Research on the Forecast and Development of China’s Public Fiscal Revenue Based on ARIMA Model

Journals Menu

Follow SCIRP

ISSN Print: 2162-2078
ISSN Online: 2162-2086
www.scirp.org/journal/tel
E-mail: tel@scirp.org

"Research on the Forecast and Development of China’s Public Fiscal Revenue Based on ARIMA Model"
written by Qingjie Liu, Huachun Wang,
published by Theoretical Economics Letters, Vol.5 No.4, 2015

has been cited by the following article(s):

[1]	Evaluation of forecasting models for improved passenger market management and rolling stock planning on Indian railways
	foresight, 2024

[2]	Modeling And Simulation Of Plastic Wastes Generation For Operational Planning And Management In The Bonaberi Industrial Region, Cameroon
	International Journal of Science …, 2022

[3]	Arima Models For Forecasting Own Source Revenue For The County Of Machakos
	2021

[4]	Seeking Accuracy in Forecasting Demand and Selling Prices: Comparison of Various Methods
	2021

[5]	Prediction of Regional Revenue and Expenditure Budget using Autoregressive Integrated Moving Average (ARIMA)
	2020

[6]	Разработка математических моделей прогнозирования объемов продаж автомобилей с использованием методов машинного обучения
	2019

[7]	Forecasting of demand using ARIMA model
	International Journal of Engineering Business Management, 2018

[1]	A Time Series Approach to Forecasting Financial Indicators in the Wholesale and Retail Trade World, 2025 DOI:10.3390/world6010005

[2]	Evaluation of forecasting models for improved passenger market management and rolling stock planning on Indian railways foresight, 2025 DOI:10.1108/FS-09-2022-0105

[3]	Forecasting in Mathematics - Recent Advances, New Perspectives and Applications 2021 DOI:10.5772/intechopen.93171

[4]	Prediction of Regional Revenue and Expenditure Budget using Autoregressive Integrated Moving Average (ARIMA) IOP Conference Series: Materials Science and Engineering, 2020 DOI:10.1088/1757-899X/851/1/012064

[5]	FORECASTING OF TAX REVENUES OF THE CONSOLIDATED BUDGET OF UKRAINE BASED ON TIME SERIES ANALYSIS Black Sea Economic Studies, 2020 DOI:10.32843/bses.55-30

[6]	Forecasting of demand using ARIMA model International Journal of Engineering Business Management, 2018 DOI:10.1177/1847979018808673

[7]	Forecasting of demand using ARIMA model International Journal of Engineering Business Management, 2018 DOI:10.1177/1847979018808673

Follow SCIRP