Effect on Trade Flows of Regional Trade Agreements

Effect on Trade Flows of Regional Trade Agreements Abstract This paper studies the effect on trade flows of RTAs signed between developing economies. It uses a variation of the gravity model of trade to asses five RTAs: Mercosur, The Andean Community, SICA, the EU, Chile-China. Contents Abstract iii List of Figures vi List of Tables vi List of Formulas vi 1. Introduction viii 1.1Background viii 1.2 Problem definition x 1.3 Research Objective x 1.3.1 Major research question x 1.3.2 Minor research question xi 1.4 Theoretical Framework xi 1.4.1 The Gravity model of trade xi 1.4.2 Research Methodology and Design xii 1.4.3 Research Assumptions xii 1.4.4 Research Limitations xii 1.5 Thesis Structure xiii 2. Literature Review xiii 2.1 Trade Creation and Trade Diversion xiv 2.1.1 Trade Creation xiv 2.1.2 Trade Diversion xvii 2.1.3 Gross Trade Creation xviii 2.2 Empirical Evidence from SS RTAs xx 3.Theoretical Framework and Research Methodology xxi 3.1 Theoretical Framework xxi 3.1.1 Multiple Regression Analysis and Model Building xxi 3.1.2 Regression Model Diagnosis xxii 3.1.3 The Gravity Model of Trade xxiii 3.1.4 Research Assumptions xxvii 3.1.5 Research Limitations xxvii 3.2 Research Methodology xxvii 3.2.1 Research Type and Approach xxvii 3.2.2 Data Collection xxx 4. Findings and Results xxxi 4.1 The effect of RTAs xxxi 5. Conclusions xxxiii 6. Appendix xxxiv 7. References xxxvii List of Figures Figure 1 Trade Creation. Figure 2 Trade Diversion Figure 3 Trade Creation Proper vrs. Gross Trade Creation Figure 4 Multiple regression hyperplane List of Tables Table 1 Dummy Variable Interpretation.. Table 2 RTAs assessed and Members Table 3 Regression results of individual years Table 4 Regression results of PCS List of Formulas Formula 1 Gravity model equation Formula 2 Log linear form of the gravity model Formula 3 Current gravity specifications.. Abbreviations CGE: Computable General Equilibrium COMESA: Common Market for Eastern and Southern Africa FTA: Free Trade Agreement GATT: General Agreement on Tariffs and Trade GDP: Gross Domestic Product MERCOSUR: Mercado ComÃÆ' ºn del Sur RTA signed between Brazil, Argentina, Uruguay and Paraguay NAFTA: North American Free Trade Agreement OLS: Ordinary Least Squares PCS: Pooled Cross-Section PTA: Preferential Trade Agreement RIA: Regional Integration Agreement RTA: Regional Trade Agreement SICA: Sistema de IntegraciÃÆ' ³n Centro Americana RTA between Honduras, Costa Rica, El Salvador, Guatemala, Nicaragua Panama and Belize SS: South-South UNCTAD: United Nations Conference on Trade and Development WB: World Bank WITS: World Integrated Trade Solution WTO: World Trade Organization 1. Introduction Background Four hundred and sixty two RTAs have been notified to the WTO up to February 2010 (WTO,2010). From 1948-1994 the GATT received one hundred and twenty four notifications of RTAs, and since its creation in 1995, the WTO has received over 300 RTA notifications, (WTO,2010). This trend of forming trading blocs is likely to become stronger as more RTAs are currently under negotiation. Of particular interest to economists, and the focus of this paper, are South-South RTAs, that is, RTAs signed between countries of low income levels. There are reasons to believe that SS RTAs may not only fail to stimulate economic growth among member countries, but also hinder growth for these countries. In their book Regional Integration and Development, Winters and Schiffer (2003) state that there is some evidence that North-South RTAs stimulate economic growth in the southern partner, little evidence that North-North RTAs stimulate growth and NO evidence that South-South RTAs do so. Specifically they argue that SS RTAs do not provide partners with access to technology or knowledge that is characteristic of rich countries; SS RTAs are unlikely to add credibility to government policies and may even hinder investment if not accompanied by liberalization of trade with the rest of the world; and, SS RTAs are likely to generate only trade diversion and no trade creation Mayda and Steinberg (2006) argue that SS RTAs are unlikely to provide the positive effects of competition and economies of scale because partner countries are both small and poor. In addition, the loss of fiscal revenues harms the member country economies and finally, SS RTAs are more likely to divert trade rather than create trade. Willmore (1976) and Nicholls (1998) make similar points using the Central American Common Market as an example. Trade creation and trade diversion are concepts that were introduced by Jacob Viner in 1950. Both terms refer to the redirection of trade flows as a consequence of an RTA. In trade creation, goods that were previously produced by a local economy are instead imported from more efficient producers in countries within the RTA. Trade diversion refers to the redirecting of trade from the more efficient producer to a less efficient producer within the RTA. In both cases, trade creation and trade diversion, the trade flows are affected by the reduction of tariffs to member countries typical of RTAs. Trade creation and trade diversion are explained with more detail in section 2.1 of this paper. A number of studies have been conducted to assess the effects of SS RTAs in partner countries -most of them attempt to determine if the RTAs were trade creating or trade diverting e.g. Evans (1998), Lewis et al. (1999), Flores (1997), Cernat (2001,2003)), Subramanian and Tamirisa (2001), Mayda and Steinberg (2006). Different methods have been used and the results are mixed. As a reference, this paper focuses on the results of Cernat (2001, 2003), Flores (1997), and Mayda and Steinberg (2006). Different methods were used in these studies and the results were mixed. Cernat (2001) used the log-linear form of the gravity equation to assess nine SS RTAs. He finds evidence that suggests that SS RTAs are less trade diverting than theoretically predicted. Cernat (2001) findings suggest that Mercosur and the Andean Community were overall, trade diverting. On the other hand Flores (1997), using a CGE analysis, concluded that Mercosur was trade creating. Mayda and Steinberg (2006) use a difference-in-difference estimation strategy at commodity level to assess the impact of COMESA on Ugandan imports. They present evidence that South-South trade agreements create positive but little economic gains, through changes in trade patterns, for their members. This is different from Cernat (2001) results, which indicate that imports into COMESA members from third countries were on average 30 per cent higher than those predicted without the trade diversion dummy variable. Mayda and Steinberg (2006) find evidence that no trade diversion takes place in COMESA. The mixed results from these studies, the increasing number of SS RTAs underway and the high number of countries wanting to join completely or in part in these RTAs poses the following questions: Why do policy makers from these countries advocate in favor of these RTAs? Should these RTAs be pursued?, and the still not categorically answered question: Are South-South Regional Trade Agreements trade creating or trade diverting? Using the gravity model, this paper aims to get evidence from SS RTAs from the Americas. 1.2 Problem definition Do South-South Regional Trade Agreements create trade or divert trade? The literature on this topic is vast and contradictory. Everybody thinks that SS-RTAs are trade diverting. Some papers present evidence of this. Other present evidence that they are actually trade creating. Finally others find evidence of very little trade creation and no significant evidence of trade diversion. With so many RTAS in place and many others underway, it is important to understand the effects of creating these trade blocs. Should poor countries pursue RTAs with poor countries? Are SS RTAs building blocks or stumbling stones towards the world liberalization of trade? 1.3 Research Objective The main objective of this paper is to determine if MERCOSUR, Andean Community, and SICA were trade creating or trade diverting in the years 1995, 1998, 1999, 2003, 2007. 1.3.1 Major research question Is there significant evidence of trade creation or trade diversion on the years 1995,1998,1999,2003,2007 for Mercosur, Andean Community and SICA? 1.3.2 Minor research question Is there significant evidence that suggests that RTA members of the above mentioned RTAs increased trade between them and their partners? Is there significant evidence that suggests that members of the above mentioned RTAs increased trade between them and third countries? Is there significant evidence that suggests that the increase in trade between RTA partners of the above mentioned RTAs is higher than the decrease in trade between RTA members and third countries? 