【作者】 Megdam Khalil Ibrahim Khalil；

【导师】 李秀敏；

【作者基本信息】 东北师范大学 ， 世界经济， 2014， 博士

【摘要】 本文研究目的是找出RMB和SDG汇率变动对中国-苏丹双边贸易影响。研究采用扩展的引力模型研究中国-苏丹贸易流。研究涵盖两个层次,第一层次是总的出口和进口,第二个层次是按照SITC分类标准,研究10组出口商品和8组进口商品。研究时间为1986年至2012年。通过修正模型计量假设,涵盖人民币汇率和苏丹镑汇率,两国GDP以及两国的技术差距。这5个变量以14个不同的数据集类型进行衡量。因此,共有20个商品组及14个不同数据集,在分析中共包括了280个方程。在这些方程中,有120个统计结果不显著,将其排除后,还有160个方程,涵盖了方程总数的57.14%。结果表明在总体水平下,人民币和苏丹镑汇率变动对总的进口和出口没有显著影响,同样的情况也适用于技术差距。中国GDP是统计显著的,并对总进口和出口有正的影响,因此认为中国GDP对总的贸易流有主要的决定作用。苏丹GDP是统计显著的,并且对总进口和总出口有正的影响。然而,苏丹GDP在决定贸易流方面的作用要小于中国GDP。在按SITC出口分组情况下,结果表明人民币汇率波动对部分出口组商品有显著正向影响,这些出口组占总出口组的比例为27.5%,不存在负向影响。SDG汇率变动对10%的分组商品有显著正向影响,不存在负向影响。技术差距对出口商品值有显著影响,且对出口商品是负向的,但对其中9组商品存在正向影响。中国GDP对65%的出口商品组有显著正向影响,不存在负向影响。苏丹GDP对20%的出口商品组有正向显著影响,对5%的出口商品组有负向影响。按SITC标准对进口商品组进行分类,表明RMB汇率变动对34%的方程有显著正向影响。SDG汇率变动对进口商品组没有显著影响。除了对部分进口商品组有正向影响外,技术差距对31%的进口商品组有显著负向影响。中国GDP对25%的进口商品组有显著正向影响,不存在负向影响。苏丹GDP对3%的进口商品组有正向显著影响,对6%的进口商品组有负向影响。论文共分为五章。第一章为研究背景,即研究目的。近年来,人民币汇率改革引起广泛关注,人民币不再单一盯住美元并对美元进行升值。1886-2012年,人民币币值下降了47%。1994-2005年,人民币汇率保持稳定。2005-2012年,人民币汇率升值了24%。除此之外,根据苏丹镑汇率的历史数据,发现1986到2012年,苏丹镑汇率伴随经济波动贬值了99%。中国和苏丹之间巨大的汇率波动被认为是贸易流的主要决定因素。研究试图回答如下问题：(1)人民币和苏丹镑汇率变动是如何影响中国和苏丹双边贸易的?(2)如果我们接受人民币币值上升而苏丹镑汇率贬值的事实,那么这种变动是否会对贸易额产生复合影响?(3)人民币和苏丹镑汇率变动对贸易额的影响会不会因为商品类型或性质变化而不同?第二章主要阐述国际贸易理论和研究模型。这一章的第一部分回顾了相关概念：汇率的定义,汇率的类型以及在不同的类型下如何得到汇率。另外,回顾了自1880年以来汇率体系的演化。汇率的演化过程划分为三个主要阶段：法定货币局制度(1880年到1998年),盯住汇率制度(1998年11月到2009年1月)和修订后的盯住汇率制度(2009年2月以后)。每个阶段表现出来的详细特征就像金本位(1880到1914年)和两次大战期间(1914到1944)的特征。然后以Jeffrey (1999)的视角看待当前汇率体系的主要类型。在第二部分,笔者基于主要国际贸易理论总结了国际贸易的动机,这些动机是国家间产生贸易的5个基本原因。然后概述了主要的国际贸易理论,包括绝对优势理论,比较优势理论,要素禀赋理论,规模报酬递增理论和引力模型理论。第二章最后一部分致力于研究模型,考察模型的理论框架,并在此基础上发展研究模型,改进的引力模型包括8个解释变量：中国和苏丹GDP、人口、汇率以及中国和苏丹之间的地理距离和技术差距。笔者解释了每一个变量的定义以及计算和数据来源。然后通过检验模型设定。用方差膨胀因子检验多重共线性问题,通过排除地理距离和人口变量来修正模型。对于内生性问题,笔者采用Matyas(1997,1998)、Egger(2000)和Giorgio(2004)的方法。这些学者建议用最可能出现内生非独立问题变量的滞后项作为工具变量,来解决这个问题,用DW值和LM检验来检查序列相关问题。用Jarque-Bera统计量检验标准化残差的正态概率分布。用ARCH LM检验标准化残差的异方差性。第三章介绍中国和苏丹的汇率体系以及两国的双边贸易。第一部分笔者回顾了中国汇率体系的演化,将其划分为7个主要时期：1978年以前,改革开放政策实施期(1978到1980年),汇率双轨制时期(1981年1月到1985年1月),官方汇率时期(1986年7月到1994年1月),汇率制度统一时期(1994年1月1日),盯住美元的汇率制度时期(1997)和有管理的浮动汇率制度时期(2005年起)。此外,笔者回顾中国经济改革的一些特征。由于汇率体系的演变,它与对外贸易的关系,以及对外贸易演化本身都是中国经济改革的一部分。第二部分涵盖了苏丹汇率体系、银行和货币政策的演变。首先强调了苏丹货币发行的历史,苏丹货币发行了七次：1956年至1969年,苏丹独立后第一次发行苏丹货币；1960年苏丹中央银行建立后第二次发行苏丹货币；1981年至1985年第三次发行和1986年至1991年第四次发行,这四个发行时期货币面值并未发生改变,并分别命名为第一、第二、第三和第四苏丹镑；第五次1991年至2007年,更名为苏丹第纳尔,1第纳尔等于10苏丹镑；第六次2006年至2011年,发行的新苏丹镑等于100苏丹第纳尔,因此相当于1000老苏丹镑。第七次发行是在2011年南苏丹从苏丹分离后,第七次的货币保留了与第六次货币相同的名字和币值,并且到现在依旧使用。为了与旧苏丹镑区分,当前货币从其阿拉伯名字Sudanese Genaih中取得名称SDG。然后笔者考察了苏丹货币汇率历史演变,其次是苏丹银行业和货币政策的演变。第三章最后一部分考察中国和苏丹的关系,根据以往的研究将其分为两个主要阶段,在苏丹发现石油前的阶段以及发现石油后的阶段。最后回顾1986年至2012年中国与苏丹的双边贸易。第四章为实证检验结果。在总的出口层面上,中国CDP对总出口有显著正向影响,因此是决定总出口额的主要因素。苏丹GDP总体上影响不显著。对于人民币汇率,苏丹镑汇率及技术差距,在所有数据集中影响均不显著。在所有数据集中,所有方程解释变量都具有较强的解释能力且比较稳定。在总的进口层面上,中国GDP对进口有显著的负向影响。苏丹GDP在大部分数据集中影响不显著。人民币汇率在大多数数据集中影响不显著,苏丹镑汇率和技术差距均不显著。所有数据集中,方程的解释能力从0.54增加到0.74.按SITC出口商品组分类得到的检验结果：在第一数据集中技术差距在14个方程中对出口分组商品有显著影响,这些影响中既有正向影响也有负向影响。所有检验方程在95%显著性水平下均是显著的。所有数据集均在0.32-0.97之间变动,研究发现按SITC分组情况下检验结果在加入技术差距后均是不显著的。中国GDP对出口商品分组值有正向显著影响,在65%的估计方程中有显著影响,不存在任何负向影响。在四十组分组商品中,苏丹GDP对其中8个出口商品分组值有显著正向影响,对其中2个有显著负向影响。在40组分组商品中,人民币汇率对其中11组出口商品额有显著正向影响,不存在显著负向影响。在40组分组商品中,苏丹镑汇率对其中4组出口商品额有显著正向影响,不存在显著负向影响。按SITC进行分组的进口商品检验结果：在32组方程中,技术差距在其中10组方程中对进口商品额有显著影响。影响分为正向和负向影响。除了SITCO和SITC9分组外,所有方程在95%显著性水平下都是有效且显著的,解释变量的有效性在0.26到0.78之间。研究发现所有分组结果均对技术差距不显著。在32组方程中,中国GDP对进口商品分组值有显著正向影响,不存在任何负向影响。在32组方程中,苏丹GDP只对其中一组进口商品分组值有显著正向影响,对其中2组商品有负向影响。从进口额角度看,苏丹GDP没有发挥主要决定作用。人民币汇率对其中11组商品有显著正向影响,不存在负向影响。苏丹镑汇率对进口商品分组额无任何显著性影响。最后一章也就是第五章由三部分组成。在完成这个研究并学习与这个主题直接或间接相关的研究之后,作者确信,对于这个问题研究者的结论并不一致。除此之外,这些研究的结果在很大程度上取决于解释变量的类型和性质。IMF(1984), Gotur(1985)和Ozturk(2006)的研究中已经提到。从另一个角度联系本文的研究目标,Gotur(1985)证明,他用与Akhtar和Hi lton(1985)相同的数据和方法仅通过改变贸易模型中解释变量的数据集的选择就能得到不同的结果。这与笔者的研究完全相符并进一步证实了笔者的研究。根据研究结果,我们可以回答如下的研究问题：(1)关于两国之间汇率的波动性如何影响两个国家双边贸易量,本研究得出的结论是在研究时期内中国人民币和苏丹镑汇率波动对中国和苏丹之间的总双边贸易量不存在负影响,同时,也没有正的影响或收益。中国GDP对贸易总量有显著影响,并被作为贸易额的主要决定因素,苏丹GDP对贸易量的影响显著性低于中国GDP,两国的GDP对贸易量的影响都为正。此外,技术差距对总贸易量没有显著影响。就单个商品组而言,中国人民币汇率变化对出口SITC[0,2,4,6,8]组和进口SITC[3,5,6,7,8]有显著的正的影响。苏丹镑汇率波动对出口SITC[0,5,6]有显著的正的影响,但对任何进口的商品组都没有显著影响。技术差距对出口SITC [0,2,6,8,9]和除SITC[0,9]之外的所有进口商品组有显著影响。中国GDP对所有的进口商品组和除SITC [0,2,9]以外的进商品口组有显著影响。苏丹GDP对除了SITC[3,4]以外的所有出口商品组以及除了SITC[0,7]以外的所有进口商品组有显著影响。(2)虽然事实表明人民币升值苏丹镑贬值,汇率波动的特性造成了对贸易额的混合效应,但是结果并没有表明这种混合效应的出现。(3)结果并没有给出人民币和苏丹镑汇率变动对两国双边贸易影响的确定性结论。此部分最后内容为研究建议：(1)通过使用人民币和苏丹镑汇率,比较研究结果可以确定将间接汇率转变成直接汇率的经济可行性。(2)通过该研究,可以比较中国贸易伙伴与不同贸易伙伴的贸易特征,从而有助于提出外贸发展的政策。(3)研究结果表明目前还不存在实现人民币与苏丹镑汇率直接兑换的必要性。更多还原

