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A bootstrap method to test Granger-causality in the frequency domain
Farnè, Matteo
;
Montanari, Angela
- In:
Computational economics
59
(
2022
)
3
,
pp. 935-966
Persistent link: https://www.econbiz.de/10013169203
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2
Post‑COVID recovery and long‑run forecasting of Indian GDP with Factor‑Augmented Error Correction Model (FECM)
Maiti, Dibyendu
;
Kumar, Naveen
;
Jha, Debajit
;
Sarkar, …
- In:
Computational economics
63
(
2024
)
3
,
pp. 1095-1120
Persistent link: https://www.econbiz.de/10014546333
Saved in:
3
A novel prediction model : ELM-ABC for annual GDP in the case of SCO countries
Xu, Xiaohan
;
Rogers, Roy Anthony
;
Estrada, Mario Arturo Ruiz
- In:
Computational economics
62
(
2023
)
4
,
pp. 1545-1566
Persistent link: https://www.econbiz.de/10014437500
Saved in:
4
Comparing out-of-sample performance of machine learning methods to forecast U.S. GDP growth
Chu, Ba
;
Qureshi, Shafiullah
- In:
Computational economics
62
(
2023
)
4
,
pp. 1567-1609
Persistent link: https://www.econbiz.de/10014437505
Saved in:
5
Quantum computing and deep learning methods for GDP growth forecasting
Alaminos, David
;
Salas, M. Belén
;
Fernández Gámez, …
- In:
Computational economics
59
(
2022
)
2
,
pp. 803-829
Persistent link: https://www.econbiz.de/10013169077
Saved in:
6
Forecasting of real GDP growth using machine learning models : gradient boosting and random forest approach
Yoon, Jaehyun
- In:
Computational economics
57
(
2021
)
1
,
pp. 247-265
Persistent link: https://www.econbiz.de/10012486898
Saved in:
7
Nowcasting US GDP using tree-based ensemble models and dynamic factors
Soybilgen, Barış
;
Yazgan, Mustafa Ege
- In:
Computational economics
57
(
2021
)
1
,
pp. 387-417
Persistent link: https://www.econbiz.de/10012486916
Saved in:
8
Yield curve and recession forecasting in a Machine Learning framework
Gkonkas, Periklēs
;
Papadimitriou, Theophilos
; …
- In:
Computational economics
45
(
2015
)
4
,
pp. 635-645
Persistent link: https://www.econbiz.de/10011440977
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