1.4 Theoretical Framework 1.4.1 The Gravity model of trade The gravity model uses Newtonian gravity principles to study human behavior. It is widely used by economists and social scientists to predict flows of trade, people, goods, money, and other variables as an effect of changes in economic policies, fiscal policies, new laws, bans and other distortions to the flow of a given variable. The original gravity model of trade assumes that two countries will trade more or less depending on the sizes of their economies and the distance between their economic centers. It was created independently by Tinbergen (1962) and PÃÆ' ¶yhÃÆ' ¶nen (1963) and augmented in later years to include other independent variables that may cause a change in trade flows. These augmented versions of the basic gravity model may include: population of the two countries, presence of common borders, same language, common colonizer, and others that the researcher regards as relevant. The gravity model specifications used in this paper are similar to those of Cernat(2001) and Cheng Hall (2003). These specifications are used to run OLS regressions on trade data of 1995, 1998, 1998, 2003 and 2007. One set of pooled data including the years mentioned is analyzed using the same gravity specifications. The results of these regressions provide evidence of gross trade creation and diversion as specified by Balassa (1967) 1.4.2 Research Methodology and Design The paper uses standard OLS analysis, with bilateral imports as a dependent variable and 17 independent variables: GDP of the importing country, GDP of the exporting country, Population of the importing country and population of the exporting country, distance between the capital cities of each country pair, Intra_x dummy variable for each RTA, Extra_x dummy variable for each RTA. The values of GDPs, distance and populations are used in their logarithmic form. GDPs and population data was collected from the WB databank. Trade data was collected from UNCTADs database using the WB banks WITS application. 1.4.3 Research Assumptions Costs of transportation are proportional to the great circle distance between economic centers of countries studied All countries have one economic center, namely their capital cities. The error coefficient of the log-linear gravity model used in this paper is normally distributed with a mean of zero and constant variance for all observations. It is also assumed that error pairs are uncorrelated. GDPs, population, and trade data collected belongs to the population 1.4.4 Research Limitations 1.5 Thesis Structure The remainder of this paper is organized as follows: Chapter 2 presents a literature review that explains trade creation and trade diversion, the effect of both and findings of previous papers that assess RTAs. Chapter 3 explains the gravity model used on the paper, how data was collected and organized, and the considerations in analyzing data. Chapter 4 summarizes the findings and Chapter 5 concludes. 2. Literature Review There is extensive literature on RTAs. This literature either predicts the effects of a RTAs using a computable-general equilibrium analysis or they measure the effects of an FTA using aggregate data or commodity level data. The concern of most authors, and the reason why they conduct their research, is that FTAs and specially SS FTAs may divert trade rather than create it. In the former case, purchases from an efficient producing country are replaced by purchases of a less efficient FTA partner. This section serves three purposes: 1. It explains trade creation and trade diversion to the reader so she can better understand the methodology used to assess the selected RTAs. 2. It presents the reader with the results of previous findings so that the reader can compare the results of this paper with previous results of other authors. 3. It gross trade creation and diversion so that the reader can understand the results of the research. 2.1 Trade Creation and Trade Diversion Trade creation and trade diversion as defined by Viner (1950), refer to changes in flow of trade between nations. Trade creation happens when trade is switched from less efficient producers of one country to more efficient producers in another country a better allocation of resources. In trade diversion trade is shifted from more efficient producers in one country to less efficient producers in another country -a worsening in the allocation of resources. 2.1.1 Trade Creation Trade creation can be defined as the net welfare gain that results from the initiation of an RTA, both on the production and on the consumption side. Some economists though, think that it is more precise to think of trade creation only as the increase in welfare from the production side (Senior-Nello S, 2010). In this paper the former definition of welfare is considered. To understand trade creation, imagine the following scenario (Figure 1): The country in question, Country X, say Honduras, imports product Q from country M (United States) at price Pw+t, which includes an ad valorem tax and is the same price offered by other nations in the world, including country E (El Salvador). At this price, Honduras imports 20 units and consumes 60. The remaining 40 units are imported from the US. This is illustrated by the Honduran supply and demand lines in Figure 1 and the perfectly elastic supply curve with free trade of El Salvador. It is understood that a change in Honduran imports of product Q cannot affect the world price of product Q. Figure 1. Trade Creation If Honduras signed an RTA with El Salvador and the price of product Q from El Salvador dropped to PE, Honduras would now produce 10 units of product Q, consume 70, and import the difference of 60 units. Because El Salvador now offers a lower price for product Q, Honduras now imports this product from El Salvador and not from the US. The consumer surplus gains of this RTA are represented by areas a+b+c+d. The loss in producer surplus is indicated by area a. The loss of tariff revenue for Honduras is area c. Therefore the net welfare increase of this RTA between El Salvador and Honduras is indicated by triangles b and d. Triangle b represents the amount of production that was shifted from less efficient producers in Honduras to more efficient producers in El Salvador a better allocation of resources. Triangle d represents the increase in consumption of product Q. 2.1.2 Trade Diversion Trade Diversion is illustrated in figure 2. Again the supply and demand lines are those of Honduras for product Q. Line S1 and S2 are the perfectly elastic supply curves of USA and El Salvador respectively, and lines S1+t and S2+t are the tax inclusive supply curves of the same two countries. Figure 2. Trade Diversion Honduras imports product Q from the US at tax inclusive price Pw+t. El Salvador offers product Q at price PE+t and thus does not benefit from Honduran purchases. At price Pw+t Honduras produces 20 units, consumes 60, and imports 40 from the US. If Honduras and El Salvador now form an RTA and do not include the US, tariffs will be removed on imports from El Salvador but not from imports from the US. After forming the RTA Honduras would produce 10 million units, consume 80 million and import 60 million units of product Q from El Salvador at price PE. The RTA has diverted trade from more efficient producers in the US to less efficient producers in El Salvador, so there is a worsening in the allocation of resources. On the other hand 10 million units are now imported from El Salvador instead of being produced at home in Honduras. At the same time 40 million units that were previously imported from the US are now being imported from El Salvador. The welfare loss from trade diversion is reflected rectangle f. The 40 million units that were imported from more efficient producers in the US whose free trade price is $1.00 are now imported from El Salvador at $2.00. The welfare loss is $40 million. The welfare gain from the customs union is calculated as the areas of triangles b and d. Triangle b is the welfare gain in the production side: $5 million. Triangle d is the welfare gain in the consumption side: $10 million. The total impact on welfare as a result of the RTA is given by the sum of the areas of triangles b and d minus the area of rectangle f (b+d-f): welfare gain minus welfare loss. In this case the RTA generated a welfare loss of $25 million. Figure 2 illustrates that the idea of trade creation and trade diversion can be misleading. If, for example, the sum of areas of triangles b and d would be greater than the area of rectangle f, the RTA would cause a net welfare gain. In this scenario, although trade has been diverted from more efficient producers in one country to less efficient producers in another, the RTA increased welfare for the RTA signing country. 2.1.3 Gross Trade Creation Following the lead of Jacob Viner, Balassa (1967) evaluated the effects of the European Common Market with reference to its trade creating and trade diverting effect using Tinbergen (1962) and PÃÆ' ¶yhÃÆ' ¶nen (1963) model -the gravity model. In his work he developed model that captured substitution of less efficient domestic and foreign suppliers for more efficient foreign suppliers gross trade creation; which is different than Viners definition of trade creation according to which trade is created only at the expense of local producers. To illustrate the difference gross trade creation and trade creation proper as defined by Viner (1950), consider three trading partners of one particular product countries A, B, and C, product Q (See Figure 3). Before signing a RTA with country B, Country A imports product Q from both, Country B and Country C in equal amounts and has 4 local producers of the same product (Figure 3a). In the case of trade creation proper (Figure 3b), after signing a RTA with country B, Country A continues to import equal amounts of product Q from countries B and C but has reduced the number of local producers of the same product. More efficient producers in Country B have absorbed market share from local producers in Country A trade creation proper. Gross trade creation on the other hand (Figure 3c), considers that trade is created not only when local producers are substituted, but also when producers in third countries are substituted. In this case, after signing a RTA with country B, Country A decreases its imports of product Q from Country C and increases imports of the same product from Country B while keeping the same number of local producers. It is important to note that gross trade creation assumes that substituted producers in Country C were less efficient than producers in country B; the contrary would constitute trade diversion. Figure 3. Trade Creation Proper vrs Gross Trade Creation Like in Cernat (2001), this paper evaluates the gross trade creating effects of the assessed RTAs. In his paper, Balassa (1967) provides evidence of trade creation in the European Common Market during six years since the Markets establishment. Again, trade creation applies to the substitution of any less efficient producer for a more efficient one, independent of the producers base country. The why of the expected differences between the results of developed country RTAs and SS RTAs is explained in the next section. 