【Abstract】 The aim of this study is to identifying the impact of RMB and SDG exchange rates variability on bilateral trade flows between China and Sudan. In addition to identifying the influence of the explanatory variables type’s data set options changing on the estimation result. This study applies augmented gravity equation model on the bilateral Chinese-Sudanese trade flows. The estimation covers two levels, the first is total export and import level, second is the SITC commodity groups level for ten export goods groups and eight import goods groups. The study covers27years from1986to2012; the study period is limited due to lack of information covering the period before1986. After correct the model econometric specification, the model includes the Renminbi exchange rate (RMB the official currency of the People’s Republic of China) and the Sudanese Pound exchange rate (SDG the official currency of the Republic of the Sudan), the two countries GDP in addition to the suggested technological difference (Tdis) between China and Sudan. Those five explanatory variables estimated in different fourteen data set types. Taking into account that, there are20commodity groups and there are14different data sets, thus the analysis been conducted for280equations.120of those280equations has statistically not valid results so were excluded from the study’s final evaluation result, the160remaining equations which represents57.14%of total equations has statistically valid results reported interpreted and discussed. The results indicate that at total level:RMB and SDG exchange rate variability has no any statistically significant impact on export or import, as well as the case for Tdis. China’s GDP is statistically significant and has positive impact on total export and total import, addition to that China’s GDP considered as the absolute major determinant for total trade flow value. Sudan’s GDP is statistically significant and has positive impact on total export and total import. However. Sudan’s GDP play fewer roles as determinant for total trade flow value comparatively with China’s GDP. At SITC export goods group’s level, the results indicate that:RMB exchange rate variability has statistically positive significant impact on export group’s value in27.5%of the estimated equations and there is no any negative significant impact for it. SDG exchange rate variability has statistically positive significant impact on export group’s value in10%of the estimated equations and there is no any negative significant impact for it. Tdis has statistically significant impact on export goods group’s value in35%of the estimated equations; Tdis impact is generally negative on export groups except in SITC9group where it is impact is positive. China’s GDP has statistically positive significant impact on export group’s value in65%of the estimated equations and there is no any negative significant impact of it. in addition to that it is showed a general tendency as a major determinant for export value of each equation where it is significant. Sudan’s GDP has statistically positive significant impact on export group’s value in20%of the estimated equations, while has statistically negative significant impact on export group’s value in5%of the estimated equations. At SITC import goods group’s level, the results indicate that:RMB exchange rate variability has positive statistically significant impact in34%of the estimated equations and there is no any negative significant impact for it. SDG exchange rate variability has no any statistically significant impact on import group’s value. Tdis has statistically significant impact on import group’s value in31%of the estimated equations; Tdis impact is generally negative on import groups except it is positive impact on (SITC [3] e.q (a)) and (SITC [7] e.q (b), e.q (c)). China’s GDP has statistically positive significant