Gravity Model

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This presentation discusses a gravity model for potential trade between India and North American countries.

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  • More bilateral trade the larger the countries
    Less bilateral trade the more the distance between them
  • Gravity Model

    1. 1. Evaluating Trade between India and North America using Gravity Models
    2. 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. 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. 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. 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. 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. 7. North America
    8. 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. 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. 10. Population & Area  Higher population translates to more trade
    11. 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. 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. 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. 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. 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. 16. The Equation
    17. 17. Thank You!

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