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Less bilateral trade the more the distance between them

- 1. Evaluating Trade between India and North America using Gravity Models
- 2. The theoretical foundations of gravity models: Newton’s Law The model has been adapted from Newton’s laws of gravitation Statistically measure bilateral trade flows between different geographical entities or regions In the simplest gravity model, bilateral trade flows between two countries are assumed to be proportional to the product of their gross domestic products and inversely proportional to a measure of the distance between them
- 3. The Two Frameworks The Gravity Model F = K×GDPi×GDPj d2 F = The Flow of Trade GDPi = GDP of country i GDPj = GDP of country j d = distance between economic capitals of countries i and j (sometimes measured by ports). K = is a constant. The Newton Model F = G×m1×m2 r2 F = The force of attraction m1 = mass of object 1 m2 = mass of object 2 r = the distance G = is a constant.
- 4. Estimated gravity equation Newton’s Law-based Normal Trade Normal trade The basic equation depend upon two major variables: GDP and distance Positive correlation of trade to GDP and negative correlation with distance ln (Tradeij) = C + a ln(GDPi) + b ln(GDPj) + +c ln(distanceij) + uij
- 5. “Augmenting” the gravity equations Income per capita (higher income countries trade more) Adjacency Common language, colonial links Institutions, infrastructures, labour flows,... Surprisingly, bilateral tariff barriers often missing!!!
- 6. “Augmenting” gravity model Traditional approach to evaluate the impact of RTAs: Trade creation and trade diversion ln (Tradeij) = a ln(GDPi) + b ln(GDPj) + +c ln(distanceij, ,adjacency, language ..) + d (Dummy i) + + e (Dummy j) + g (intra-RTAij)+ h (extra-RTAij) + uij IMPORTANT the gravity model does not estimate welfare effects
- 7. North America
- 8. GDP & Distance GDP is used to determine the size of the country The more the GDP, the more the trade India’s GDP is tenth largest in the world India’s trade with larger economies is more Distance between India and North America is high High distances convert to high freight and transportation cost
- 9. Common Language Dummy variable which was augmented on the Gravity Model We took binary variable i.e. 0 and 1 values for having a common language with India Perception is that common language increases trade between nations
- 10. Population & Area Higher population translates to more trade
- 11. Methodology Data has been taken from 2003 to 2010 Demographic and GDP data : WorldBank Distances data: WorldAtlas Trade data: WITS Multiple regression using SPSS Data available only for 19 out of 23 countries
- 12. The Output Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate 1 0.888385 0.789228 0.782317 1.149847 a. Predictors: (Constant), Population, GDP_India, Distance, Area, Language, GDP ANOVAb Model Sum of Squares df Mean Square F Sig. 1 Regression 905.9843 6 150.9974 114.2061 0 Residual 241.953 183 1.322148 Total 1147.937 189 a. Predictors: (Constant), Population, GDP_India, Distance, Area, Language, GDP b. Dependent Variable: Export
- 13. The Output Coefficientsa Model Unstandardized Coefficients Standardized Coefficients t Sig. Std. Error Beta 1 (Constant) 16.76 17.78 0.94 0.35 GDP 0.12 0.05 0.14 2.30 0.02 GDP_India 1.33 0.20 0.22 6.56 0.00 Area 0.55 0.05 0.67 10.41 0.00 Language 0.16 0.28 0.03 0.58 0.56 Distance -6.04 1.71 -0.18 -3.53 0.00 Population 0.03 0.04 0.04 0.80 0.42 a. Dependent Variable: Export Language and Population are not significant
- 14. The Output Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate Change Statistics R Square Change F Change 1 0.887876 0.7883 0.783747 1.146065 0.788324 172.2439 a. Predictors: (Constant), Distance, GDP_India, GDP, Area ANOVAb Model Sum of Squares df Mean Square F Sig. 1 Regression 904.946 4.000 226.237 172.244 0.000 Residual 242.991 185.000 1.313 Total 1147.937 189.000 a. Predictors: (Constant), Distance, GDP_India, GDP, Area b. Dependent Variable: Export
- 15. The Output Coefficientsa Model Unstandardized Coefficients Standardized Coefficients t Sig. Collinearity Statistics Std. Error Beta Tolerance VIF 1 (Constant) 28.108 12.651 2.222 0.028 GDP 0.144 0.043 0.172 3.312 0.001 0.425 2.354 GDP_India 1.318 0.202 0.223 6.539 0.000 0.988 1.013 Area 0.538 0.043 0.653 12.508 0.000 0.420 2.379 Distance -6.457 1.140 -0.197 -5.663 0.000 0.950 1.053 a. Dependent Variable: Export
- 16. The Equation
- 17. Thank You!

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