2.2 Empirical Evidence from SS RTAs A number of studies have been conducted to assess the effects of SS RTAs in partner countries -most of them attempt to determine if the RTAs were trade creating or trade diverting e.g. Evans (1998), Lewis et al. (1999), Flores (1997), Cernat (2001), Subramanian and Tamirisa (2001), Cernat (2003), Mayda and Steinberg (2006). Different methods have been used and the results are mixed. This paper uses methods similar to Cernat (2001) and Cheng Wall (2003). In his paper, Cernat(2001) used the log-linear form of the gravity equation to asses nine SS RTAs. He finds evidence that suggests that SS RTAs are less trade diverting than theoretically predicted. Cernats(2001) findings suggest that Mercosur and the Andean Community were overall, trade diverting. Mayda and Steinberg(2006) use a difference-in-difference estimation strategy at commodity level to assess the impact of COMESA on Ugandan imports. They present evidence that South-South trade agreements create positive but little economic gains, through changes in trade patterns, for their members (Mayda and Steinberg, 2003). This is different from Cernats(2001) results, which indicate that imports into COMESA members from third countries were on average 30 per cent higher than those predicted without the trade diversion dummy variable. Mayda and Steinberg (2006) find evidence that no trade diversion takes place in COMESA. The mixed results from these studies, the increasing number of SS RTAs underway and the high number of countries wanting to join completely or in part in these RTAs poses the following questions: Why do policy makers from these countries advocate in favor of these RTAs? Should these RTAs be pursued?, and the still not categorically answered question: Are South-South Regional Trade Agreements trade creating or trade diverting? Using the gravity model, this paper aims to get evidence from SS RTAs from the Americas. Theoretical Framework and Research Methodology ***Intro*** Problem Definition Research Objective Research Questions 3.1 Theoretical Framework 3.1.1 Multiple Regression Analysis and Model Building Figure 4. Regression Hyperplane Multiple regression analysis is a method of inferential statistics that measures the relationship between two or more independent variables and one dependent variable. The multiple regression model is given by: Where: y = dependent variable = regression constant of the population = regression coefficient for each variable xj=1,2,k k = number of independent variables = error of the model Different from a simple regression equation -which forms a straight line in a two-dimensional space to represent the linear relationship between two variables the multiple regression model forms a hyperplane in a multidimensional space (Figure 4). This hyperplane represents the relationship between the dependent variable and k independent variables. To build a multiple regression model, that is, to construct a mathematical equation that represents the relationship between independent and dependent variables, a researcher must decide: The question that needs to be answered The potential independent variables What is a representative sample of the population should be at least four times the number of independent variables (Groebner, et al, 2008) The model used in this paper is well known and widely used by social scientists to measure the flow of various types of variables. This model is explained in section 3.1.3. 3.1.2 Regression Model Diagnosis To ensure the significance of an OLS regression analysis results, the following evaluation criteria are usually used (Groebner, et al, 2008): The coefficient of determination (R2 and R2 adjusted) Significance of the overall model (F-test) Significance of individual variables (t-tests) Size of the standard deviation of the model Multicollinearity of variables The coefficient of determination measures the proportion of variation in the dependent variable that can be explained with the independent variables used by the model. The value of R2 may range from 0-1, with 1 representing a perfect linear relationship between dependent and independent variables. Higher values of R2 are preferred as they would indicate that the chosen independent variables explain better the variations in the dependent variables. A derivate indicator, called adjusted R2, takes into account the number of independent variables in the model, and their contribution the variations in the dependent variable. Because R2 increases when independent variables are added to the model, even if the new variables have no relationship with the dependent variable, adjusted R2 evaluates the model more precisely. The Significance of the overall model can be determined by comparing the Significance F value given in the regression output of a statistical software application, and the critical value for a given alpha level. The critical value for a given alpha level is determined using t-tables and statistical procedures explained in Groebner (2008). The Significance of individual variables is determined by comparing their calculated t-values with the critical t-value of the model. If their calculated t-values are greater than their critical t-values the variable is considered significant. To determine the critical t-values of independent variables, degrees of freedom need to be calculated and interpolated with the desired level of significance in a t-table. For detailed explanations see Groebner (2008). The size of the standard deviation of the model measures the dispersion of observed values of the dependent variable, and the predicted values for the same variable. It is up to the researcher to determine an acceptable range for the standard error estimation. Multicollinearity occurs when two variables provide overlapping information to explain the variation in the dependent variable. To measure multicollinearity the researcher can use the VIF as an indicator. Generally, if the VIF 3.1.3 The Gravity Model of Trade Following Isaac Newtons principle of gravity, according to which two bodies will attract each other more when their sizes are increased and the distance between them is shortened; the gravity model explains trade flow between two countries based on the size of their economies and the distance between their economic centers. The equation representation of the gravity model of trade is: (Formula 1) Where Fg represents trade flow, G is the constant, m1 and m2 are the economic dimensions of the two countries in question, and d is the distance between the two countries. In its basic log-linear form, the gravity equation is as follows: (Formula2) Where is the bilateral trade flow between countries i and j at time t, ÃŽÂ ± is the constant, is the natural logarithm of the GDP of country i, is the natural logarithm of the GDP of country j, is the natural logarithm of the distance between country i and country j, and ÃŽÂ µ is the normally distributed error. This basic gravity model is usually augmented by including other variables like adjacency, common language, colonial links, common currency, and RTA membership among others. Different authors have suggested many different specifications for the gravity model of trade  [1]  , however there is no consensus about which model specification is more accurate and serves best in assessing RTAs. Moreover other authors have suggested that the gravity model is biased due to endogeneity and reverse causality (Magee, 2003) and have led others to use entirely different methods to asses RTAs (Mayda Steinberg (2006). This paper uses a gravity model specification that is similar to Cernat (2001) but considers Cheng Walls (2003) suggestions of eliminating dummy variables that might capture unintended trade distorting variables. To assess trade creation and trade diversion in nine RTAs, Cernat(2001) adds two dummy variables to an already augmented specification of the model: Intra_RTA and Extra_RTA. The Intra_RTA dummy becomes a 1 when both, the importing and the exporting countries, are partners in the RTA being assessed by the two dummies. The Extra_RTA dummy becomes one when the importing country is part of the assessed RTA but the exporter is a third country. The model uses bilateral trade flows as a dependent variable and 18 independent variables: GDP of importing