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Articles

Innovation, exports, productivity and investment climate; a study based on Indian manufacturing firm-level data

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Pages 4455-4476 | Published online: 01 Apr 2019
 

ABSTRACT

In this paper, we use univariate instrumental estimations to study the interactions between firm-level innovation, exports and productivity in the Indian manufacturing sector. To differentiate incentives to innovate from the ability to innovate, we distinguish the inputs of innovation (R&D and training) from the outputs. Our findings highlight a virtuous circle between the three components of innovation, as well as between firms’ R&D, innovation and exports. The productivity of Indian manufacturing firms is benefiting from this dynamics, as exports and innovation improve firms’ TFP. With respect to the investment climate, our results suggest that differences in the environment of Indian companies contribute to their performance gaps. These results are all the more important in the context of the Make in India campaign and the weaknesses of India’s business environment.

JEL CLASSIFICATIONS:

Acknowledgments

Authors wish to thank Baptiste Souillard for his excellent research assistance.

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

1 This share was of 34% in Thailand, 32% in China, 31% in Korea and 24% in Indonesia in 2014.

4 Instruments are as follows: firm’s age and size (proxied by the number of workers), production in t-3, manager experience, share of capital belonging to foreign companies, type of firm, belonging to a big enterprise, power and water shortages, States and sectors fixed-effects.

5 It is then possible that the instrument is not one of the explanatory variables.

6 Due to space constraint, we only present the results when using (i)-the number of different types of innovations (variable between 0–4) and its decomposition, (ii)-the labour productivity (LP) and total factor productivity (TFP), (iii)-the share of production exported (directly and indirectly).

Additional information

Funding

This work was supported by the Agence Nationale de la Recherche [ANR-10-LABX-14-01].

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