impact on import group’s value in25%of the estimated equations, there is no any negative significant impact for it, in addition to that it is showed a general tendency as absolute major determinant for import value of each equation where it is significant. Sudan’s GDP has statistically positive significant impact in3%of the estimated equations, while has negative statistically significant impact on import group’s value in6%of the estimated equations. Change the nature of the (the type) explanatory variables within the data sets leads to change in the result of the final estimate. So that-for example-the use of the nominal exchange rate rather than real one, change the result from statistically valid result to distorted result cannot be reliable. Moreover, changing the unit of measurement the GDP from national currency to the US dollar with the survival the rest of the data set components without change in terms of the type and number also leads to change the result from significant to insignificant one. This explains the difference in results of studies dealing with this subject, despite the use of the same approach in some cases the use of the same data.This thesis divided to five chapters. Chapter one content the research background, where the research motivation to do this study is that, the Yuan’s exchange rate regime raise considerable debate in recent years, this controversy has increased after the announcement of De-Pegging the RMB Currency against the USD and appreciated accordingly in2005. The Yuan value decreased by47%in the period from1986to2012, while the Yuan’s exchange rate remained stable from1994to early2005and increase by24%in the period from2005to2012. In addition to that, based on historical data of the Sudanese Pound exchange rate, one find that in the period from1986to2012the value of the SDG decreased by99%according to economic fluctuations. This huge exchange rate variability between China and Sudan expected to be a major determinant for the trade flows. In addition to that, Researcher noted that studies deal with impact of exchange rate volatility on trade-whether bilateral trade or international trade-Note that most studies tend to choose the independent variables in a selective manner, especially with regard to the kind of exchange rate whether the exchange rate is nominal or real. Also in terms of the kind of GDP whether, it was nominal or real GDP, whether, expressed in Local Unit Currency (LUC) or in U.S. dollars (USD). whether, been expressed in terms of current price or by selecting a base year price. All these available options for the independent variables has used in many relevant studies and there is no conclusive agreed identification for the impact of exchange rate volatility on the volume of trade, which constitutes another problem from the perspective of the researcher. Based on those motivations the research questions are:1. How this volatility in RMB and SDG exchange rate effect the bilateral trade volume between China and Sudan?2. If we accept the reality that the value of the RMB increasing and the value of the SDG decreasing. Is there a compound effect on the trade value caused by this nature of volatility?3. Is the effect of RMB and SDG exchange rate volatility on the trade value depends on the difference in goods type or properties?The second chapter devoted to view international trade theory and research model. In the first section of this chapter has been reviewed general concepts related to research such as definitions of exchange rate and types of exchange rate. Also, view the historical evolution of exchange rate regime since1880. Where the evolution divided to, main three phases are the de jure phase (1880to1998), de facto phase (November1998to January2009) and revised de facto (February2009and later). Within each phase, the characteristics presented in detail like the gold standard (period from1880to1914) and the characteristics of inter-war period (period from1914to1944) and so on until we get to the current situation of exchange systems. Then viewed the current main types of exchange rate regimes in the perspective of Jeffrey (1999) where explained and built his