金融學(xué)外文翻譯------加工貿(mào)易與經(jīng)濟增長基于中國的實證分析

1、<p>　　本科畢業(yè)論文外文原文</p><p>　　外文題目： Processing Trade and Economic Growth:Evidence from China </p><p>　　出 處： The 2nd International Conference on Vale Engineering </p><p>　　

2、and Vale Management </p><p>　　作 者： Xi-jun Wang </p><p>　　Abstract：Presently, processing trade has become China’s major trade method

3、．In order to make clear the relationship between processing trade and China’s economic growth, this paper,based on China’s statistical data from 1985 to 2007，by employing co-integration theory, Granger causality test and

4、 error correction model(ECM)，respectively investigates the relationship between processing trade import, processing trade export and economic growth．The empirical result denotes that there exists unilateral</p>&l

5、t;p>　　1. Introduction</p><p>　　Since the reform and open poficy, China's foreign trade has been developing rapidly. At preseng foreign trade，investment and consumption have been“the three carriages”dr

6、iving the growth of China’s economy. On the basis of developing the general trade，our country actively implements the policy of encouraging the development of processing trade so as to make it realize the breakthrough de

7、velopment Presently,processing trade has become China’s major trade method，playing an extremely important role </p><p>　　Obviously,the internal academic community holds different beliefs about the relationsh

8、ip between processing trade and economic growth；meanwhile，these research literatures do not illustrate the long-run and short-run equilibrium relationship between processing trade and economic growth and the impact mecha

9、nism．Therefore，this paper will analyze the relationship between processing trade and economic growth by employing methods of co-integration theory, Granger causality test and error correction mo</p><p>　　2.

10、Methodology</p><p>　　The purpose of empirical analysis in this paper is to test the relationship between processing trade and economic growth by means of co-integration technique．Co-integration technique is

11、a new one which is applied to dynamic models’enactment,estimation and verification．It mainly analyzes the nonstationarity of time series，build nonstationary variable economic model，and explore the long-term equilibrium r

12、elationship between nonstationary variables．Firstly, the paper has the stationary test of time</p><p>　　2.1. Stationary Test</p><p>　　The time-series data of many economic indicators do not have

13、 the feature of stable process．For the time-series data formed in nonstationary process，traditional mathematical statistics and econometrics methods seem powerless．Besides using sequential autocorrelation analytic chart,

14、modem econometrics judges the stationarity of time series by a more formal approach, that is，to have statistical tests．Unit root test is one of the statistical tests which is universally applied．This approach judges the

15、</p><p><b>　　(1)</b></p><p><b>　　(2)</b></p><p><b>　　(3)</b></p><p>　　Where，t is time variable，which stands for a certain trend that

16、 time series vary as time goes by．Null hypothesis , alternative hypothesis .</p><p>　　The text begins with Expression(1)，then Expression(2)，and at last with Expression(3)．Whenever the test rcjects null hypot

17、hesis，that is the original series does not include unit roots, working as stationary series，the test is finished．Otherwise，it is to be continued until Expression(1) has been tested. When none of the test results of the t

18、hree models can reject null hypothesis，it is believed that the time series is stationary．</p><p>　　2.2. Co-Integration Test</p><p>　　In the domain of economy,previous modeling echnique has hypot

19、hesis of dynamic stationarity,and mpirical analysis based on time series assumes that ime series is stationary．While in fact,economic time series is usually nonstationary． Engle and Granger(1987)point that if the linear

20、combination of two nonstationary time series is smtionary,the two nonstationary time series have a co-integration relationship，that is，the two series have a common time tendency，so it can be viewed that there exists a l&

21、lt;/p><p>　　This paper, by adopting Engle-Granger’s two-stage Co-integration test method，has a co-integration test of time series．The steps of Engle-Granger’s two-stage test method go as follows：</p><

22、;p>　　Step 1：use common least square method(OLS) to estimate the long-term static regression equation and calculate non-equilibrium error．</p><p>　　Step 2：use ADF statistics test to estimate the stationari

23、ty of the residual error series．If the residual error series is estimated to be stationary, it suggests there exists a co-integration relationship between variables．</p><p>　　2.3. Error Correction Model(ECM)

24、</p><p>　　Error correction model was firstly adopted by Sargon，and then its application was promoted by Herdry, Anderson and Davidson．The main purpose of the initial application of error-correction model is

25、to set up short-term dynamic model so as to make up for the shortcomings of long-term static model．It can reflect the mechanism of the short-term deviation to long-run equilibrium as well as the long·run equilibrium

26、 relationship between different time series．In recent years，error-correction method has </p><p>　　between economic variables．</p><p>　　Granger Formulation Theorem put forward by Engle and Grange

27、r(1987) suggests that if two ariables X and Y are co-integration，there is always an error correction model(ECM) to define their short-term non-equilibrium relationship．That is：</p><p>　　Where is non-equilib