country, GDP of the exporting country, GDP per capita of the importing country, GDP per capita of the exporting country, Population of the importing country, population of the exporting country, distance between the capital cities of both countries, an adjacency dummy variable, a common language dummy variable, nine Intra_RTA dummy variables (one for each RTA assessed), and nine Extra_RTA dummy variables (one for each RTA assessed). All non-dummy variables expressed in their logarithmic form. In theory, the Intra_RTA dummies will capture the effect that the assessed RTA had on trade between partners of the RTA; and the Extra_RTA dummy captures the effect of the same RTA on trade of RTA members with third countries. To diagnose a RTA as trade crating or trade diverting, Cernat (2001) designed an Intra-Extra coefficient table (Table# in this paper). According to this table, if a trade agreement increased trade between its partners at the expense of third countries -diverted trade, the Intra_RTA dummy should be positive and the Extra_RTA dummy negative. If the agreement created trade instead, the coefficients of both dummies would be positive. Coefficient Extra_RTA Intra_RTA Sign + + Trade creation and trade expansion Trade diversion Trade expansion Trade contraction Table 1: Dummy Variable Interpretation Cheng Wall (2003) use a fixed-effect panel data analysis to measure the effect on trade of RTAs over time. Their proposed model allegedly controls the heterogeneity bias in the gravity model of trade. In it, Cheng Wall (2003) drop all dummy variables and even drop the distance variable. They argue that these variables bias the gravity model and they motivate their argument in a number of ways. First, they reason that economic distances are too hard to measure with accuracy because big countries have many economic centers, that are thousands of miles apart and that serve as trade centers for diffe Effect on Trade Flows of Regional Trade Agreements Effect on Trade Flows of Regional Trade Agreements Abstract This paper studies the effect on trade flows of RTAs signed between developing economies. It uses a variation of the gravity model of trade to asses five RTAs: Mercosur, The Andean Community, SICA, the EU, Chile-China. Contents Abstract iii List of Figures vi List of Tables vi List of Formulas vi 1. Introduction viii 1.1Background viii 1.2 Problem definition x 1.3 Research Objective x 1.3.1 Major research question x 1.3.2 Minor research question xi 1.4 Theoretical Framework xi 1.4.1 The Gravity model of trade xi 1.4.2 Research Methodology and Design xii 1.4.3 Research Assumptions xii 1.4.4 Research Limitations xii 1.5 Thesis Structure xiii 2. Literature Review xiii 2.1 Trade Creation and Trade Diversion xiv 2.1.1 Trade Creation xiv 2.1.2 Trade Diversion xvii 2.1.3 Gross Trade Creation xviii 2.2 Empirical Evidence from SS RTAs xx 3.Theoretical Framework and Research Methodology xxi 3.1 Theoretical Framework xxi 3.1.1 Multiple Regression Analysis and Model Building xxi 3.1.2 Regression Model Diagnosis xxii 3.1.3 The Gravity Model of Trade xxiii 3.1.4 Research Assumptions xxvii 3.1.5 Research Limitations xxvii 3.2 Research Methodology xxvii 3.2.1 Research Type and Approach xxvii 3.2.2 Data Collection xxx 4. Findings and Results xxxi 4.1 The effect of RTAs xxxi 5. Conclusions xxxiii 6. Appendix xxxiv 7. References xxxvii List of Figures Figure 1 Trade Creation. Figure 2 Trade Diversion Figure 3 Trade Creation Proper vrs. Gross Trade Creation Figure 4 Multiple regression hyperplane List of Tables Table 1 Dummy Variable Interpretation.. Table 2 RTAs assessed and Members Table 3 Regression results of individual years Table 4 Regression results of PCS List of Formulas Formula 1 Gravity model equation Formula 2 Log linear form of the gravity model Formula 3 Current gravity specifications.. Abbreviations CGE: Computable General Equilibrium COMESA: Common Market for Eastern and Southern Africa FTA: Free Trade Agreement GATT: General Agreement on Tariffs and Trade GDP: Gross Domestic Product MERCOSUR: Mercado ComÃÆ' ºn del Sur RTA signed between Brazil, Argentina, Uruguay and Paraguay NAFTA: North American Free Trade Agreement OLS: Ordinary Least Squares PCS: Pooled Cross-Section PTA: Preferential Trade Agreement RIA: Regional Integration Agreement RTA: Regional Trade Agreement SICA: Sistema de IntegraciÃÆ' ³n Centro Americana RTA between Honduras, Costa Rica, El Salvador, Guatemala, Nicaragua Panama and Belize SS: South-South UNCTAD: United Nations Conference on Trade and Development WB: World Bank WITS: World Integrated Trade Solution WTO: World Trade Organization 1. Introduction Background Four hundred and sixty two RTAs have been notified to the WTO up to February 2010 (WTO,2010). From 1948-1994 the GATT received one hundred and twenty four notifications of RTAs, and since its creation in 1995, the WTO has received over 300 RTA notifications, (WTO,2010). This trend of forming trading blocs is likely to become stronger as more RTAs are currently under negotiation. Of particular interest to economists, and the focus of this paper, are South-South RTAs, that is, RTAs signed between countries of low income levels. There are reasons to believe that SS RTAs may not only fail to stimulate economic growth among member countries, but also hinder growth for these countries. In their book Regional Integration and Development, Winters and Schiffer (2003) state that there is some evidence that North-South RTAs stimulate economic growth in the southern partner, little evidence that North-North RTAs stimulate growth and NO evidence that South-South RTAs do so. Specifically they argue that SS RTAs do not provide partners with access to technology or knowledge that is characteristic of rich countries; SS RTAs are unlikely to add credibility to government policies and may even hinder investment if not accompanied by liberalization of trade with the rest of the world; and, SS RTAs are likely to generate only trade diversion and no trade creation Mayda and Steinberg (2006) argue that SS RTAs are unlikely to provide the positive effects of competition and economies of scale because partner countries are both small and poor. In addition, the loss of fiscal revenues harms the member country economies and finally, SS RTAs are more likely to divert trade rather than create trade. Willmore (1976) and Nicholls (1998) make similar points using the Central American Common Market as an example. Trade creation and trade diversion are concepts that were introduced by Jacob Viner in 1950. Both terms refer to the redirection of trade flows as a consequence of an RTA. In trade creation, goods that were previously produced by a local economy are instead imported from more efficient producers in countries within the RTA. Trade diversion refers to the redirecting of trade from the more efficient producer to a less efficient producer within the RTA. In both cases, trade creation and trade diversion, the trade flows are affected by the reduction of tariffs to member countries typical of RTAs. Trade creation and trade diversion are explained with more detail in section 2.1 of this paper. A number of studies have been conducted to assess the effects of SS RTAs in partner countries -most of them attempt to determine if the RTAs were trade creating or trade diverting e.g. Evans (1998), Lewis et al. (1999), Flores (1997), Cernat (2001,2003)), Subramanian and Tamirisa (2001), Mayda and Steinberg (2006). Different methods have been used and the results are mixed. As a reference, this paper focuses on the results of Cernat (2001, 2003), Flores (1997), and Mayda and Steinberg (2006). Different methods were used in these studies and the results were mixed. Cernat (2001) used the log-linear form of the gravity equation to assess nine SS RTAs. He finds evidence that suggests that SS RTAs are less trade diverting than theoretically predicted. Cernat (2001) findings suggest that Mercosur and the Andean Community were overall, trade diverting. On the other hand Flores (1997), using a CGE analysis, concluded that Mercosur was trade creating. Mayda and Steinberg (2006) use a difference-in-difference estimation strategy at commodity level to assess the impact of COMESA on Ugandan imports. They present evidence that South-South trade agreements create positive but little economic gains, through changes in trade patterns, for their members. This is different from Cernat (2001) results, which indicate that imports into COMESA members from third countries were on average 30 per cent higher than those predicted without the trade diversion dummy variable. Mayda and Steinberg (2006) find evidence that no trade diversion takes place in COMESA. The mixed results from these studies, the increasing number of SS RTAs underway and the high number of countries wanting to join completely or in part in these RTAs poses the following questions: Why do policy makers from these countries advocate in favor of these RTAs? Should these RTAs be pursued?, and the still not categorically answered question: Are South-South Regional Trade Agreements trade creating or trade diverting? Using the gravity model, this paper aims to get evidence from SS RTAs from the Americas. 