Sune Karlsson (), Stepan Mazur () and Mariya Raftab ()
Additional contact information
Sune Karlsson: Örebro University School of Business, Postal: Örebro University, School of Business, SE - 701 82 ÖREBRO, Sweden
Stepan Mazur: Örebro University School of Business, Postal: Örebro University, School of Business, SE - 701 82 ÖREBRO, Sweden
Mariya Raftab: Örebro University School of Business, Postal: Örebro University, School of Business, SE - 701 82 ÖREBRO, Sweden
Abstract: This paper focuses on identifying useful indicators for nowcasting GDP in Sweden. We analyze 35 monthly indicators spanning the period from 1993 to 2023. Additionally, we evaluate the group-wise performance of these indicators. The analysis is conducted using mixed-data sampling (MIDAS) and mixed-frequency VAR models in both individual and pooled setups for nowcasting. While the primary focus is on nowcasting, we also assess the performance of the indicators for backcasting and forecasting. For nowcasting, we identify 16 indicators in the individual setup and 23 indicators in the pooled setup that outperform the benchmark. Group-wise, indicators belonging to the survey, interest & exchange rates, and public finance groups exhibit strong performance in the individual setup. Notably, in the pooled setup, the output, survey, price, interest & exchange rates, and public finance groups demonstrate strong performance.
Keywords: Nowcasting; Swedish GDP; MIDAS; Mixed-frequency VAR
Language: English
26 pages, February 13, 2025
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