28、rium error item (long-run equalization deviation)； is short-run adjustment parameter．</p><p>　　Error-correction model is short-term dynamic one．a(chǎn)nd it cannot reach the state of being equilibrium．Thus， add er

29、ror-correction item in it to make Y and X gradually approach the state of long-term equilibrium． has the controlling and amending effect on ; when t-1 works，Y is more than its long-run equilibrium solution， is positive，t

30、henis negative，making decrease；while when t-1 works，Y is less than its long-term equilibrium solution， is negative，then is positive，making increase.</p><p>　　2.4. Granger Causality Test</p><p&g

31、t;　　Based on error correction model(ECM), we can apply Granger causality test to have a test of both long-term and short-term cause and effect relationship. Granger causality test was put forward by Granger(1969) and Sim

32、s(1972)，with its basic idea that the predictive validity of the variable Y under the condition of including the past information of the variables X and Y is superior to that of only considering the past information of Y,

33、 that is，the variable X helps to explain Y’s future variation, s</p><p>　　3. Conclusion</p><p>　　1)Granger causality test shows that there exists unilateral Granger causality relationship betwee

34、n processing trade import and economic growth. Processing trade import influences the growth of GDP.</p><p>　　2)For a long period, there exists long term stable equilibrium relationship between GDP and proce

35、ssing trade，processing trade import remarkably promotes the growth of GDP, while processing trade export restricts the growth of GDE Whenever processing trade export increases by 1%，GDP will decrease by 0.39365%%；wheneve

36、r processing trade import increases by l%，GDP will increase by 1.1134%. For a short period，processing trade import and processing trade export both spur the growth of GDP, but the imp</p><p>　　3)The rcason w

37、hy processing trade export brings adverse impact on China’s economic growth is as follows: firstly, processing trade’s forward and backward effects on internal economy are limited； secondly, china’s processing trade lies

38、 at the bottom-end in global manufacturing system，which restricts the optimization and modulation of our country’s economic structure；thirdly, the spare parts and raw materials of processing trade excessively depend on i

39、mport,and intermediate products cannot realize</p><p>　　本科畢業(yè)論文外文翻譯</p><p>　　外文題目： Processing Trade and Economic Growth:Evidence from China </p><p>　　出 處： The 2nd Internation

40、al Conference on Vale Engineering </p><p>　　and Vale Management </p><p>　　作 者： Xi-jun Wang </p><p><b>　　譯 文：&

41、lt;/b></p><p>　　加工貿(mào)易與經(jīng)濟增長：基于中國的實證分析</p><p>　　摘要：目前，加工貿(mào)易已成為中國的主要貿(mào)易方式。為了弄清加工貿(mào)易與中國經(jīng)濟增長的關(guān)系，本文以中國1985年到2007年的統(tǒng)計數(shù)據(jù)為基礎(chǔ)，通過采用協(xié)整理論，格蘭杰因果關(guān)系檢驗和誤差修正模型（ECM），分別考察了加工貿(mào)易進口和出口與經(jīng)濟增長的關(guān)系。實證結(jié)果表示加工貿(mào)易進口與經(jīng)濟增長之間存在單方面的

42、格蘭杰因果關(guān)系。加工貿(mào)易進口影響了GDP的增長。在短期內(nèi)，加工貿(mào)易進口和加工貿(mào)易出口均刺激了GDP的增長，但這種影響比較低；很長一段時間里，加工貿(mào)易進口顯著地促進了GDP的增長，而加工貿(mào)易出口限制了GDP的增長。</p><p><b>　　1、介紹</b></p><p>　　自改革開放以來，中國的對外貿(mào)易發(fā)展迅速。目前，對外貿(mào)易、投資和消費成為了推動中國經(jīng)濟增長的

43、“三架馬車”。在發(fā)展一般貿(mào)易的基礎(chǔ)上，我國積極實施了鼓勵加工貿(mào)易發(fā)展的政策，以使其實現(xiàn)突破性的發(fā)展。目前，加工貿(mào)易已成為中國的主要貿(mào)易方式，發(fā)揮著調(diào)節(jié)和完善工業(yè)結(jié)構(gòu)的重要作用，刺激了加工技術(shù)的改善和增加了勞動就業(yè)的機會。因此如何從一個客觀的角度去衡量加工貿(mào)易對中國經(jīng)濟增長的貢獻，已成一個非常重要的問題。由于從發(fā)達國家的立場來看加工貿(mào)易是不引人注目的，因而在國外很少有對加工貿(mào)易與國民經(jīng)濟的關(guān)系研究。改革開放以來，加工貿(mào)易在我國迅速增加，并