1.2 Problem definition Do South-South Regional Trade Agreements create trade or divert trade? The literature on this topic is vast and contradictory. Everybody thinks that SS-RTAs are trade diverting. Some papers present evidence of this. Other present evidence that they are actually trade creating. Finally others find evidence of very little trade creation and no significant evidence of trade diversion. With so many RTAS in place and many others underway, it is important to understand the effects of creating these trade blocs. Should poor countries pursue RTAs with poor countries? Are SS RTAs building blocks or stumbling stones towards the world liberalization of trade? 1.3 Research Objective The main objective of this paper is to determine if MERCOSUR, Andean Community, and SICA were trade creating or trade diverting in the years 1995, 1998, 1999, 2003, 2007. 1.3.1 Major research question Is there significant evidence of trade creation or trade diversion on the years 1995,1998,1999,2003,2007 for Mercosur, Andean Community and SICA? 1.3.2 Minor research question Is there significant evidence that suggests that RTA members of the above mentioned RTAs increased trade between them and their partners? Is there significant evidence that suggests that members of the above mentioned RTAs increased trade between them and third countries? Is there significant evidence that suggests that the increase in trade between RTA partners of the above mentioned RTAs is higher than the decrease in trade between RTA members and third countries? 1.4 Theoretical Framework 1.4.1 The Gravity model of trade The gravity model uses Newtonian gravity principles to study human behavior. It is widely used by economists and social scientists to predict flows of trade, people, goods, money, and other variables as an effect of changes in economic policies, fiscal policies, new laws, bans and other distortions to the flow of a given variable. The original gravity model of trade assumes that two countries will trade more or less depending on the sizes of their economies and the distance between their economic centers. It was created independently by Tinbergen (1962) and PÃÆ' ¶yhÃÆ' ¶nen (1963) and augmented in later years to include other independent variables that may cause a change in trade flows. These augmented versions of the basic gravity model may include: population of the two countries, presence of common borders, same language, common colonizer, and others that the researcher regards as relevant. The gravity model specifications used in this paper are similar to those of Cernat(2001) and Cheng Hall (2003). These specifications are used to run OLS regressions on trade data of 1995, 1998, 1998, 2003 and 2007. One set of pooled data including the years mentioned is analyzed using the same gravity specifications. The results of these regressions provide evidence of gross trade creation and diversion as specified by Balassa (1967) 1.4.2 Research Methodology and Design The paper uses standard OLS analysis, with bilateral imports as a dependent variable and 17 independent variables: GDP of the importing country, GDP of the exporting country, Population of the importing country and population of the exporting country, distance between the capital cities of each country pair, Intra_x dummy variable for each RTA, Extra_x dummy variable for each RTA. The values of GDPs, distance and populations are used in their logarithmic form. GDPs and population data was collected from the WB databank. Trade data was collected from UNCTADs database using the WB banks WITS application. 1.4.3 Research Assumptions Costs of transportation are proportional to the great circle distance between economic centers of countries studied All countries have one economic center, namely their capital cities. The error coefficient of the log-linear gravity model used in this paper is normally distributed with a mean of zero and constant variance for all observations. It is also assumed that error pairs are uncorrelated. GDPs, population, and trade data collected belongs to the population 1.4.4 Research Limitations 1.5 Thesis Structure The remainder of this paper is organized as follows: Chapter 2 presents a literature review that explains trade creation and trade diversion, the effect of both and findings of previous papers that assess RTAs. Chapter 3 explains the gravity model used on the paper, how data was collected and organized, and the considerations in analyzing data. Chapter 4 summarizes the findings and Chapter 5 concludes. 2. Literature Review There is extensive literature on RTAs. This literature either predicts the effects of a RTAs using a computable-general equilibrium analysis or they measure the effects of an FTA using aggregate data or commodity level data. The concern of most authors, and the reason why they conduct their research, is that FTAs and specially SS FTAs may divert trade rather than create it. In the former case, purchases from an efficient producing country are replaced by purchases of a less efficient FTA partner. This section serves three purposes: 1. It explains trade creation and trade diversion to the reader so she can better understand the methodology used to assess the selected RTAs. 2. It presents the reader with the results of previous findings so that the reader can compare the results of this paper with previous results of other authors. 3. It gross trade creation and diversion so that the reader can understand the results of the research. 2.1 Trade Creation and Trade Diversion Trade creation and trade diversion as defined by Viner (1950), refer to changes in flow of trade between nations. Trade creation happens when trade is switched from less efficient producers of one country to more efficient producers in another country a better allocation of resources. In trade diversion trade is shifted from more efficient producers in one country to less efficient producers in another country -a worsening in the allocation of resources. 2.1.1 Trade Creation Trade creation can be defined as the net welfare gain that results from the initiation of an RTA, both on the production and on the consumption side. Some economists though, think that it is more precise to think of trade creation only as the increase in welfare from the production side (Senior-Nello S, 2010). In this paper the former definition of welfare is considered. To understand trade creation, imagine the following scenario (Figure 1): The country in question, Country X, say Honduras, imports product Q from country M (United States) at price Pw+t, which includes an ad valorem tax and is the same price offered by other nations in the world, including country E (El Salvador). At this price, Honduras imports 20 units and consumes 60. The remaining 40 units are imported from the US. This is illustrated by the Honduran supply and demand lines in Figure 1 and the perfectly elastic supply curve with free trade of El Salvador. It is understood that a change in Honduran imports of product Q cannot affect the world price of product Q. Figure 1. Trade Creation If Honduras signed an RTA with El Salvador and the price of product Q from El Salvador dropped to PE, Honduras would now produce 10 units of product Q, consume 70, and import the difference of 60 units. Because El Salvador now offers a lower price for product Q, Honduras now imports this product from El Salvador and not from the US. The consumer surplus gains of this RTA are represented by areas a+b+c+d. The loss in producer surplus is indicated by area a. The loss of tariff revenue for Honduras is area c. Therefore the net welfare increase of this RTA between El Salvador and Honduras is indicated by triangles b and d. Triangle b represents the amount of production that was shifted from less efficient producers in Honduras to more efficient producers in El Salvador a better allocation of resources. Triangle d represents the increase in consumption of product Q. 2.1.2 Trade Diversion Trade Diversion is illustrated in figure 2. Again the supply and demand lines are those of Honduras for product Q. Line S1 and S2 are the perfectly elastic supply curves of USA and El Salvador respectively, and lines S1+t and S2+t are the tax inclusive supply curves of the same two countries. Figure 2. Trade Diversion Honduras imports product Q from the US at tax inclusive price Pw+t. El Salvador offers product Q at price PE+t and thus does not benefit from Honduran purchases. At price Pw+t Honduras produces 20 units, consumes 60, and imports 40 from the US. If Honduras and El Salvador now form an RTA and do not include the US, tariffs will be removed on imports from El Salvador but not from imports from the US. After forming the RTA Honduras would produce 10 million units, consume 80 million and import 60 million units of product Q from El Salvador at price PE. The RTA has diverted trade from more efficient producers in the US to less efficient producers in El Salvador, so there is a worsening in the allocation of resources. On the other hand 10 million units are now imported from El Salvador instead of being produced at home in Honduras. At the same time 40 million units that were previously imported from the US are now being imported from El Salvador. The welfare loss from trade diversion is reflected rectangle f. The 40 million units that were imported from more efficient producers in the US whose free trade price is $1.00 are now imported from El Salvador at $2.00. The welfare loss is $40 million. The welfare gain from the customs union is calculated as the areas of triangles b and d. Triangle b is the welfare gain in the production side: $5 million. Triangle d is the welfare gain in the consumption side: $10 million. The total impact on welfare as a result of the RTA is given by the sum of the areas of triangles b and d minus the area of rectangle f (b+d-f): welfare gain minus welfare loss. In this case the RTA generated a welfare loss of $25 million. Figure 2 illustrates that the idea of trade creation and trade diversion can be misleading. If, for example, the sum of areas of triangles b and d would be greater than the area of rectangle f, the RTA would cause a net welfare gain. In this scenario, although trade has been diverted from more efficient producers in one country to less efficient producers in another, the RTA increased welfare for the RTA signing country. 