"coefficientrepresentingtheresponsivenessofImports(Dependent variable ) with thechange in Indian Domestic Income (Independent variable) and a is the slope coefficient3representing the responsiveness of Imports (Dependent variable ) with the change in RealExchange Rate (Independent variable). µ and µ = the disturbance term in the export and 1 2 import equation respectively. 4.2 Major Findings The empirical estimation begins with first testing the time series for the Stationarity using UnitRoot test and Cointergration using Augmented-Dickey Fuller Test. The results show that theseries are stationary (table 3) and no Cointegration is present (table 4). Thereafter, all the timeseries are converted into Log and OLS is used to determine the slope coefficients at 95%confidence level and conclusion are drawn about the export and import demand elasticity andMarshall-Lerner Condition (table 4 and table 5).Table 3: Stationary Testing using SAS Variable Test Statistic 5 % Critical Value ResultExports from India3.40 3.41 StationaryImports to India 3.38 3.41 StationarySource: Author’s own calculation, World Bank database 2016Table 4:Cointegration Testing using SASVariables Test Statistic 5 % Critical Value ResultExports Model -3.45 -3.34 No CointegrationImportsModel-3.77 -3.34 No CointegrationSource: Author’s own calculation, World Bank database 201611 Table 5: Exports equation of India (1962-2015)Regression StatisticsMultiple R 0.945738901R Square 0.894422068Adjusted R Square 0.890281757Standard Error 0.092613314Observations 54Coefficients Standard Error t StatIntercept -2.02870989 0.790324745 -2.566932017Real Exchange rate (RER) 0.462750871 0.097629988 4.739843563World Income (WI) 0.168982549 0.064425442 2.622916399Source: Author’s own calculation, World Bank database 2016 for exports, imports, exchangerate and GNI.^ ^ Thus, the export equation becomes X = -2.02 + 0.16 WI + 0.46 RER(0.79)(0.06) (0.09) Export Elasticity =?X/?RER=1/ 0.46=2.17 &World Income Elasticity=?X/?WI=1/0.16=6.25. There is high level of regression (0.94) between the dependent variable (Exports) and theindependent variables (RER and WI) and 89% of the variations in Exports can be explained bythem (table 5). RER and WI are positively related with the Exports showing that as theexchange rate appreciates and world income increases by 1 unit each, the exports (% of GDP)12 also increases by 0.46 units and 0.16 units respectively (table 5). Price elasticity of demand forexports is perfectly elastic indicating that there are no demand constraints.Table 6: Import equation of India (1962-2015)Regression StatisticsMultiple R 0.943548989R Square 0.890284695Adjusted R Square 0.885982134Standard Error 0.090809815Observations 54Coefficients Standard Error t StatIntercept -4.34175463 0.680945437 -6.376068329Domestic Income (DI) 0.457531745 0.068577311 6.671765593Real Exchange rate (RER) 0.082448805 0.090306589 1.912987701Source: Author’s own calculation, World Bank database 2016 for exports, imports, exchangerate and GNI. Thus, the import equation become Y= -4.3 + 0.082 RER + 0.45 DI (0.68) (0.09) (0.06) Import Elasticity =?M/?RER=1/0.082=12.1 & Domestic Income Elasticity=?Y/?DI=1/0.45=2.22. There is high level of regression (0.94) between the dependent variable (Imports) and theindependent variables (RER and DI) and 88% of the variations in Imports can be explained bythem (table 6). RER and DI are positively related with the Imports showing that as theexchange rate appreciates and domestic income increases by 1 unit each, the imports (% of13 GDP) also increases by 0.08 units and 0.45 units respectively (table 6). Price elasticity ofdemand for imports is perfectly elastic. Summing up, the Marshall-Lerner Condition will become Export Elasticity + Import Elasticity= 2.17 +12.1 = 14.27 (table 5 and 6). Thus, it is verified that ML is satisfied for India over 54years (1962-2015) as it is greater than 1 (taking the assumption of perfect elasticity of supply ofexports). This indicates that depreciation of the Indian currency should be able to improve thetrade balance. To analyze this aspect practically, the Indian trade balance is discussed in thenext objective.5 Research Methodology and Empirical Findings of J-curve in India (1979-2014) J-curve depicts the graphical representation of the trade balance over the time period. The timeperiod is of 36 years (1979-2014) as the data is unavailable prior to 1979. The net trade ofgoods and services data in USD million is taken from the World Bank databank and tradebalance so obtained is plotted against the time to understand the changes in trade balance withrespect to the exchange rate. Three figures are used to cogently explain the trade balance trend.14 Fig 1: India's J-curve (1979-1990) India's J-curve (1979-1990) 0 8.12Rs/$-1000 -2000 -3000 10.09 11.36 -4000 -5000 12.61 -6000 9.4 -7000 8.65 7.86 12.36 -8000 -9000 197 198 198 198 198 198 198 198 198 198 198 199 9 0 1 2 3 4 5 6 7 8 9 0 India Trade Balance -225 -565 -616 -535 -451 -443 -613 -615 -704 -811 -784 -661 Source: Author’s own calculation, World Bank database 2016 for exchange rate and net tradeof goods and services.Fig 2:India’s J-Curve (1991-2002)India's J-cuve 1991-2002 0 -2000 -4000 -6000 -8000 -10000 -12000 -14000 -16000 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 India Trade Balance -401 -471 -348 -631 -102 -139 -133 -136 -114 -131 -918 -512 Source: Author’s own calculation, World Bank database 2016 for exchange rate and net trade ofgoods and services.Fig 3: India’s J-curve (2003-2014)15Trade Balance (Exports – Imports) InUSD million Trade Balance (Exports – Imports)In USD million"