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Revenue Forecasting with Machine Learning Approach
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머신러닝 접근의 재정관리: 세입추세 예측모형 연구

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Type
Academic journal
Author
Il Hwan Chung (성균관대학교)
Journal
성균관대학교 국정관리대학원 국정관리연구 국정관리연구 제16권 제4호 KCI Accredited Journals
Published
2021.12
Pages
1 - 28 (28page)

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Revenue Forecasting with Machine Learning Approach
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Fiscal sustainability received much attention due to recent pandemic and countercyclical fiscal policy. This study attempts to apply the logic of machine learning algorithms to financial management for policy implications. Practically, the growing evidence has documented the increasing use of cases with machine learning algorithms. However, there are limited studies with in scholarly works from the field of public administration. Using 50 years of revenue data from Seoul metropolitan area and 20 years of 69 local governments, our findings reveal that exponential smoothing works better for Seoul metropolitan area, while KNN is superior to revenue forecasting in other local governments.
#세입예측 #기계학습 #인공지능 #지방재정 #머신러닝 #Revenue Forecasting #Machine Learning #Fiscal Sustainability

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