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1
Electricity demand analysis and forecasting : a
panel
cointegration approach
Shazly, Alaa el-
- In:
Energy economics
40
(
2013
),
pp. 251-258
Persistent link: https://www.econbiz.de/10010349564
Saved in:
2
Forecasting regional long-run energy demand : a functional coefficient
panel
approach
Chang, Yoosoon
;
Choi, Yongok
;
Kim, Chang Sik
;
Miller, …
- In:
Energy economics
96
(
2021
),
pp. 1-10
Persistent link: https://www.econbiz.de/10012817942
Saved in:
3
Panel
evidence on the ability of oil returns to predict stock returns in the G7 area
Westerlund, Joakim
;
Sharma, Susan Sunila
- In:
Energy economics
77
(
2019
),
pp. 3-12
Persistent link: https://www.econbiz.de/10012306331
Saved in:
4
Forecasting the real prices of crude oil : a robust weighted least squares approach
Wang, Yudong
;
Hao, Xianfeng
- In:
Energy economics
116
(
2022
),
pp. 1-18
Persistent link: https://www.econbiz.de/10013542061
Saved in:
5
Modeling, forecasting, and nowcasting U.S. CO2 emissions using many macroeconomic predictors
Bennedsen, Mikkel
;
Hillebrand, Eric
;
Koopman, Siem Jan
- In:
Energy economics
96
(
2021
),
pp. 1-17
Persistent link: https://www.econbiz.de/10012818590
Saved in:
6
Forecasting U.S. real GDP using oil prices : a time-varying parameter MIDAS model
Pan, Zhiyuan
;
Wang, Qing
;
Wang, Yudong
;
Li, Yang
- In:
Energy economics
72
(
2018
),
pp. 177-187
Persistent link: https://www.econbiz.de/10011972301
Saved in:
7
Forecasting the good and bad uncertainties of crude oil prices using a HAR framework
Gong, Xu
;
Lin, Boqiang
- In:
Energy economics
67
(
2017
),
pp. 315-327
Persistent link: https://www.econbiz.de/10011897926
Saved in:
8
Oil price assumptions for macroeconomic policy
Degiannakis, Stavros
;
Filis, George
- In:
Energy economics
117
(
2023
),
pp. 1-16
Persistent link: https://www.econbiz.de/10014436377
Saved in:
9
Forecasting Chinese provincial CO2 emissions : a universal and robust new-information-based grey model
Ding, Song
;
Zhang, Huahan
- In:
Energy economics
121
(
2023
),
pp. 1-18
Persistent link: https://www.econbiz.de/10014439028
Saved in:
10
Predicting gasoline prices using Michigan survey data
Baghestani, Hamid
- In:
Energy economics
50
(
2015
),
pp. 27-32
Persistent link: https://www.econbiz.de/10011563870
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