2.1.3 Gross Trade Creation Following the lead of Jacob Viner, Balassa (1967) evaluated the effects of the European Common Market with reference to its trade creating and trade diverting effect using Tinbergen (1962) and PÃÆ' ¶yhÃÆ' ¶nen (1963) model -the gravity model. In his work he developed model that captured substitution of less efficient domestic and foreign suppliers for more efficient foreign suppliers gross trade creation; which is different than Viners definition of trade creation according to which trade is created only at the expense of local producers. To illustrate the difference gross trade creation and trade creation proper as defined by Viner (1950), consider three trading partners of one particular product countries A, B, and C, product Q (See Figure 3). Before signing a RTA with country B, Country A imports product Q from both, Country B and Country C in equal amounts and has 4 local producers of the same product (Figure 3a). In the case of trade creation proper (Figure 3b), after signing a RTA with country B, Country A continues to import equal amounts of product Q from countries B and C but has reduced the number of local producers of the same product. More efficient producers in Country B have absorbed market share from local producers in Country A trade creation proper. Gross trade creation on the other hand (Figure 3c), considers that trade is created not only when local producers are substituted, but also when producers in third countries are substituted. In this case, after signing a RTA with country B, Country A decreases its imports of product Q from Country C and increases imports of the same product from Country B while keeping the same number of local producers. It is important to note that gross trade creation assumes that substituted producers in Country C were less efficient than producers in country B; the contrary would constitute trade diversion. Figure 3. Trade Creation Proper vrs Gross Trade Creation Like in Cernat (2001), this paper evaluates the gross trade creating effects of the assessed RTAs. In his paper, Balassa (1967) provides evidence of trade creation in the European Common Market during six years since the Markets establishment. Again, trade creation applies to the substitution of any less efficient producer for a more efficient one, independent of the producers base country. The why of the expected differences between the results of developed country RTAs and SS RTAs is explained in the next section. 2.2 Empirical Evidence from SS RTAs A number of studies have been conducted to assess the effects of SS RTAs in partner countries -most of them attempt to determine if the RTAs were trade creating or trade diverting e.g. Evans (1998), Lewis et al. (1999), Flores (1997), Cernat (2001), Subramanian and Tamirisa (2001), Cernat (2003), Mayda and Steinberg (2006). Different methods have been used and the results are mixed. This paper uses methods similar to Cernat (2001) and Cheng Wall (2003). In his paper, Cernat(2001) used the log-linear form of the gravity equation to asses nine SS RTAs. He finds evidence that suggests that SS RTAs are less trade diverting than theoretically predicted. Cernats(2001) findings suggest that Mercosur and the Andean Community were overall, trade diverting. Mayda and Steinberg(2006) use a difference-in-difference estimation strategy at commodity level to assess the impact of COMESA on Ugandan imports. They present evidence that South-South trade agreements create positive but little economic gains, through changes in trade patterns, for their members (Mayda and Steinberg, 2003). This is different from Cernats(2001) results, which indicate that imports into COMESA members from third countries were on average 30 per cent higher than those predicted without the trade diversion dummy variable. Mayda and Steinberg (2006) find evidence that no trade diversion takes place in COMESA. The mixed results from these studies, the increasing number of SS RTAs underway and the high number of countries wanting to join completely or in part in these RTAs poses the following questions: Why do policy makers from these countries advocate in favor of these RTAs? Should these RTAs be pursued?, and the still not categorically answered question: Are South-South Regional Trade Agreements trade creating or trade diverting? Using the gravity model, this paper aims to get evidence from SS RTAs from the Americas. Theoretical Framework and Research Methodology ***Intro*** Problem Definition Research Objective Research Questions 3.1 Theoretical Framework 3.1.1 Multiple Regression Analysis and Model Building Figure 4. Regression Hyperplane Multiple regression analysis is a method of inferential statistics that measures the relationship between two or more independent variables and one dependent variable. The multiple regression model is given by: Where: y = dependent variable = regression constant of the population = regression coefficient for each variable xj=1,2,k k = number of independent variables = error of the model Different from a simple regression equation -which forms a straight line in a two-dimensional space to represent the linear relationship between two variables the multiple regression model forms a hyperplane in a multidimensional space (Figure 4). This hyperplane represents the relationship between the dependent variable and k independent variables. To build a multiple regression model, that is, to construct a mathematical equation that represents the relationship between independent and dependent variables, a researcher must decide: The question that needs to be answered The potential independent variables What is a representative sample of the population should be at least four times the number of independent variables (Groebner, et al, 2008) The model used in this paper is well known and widely used by social scientists to measure the flow of various types of variables. This model is explained in section 3.1.3. 3.1.2 Regression Model Diagnosis To ensure the significance of an OLS regression analysis results, the following evaluation criteria are usually used (Groebner, et al, 2008): The coefficient of determination (R2 and R2 adjusted) Significance of the overall model (F-test) Significance of individual variables (t-tests) Size of the standard deviation of the model Multicollinearity of variables The coefficient of determination measures the proportion of variation in the dependent variable that can be explained with the independent variables used by the model. The value of R2 may range from 0-1, with 1 representing a perfect linear relationship between dependent and independent variables. Higher values of R2 are preferred as they would indicate that the chosen independent variables explain better the variations in the dependent variables. A derivate indicator, called adjusted R2, takes into account the number of independent variables in the model, and their contribution the variations in the dependent variable. Because R2 increases when independent variables are added to the model, even if the new variables have no relationship with the dependent variable, adjusted R2 evaluates the model more precisely. The Significance of the overall model can be determined by comparing the Significance F value given in the regression output of a statistical software application, and the critical value for a given alpha level. The critical value for a given alpha level is determined using t-tables and statistical procedures explained in Groebner (2008). The Significance of individual variables is determined by comparing their calculated t-values with the critical t-value of the model. If their calculated t-values are greater than their critical t-values the variable is considered significant. To determine the critical t-values of independent variables, degrees of freedom need to be calculated and interpolated with the desired level of significance in a t-table. For detailed explanations see Groebner (2008). The size of the standard deviation of the model measures the dispersion of observed values of the dependent variable, and the predicted values for the same variable. It is up to the researcher to determine an acceptable range for the standard error estimation. Multicollinearity occurs when two variables provide overlapping information to explain the variation in the dependent variable. To measure multicollinearity the researcher can use the VIF as an indicator. Generally, if the VIF 3.1.3 The Gravity Model of Trade Following Isaac Newtons principle of gravity, according to which two bodies will attract each other more when their sizes are increased and the distance between them is shortened; the gravity model explains trade flow between two countries based on the size of their economies and the distance between their economic centers. The equation representation of the gravity model of trade is: (Formula 1) Where