44、且在我國有有關(guān)加工貿(mào)易的大量研究。劉治中和王耀中（2003）的實證分析顯示，加工貿(mào)易對經(jīng)濟增長的貢獻程度和它對經(jīng)濟增長的推動相對較低，在郭清和陳李京（2005）的實證結(jié)果表明，每當(dāng)中國的加工貿(mào)易增長1%，國內(nèi)生產(chǎn)總值將增加0.761%，并且加工貿(mào)易的貢獻度同樣為53%；孫楚仁、沈玉良和趙泓君（2006）計算出，加工貿(mào)易和其他貿(mào)易進口對經(jīng)濟增長的總貢獻是負(fù)的；朱啟镕（2007）運用線性回歸方法，得出的結(jié)論是，一般貿(mào)易進口與出口及加工貿(mào)易出

45、口兩者的增長都推動了GDP，而</p><p><b>　　2、方法論</b></p><p>　　本文實證分析的目的是通過協(xié)整技術(shù)去檢驗加工貿(mào)易與經(jīng)濟增長之間的關(guān)系。協(xié)整技術(shù)是一種新的適用于動態(tài)模型的制定、評估和驗證。它主要分析時間序列的非平穩(wěn)性，建立非平穩(wěn)變量的經(jīng)濟模型，并探討非平穩(wěn)之間的長期均衡關(guān)系。首先，本文有時間序列變量的平穩(wěn)性檢驗；其次，本文測試變量之間的

46、協(xié)整關(guān)系；第三，本文建立誤差修正模型，它不僅檢查變量之間的長期關(guān)系，還檢驗短期因果關(guān)系；最后，本文作進一步的測試和分析關(guān)于時間變量涉及到協(xié)整關(guān)系之間的因果關(guān)系。</p><p><b>　　2.1 平穩(wěn)性檢驗</b></p><p>　　許多經(jīng)濟指標(biāo)的時間序列數(shù)據(jù)沒有穩(wěn)定的過程特征。對于非穩(wěn)定過程中形成的時間序列數(shù)據(jù)，傳統(tǒng)的數(shù)理統(tǒng)計和計量經(jīng)濟學(xué)方法似乎無能為力。除了使

47、用按順序的自相關(guān)分析圖表，現(xiàn)代計量經(jīng)濟學(xué)判斷時間序列的平穩(wěn)性，更正式的方法就是統(tǒng)計檢驗。單位根檢驗是其中的一個普遍使用的統(tǒng)計學(xué)檢驗。這種方法是通過判斷它是否有單位根來判斷某個時間序列的穩(wěn)定性。常用的假設(shè)性檢驗方法包括DF檢驗、ADF檢驗和PP檢驗。本文通過采用ADF檢驗，給出了時間序列的平穩(wěn)性檢驗。ADF檢驗是Dickey 和 Fuller完成的，他們通過改進DF檢驗， 以確保隨機干擾項的無色干擾特性。ADF的試驗?zāi)Ｐ捅磉_式如下：<

48、;/p><p><b>　　(1)</b></p><p><b>　　(2)</b></p><p><b>　　(3)</b></p><p>　　T為時間變量，它代表了某種趨勢的時間序列變化，隨著時間的推移。任何零假設(shè)，替代了假設(shè)。</p><p>　

49、　本文開頭的表達式（1），和表達式（2），最后的表達式（3）。每當(dāng)檢驗拒絕零假設(shè)，即原系列不包括單位根，作為平穩(wěn)序列時，測試完成。否則，它要繼續(xù)到表達式（1）被測試。當(dāng)這三個模型的檢驗結(jié)果都不能拒絕零假設(shè)，則認(rèn)為這個時間序列是平穩(wěn)的。</p><p><b>　　2.2 協(xié)整性檢驗</b></p><p>　　在經(jīng)濟領(lǐng)域，以往的建模技術(shù)具有動態(tài)平穩(wěn)性的假設(shè)，和實證分析

50、基于時間序列的假設(shè)時間序列是平穩(wěn)的。而實際上，經(jīng)濟時間序列通常是非平穩(wěn)的。恩格爾和格蘭杰（1987年）指出，如果兩非平穩(wěn)時間序列的線性組合是平穩(wěn)的，這兩個非平穩(wěn)時間序列具有協(xié)整關(guān)系，也就是說，這兩個時間序列有一個共同的趨向，所以它們可以被認(rèn)為存在長期的均衡關(guān)系。因此，我們可以應(yīng)用協(xié)整檢驗的方法來測試序列里是否存在長期均衡的協(xié)整關(guān)系。目前，協(xié)整檢驗方法主要包括Engle-Granger的兩個階段的協(xié)整檢驗和Johansen協(xié)整檢驗。Eng

