全國能源生產(chǎn)和消費(fèi)彈性系數(shù)的分析及預(yù)測

信息計(jì)算科學(xué)論文編號:XXLW108 論文字?jǐn)?shù):14846,頁數(shù):44

目  錄
摘  要 i
Abstract ii
目  錄 iii
第一章    緒  論 1
1.1   研究動(dòng)機(jī)與目的 1
1.2   研究的背景 1
1.2.1  我國能源以及國民經(jīng)濟(jì) 1
1.2.2  我國能源彈性系數(shù) 2
1.3   研究方法與系統(tǒng)描述 3
1.4   論文內(nèi)容概述 4
第二章    能源彈性系數(shù) 5
2.1   能源彈性系數(shù) 5
2.1.1  能源消費(fèi)彈性系數(shù) 5
2.1.2  能源生產(chǎn)彈性系數(shù) 6
2.2   電力彈性系數(shù) 6
第三章    時(shí)間序列分析 7
3.1   時(shí)間序列 7
3.1.1  平穩(wěn)時(shí)間序列 8
3.1.2  非平穩(wěn)時(shí)間序列 10
第四章    彈性系數(shù)的實(shí)證研究 11
4.1   國內(nèi)關(guān)于彈性系數(shù)的實(shí)證研究 11
4.2   能源消費(fèi)彈性系數(shù)的分析與預(yù)測 11
4.3   能源生產(chǎn)彈性系數(shù)的分析與預(yù)測 15
4.4   電力消費(fèi)彈性系數(shù)的分析與預(yù)測 18
4.5   電力生產(chǎn)彈性系數(shù)的分析與預(yù)測 21
第五章   電力消費(fèi)量的聚類分析 24
第六章    結(jié) 論 26
致  謝 27
參考文獻(xiàn) 28
附錄A：程序 29
附錄B：數(shù)據(jù) 37

摘  要
 當(dāng)代時(shí)間序列分析主要是建立相對簡單的模型，能夠用于經(jīng)濟(jì)數(shù)據(jù)的預(yù)測、解釋與假設(shè)檢驗(yàn)。時(shí)間序列模型最初主要是作為預(yù)測的輔助工具，因此，經(jīng)濟(jì)學(xué)家創(chuàng)造了一套方法，可將時(shí)間序列分解為趨勢性、季節(jié)性、周期性和無規(guī)則成分。1970年，Box和Jenkins提出了以隨機(jī)理論為基礎(chǔ)的時(shí)間序列分析方法，使時(shí)間序列分析理論上升到了一個(gè)新的高度，預(yù)測的精確度大大提高。平穩(wěn)時(shí)間序列與非平穩(wěn)時(shí)間序列有著完全不同的經(jīng)濟(jì)含義和統(tǒng)計(jì)性質(zhì)，它們來自不同數(shù)據(jù)生成過程，其處理方法也迥然不同。自回歸移動(dòng)平均模型（ARMA模型）是研究時(shí)間序列的重要方法，由自回歸模型（簡稱AR模型）與滑動(dòng)平均模型（簡稱MA模型）混合構(gòu)成。
 能源是國家發(fā)展和安全的重要保證，是推動(dòng)經(jīng)濟(jì)社會系統(tǒng)運(yùn)轉(zhuǎn)的動(dòng)力，但能源的利用也會帶來嚴(yán)重的環(huán)境生態(tài)問題。能源是經(jīng)濟(jì)的命脈，是發(fā)展國民經(jīng)濟(jì)和提高人民生活水平的重要保障。我國經(jīng)濟(jì)正處于一個(gè)穩(wěn)定發(fā)展的時(shí)期，能源需求量在未來幾十年內(nèi)將快速增長，我國對世界能源市場的依賴性也將不斷增強(qiáng)。為此本文將利用ARMA模型以及1990-2007年歷年全國能源彈性系數(shù)對能源發(fā)展和國民經(jīng)濟(jì)的增長之間的關(guān)系進(jìn)行分析及預(yù)測，并對2008年我國各省電力消費(fèi)量做聚類分析。
關(guān)鍵詞：ARMA模型  能源  國民經(jīng)濟(jì)

Abstract
 In modern time, time series analysis is especially used to establish a relatively simple model. And it can be used to forecast economic data, interpretation and hypothesis testing. Time series model was originally forecast primarily as a support tool. Therefore, economists create a set of methods that time series can be decomposed as the trend, seasonal, cyclical, and no rules of composition. 1970, Box and Jenkins proposed time series analysis theory which base on the theory of random. So that time series analysis methods rose to a new level, and the prediction accuracy greatly improved. Stationary time series and non-stationary time series come form different data generating processes, they have different contents, properties and analysis technique. Autoregressive moving average model （ARMA model） is an important method of time series. It is a mixed form of autoregressive model (AR model) and moving average models (MA model).
 Energy is an important guarantee of national development and security. And it is the power to promote the system of economical society operation. But energy using will cause serious ecological problems in the environment. Energy is the lifeblood of the economy. And it is an important guarantee of the development of national economy and the people's standard of living increase. Chinese economy is in a stable period of development so that energy demand in the coming decades will be rapid growth. Dependence on world energy markets of china will continue to increase. Therefore, the paper will use the ARMA model and the calendar year 1990-2007 national energy elasticity coefficient of energy development and the relationship between national economic growth analysis and forecasting, and in 2008 electricity consumption in each province to do cluster analysis.
Key words: ARMA model  energy  national economy