This study differentiates total factor productivity (TFP) between the exporting and non-exporting firms in manufacturing sector of India. We use data from the Centre for Monitoring Indian Economy (CMIE) from 2003 to 2015. For a better understanding of the productivity distribution, we create two subgroups of sample based on firm age and size. Moving away from parametric tests this study adopts non-parametric statistics in testing the hypothesis. Productivity levels are found to be higher for the exporting firms as compared to the non-exporting firm. Further, within the exporting firms, those with larger firm size have higher productivity compared to the smaller firms.
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The Kolmogorov–Smirnov test is a non-parametric test of the equality of continuous, one-dimensional probability distribution that can be used to compare a sample with a reference probability distribution. This can be either of one-sample or two-sample test. For more details, see Darling (1957).
Productivity distributions are also higher in all quartiles for firms in the export market as compared to the non-exporting firms. The median productivity of the former is 26% higher than the productivity of the latter. Similarly, productivity differences are greater at the lower part of the distribution, 7% in favour of exporting firms at the lower quartile, and smaller in the upper part, 5% in favour of exporting firms at the upper quartile.
On the entry side, the implication of selection is that only firms with higher productivity should enter the export market. On the exit side, if selection is at work, low productivity exporters should leave the export market.