51、le-Granger協(xié)整檢驗由恩格爾和格蘭杰提出，其只考慮到了雙變量的過程，這個過程僅擁有零或只有一個協(xié)整向量。雖然Johansen協(xié)整檢驗由Johansen 和 Juselius首次提出，這是適用于測試用向量自回歸（VAR）系統(tǒng)的最大似然估計的多變量之間的協(xié)整關(guān)系。</p><p>　　本文采用Engle-Granger的兩個階段的協(xié)整檢驗方法入手，有一個時間序列的協(xié)整檢驗。Engle-Granger的兩個階段

52、的協(xié)整檢驗方法的步驟如下：</p><p>　　第一步：使用普通最小二乘法（OLS模型）來估計長期靜態(tài)回歸方程和計算非均衡誤差。</p><p>　　第二步：使用ADF統(tǒng)計量來估計殘差序列的平穩(wěn)性。如果殘差誤差序列估計是靜止的，它表明變量之間存在協(xié)整關(guān)系。</p><p>　　2.3 誤差修正模型（ECM）</p><p>　　Sargon首

53、先采用了誤差修正模型，然后由Herdry,Anderson 和 Davidson將其應(yīng)用推廣。該誤差修正模型的最初應(yīng)用的主要目的是建立短期動態(tài)模型，以彌補長期靜態(tài)模型的不足。它可以反映到長期均衡機制的短期偏差以及不同時間序列之間的長期均衡關(guān)系。近年來，誤差修正方法已成為運用經(jīng)濟計量時間模型的主要方法之一。采用長期誤差修正模型，可以通過其長期均衡項目，集中顯示非平衡解釋變量的修改機制，它在經(jīng)濟理論中被長期均衡規(guī)則推動。同時，由于通常在短期

54、動態(tài)干擾項和長期均衡項之間不存在顯著的統(tǒng)計相關(guān)，因此，我們可以分別作出經(jīng)濟解釋。因為只要我們說明解釋變量和被解釋變量之間有協(xié)整關(guān)系，還有一定存在唯一的格蘭杰因果關(guān)系，通過誤差修正方法建立的模型就不會造成“虛假回歸”。因為通常會顯示在傳統(tǒng)的經(jīng)濟計量模型的建立中，因此，它要求明確地揭示經(jīng)濟變量之間的作用機制。</p><p>　　恩格爾和格蘭杰（1987年）提出格蘭杰定理認(rèn)為，如果兩個變量X和Y是協(xié)整的，總有一個誤差

55、修正模型（ECM）來定義它們的短期非均衡的關(guān)系。這就是：</p><p>　　是非均衡誤差項（長期均衡偏差）；是短期調(diào)整參數(shù)。</p><p>　　誤差修正模型是短期動態(tài)的，它是不能達到平衡狀態(tài)。因此，加入誤差項使Y和X逐步接近長期均衡狀態(tài)。對具有控制和修改的影響；當(dāng)t-1產(chǎn)生效果時，Y多于其長期均衡解決方案，是負(fù)的，則為正，使下降；而當(dāng)t-1產(chǎn)生效果時，Y是少于其長期均衡的解決方案，是負(fù)

56、的，則為正，使增加。</p><p>　　2.4 格蘭杰因果檢驗</p><p>　　基于誤差修正模型（ECM），我們可以應(yīng)用格蘭杰因果檢驗有兩個長期和短期的因果關(guān)系檢驗。由格蘭杰（1969）和Sims（1972）提出了格蘭杰因果檢驗，其基本想法，即變量的預(yù)測效度下Y對包括變量X和Y過去信息的條件下優(yōu)先只考慮Y的過去信息，那就是，變量X有助于解釋Y的未來變化，所以X是格蘭杰因果關(guān)系的Y，否

57、則被稱為非格蘭杰因果關(guān)系。</p><p><b>　　3、總結(jié)</b></p><p>　　1）格蘭杰因果檢驗表明，加工貿(mào)易進口與經(jīng)濟增長之間存在單方面的格蘭杰因果關(guān)系。加工貿(mào)易進口對GDP的增長有影響。</p><p>　　2）在很長一段時期，GDP和加工貿(mào)易之間存在長期穩(wěn)定的均衡關(guān)系，加工貿(mào)易顯著地促進著GDP的增長，而加工貿(mào)易出口限制了

58、GDP的增長。當(dāng)加工貿(mào)易出口增長1%，GDP將下降0.39365%；當(dāng)加工貿(mào)易進口增長1%，GDP將增長1.1134%。在短時期內(nèi)，加工貿(mào)易進口和加工貿(mào)易出口都刺激了GDP的增長，但影響相對較低。</p><p>　　3）加工貿(mào)易出口對中國的經(jīng)濟增長產(chǎn)生不利影響的原因如下：首先，加工貿(mào)易前進和后退對內(nèi)部經(jīng)濟的影響是有限的；第二，中國的加工貿(mào)易在自上而下的全球制造系統(tǒng)的底端，這限制了我國經(jīng)濟結(jié)構(gòu)的優(yōu)化和調(diào)整；第三，