Fg represents trade flow, G is the constant, m1 and m2 are the economic dimensions of the two countries in question, and d is the distance between the two countries. In its basic log-linear form, the gravity equation is as follows: (Formula2) Where is the bilateral trade flow between countries i and j at time t, ÃŽÂ ± is the constant, is the natural logarithm of the GDP of country i, is the natural logarithm of the GDP of country j, is the natural logarithm of the distance between country i and country j, and ÃŽÂ µ is the normally distributed error. This basic gravity model is usually augmented by including other variables like adjacency, common language, colonial links, common currency, and RTA membership among others. Different authors have suggested many different specifications for the gravity model of trade  [1]  , however there is no consensus about which model specification is more accurate and serves best in assessing RTAs. Moreover other authors have suggested that the gravity model is biased due to endogeneity and reverse causality (Magee, 2003) and have led others to use entirely different methods to asses RTAs (Mayda Steinberg (2006). This paper uses a gravity model specification that is similar to Cernat (2001) but considers Cheng Walls (2003) suggestions of eliminating dummy variables that might capture unintended trade distorting variables. To assess trade creation and trade diversion in nine RTAs, Cernat(2001) adds two dummy variables to an already augmented specification of the model: Intra_RTA and Extra_RTA. The Intra_RTA dummy becomes a 1 when both, the importing and the exporting countries, are partners in the RTA being assessed by the two dummies. The Extra_RTA dummy becomes one when the importing country is part of the assessed RTA but the exporter is a third country. The model uses bilateral trade flows as a dependent variable and 18 independent variables: GDP of importing country, GDP of the exporting country, GDP per capita of the importing country, GDP per capita of the exporting country, Population of the importing country, population of the exporting country, distance between the capital cities of both countries, an adjacency dummy variable, a common language dummy variable, nine Intra_RTA dummy variables (one for each RTA assessed), and nine Extra_RTA dummy variables (one for each RTA assessed). All non-dummy variables expressed in their logarithmic form. In theory, the Intra_RTA dummies will capture the effect that the assessed RTA had on trade between partners of the RTA; and the Extra_RTA dummy captures the effect of the same RTA on trade of RTA members with third countries. To diagnose a RTA as trade crating or trade diverting, Cernat (2001) designed an Intra-Extra coefficient table (Table# in this paper). According to this table, if a trade agreement increased trade between its partners at the expense of third countries -diverted trade, the Intra_RTA dummy should be positive and the Extra_RTA dummy negative. If the agreement created trade instead, the coefficients of both dummies would be positive. Coefficient Extra_RTA Intra_RTA Sign + + Trade creation and trade expansion Trade diversion Trade expansion Trade contraction Table 1: Dummy Variable Interpretation Cheng Wall (2003) use a fixed-effect panel data analysis to measure the effect on trade of RTAs over time. Their proposed model allegedly controls the heterogeneity bias in the gravity model of trade. In it, Cheng Wall (2003) drop all dummy variables and even drop the distance variable. They argue that these variables bias the gravity model and they motivate their argument in a number of ways. First, they reason that economic distances are too hard to measure with accuracy because big countries have many economic centers, that are thousands of miles apart and that serve as trade centers for diffe

Prevention Postoperative Vision Loss Study Health And Social Care Essay

Postoperative ocular loss ( POVL ) after non-ocular surgery is a rare, but lay waste toing complication that has been associated legion types of surgeries and patient hazard factors. Stoelting and Miller ( 2007 ) estimate the incidence of POVL from 1 in 60,965 to 1 in 125,234 for patients undergoing noncardiac, nonocular surgeries, from 0.06 % to 0.113 % in cardiac surgery patients with cardiorespiratory beltway and 0.09 % of prone spinal column surgeries. The demand to understand the causes of POVL and the preventive steps that can be taken to decrease the likeliness of vision loss happening are deductions for anaesthesia suppliers and patients likewise. Consequences of POVL non merely affect the enfeebling impact on the patient ‘s quality of life, but besides the legion medical and legal branchings for the anaesthesia suppliers. Although POVL is considered a comparatively uncommon complication, the demand to understand the frequence of POVL and related hazards and causes are of import issues. In 1999, the American Society of Anesthesiologists ‘ ( ASA ) Committee on Professional Liability established the ASA Postoperative Visual Loss Registry to better understand the job ( Stoelting & A ; Miller ) . Reports of loss of vision have occurred after assorted non-ocular related surgical processs. Some illustrations of these are cardiorespiratory beltway, spinal surgery, hip arthroplasty, abdominal processs, craniotomies and processs of the caput and cervix ( Morgan, Mikhail & A ; Murray, 2006 ) . The three recognized causes of postoperative ocular loss are ischaemic ocular neuropathy ( ION ) either anterior ( AION ) or posterior ( PION ) , cardinal retinal arteria occlusion ( CRAO ) , cardinal retinal vena occlusion ( CRVO ) and cortical sightlessness. Ischemic ocular neuropathy is the most often cited cause of postoperative ocular loss following general anaesthesia with cardinal retinal arteria occlusion from direct retinal force per unit area as a lesser cause. ( Stoelting & A ; Miller, 2007 ) . Factors that have been identified as possible perioperative factors for ION include drawn-out hypotension, extended continuance of surgery, prone placement, inordinate blood loss, unneeded crystalloid usage, anaemia, and increased intraocular force per unit area from prone placement. Patient related hazard factors associated with ION include diabetes mellitus, high blood pressure, morbid fleshiness, coronary artery disease, and smoke. ( Stoelting & A ; Miller, 2007 ) . Literature Review Several retrospective surveies have examined the natural history of POVL after nonocular surgery in an effort to place patients at hazard for POVL and cut down surgical hazard factors. The first, from 1996, Roth, Thisted, Erickson, Black, and Schreider reviewed oculus hurts in 60,985 patients undergoing anaesthesia between 1988 and 1992. The overall incidence of oculus hurt in this survey was 0.56 % . Duration of anaesthesia was found to be an independent hazard factor for oculus hurt. The hazard was further increased with general anaesthesia and endotracheal cannulation and in patients undergoing surgery of the caput or cervix. The bulk of the patients with oculus hurts had corneal scratchs or pinkeye. Merely one patient was found to hold POVL as a consequence of ION. This patient underwent lumbar spinal merger and the writers noted that calculated hypotension and hemodilution were used. In 1997, Stevens, Glazer, Kelley, Lietman and Bradford focused on ophthalmic complications specifically after spinal surgery. Of 3450 spinal column surgeries that the writers reviewed, seven ( 0.2 % ) instances of ocular loss were identified. Four ( 57 % ) of the seven patients suffered ION of which three had PION. Two of the seven patients had occipital infarcts, both of which were embolic. The 7th patient had a CRVO without associated periorbital hydrops or force per unit area mortification. The surgical times ranged from 3-8 hours in these patients. The estimated blood loss ranged from minimum to 8.5 litres. A 3rd survey, besides conducted in 1997, by Myers, Hamilton, Bogoosia, Smith and Wagner, collected patients by beging studies from the Scoliosis Research Study of POVL after spinal surgery every bit good as 10 good documented instances from the spinal literature. They found that longer surgical times and important blood loss were positively correlated with POVL. However, the haematocrit and blood force per unit area degrees were no different than in age matched controls without POVL. Twenty-three of the 37 ( 62.2 % ) patients had ION, 9 ( 24.3 % ) had CRAO, 3 ( 8.1 % ) had occipital infarcts and the staying three did non hold clear diagnosings. The writers concluded that reduced blood force per unit area is by and large good tolerated by patients, but that consideration should be given to set uping a minimal systolic blood force per unit area for each patient. In add-on, the writers recommended presenting long processs and protecting oculus place. More late the American Society of Anesthesiologists POVL register analyzed 93 instances of POVL happening after spinal surgery. The instances were collected via voluntary entry from1999 through June 2005. Eighty three ( 89.2 % ) of the patients had ION and the staying 10 ( 10.8 % ) patients had CRAO. All of the patients were placed prone. Surgical clip exceeded 6 hours in 94 % of the instances. In 34 % of instances the average arterial force per unit area or systolic blood force per unit area ( SBP ) was reduced to 40 % or more below baseline. The average haematocrit was 26 % with 82 % of patients