nine types of exchange rate regimes on the degree of flexibility of exchange rate. This section concluded by viewing the four best-known alternatives to de jure classifications. In section two. the researcher cover different international trade motivations, which based on main international trade theory, those motivations are the five basic reasons why trade may take place between nations. Then made an overview about main international trade theories, this overview covers the pure exchange economy theory, the theory of comparative advantage, the factor proportions theory, increasing returns to scale theory and gravity model theory of world trade. The last section of chapter two devoted for the research model, has been viewed the model theoretical framework and based on those theoretical foundations the researcher became have conviction and good motivation to use the gravity equation in this study. This was followed by the development of the research model, where the researcher develop augmented gravity model contains eight explanatory variables are the GDP. the population and the exchange rate for both China and Sudan in addition to the geographical distance and suggested the technological distance between China and Sudan. Then explained the definition of each variables and it is calculation and the data sources for them. The last part of this section was the correction of the model specification by testing and correcting the: Multicollinearity problem examined using variance inflation factor test and the model corrected by exclude the Geographical distance variable and Population variables because they are the source of Multicollinearity problem. For Endogeneity problem the researcher go in the line with Matyas (1997,1998) and Egger (2000) and Giorgio (2004) those studies suggest to bypass this problem using the lags of the most likely endogenous independent variables as their instruments. Suggesting that in this case simultaneous bias is not a severe problem. Serial Correlation examined by using (Durbin-Watson) test and Serial Correlation LM Test. The estimates were adjusted for first and second degree serial correlation.(D-W) test result not reported. LM Test results reported in the appendixes. The Normal Probability Distribution of the standardized residuals examined by using (Jarque-Bera) statistic for normality test. The Heteroskedasticity of the standardized residuals examined for first and second degree by using (ARCH LM) test.Chapter three is relevant to the exchange rate system for China and Sudan in addition to preview China-Sudan bilateral trade. The first section researcher reviews the historical evolution of foreign exchange system in China. This historical evolution divided to main seven periods as following:the period before1978, reform and opening-up economy policy period (1978to1980) followed by dual exchange rate system period (January1981to January1985). Then the period of official rate and foreign swap market rate (July1986to January1994), unification of exchange rate regime period (on January1,1994). addition to De Facto pegged to US dollar exchange rate regime period (1997) and the current managed floating exchange rate regime period (since2005). In addition, the researcher review some features of economic reform in China. Because the evolution of the foreign exchange system and it is relation with foreign trade in addition to foreign trade evolution itself all are part of China’s economic reform. Where talked about the main characteristics of Opening-Up policy, agricultural reform, decentralization of the government, growth of the non-state sector, state-owned enterprise reform. also make highlight on banking system reform and historical evolution and the last point is about moving toward a market economy. Section two covers the Sudanese exchange system, banking and monetary policy evolution. First highlighted the history the Sudanese currency issuance where the currency issued seven times as following:The first period1956to1969where the first Sudanese currency issued after Sudan’s independence, the second issuance period1970to1980after the establishment of the Central Bank of Sudan in1960. Then