Refined oil prices with family cars

International Journal of Mathematics and Systems Science

View Publication Info
Field Value
Title Refined oil prices with family cars
Creator Zhen, Aiqing
Huo, Cuxiao
Feng, Chunqing
Description Nowadays, more and more cars have begun to enter into innumerable families; the family car has become a necessity for Chinese households who have certain purchasing power. However, the ups and downs of oil prices have brought some impact on people's automobile consumption activities. Therefore, after collecting the information of the oil price and family car consumer, carried on through in-depth analysis of the relevant data with reasonable relationship, and then developed a suitable for China's national conditions and finished oil pricing model, thereby the National Development and Reform Commission have proposed the suggestion for China's refined oil pricing mechanisms and promoting the healthy development of new energy vehicles with specific measures. For question 1, through the problem analysis and information access, combined with the past and current situation of the domestic refined oil prices, we analyze the following seven factors: international crude oil prices, China's annual crude oil imports, China's annual crude oil exports, crude oil output in China, China's annual GDP per capita, China's annual consumption of crude oil, the total annual energy consumption in China, all have influence on China's refined oil prices. By monadic linear regression analysis, annual average prices of domestic refined oil products have a certain correlation with the various influencing factors, and then by multiple linear regression way eventually concluded the final relationship between oil prices and the influence factors, which compared with the current price, and make reasonable evaluation model. Through the establishment of various influencing factors and function of time, and using the evaluation model for refined oil product price to make reasonable forecast. According to this model, in order to predict refined oil product price as $122.15 per barrel in 2016. For question two, we basically sums up three key factor which influence the quantity of family vehicle: China's oil product prices, the annual GDP per capita, total road mileage. Through Excel to make the relationship curves of different quantity of family cars against influencing factors, and use Grey Forecasting method to forecast the quantity of family cars. And carries on the residual error test, it is used to conclude that the rationality of the model is highly. The number of private cars of the city of xi 'an is predicts that to 8.302 million vehicles by 2020. For question three, we discussed the relationship between international crude oil prices and domestic exports of crude oil export with domestic refined oil prices, through its multiple linear regressions to get the final pricing model. For question four, according to three previous established models, we proposed China's refined oil pricing mechanism proposal to the national development and Reform Commission: perfect price controls, deeper product market, and integration of resources consideration and environmental protection class tax types, adjust the consumption tax collection and Administration links, and improve the production cost accounting.
Publisher EnPress Publisher LLC
Contributor Mathematics and Physics College, Dongying Teachers College, Shandong, China
Date 2018-02-07
Type info:eu-repo/semantics/article
Peer-reviewed Article
Format application/pdf
Source International Journal of Mathematics and Systems Science; Vol 1, No 1 (published)
Language eng
Rights Copyright (c) 2018 International Journal of Mathematics and Systems Science

Contact Us

The PKP Index is an initiative of the Public Knowledge Project.

For PKP Publishing Services please use the PKP|PS contact form.

For support with PKP software we encourage users to consult our wiki for documentation and search our support forums.

For any other correspondence feel free to contact us using the PKP contact form.

Find Us


Copyright © 2015-2018 Simon Fraser University Library