Common use of Empirical Results Clause in Contracts

Empirical Results. The data used to measure the variables defined above were all obtained from the SIS database. The non-trade data are based on their annual Census of Industrial Production. This data was only available for the period 1974-1999; hence, we considered it in the estimations. This, however, is not an important shortcoming since the rate of IIT starts reaching meaningful levels after 1980. All data have been deflated using the 1987- based WPI. We used three proxies for the IIT variable. These are, the A-index for MIIT, the change in the GL index, ΔGL, and the GL index itself. The A index and ΔGL have been calculated as yearly changes. It has been shown by ▇▇▇▇▇▇▇▇ and Terra (1997) that A-indexes calculated for subintervals of a given interval cannot be aggregated to the A index for the parent interval unless the net balance of trade changes has the same sign in all subintervals. Since this situation may be the exception rather than the rule, choice of interval in calculating the A index is important. ▇▇▇▇▇▇▇▇ (1999) has investigated this question within the context of testing the SAH and has reached the conclusion that A indexes based on yearly changes give the best results.3 The estimates are given in Table 1. We find that (a) the coefficient of IIT is positive in all specifications and for all proxies except for the coefficient of GLxLTREX; this estimate, however, is not statistically significant, (b) the coefficient of the A-index, even though positive, is statistically significant in the specification with the interaction term and so is the coefficient of the interaction term, (c) the coefficients of ΔGL and ΔGLxLTREX are positive but statistically insignificant, while the coefficient of GL in the model without an interaction term is positive and significant, but becomes insignificant when GLxLTREX is introduced. These results are the reverse of what is expected when testing the SAH and appear to be closer to what ▇▇▇▇▇▇▇▇ and ▇▇▇▇▇▇ (2000) found for Malaysia. They call their findings for Malaysia “puzzling” but, in view of ▇▇▇▇▇▇▇▇ and ▇▇▇▇▇▇ (1999) and ▇▇▇▇▇▇▇▇▇ et al. (2002)’s Table 1 Panel Data Estimates For Yearly Changes (1) (2) (3) No interaction Interaction No interaction Interaction No interaction Interaction LDCONS 0.219 (5.236)c1 0.225 (5.379)c 0.224 (5.346)c 0.224 (5.345)c 0.212 (5.038)c 0.212 (5.043)c LDPROD -0.024 (-0.577) -0.020 (-0.490) -0.024 (-0.569) -0.024 (-0.566) -0.035 (-0.841) -0.036 (-0.845) LTREX 0.172 (2.366)b 0.099 (1.259) 0.178 (2.454)b 0.178 (2.437)b 0.149 (2.034)b 0.168 (1.757)a A 0.228 (1.403) 0.626 (2.686)c - - - - AxLTREX - 0.320 (2.374)b - - - - ΔGL - - 0.262 (1.043) 0.312 (0.737) - - ΔGLxLTRE X - - - 0.019 (0.145) - - GL - - - - 0.492 0.417 (2.322)b (1.283) GLxLTREX - - - - - -0.041 (-0.306) R2 0.3631 0.3682 0.3623 0.3623 0.3662 0.3663 F 131.499c 100.695c 131.041c 98.147c 133.287c 99.858c SSR2 1099.996 1091.093 1101.391 1101.357 1094.593 1094.445 DW 1.836 1.832 1.829 1.829 1.833 1.833 FE Test3 6.752c 6.779c 6.777c 6.677c 6.824c 6.817c Chow Test4 3.236b 2.137a 2.595b 2.756b 2.318a 2.030a NT 725 725 725 725 725 725

Empirical Results. The data used to measure the variables defined above were all obtained from the SIS database. The non-trade data are based on their annual Census of Industrial Production. This data was only available for the period 1974-1999; hence, we considered it in the estimations. This, however, is not an important shortcoming since the rate of IIT starts reaching meaningful levels after 1980. All data have been deflated using the 1987- based WPI. We used three proxies for the IIT variable. These are, the A-index for MIIT, the change in the GL index, ΔGL∆GL, and the GL index itself. The A index and ΔGL ∆GL have been calculated as yearly changes. It has been shown by ▇▇▇▇▇▇▇▇ and Terra (1997) that A-indexes calculated for subintervals of a given interval cannot be aggregated to the A index for the parent interval unless the net balance of trade changes has the same sign in all subintervals. Since this situation may be the exception rather than the rule, choice of interval in calculating the A index is important. ▇▇▇▇▇▇▇▇ Brulhart (1999) has investigated this question within the context of testing the SAH and has reached the conclusion that A indexes based on yearly changes give the best results.3 The estimates are given in Table 1. We find that (a) the coefficient of IIT is positive in all specifications and for all proxies except for the coefficient of GLxLTREX; this estimate, however, is not statistically significant, (b) the coefficient of the A-index, even though positive, is statistically significant in the specification with the interaction term and so is the coefficient of the interaction term, (c) the coefficients of ΔGL ∆GL and ΔGLxLTREX ∆GLxLTREX are positive but statistically insignificant, while the coefficient of GL in the model without an interaction term is positive and significant, but becomes insignificant when GLxLTREX is introduced. These results are the reverse of what is expected when testing the SAH and appear to be closer to what ▇▇▇▇▇▇▇▇ Brulhart and ▇▇▇▇▇▇ (2000) found for Malaysia. They call their findings for Malaysia “puzzling” but, in view of ▇▇▇▇▇▇▇▇ and ▇▇▇▇▇▇ Calfat (1999) and ▇▇▇▇▇▇▇▇▇ et al. (2002)’s Table 1 Panel Data Estimates For Yearly Changes Changes (1) (2) (3) No interaction Interaction No interaction Interaction No interaction Interaction LDCONS 0.219 (5.236)c1 0.225 (5.379)c 0.224 (5.346)c 0.224 (5.345)c 0.212 (5.038)c 0.212 (5.043)c LDPROD -0.024 (-0.577) -0.020 (-0.490) -0.024 (-0.569) -0.024 (-0.566) -0.035 (-0.841) -0.036 (-0.845) LTREX 0.172 (2.366)b 0.099 (1.259) 0.178 (2.454)b 0.178 (2.437)b 0.149 (2.034)b 0.168 (1.757)a A 0.228 (1.403) 0.626 (2.686)c - - - - AxLTREX - 0.320 (2.374)b - - - - ΔGL ∆GL - - 0.262 (1.043) 0.312 (0.737) - - ΔGLxLTRE ∆GLxLTRE X - - - 0.019 (0.145) - - GL - - - - 0.492 0.417 (2.322)b (1.283) GLxLTREX - - - - - -0.041 (-0.306) R2 0.3631 0.3682 0.3623 0.3623 0.3662 0.3663 F 131.499c 100.695c 131.041c 98.147c 133.287c 99.858c SSR2 1099.996 1091.093 1101.391 1101.357 1094.593 1094.445 DW 1.836 1.832 1.829 1.829 1.833 1.833 FE Test3 6.752c 6.779c 6.777c 6.677c 6.824c 6.817c Chow Test4 3.236b 2.137a 2.595b 2.756b 2.318a 2.030a NT 725 725 725 725 725 725