Data-driven estimation of economic indicators with search big data in discontinuous situation
Economic indicators are essential for policymaking and strategic decisions in both the public and private sectors. However, due to delays in the release of government indicators based on macroeconomic factors, there is a high demand for timely estimates or “nowcasting”. Many attempts have been made...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
KeAi Communications Co., Ltd.
2023-11-01
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| Series: | Journal of Finance and Data Science |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2405918823000223 |
| _version_ | 1797656143715106816 |
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| author | Goshi Aoki Kazuto Ataka Takero Doi Kota Tsubouchi |
| author_facet | Goshi Aoki Kazuto Ataka Takero Doi Kota Tsubouchi |
| author_sort | Goshi Aoki |
| collection | DOAJ |
| description | Economic indicators are essential for policymaking and strategic decisions in both the public and private sectors. However, due to delays in the release of government indicators based on macroeconomic factors, there is a high demand for timely estimates or “nowcasting”. Many attempts have been made to overcome this challenge using macro indicators and key variables such as keywords from social networks and search queries, but with a reliance on human selection. We present a fully data-driven methodology using non-prescribed search engine query data (Search Big Data) to approximate economic variables in real time. We evaluate this model by estimating representative Japanese economic indicators and confirm its success in nowcasting prior to official announcements, even during the COVID-19 pandemic, unlike human-selected variable models that struggled. Our model shows consistent performance in nowcasting indices both before and under the pandemic before government announcements, adapting to unexpected circumstances and rapid economic fluctuations. An exhaustive analysis of key queries reveals the pivotal role of libidinal drives and the pursuit of entertainment in influencing economic indicators within the temporal and geographic context examined. This research exemplifies a novel approach to economic forecasting that utilizes contemporary data sources and transcends the limitations of existing methodologies. |
| first_indexed | 2024-03-11T17:25:06Z |
| format | Article |
| id | doaj.art-bd39137d110545a98b73028dd2766a47 |
| institution | Directory Open Access Journal |
| issn | 2405-9188 |
| language | English |
| last_indexed | 2024-03-11T17:25:06Z |
| publishDate | 2023-11-01 |
| publisher | KeAi Communications Co., Ltd. |
| record_format | Article |
| series | Journal of Finance and Data Science |
| spelling | doaj.art-bd39137d110545a98b73028dd2766a472023-10-19T04:22:36ZengKeAi Communications Co., Ltd.Journal of Finance and Data Science2405-91882023-11-019100106Data-driven estimation of economic indicators with search big data in discontinuous situationGoshi Aoki0Kazuto Ataka1Takero Doi2Kota Tsubouchi35322 Endo, Fujisawa-shi, Kanagawa 252-0882, Japan; Kioi Tower 1-3 Kioicho, Chiyoda-ku, Tokyo 102-8282, Japan5322 Endo, Fujisawa-shi, Kanagawa 252-0882, Japan; Kioi Tower 1-3 Kioicho, Chiyoda-ku, Tokyo 102-8282, Japan; Corresponding author.2-15-45 Mita, Minato-ku, Tokyo 108-8345, JapanKioi Tower 1-3 Kioicho, Chiyoda-ku, Tokyo 102-8282, JapanEconomic indicators are essential for policymaking and strategic decisions in both the public and private sectors. However, due to delays in the release of government indicators based on macroeconomic factors, there is a high demand for timely estimates or “nowcasting”. Many attempts have been made to overcome this challenge using macro indicators and key variables such as keywords from social networks and search queries, but with a reliance on human selection. We present a fully data-driven methodology using non-prescribed search engine query data (Search Big Data) to approximate economic variables in real time. We evaluate this model by estimating representative Japanese economic indicators and confirm its success in nowcasting prior to official announcements, even during the COVID-19 pandemic, unlike human-selected variable models that struggled. Our model shows consistent performance in nowcasting indices both before and under the pandemic before government announcements, adapting to unexpected circumstances and rapid economic fluctuations. An exhaustive analysis of key queries reveals the pivotal role of libidinal drives and the pursuit of entertainment in influencing economic indicators within the temporal and geographic context examined. This research exemplifies a novel approach to economic forecasting that utilizes contemporary data sources and transcends the limitations of existing methodologies.http://www.sciencedirect.com/science/article/pii/S2405918823000223NowcastingBusiness cycle indicatorsSearch big dataJapanese economyDiscontinuityHumanneeds |
| spellingShingle | Goshi Aoki Kazuto Ataka Takero Doi Kota Tsubouchi Data-driven estimation of economic indicators with search big data in discontinuous situation Journal of Finance and Data Science Nowcasting Business cycle indicators Search big data Japanese economy Discontinuity Humanneeds |
| title | Data-driven estimation of economic indicators with search big data in discontinuous situation |
| title_full | Data-driven estimation of economic indicators with search big data in discontinuous situation |
| title_fullStr | Data-driven estimation of economic indicators with search big data in discontinuous situation |
| title_full_unstemmed | Data-driven estimation of economic indicators with search big data in discontinuous situation |
| title_short | Data-driven estimation of economic indicators with search big data in discontinuous situation |
| title_sort | data driven estimation of economic indicators with search big data in discontinuous situation |
| topic | Nowcasting Business cycle indicators Search big data Japanese economy Discontinuity Humanneeds |
| url | http://www.sciencedirect.com/science/article/pii/S2405918823000223 |
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