【摘要】：基礎(chǔ)設(shè)施既作為一項政府公共支出可以直接促進經(jīng)濟增長，同時兼具“溢出效應(yīng)”和“網(wǎng)絡(luò)效應(yīng)”等特殊性質(zhì)，是一國經(jīng)濟發(fā)展必不可少的重要物質(zhì)基礎(chǔ)�；A(chǔ)設(shè)施的投資建設(shè)對國民經(jīng)濟、行業(yè)發(fā)展以及所在地區(qū)的社會經(jīng)濟產(chǎn)生重大而深遠的影響，投資形成的后果呈連鎖反應(yīng)和投資乘數(shù)效應(yīng)。然而其投資規(guī)模并非越大越好，過大的基礎(chǔ)設(shè)施投資規(guī)模會對私人資本產(chǎn)生擠出效應(yīng)，因此存在一個帕累托最優(yōu)的問題，應(yīng)與私人物品的供應(yīng)、總體經(jīng)濟的增長等相協(xié)調(diào)。鑒于此，如何衡量各省基礎(chǔ)設(shè)施的實際投資是否達到最優(yōu)規(guī)模？如何根據(jù)各項基礎(chǔ)設(shè)施投資的缺口和緊缺程度，做出合理的投資安排？不同地區(qū)之間對基礎(chǔ)設(shè)施的需求類型是否是相同的？以及如何科學(xué)、全面、可靠地對基礎(chǔ)設(shè)施的投資規(guī)模進行優(yōu)化預(yù)測？對于我國基礎(chǔ)設(shè)施資金規(guī)劃以及基礎(chǔ)設(shè)施項目投融資管理、確定政府補貼額度有著重要的理論意義和現(xiàn)實意義。 本文以基礎(chǔ)設(shè)施投資規(guī)模及其相關(guān)影響因素為研究對象，首先利用DEMATEL因素分析模型識別影響基礎(chǔ)設(shè)施投資規(guī)模的關(guān)鍵因素，其次將最優(yōu)政府支出模型的政府公共支出分項引入生產(chǎn)函數(shù)，得到基礎(chǔ)設(shè)施投資的邊際產(chǎn)出與最優(yōu)規(guī)模理論模型。進而采用中國1996-2012年省級面板數(shù)據(jù)進行實證研究，探討我國以及東、中、西部地區(qū)基礎(chǔ)設(shè)施投資的產(chǎn)出效應(yīng)和最優(yōu)投資規(guī)模，并將我國的實際投資規(guī)模和最優(yōu)規(guī)模水平相比較，檢驗各項基礎(chǔ)設(shè)施的實際投資是否達到最優(yōu)規(guī)模？以及為實現(xiàn)投資收益最大化，東中西地區(qū)各項基礎(chǔ)設(shè)施的投資次序建議。在此基礎(chǔ)上，將基于改進的GA-PSO-V-SVR模型應(yīng)用于基礎(chǔ)設(shè)施投資規(guī)模預(yù)測，，同時為得到有效輸入變量，本文結(jié)合前文DEMATEL因素分析模型所得結(jié)果，以剔除基礎(chǔ)設(shè)施投資規(guī)模影響因素的冗余變量，從而達到降維去噪的目的。最后以全國以及東中西部地區(qū)1990—2012年的基礎(chǔ)設(shè)施投資相關(guān)數(shù)據(jù)進行實例研究，預(yù)測全國以及各地區(qū)各項基礎(chǔ)設(shè)施2013年、2015年及2020年的投資規(guī)模，為政府基礎(chǔ)設(shè)施投資提供決策參考。
[Abstract]:As a government public expenditure, infrastructure can directly promote economic growth, and it also has special properties such as "spillover effect" and "network effect". It is an indispensable material basis for a country's economic development. The investment and construction of infrastructure have great and far-reaching influence on the national economy, the development of the industry and the social economy of the region, and the consequences of the investment are chain reaction and investment multiplier effect. However, the larger the investment scale is, the better, and the larger the infrastructure investment scale is, the more the private capital will be squeezed out. Therefore, there is a Pareto optimal problem, which should be coordinated with the supply of private goods and the growth of the overall economy. In view of this, how can we measure whether the actual investment in infrastructure in the provinces is optimal? How to make reasonable investment arrangements according to the gap and shortage of infrastructure investment? Is the type of infrastructure demand the same across regions? And how to optimize and predict the scale of infrastructure investment scientifically, comprehensively and reliably? It is of great theoretical and practical significance to determine the amount of government subsidy for the planning of infrastructure funds and the management of investment and financing of infrastructure projects in China. In this paper, the scale of infrastructure investment and its related influencing factors are studied. Firstly, the key factors affecting the scale of infrastructure investment are identified by using the DEMATEL factor analysis model. Secondly, the government public expenditure of the optimal government expenditure model is introduced into the production function, and the marginal output and optimal scale model of infrastructure investment are obtained. Then using the provincial panel data from 1996 to 2012 in China, the paper discusses the output effect and optimal investment scale of infrastructure investment in China and the east, middle and west regions, and compares the actual investment scale with the optimal scale level in China. Test whether the actual investment in infrastructure is optimal? And in order to maximize investment returns, East, West and East infrastructure investment order suggestions. On this basis, the improved GA-PSO-V-SVR model is applied to the prediction of the scale of infrastructure investment. In order to obtain the effective input variables, this paper combines the previous DEMATEL factor analysis model to obtain the results. In order to eliminate the redundant variables which influence the scale of infrastructure investment, the dimension reduction and denoising can be achieved. Finally, using the relevant data of infrastructure investment from 1990 to 2012 in China and the eastern, western and central regions, the paper forecasts the investment scale of the whole country and all regions in 2013, 2015 and 2020. To provide decision-making reference for government infrastructure investment.
【學(xué)位授予單位】：華南理工大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2014
【分類號】：F299.24

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