Indexing Economic Fluctuation Narratives from Keiki Watchers Survey
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arXiv
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| Format: | Preprint |
| Published: |
2024
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| _version_ | 1866913655348527104 |
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| author | Shigetsugu, Eriko Sakaji, Hiroki Noda, Itsuki |
| author_facet | Shigetsugu, Eriko Sakaji, Hiroki Noda, Itsuki |
| contents | In this paper, we design indices of economic fluctuation narratives derived from economic surveys. Companies, governments, and investors rely on key metrics like GDP and industrial production indices to predict economic trends. However, they have yet to effectively leverage the wealth of information contained in economic text, such as causal relationships, in their economic forecasting. Therefore, we design indices of economic fluctuation from economic surveys by using our previously proposed narrative framework. From the evaluation results, it is observed that the proposed indices had a stronger correlation with cumulative lagging diffusion index than other types of diffusion indices. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2412_01265 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Indexing Economic Fluctuation Narratives from Keiki Watchers Survey Shigetsugu, Eriko Sakaji, Hiroki Noda, Itsuki Computation and Language Artificial Intelligence In this paper, we design indices of economic fluctuation narratives derived from economic surveys. Companies, governments, and investors rely on key metrics like GDP and industrial production indices to predict economic trends. However, they have yet to effectively leverage the wealth of information contained in economic text, such as causal relationships, in their economic forecasting. Therefore, we design indices of economic fluctuation from economic surveys by using our previously proposed narrative framework. From the evaluation results, it is observed that the proposed indices had a stronger correlation with cumulative lagging diffusion index than other types of diffusion indices. |
| title | Indexing Economic Fluctuation Narratives from Keiki Watchers Survey |
| topic | Computation and Language Artificial Intelligence |
| url | https://arxiv.org/abs/2412.01265 |