MIDAS touch at work
Christiane Baumeister, Pierre Guérin, Lutz Kilian
International Journal of Forecasting (2015) Vol. 31, Iss. 2, pp. 238-252
Open Access | Times Cited: 133
Realtime Nowcasting with a Bayesian Mixed Frequency Model with Stochastic Volatility
Andrea Carriero, Todd E. Clark, Massimiliano Marcellino
Journal of the Royal Statistical Society Series A (Statistics in Society) (2015) Vol. 178, Iss. 4, pp. 837-862
Open Access | Times Cited: 98
Bayesian Mixed Frequency VARs
Bjørn Eraker, Ching Wai Chiu, Andrew T. Foerster, et al.
Journal of Financial Econometrics (2014) Vol. 13, Iss. 3, pp. 698-721
Closed Access | Times Cited: 69
Using low frequency information for predicting high frequency variables
Claudia Foroni, Pierre Guérin, Massimiliano Marcellino
International Journal of Forecasting (2018) Vol. 34, Iss. 4, pp. 774-787
Open Access | Times Cited: 62
Testing for Granger Causality with Mixed Frequency Data
Éric Ghysels, Jonathan B. Hill, Kaiji Motegi
RePEc: Research Papers in Economics (2013)
Closed Access | Times Cited: 46
Forecasting economic activity with mixed frequency BVARs
Scott A. Brave, R. Andrew Butters, Alejandro Justiniano
International Journal of Forecasting (2019) Vol. 35, Iss. 4, pp. 1692-1707
Closed Access | Times Cited: 41
Testing for Granger causality in large mixed-frequency VARs
Thomas Götz, Alain Hecq, Stephan Smeekes
Journal of Econometrics (2016) Vol. 193, Iss. 2, pp. 418-432
Open Access | Times Cited: 38
Future directions in nowcasting economic activity: A systematic literature review
Alina Stundžienė, Vaida Pilinkienė, Jurgita Bruneckienė, et al.
Journal of Economic Surveys (2023) Vol. 38, Iss. 4, pp. 1199-1233
Closed Access | Times Cited: 10
Testing a large set of zero restrictions in regression models, with an application to mixed frequency Granger causality
Éric Ghysels, Jonathan B. Hill, Kaiji Motegi
Journal of Econometrics (2020) Vol. 218, Iss. 2, pp. 633-654
Closed Access | Times Cited: 27
Real-Time Nowcasting with a Bayesian Mixed Frequency Model with Stochastic Volatility
Andrea Carriero, Todd E. Clark, Massimiliano Marcellino
Working paper (2012)
Open Access | Times Cited: 28
Markov-switching mixed-frequency VAR models
Claudia Foroni, Pierre Guérin, Massimiliano Marcellino
International Journal of Forecasting (2014) Vol. 31, Iss. 3, pp. 692-711
Closed Access | Times Cited: 28
Sluggish private investment in Japan’s Lost Decade: Mixed frequency vector autoregression approach
Kaiji Motegi, Akira Sadahiro
The North American Journal of Economics and Finance (2017) Vol. 43, pp. 118-128
Closed Access | Times Cited: 27
Combining Time Variation and Mixed Frequencies: an Analysis of Government Spending Multipliers in Italy
Jacopo Cimadomo, Antonello D’Agostino
Journal of Applied Econometrics (2015) Vol. 31, Iss. 7, pp. 1276-1290
Open Access | Times Cited: 25
Should we Sample a time Series more Frequently?: Decision Support via Multirate Spectrum Estimation
Guy P. Nason, Ben Powell, D. G. Elliott, et al.
Journal of the Royal Statistical Society Series A (Statistics in Society) (2016) Vol. 180, Iss. 2, pp. 353-407
Open Access | Times Cited: 21
Nowcasting Tail Risks to Economic Activity with Many Indicators
Andrea Carriero, Todd E. Clark, Massimiliano Marcellino
Working paper (2020)
Open Access | Times Cited: 20
How do daily changes in oil prices affect US monthly industrial output?
Abbas Valadkhani, Russell Smyth
Energy Economics (2017) Vol. 67, pp. 83-90
Closed Access | Times Cited: 21
The estimation of continuous time models with mixed frequency data
Marcus J. Chambers
Journal of Econometrics (2016) Vol. 193, Iss. 2, pp. 390-404
Open Access | Times Cited: 19
Mixed Frequency Structural Vector Auto-Regressive Models
Claudia Foroni, Massimiliano Marcellino
Journal of the Royal Statistical Society Series A (Statistics in Society) (2015) Vol. 179, Iss. 2, pp. 403-425
Closed Access | Times Cited: 17
Nowcasting Tail Risks to Economic Activity with Many Indicators
Andrea Carriero, Todd E. Clark, Massimiliano Marcellino
Working paper (2020)
Open Access | Times Cited: 15
Asymmetric responses in the timing, and magnitude, of changes in Australian monthly petrol prices to daily oil price changes
Abbas Valadkhani, Russell Smyth
Energy Economics (2017) Vol. 69, pp. 89-100
Closed Access | Times Cited: 16
Nowcasting Tail Risks to Economic Activity with Many Indicators
Andrea Carriero, Todd E. Clark, Massimiliano Marcellino
Working paper (2020)
Open Access | Times Cited: 14
Testing for Common Cycles in Non-Stationary VARs with Varied Frequency Data
Thomas Götz, Alain Hecq, Jean‐Pierre Urbain
Advances in econometrics (2013), pp. 361-393
Closed Access | Times Cited: 14
Testing for Granger Causality with Mixed Frequency Data
Éric Ghysels, Jonathan B. Hill, Kaiji Motegi
SSRN Electronic Journal (2014)
Closed Access | Times Cited: 13
Current account dynamics and the housing cycle in Spain
Daniel Maas, Eric Mayer, Sebastian K. Rüth
Journal of International Money and Finance (2018) Vol. 87, pp. 22-43
Open Access | Times Cited: 12
Should Forecasters Use Real-Time Data to Evaluate Leading Indicator Models for GDP Prediction? German Evidence
Katja Heinisch, Rolf Scheufele
German Economic Review (2018) Vol. 20, Iss. 4, pp. e170-e200
Open Access | Times Cited: 10
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