基于EVA的我國制造業(yè)上市公司并購績效的實證研究
本文選題:制造業(yè) + 并購績效; 參考:《遼寧大學(xué)》2013年碩士論文
【摘要】:企業(yè)的并購重組在發(fā)達國家中已經(jīng)發(fā)展了一百多年,共經(jīng)歷5次大規(guī)模的并購浪潮。20世紀90年代以來,全球化和互聯(lián)網(wǎng)的迅猛發(fā)展再次打破了原有的經(jīng)濟格局,第五次并購浪潮應(yīng)運而生。這次并購浪潮以美國和英國的大型企業(yè)為火車頭,帶動了其他發(fā)達國家的并購熱情。這次并購浪潮的特點主要表現(xiàn)在:以跨國并購為主、參與企業(yè)資本雄厚,交易金額龐大,,涉及領(lǐng)域廣闊,新興產(chǎn)業(yè)與傳統(tǒng)產(chǎn)業(yè)并購齊頭并進。 而我國企業(yè)的并購出現(xiàn)在改革開放以后,發(fā)展歷史相對較短,共經(jīng)歷三個發(fā)展階段。隨著2002年中國正式加入WTO,經(jīng)濟全球化的發(fā)展,資本市場的逐步完善,我國也掀起了新一輪的并購潮。作為我國國民經(jīng)濟的支柱產(chǎn)業(yè),制造業(yè)是我國經(jīng)濟增長的主導(dǎo)部門和經(jīng)濟轉(zhuǎn)型的基礎(chǔ),因此研究我國制造業(yè)上市公司的并購績效對保持制造業(yè)企業(yè)的長期穩(wěn)定發(fā)展有重要意義。 本文以2008年我國制造業(yè)上市公司的并購為研究對象,采用EVA作為評價上市公司績效的指標,通過計算07年至11年制造業(yè)上市公司EVA的數(shù)值,比較分析EVA的走向,得到如下結(jié)論:(1)并購當(dāng)年制造業(yè)上市公司的績效下降明顯,并購后第一年較并購當(dāng)年有所上升,但仍然低于并購前一年,并購后第二年及第三年的績效高于并購前一年;(2)國有控股、行業(yè)相關(guān)性及關(guān)聯(lián)交易對制造業(yè)上市公司都存在不同程度的影響。 由于筆者知識結(jié)構(gòu)的局限性、研究時間的倉促和我國相關(guān)領(lǐng)域的特殊情況,本文在采用EVA對上市公司并購績效進行研究時可能存在以下不足:(1)EVA績效評價模型雖然它優(yōu)于傳統(tǒng)的會計研究法,但是其模型仍然是建立在財務(wù)指標的基礎(chǔ)上,沒有考慮非財務(wù)指標對績效的評價。(2)在實證研究部分,本文局限于對并購公司的研究,沒有對被并購公司進行研究,比較分析不足。(3)在對并購績效影響因素進行分析時,由于受到選取樣本的限制,影響因素指標較少。
[Abstract]:M & A of enterprises has been developed for more than 100 years in developed countries. After five large-scale M & A waves since 1990s, globalization and the rapid development of the Internet have once again broken the original economic pattern.The fifth wave of mergers and acquisitions came into being.This wave of mergers and acquisitions, with large companies in the United States and the United Kingdom as the locomotive, led to the acquisition enthusiasm of other developed countries.The characteristics of this wave of M & A are as follows: transnational M & A is the main part, the capital of the participating enterprises is abundant, the transaction amount is huge, the scope of the merger and acquisition is broad, and the new industries and the traditional industries are in step with each other.The M & A of Chinese enterprises appeared after the reform and opening up, the history of development is relatively short, and it has experienced three stages of development.With China's entry into WTO in 2002, the development of economic globalization and the gradual improvement of capital market, China has also set off a new wave of mergers and acquisitions.As the pillar industry of our national economy, manufacturing industry is the leading department of economic growth and the basis of economic transformation. Therefore, it is of great significance to study the M & A performance of listed manufacturing companies in order to maintain the long-term and stable development of manufacturing enterprises.This paper takes the M & A of Chinese manufacturing listed companies in 2008 as the research object, adopts EVA as the index to evaluate the performance of listed companies, and compares and analyzes the trend of EVA by calculating the value of EVA of manufacturing listed companies from 2007 to 11 years.The following conclusion is drawn: 1) the performance of the manufacturing listed companies in the year of M & A decreased significantly. The first year of M & A was higher than that of the year of M & A, but still lower than that of the year before the merger.The performance in the second and third years after M & A is higher than that in the year before M & A.Due to the limitations of the author's knowledge structure, the haste of the research time and the special situation of the related fields in China,In this paper, we use EVA to study the M & A performance of listed companies. Although it is superior to the traditional accounting research method, the model is still based on the financial indicators.In the part of empirical research, this paper is limited to the research of M & A companies, and does not study the M & A companies. The comparative analysis is insufficient when analyzing the influencing factors of M & A performance.Because of the limitation of selecting samples, the influencing factors are few.
【學(xué)位授予單位】:遼寧大學(xué)
【學(xué)位級別】:碩士
【學(xué)位授予年份】:2013
【分類號】:F275;F271;F424
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