Symitsi, E orcid.org/0000-0001-6371-4156, Stamolampros, P orcid.org/0000-0001-8143-7244 and Karatzas, A (2021) Augmenting Household Expenditure Forecasts with Online Employee-generated Company Reviews. Public Opinion Quarterly, 85 (S1). pp. 463-491. ISSN 0033-362X
Abstract
We assess the ability of online employee-generated content in predicting consumption expenditures. In so doing, we aggregate millions of employee expectations for the next six-month business outlook of their employer and build an employee sentiment index. We test whether forward-looking employee sentiment can contribute to baseline models when forecasting aggregate consumption in the United States and compare its performance to well-established, survey-based consumer sentiment indexes. We reveal that online employee opinions have incremental information that can be used to augment the accuracy of consumption forecasting models and inform economic policy decisions.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © The Author(s) 2021. Published by Oxford University Press on behalf of American Association for Public Opinion Research. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Business (Leeds) > Accounting & Finance Division (LUBS) (Leeds) The University of Leeds > Faculty of Business (Leeds) > Management Division (LUBS) (Leeds) > Management Division Decision Research (LUBS) |
Depositing User: | Symplectic Publications |
Date Deposited: | 29 Mar 2021 09:49 |
Last Modified: | 25 Jun 2023 22:37 |
Status: | Published |
Publisher: | Oxford University Press |
Identification Number: | 10.1093/poq/nfab017 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:172625 |