{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,8,2]],"date-time":"2025-08-02T17:27:04Z","timestamp":1754155624022,"version":"3.41.2"},"reference-count":37,"publisher":"Emerald","issue":"5","license":[{"start":{"date-parts":[[2020,4,20]],"date-time":"2020-04-20T00:00:00Z","timestamp":1587340800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.emerald.com\/insight\/site-policies"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["K"],"published-print":{"date-parts":[[2021,5,3]]},"abstract":"<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Purpose<\/jats:title>\n<jats:p>The purpose of this paper is to calculate the local guaranteed fiscal revenue with the local fiscal revenue of 31 provinces, and predict their guaranteed fiscal revenue in 2018 with the artificial neural network (ANN).<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Design\/methodology\/approach<\/jats:title>\n<jats:p>The principal components analysis (PCA), particle swarm optimization (PSO) and extreme learning machine (ELM) model was designed to produce the inputs of KMV model. Then the KMV model was used for obtaining the default probabilities under different issuance scales. Data were collected from Wind Database. MATLAB 2018b and SPSS 22 were used in the field of modeling and results analysis.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Findings<\/jats:title>\n<jats:p>This study\u2019s findings show that PCA\u2013PSO\u2013ELM proposed in this research has the highest accuracy in terms of the prediction compared with ELM, back propagation neural network and auto regression. And PCA\u2013PSO\u2013ELM\u2013KMV model can calculate the secure issuance scale of local government bonds effectively.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Practical implications<\/jats:title>\n<jats:p>The sustainability forecast in this study can help local governments effectively control the scale of debt issuance, strengthen the budget management of local debt and establish the corresponding risk warning mechanism, which could make local governments maintain good credit ratings.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Originality\/value<\/jats:title>\n<jats:p>This study sheds new light on helping local governments avoid financial risks effectively, and it is conducive to establish a debt repayment reserve system for local governments and the proper arrangement for stock debt.<\/jats:p>\n<\/jats:sec>","DOI":"10.1108\/k-10-2019-0699","type":"journal-article","created":{"date-parts":[[2020,4,29]],"date-time":"2020-04-29T07:05:56Z","timestamp":1588143956000},"page":"1125-1143","source":"Crossref","is-referenced-by-count":2,"title":["A prediction model for the secure issuance scale of Chinese local government bonds"],"prefix":"10.1108","volume":"50","author":[{"given":"Bowen","family":"Jia","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiaying","family":"Wu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Juan","family":"Du","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yun","family":"Ji","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lina","family":"Zhu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"140","published-online":{"date-parts":[[2020,4,20]]},"reference":[{"issue":"2","key":"key2024071512195017500_ref001","doi-asserted-by":"publisher","first-page":"297","DOI":"10.1177\/0312896211432369","article-title":"The fluctuating default risk of Australian banks","volume":"37","year":"2012","journal-title":"Australian Journal of Management"},{"issue":"4","key":"key2024071512195017500_ref002","doi-asserted-by":"publisher","first-page":"727","DOI":"10.1016\/s0378-4266(03)00197-3","article-title":"Issues in the credit risk modeling of retail markets","volume":"28","year":"2004","journal-title":"Journal of Banking and Finance"},{"key":"key2024071512195017500_ref003","doi-asserted-by":"publisher","first-page":"31","DOI":"10.1016\/j.jmoneco.2017.08.004","article-title":"Low frequency effects of macroeconomic news on government bond yields","volume":"92","year":"2017","journal-title":"Journal of Monetary Economics"},{"key":"key2024071512195017500_ref004","doi-asserted-by":"publisher","first-page":"115","DOI":"10.1016\/j.seppur.2019.115868","article-title":"Prediction of full-scale filtration plant performance using artificial neural networks based on principal component analysis","volume":"230","year":"2020","journal-title":"Separation and Purification Technology"},{"issue":"5","key":"key2024071512195017500_ref005","doi-asserted-by":"publisher","first-page":"559","DOI":"10.1016\/j.bar.2018.02.003","article-title":"Predicting unlisted SMEs\u2019 default: incorporating market information on accounting-based models for improved accuracy","volume":"50","year":"2018","journal-title":"The British Accounting Review"},{"issue":"4","key":"key2024071512195017500_ref006","doi-asserted-by":"publisher","first-page":"685","DOI":"10.1111\/j.1538-4616.2012.00506.x","article-title":"Too dispersed to monitor? 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