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      Research on China insurance demand forecasting: Based on mixed frequency data model

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          Abstract

          In this paper, we introduce the mixed-frequency data model (MIDAS) to China’s insurance demand forecasting. We select the monthly indicators Consumer Confidence Index (CCI), China Economic Policy Uncertainty Index (EPU), Consumer Price Index (PPI), and quarterly indicator Depth of Insurance (TID) to construct a Mixed Data Sampling (MIDAS) regression model, which is used to study the impact and forecasting effect of CCI, EPU, and PPI on China’s insurance demand. To ensure forecasting accuracy, we investigate the forecasting effects of the MIDAS models with different weighting functions, forecasting windows, and a combination of forecasting methods, and use the selected optimal MIDAS models to forecast the short-term insurance demand in China. The experimental results show that the MIDAS model has good forecasting performance, especially in short-term forecasting. Rolling window and recursive identification prediction can improve the prediction accuracy, and the combination prediction makes the results more robust. Consumer confidence is the main factor influencing the demand for insurance during the COVID-19 period, and the demand for insurance is most sensitive to changes in consumer confidence. Shortly, China’s insurance demand is expected to return to the pre-COVID-19 level by 2023Q2, showing positive development. The findings of the study provide new ideas for China’s insurance policymaking.

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          Most cited references28

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          Measuring Economic Policy Uncertainty

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            MIDAS Regressions: Further Results and New Directions

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              There is a risk-return trade-off after all

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                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: Funding acquisitionRole: MethodologyRole: SoftwareRole: ValidationRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: Formal analysisRole: MethodologyRole: SoftwareRole: SupervisionRole: ValidationRole: Writing – review & editing
                Role: Project administrationRole: SupervisionRole: Validation
                Role: Funding acquisitionRole: Project administration
                Role: Editor
                Journal
                PLoS One
                PLoS One
                plos
                PLOS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                31 July 2024
                2024
                : 19
                : 7
                : e0305523
                Affiliations
                [1 ] School of Medical Economics and Management, Anhui University of Chinese Medicine, Hefei, China
                [2 ] Key Laboratory of Data Science & Innovative Development of Traditional Chinese Medicine, Philosophy and Social Sciences of Anhui Province, Hefei, China
                Royal Melbourne Institute of Technology, AUSTRALIA
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Author information
                https://orcid.org/0009-0006-0770-5259
                Article
                PONE-D-24-03511
                10.1371/journal.pone.0305523
                11290696
                39083556
                5d1bbfa7-68ad-4e72-aa74-579fe438fd51
                © 2024 Wang et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 26 January 2024
                : 1 June 2024
                Page count
                Figures: 5, Tables: 6, Pages: 16
                Funding
                Funded by: Anhui Province University Scientific Research Project
                Award ID: 2023AH050701
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/100015801, Anhui Provincial Quality Engineering Project;
                Award ID: 2023xxkc175
                Award Recipient :
                Funded by: Anhui Province Science and Technology Innovation Strategy and Soft Science Research Special Project
                Award ID: 202006f01050072
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/100015801, Anhui Provincial Quality Engineering Project;
                Award ID: 2022xqhz036
                Anhui Province University Scientific Research Project (2023AH050701, Cheng Wang) Anhui Provincial Quality Engineering Project (2023xxkc175,Cheng Wang) Anhui Province Science and Technology Innovation Strategy and Soft Science Research Special Project (202006f01050072, Wenjing Sun) Anhui Provincial Quality Engineering Project (2022xqhz036, Qinghe Peng). The roles of authors and funders other than Qinghe Peng in research design, data collection and analysis, publication decisions, or manuscript preparation are presented in the paper files.
                Categories
                Research Article
                Engineering and Technology
                Management Engineering
                Risk Management
                Insurance
                Research and Analysis Methods
                Mathematical and Statistical Techniques
                Statistical Methods
                Forecasting
                Physical Sciences
                Mathematics
                Statistics
                Statistical Methods
                Forecasting
                Social Sciences
                Economics
                Macroeconomics
                Medicine and Health Sciences
                Medical Conditions
                Infectious Diseases
                Viral Diseases
                Covid 19
                Social Sciences
                Economics
                People and Places
                Geographical Locations
                Asia
                China
                Physical Sciences
                Mathematics
                Algebra
                Polynomials
                Social Sciences
                Economics
                Finance
                Custom metadata
                The interval for the monthly indicators CCI, EPU, and CPI is 2006M1-2022M3, and the interval for the quarterly indicator TID is 2006Q1-2022Q1. where CCI and CPI are downloaded from the Wind database ( www.wind.com.cn), and EPU is constructed using data from Baker et al. 2013, downloaded from www.policyuncertainty.com.

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