| 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. |
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