the third period1981to1985and the fourth period1986to1991, in those four issuances time the currency remained the nominal value and named as First, Second, Third and Fourth Sudanese Pound respectively. In The fifth period1991to2007the name changed to the Sudanese Dinar, one dinar is equivalent to ten Sudanese Pounds; in the sixth period,2006to2011issued new Sudanese Pound which equivalent to one hundred Sudanese Dinar and therefore equivalent to a thousand old Sudanese Pounds. The seventh issuance was in2011after the separation of South Sudan from Sudan; the seventh currency retained the same name Sudanese Pound and the value of the sixth currency and is still in use today. However, to distinguish this currency from the old Sudanese Pounds, the current currency takes his short name as (SDG) from the Arabic name of the currency (Sudanese Gunaih). Then the researcher reviews the Sudanese currency exchange rate history and evolution, followed by Sudanese banking sector and monetary policy evolution. In the last section of chapter three viewed, the historical China-Sudan relation which divided to two main phase based on the previous studies, the phase before discovering the oil in Sudan and the second is after it. Then in the last point review the China-Sudan bilateral trade during the study period1986to2012.Chapter four review the estimation results based on the following preface to view the result. Total export estimations result in table:4.1.1provide that:for China GDP (GDPc) in all data sets-except (a) data set-GDPc is statistically significant and has positive impact on total export, addition to that also (GDPc) considered as the absolute major determinant for total export value of each equation. Sudan GDP (GDPs) is not statistically significant in all data sets-except (b) data set where (GDPs) is statistically significant and has positive impact on total export. For Yuan exchange rate (RMB), Sudanese Pound exchange rate (SDG) and the suggested Technological distance (Tdis) they are not statistically significant in all data sets. The explanatory power of the all estimated data set equation is considered high and stable in all data sets and ranging between0.95and0.97. In addition, the explanatory power of the equations do not affected if the regression runs with (1) data sets or with (2) data sets. Total import estimations results in table (4.1.2) provide that:(GDPc) in (a.2),(b.2).(c.2), and (d.1) data sets is statistically significant and has positive impact on total import. Otherwise, there is no significant impact in other data sets.(GDPs) is not statistically significant in all data sets-except (d) data set where (GDPs) is statistically significant and has positive impact on total import.(RMB) is not statistically significant in all data sets-except (a.2) data set where (RMB) is statistically significant and has positive impact on total import. For (SDG) and suggested (Tdis) they are not statistically significant in all data sets. The explanatory power of the all estimated data set equation is increase from about0.54in (a.2) data set to reach its maximum value0.74in (d.1) data set. Nevertheless, the explanatory power of the equations is considered stable and not affected if the regression run with (1) data sets or with (2) data sets. The SITC export goods group estimation results:export estimation result for all data sets seen in appendix (4), suggested that,(Tdis) in (1) data sets has statistically significant impact on export goods group’s value in14out of40estimated equations and that represents35%of the estimated equations. This impact is divided to negative impact on (SITC [0] e.q (c), e.q (d)),(SITC [2] e.q (a), e.q (c). e.q (d.)),(SITC [6] e.q (d)) and all data sets for SITC [8]. While has positive impact on all data sets for SITC [9]. All estimated equations are useful and significant at95%significance level, the explanatory power for all SITC good group with (1) data sets ranging between0.32to0.97. The researcher fined that the estimation results for all (SITC) goods groups are not sensitive to inclusion of (Tdis). Where omit it from the estimated equation in (2) data sets does not affect the overall equations explanatory power or the significant of explanatory variables. Thus the researcher will view the result in accordance to the estimated equation in (2) dcta sets. (GDPc) showed a general tendency for statistically positive significant impact on export group’s value. It is significant in26out of40estimated equations and that represents65%of the estimated equations. There is no any negative significant impact on equations, also (GDPc) considered as a major determinant for export value of each equation where it is significant.