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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:

Real-time forecasting of the US federal government budget: A simple mixed frequency data regression approach
Éric Ghysels, Nazire Özkan
International Journal of Forecasting (2015) Vol. 31, Iss. 4, pp. 1009-1020
Closed Access | Times Cited: 40

Showing 1-25 of 40 citing articles:

Forecasting carbon prices in the Shenzhen market, China: The role of mixed-frequency factors
Meng Han, Lili Ding, Xin Zhao, et al.
Energy (2019) Vol. 171, pp. 69-76
Open Access | Times Cited: 154
Geopolitical risk and China's oil security
Xu Gong, Sun Yi, Zhili Du
Energy Policy (2022) Vol. 163, pp. 112856-112856
Closed Access | Times Cited: 82
Usefulness of economic and energy data at different frequencies for carbon price forecasting in the EU ETS
Xin Zhao, Meng Han, Lili Ding, et al.
Applied Energy (2018) Vol. 216, pp. 132-141
Open Access | Times Cited: 144
A novel mixed frequency sampling discrete grey model for forecasting hard disk drive failure
Rongxing Chen, Xinping Xiao, Mingyun Gao, et al.
ISA Transactions (2024) Vol. 147, pp. 304-327
Closed Access | Times Cited: 12
A multiple support vector machine approach to stock index forecasting with mixed frequency sampling
Yuchen Pan, Zhi Xiao, Xianning Wang, et al.
Knowledge-Based Systems (2017) Vol. 122, pp. 90-102
Closed Access | Times Cited: 73
Forecasting China's total energy demand and its structure using ADL-MIDAS model
Yongda He, Boqiang Lin
Energy (2018) Vol. 151, pp. 420-429
Open Access | Times Cited: 66
Probability density forecasts for steam coal prices in China: The role of high-frequency factors
Lili Ding, Zhongchao Zhao, Meng Han
Energy (2021) Vol. 220, pp. 119758-119758
Open Access | Times Cited: 39
Mixed-frequency data Sampling Grey system Model: Forecasting annual CO2 emissions in China with quarterly and monthly economic-energy indicators
Yimeng An, Yaoguo Dang, Junjie Wang, et al.
Applied Energy (2024) Vol. 370, pp. 123531-123531
Closed Access | Times Cited: 4
Prospective Models of Financial Forecasting of budget Revenues
Alan K. Karaev, Olga Borisova
Finance Theory and Practice (2025) Vol. 29, Iss. 1, pp. 20-33
Open Access
Transmuting Unequally Spaced Data A MIDAS Regression Touch to Forecast Real GDP Growth in Brazil 
Pedro L. Valls Pereira
(2025)
Closed Access
Monthly forecasting of GDP with mixed-frequency multivariate singular spectrum analysis
Hossein Hassani, António Rua, Emmanuel Sirimal Silva, et al.
International Journal of Forecasting (2019) Vol. 35, Iss. 4, pp. 1263-1272
Open Access | Times Cited: 30
QRNN-MIDAS: A novel quantile regression neural network for mixed sampling frequency data
Qifa Xu, Shuting Liu, Cuixia Jiang, et al.
Neurocomputing (2021) Vol. 457, pp. 84-105
Closed Access | Times Cited: 25
Forecasting China's wastewater discharge using dynamic factors and mixed-frequency data
Lili Ding, Zhanlei Lv, Meng Han, et al.
Environmental Pollution (2019) Vol. 255, pp. 113148-113148
Open Access | Times Cited: 28
Boosting tax revenues with mixed-frequency data in the aftermath of COVID-19: The case of New York
Kajal Lahiri, Cheng Yang
International Journal of Forecasting (2021) Vol. 38, Iss. 2, pp. 545-566
Open Access | Times Cited: 21
A MIDAS multinomial logit model with applications for bond ratings
Cuixia Jiang, Yubing Nie, Qifa Xu
Global Finance Journal (2023) Vol. 57, pp. 100867-100867
Closed Access | Times Cited: 5
Real‐Time Fiscal Forecasting Using Mixed‐Frequency Data*
Stylianos Asimakopoulos, Joan Paredes, Thomas Warmedinger
Scandinavian Journal of Economics (2018) Vol. 122, Iss. 1, pp. 369-390
Open Access | Times Cited: 13
Forecasting the Daily Time‐Varying Beta of European Banks During the Crisis Period: Comparison Between GARCH Models and the Kalman Filter
Yuanyuan Zhang, Taufiq Choudhry
Journal of Forecasting (2016) Vol. 36, Iss. 8, pp. 956-973
Open Access | Times Cited: 12
Sources and Types of Big Data for Macroeconomic Forecasting
Philip M. E. Garboden
Advanced studies in theoretical and applied econometrics (2019), pp. 3-23
Closed Access | Times Cited: 12
An improved GM (1.1) model with background value optimization and Fourier-series residual error correction and its application in cost forecasting of coal mine
D Liu, Guoqing Li, Emmanuel Chanda, et al.
Gospodarka Surowcami Mineralnymi - Mineral Resources Management (2023)
Open Access | Times Cited: 4
Mixed-frequency Growth-at-Risk with the MIDAS-QR method: Evidence from China
Qifa Xu, Mengnan Xu, Cuixia Jiang, et al.
Economic Systems (2023) Vol. 47, Iss. 4, pp. 101131-101131
Closed Access | Times Cited: 4
A data-driven newsvendor problem: A high-dimensional and mixed-frequency method
Yang Cheng-hu, Haitang Wang, Xin Ma, et al.
International Journal of Production Economics (2023) Vol. 266, pp. 109042-109042
Closed Access | Times Cited: 4
Variable Weights Combination MIDAS Model Based on ELM for Natural Gas Price Forecasting
Lue Li, Caihong Han, Shengwei Yao, et al.
IEEE Access (2022) Vol. 10, pp. 52075-52093
Open Access | Times Cited: 6
Regional eco-efficiency prediction with Support Vector Spatial Dynamic MIDAS
Xianning Wang, Zhi Xiao
Journal of Cleaner Production (2017) Vol. 161, pp. 165-177
Open Access | Times Cited: 8
Forecasting China’s Steam Coal Prices Using Dynamic Factors and Mixed-Frequency Data
Chunyang Wang, Wanglin Kang
Polish Journal of Environmental Studies (2021) Vol. 30, Iss. 5, pp. 4241-4254
Open Access | Times Cited: 5
Fire officer leadership strategies for cost management
Leo R. Sedlmeyer, Rocky J. Dwyer
Disaster Prevention and Management An International Journal (2018) Vol. 27, Iss. 5, pp. 495-507
Open Access | Times Cited: 3
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