losing one or more litres of blood. All of the patients with CRAO used head restraints alternatively of Mayfield pins and were somewhat younger than the ION patients ( 46 vs. 50 old ages ) . In add-on, 66 % of the ION patients had bilateral ocular loss and none of the CRAO patients did. Ipsilateral periocular injury was more often seen in the CRAO patients ( 70 % vs. 1 % ) than in ION patie nts. They once more identified the hazard of prone placement, blood loss and long surgical times. However, they were unable to definitively delegate a function to hypotension in POVL ( Lee, Roth, Posner, Cheney & A ; Caplan, 2006 ) . Another survey examined the published instance studies of ION after spinal surgery in the prone place. The writers found that PION was more often reported than AION ( n = 17 vs. n = 5 ) .3 In the bulk of the instances, some degree of hypotension and anaemia was reported. However, the writers note that the degree of blood force per unit area and anaemia sustained by these patients would be considered acceptable in most anesthesia patterns. Furthermore, the writers observed that average surgical clip was over 7.5 hours. Strategies the writers suggested to avoid postoperative ION included careful usage of deliberate hypotension tailored to the patient ‘s hazard degree and theatrical production of long, complex processs ( Ho, Newman, Song, Ksiazek & A ; Roth, 2005 ) . Case Study A 62 twelvemonth old male was scheduled for a three degree lumbosacral laminectomy and diskectomy ( L2 through L4 ) . He had a history of high blood pressure, fleshiness, stomachic reflux disease, myocardial infarction 5 old ages antecedently with two stents placed in the LAD, and a 50-pack-year smoke history. The patient had a surgical history of bilateral carpal tunnel release and ventral hernia fix with mesh. No old anaesthetic complications were noted. Current medicines included omeprazole, and Lopressor. He had no known drug allergic reactions. The patient ‘s physical scrutiny revealed an afebrile patient, pulse 67, respirations 16, blood force per unit area 162/92, SpO2 of 95 % on room air. The patient ‘s general visual aspect was a reasonably corpulent adult male in no evident hurt. Airway appraisal revealed a category 2 Malampatti, natural teething and normal cervix scope of gesture. Laboratory findings were hemoglobin 14.4 and hematocrit 40 % . All other haematol ogy, curdling profiles were normal. EKG was normal sinus beat and Chest X ray was normal. The patient underwent a criterions initiation and cannulation. He was turned prone, appendages were good padded and airing and critical marks were satisfactory. The process lasted for 3 hours and during a period of moderate blood loss, the patient had a period of hypotension enduring for about seven proceedingss. His blood force per unit area averaged 95/55 for about 30 proceedingss and for five proceedingss blood force per unit area averaged 80/45. Fluid resuscitation totaled 3 litres of crystalloid. Estimated blood loss was 550ml with a postoperative haematocrit of 29 % . On waking up, the patient did non exhibit any marks of orbital hydrops or POVL. The patient stated that vision was present in both eyes and his neurologic scrutiny was normal. Schemes for bar of POVL ION is the most common cause of POVL and may be designated as anterior ( AION ) or posterior ( PION ) depending on the location of the ocular nervus lesion. Ocular loss of AION is due to infarction at watershed zones within the ciliary arterias of the choroid bed of the ocular disc which flows into the choriocapillaris. The choriocapillaris is an end-arterial circulation with small transverse circulation and may be prone to ischemia. The posterior ocular nervus is served by subdivisions of the ocular arteria and the cardinal retinal arteria ; blood flow to the posterior ocular nervus is significantly less than the anterior ocular nervus ( Lee, et Al, 2006 ) . Many interventions have been attempted to change by reversal POVL, including anticoagulation, antiplatelet therapy, retrobulbar steroid injections, norepinepherine extracts ( to better perfusion force per unit area ) , diphenylhydantoin, osmotic water pills, blood replacing, carbonaceous anhydrase inhibitors, steroids and ocular nervus decompression. The most common forecast of POVL is small return of ocular map ( Lee, et al 2006 ) . ION should be suspected if a patient complains of painless ocular loss during the first postoperative hebdomad and may be noticed foremost on rousing from slumber, when intraocular force per unit area is highest. Pressing opthamologic audience should be sought to analyze the patient comprehensively, set up the diagnosing, and urge farther rating and therapy. Even though forecast tends to be hapless, prompt intervention may be the lone opportunity at retrieving vision ( Ho, Newman, Song, Ksiazek, & A ; Roth, 2005 ) . Obvious turning away of force per unit area on the oculus is a primary scheme to avoid ION. However, POVL has been noted in patients besides in the supine place. Current anaesthesia supplier instruction refering turning away of compaction of a patient ‘s eyes has made it a rare intraoperative event. Possibly nore good is keeping acceptable blood force per unit area and haematocrit, particularly in patients with multiple hazard factors. More than one-half of the patients entered in the ASA POVL database were positioned prone and were noted as holding important facial puffiness. When associated with systemic hypotension, optic perfusion force per unit area is diminished. Decreased haematocrit in the presence of other hazard factors seems to patients at hazard for ocular loss. Induced hypotension and hemodilution during prone spinal column instances should be avoided when patients have risk factors for POVL ( Lee, et Al, 2006 ) .

Esl Advanced Essay Topics - the Story

Esl Advanced Essay Topics - the Story Here's What I Know About Esl Advanced Essay Topics Though the essay questions change, the topic of the essays often stays the same. Perhaps, writing argumentative essays isn't that an effortless endeavor. You should research the selected topic and discover facts to contradict your primary thesis. You can begin with the kind of topic you select for your compare and contrast essay. Interest is among the conditions last expert assignment. You see that it's an unusual topic that might be quite tough to imagine or explain, but some students might just turn that topic into a masterpiece. Students only have to discover their niche from the multitude of topics they can explore. Additionally, they are much likelier to have the requisite knowledge about and interest in the topic. In other kinds of essays, the content can fluctuate. Essay's essential element is the topic, that's the subject you're going to describe. You will obviously not have the capability to predict the precise topic that will come up. Each topic is broken up into subtopics that you should prepare. Heres one of several public speaking tips you'll get from me Don't be scared to request the huge money. There are cases which people have variations in regards to interpreting or giving meanings to words. Different significance of a specific word depends upon the group of individuals who uses it. Looking words up in the dictionary requires a lot of time. Definitions of Esl Advanced Essay Topics Writing is typically a pretty solitary activity. Life was better 20 years back. It is better than it was 50 years ago. Most people in most countries do a great quantity of cooking. To be great at public speaking, you need to have the ability to wow your audience from the beginning. In an is sue of speaking, picking out persuasive essay topics is similar to telling yourself what you wish to convey to the rest of the planet. Just because you're given total freedom what you're going to write, does not indicate that you ought to write casually without giving any proof. Year round school isn't a good idea. A mix of teacher and student selection may be used to reduce at least one of the disadvantages of each method. A student is provided a paper with four words (you are able to alter the number to fit your class). For each topic, he should provide an explanation of his or her choice. The aim is to develop something that nobody else in the class has done. Naturally, it may be any variety of factors. You may even fail the class. You have to present your topic, naturally, and also your thesis statement that has the function of indicating to your readers what is the probable path of the whole work. Essay writing is definitely thought to be part of academic life and essay writing demands certain abilities or the portion of the writer. Brainstorming is a trustworthy way of generating ideas for a huge variety of projects. As stated above, one of the methods where the examiner judges your vocabulary is the way many topic particular words you use. If necessary, you could always turn to professionals to supply you with a nudge or assist you with your topics or sources. Who chooses a writing topic depends on the learning aims of the assignment. It's not essential to use all the words. For advanced students, you can choose a more challenging word for them to attempt to guess. You might have the students tackle the writing to the class. By and large, however, students are usually required to execute their writing tasks alone. Or you supply the student one or more lists from which to select.

What Led to the Formation of the NAACP