(GDPs) has statistically positive significant impact on export group’s value in8out of40estimated equations and that represents20%of the estimated equations. Also has statistically negative significant impact on export group’s value in2out of40estimated equations and that represents5%of the estimated equations.(RMB) has statistically positive significant impact on export group’s value in11out of40estimated equations and that represents27.5%of the estimated equations, there is no any negative significant impact for (RMB).(SDG) has statistically positive significant impact on export group’s value in4out of40estimated equations and that represents10%of the estimated equations, there is no any negative significant impact for (RMB). The SITC import goods group estimation results:Import estimation result for all data sets seen in appendix (5) suggested that (Tdis) in (1) data sets has statistically significant impact on import group’s value in10out of32estimated equations and that represents31%of the estimated equations. This impact is divided to negative impact on (SITC [2] e.q (d)).(SITC [5] e.q (a), e.q (b.)),(SITC [6] e.q (c). e.q (d)) and (SITC [8] e.q (b), e.q (d)). While has positive impact on (SITC [3] e.q (a)) and (SITC [7] e.q (b). e.q (c)). All estimated equations are useful and significant at95%significance level-except SITC [0] and SITC [9] groups equation-The explanatory power for all useful SITC good group with (1) data sets ranging between0.26and0.78. The researcher fined that the estimation results for all (SITC) goods groups are not sensitive to inclusion of (Tdis). Where omit it from the estimated equation in (2) data sets does not affect the overall equations explanatory power or the significant of explanatory variables. Thus the researcher will view the result in accordance to the estimated equation in (2) data sets.(GDPc) showed a general tendency for statistically positive significant impact on import group’s value, where it is significant in8out of32estimated equations and that represents25%of the estimated equations. There is no any negative significant impact on equations, also (GDPc) considered as absolute major determinant for import value of each equation where it is significant.(GDPs) has statistically positive significant impact in (SITC[3] e.q(d.2)) value, which means only1out of32estimated equations and that represents3%of the estimated equations. Also has negative statistically significant impact on import group’s value in2out of32estimated equations and that represents6%of the estimated equations.(GDPs) do not play any major determinant role for import value.(RMB) has positive statistically significant impact on import group’s value in11out of32estimated equations and that represents34%of the estimated equations, there is no any negative significant impact for (RMB).(SDG) has no any statistically significant impact on import group’s value. The last chapter is chapter five which consisting of three parts. The result discussion conclusion is that, after the completion of this research and the large number of studies that learned by the researcher whether related directly or indirectly to the subject of search, the researcher believer that, this topic does not have an agreement among researchers about the result of such research. In addition to that, the result of such researches depends largely on the type and nature of the explanatory variables. This is what was been referred by studies such as International Monetary Fund (1984), Gotur (1985) and Ozturk (2006). From another perspective linked to one of the goals of this research, Gotur (1985) prove that he can get different results using the same data and methodology of Akhtar and Hilton (1985) only by change the data set options for the explanatory variables type in the trade model. This is a full accordance and even confirms the result reached by the researcher. While study conclusion is:1. About how the volatility in exchange rate for the two-country effect on the volume of bilateral trade between the two countries, The results of this study provide that exchange rate variability for both Chinese Yuan and Sudanese Pound do not negatively affect the total bilateral trade volume between China and Sudan during the study period. As well, there are no positive effects or gains. While Chinese GDP has significant impact on total trade volume and considered as the major determinant for trade value. Sudanese GDP has less significant impact on total trade volume than China GDP; In addition to that, both GDP has positive significant impact on total trade volume. In addition, the suggested Technological distance has no significant impact on total trade volume. The findings concern the individual goods groups provide that Chinese Yuan exchange rate variability has significant positive affect on export SITC [0,2,4,6, and8] groups and on import SITC [3,5,6.7and8] groups. Sudanese Pound exchange rate variability has significant positive impact on export SITC [0.5and6] groups while has no impact on any import groups. The suggested technological distance has significant impact on export SITC [0,2,6,8, and9] groups and on all import SITC groups-except SITC [0and9] groups. China GDP has significant impact on all export and import groups-except SITC [0,2and9] import groups. Sudan GDP has significant impact on all export groups-except SITC [3and4] groups. Also has significant impact on all import groups-except SITC [0and7] groups.2. About the compound effect on the trade value caused by this nature of volatility, although the reality indicates that the value of the RMB is increasing and the value of the Pound decreasing. There is no indication in the research results to the presence of a compound effect as result of reality (the nature of decreasing or increasing) of the exchange rates volatility.3. The result did not show conclusive evidence or even an indicator by which one can give conclusion about the relationship between the effect of exchange rate volatility on bilateral trade and a certain properties or type of the goods group.The study conclusion bottom line is that, my findings provide how exchange rate and other explanatory variable impact the bilateral trade flow between China and Sudan and the researcher are able to determine the value of impact as a percentage out of the total estimated equations. However, it is extremely difficult to determine the absolute value of that impact because there is no conclusively determine-not even from the theoretical side-any of the data sets the researcher can base on its result.The last point in this chapter is the research suggestions and coms as following:1) The economic researchers need to work on finding a common basis to identifying data sets options, which used to analyzed in trade flow models. So we can achieves reliable results and comparable between different studies. Thereby achieving the target of economic research, which represents in economy development and the welfare of society.2) Increase the studies covered periods to get a more realistic results, because the researcher noted that studies covering relatively short periods, which may make the results susceptible to non-economic effects belonging to those the short periods.3) With regard to Chinese Sudanese trade and the use of the indirect exchange rate in dealings with the bilateral trade. There is no proven based on this study results indicate to presence of negative impact of the exchange rate volatility on two currencies bilateral trade value, whether at the level of the total exports and imports value, or on the level of commodity groups. There is no negative impact on the bilateral trade requires a shift to the use of direct exchange rate unless governments see the presence of non-economic reasons for this shift.更多还原