The determinants of outward foreign direct investment: a firm‐level analysis of Indian manufacturing

Abstract

This paper analyses the determinants of the overseas direct investment activity of Indian manufacturing enterprises. In general, several firm‐specific characteristics such as age, size, R&D intensity, skill intensity and export orientation are observed to be important explanatory factors in the outward foreign direct investment (O‐FDI) activity of Indian firms. The impact of age and size on O‐FDI has been observed to be non‐linear. The product differentiation activities and the productivity of firms are other useful factors in overseas production expansion in certain industries. The study reveals that the performance of these firm‐specific variables is subject to sectoral dynamics. Internationalization of production activities of Indian firms has been observed to be partly fuelled by policy liberalization during the 1990s.

Notes

* Jaya Prakash Pradhan, Assistant Professor, Gujarat Institute of Development Research, Gota, Gandhi Nagar Highway, Ahmedabad‐380060, Gujarat, India.

I am grateful to Dr Nagesh Kumar, Director General, RIS, for introducing me to this area of research. I am also thankful to Vinoj Abraham for his constant support. I also gratefully acknowledge the valuable comments of an anonymous referee of the journal who was instrumental in the substantial improvement of the paper. However, the author alone is responsible for views expressed in the paper.

Between 1980 and 1993 the share of developed countries in the outward FDI stock increased from 34 to 71% in the case of China, 32 to 48% for South Korea, 9 to 21% for Singapore and 8 to 18% for Hong Kong (Source: Kumar, 1998).

Over 1985–98 the high‐technology exports from developing countries increased at a rate of 21.4%, nearly twice the growth rate of developed countries. The share of developing countries in the world trade of high‐technology products increased from 11% in 1985 to 27% in 1998 (see Lall, 2000, pp. 10–11).

Chinese brands are fast joining the established names from Japan, Korea and Europe in consumer electronics. Several Chinese domestic mobile phone brands such as Ningbo Bird and TCL have become bigger than US, European and Japanese brands (Economic Times, 27 August 2003, Europe sees Chinese brands going global).

Results obtained from this regression analysis are not reported in the paper due to space constraints, but are available from the author on request.

The author is grateful to the editor for making some clarifications regarding the variable managerial skill.

We had depended on the online data collected from the ICICI on the recent name changes of Indian companies in ensuring this objective. These data along with other valuable financial data on more than 3000 Indian firms can be accessed at www.icicidirect.com.

Quadchk is the quadrature check for determining whether the quadrature is stable for a particular model or not. To estimate random‐effects Tobit models, STATA uses Gauss–Hermite quadrature to approximate the high‐dimension integrals that are part of the likelihood for these models. Even though quadrature is one of the most accepted approaches in estimating these models, there are cases where it can be poor, such as in the case of large panel size, high within‐panel correlation or variables that are constant or nearly constant within panel.

Detailed results are not reported and are available from the author on request.

To obtain these coefficients one needs to compute the standardized variables and then re‐estimate the Tobit model. Alternatively, the standardized coefficient β _1s for a particular variable X ₁ can be obtained as β _1s=β _1u * (σ ₁/σ_y ), where β _1u is the un‐standardized coefficient associated with X ₁, σ ₁ and σ_y are the standard deviation of X ₁ and Y (the dependent variable), respectively.

Detailed results from industry‐level regression analysis can be obtained from the author on request.

Additional information

Notes on contributors

Jaya Prakash Pradhan *

* Jaya Prakash Pradhan, Assistant Professor, Gujarat Institute of Development Research, Gota, Gandhi Nagar Highway, Ahmedabad‐380060, Gujarat, India. I am grateful to Dr Nagesh Kumar, Director General, RIS, for introducing me to this area of research. I am also thankful to Vinoj Abraham for his constant support. I also gratefully acknowledge the valuable comments of an anonymous referee of the journal who was instrumental in the substantial improvement of the paper. However, the author alone is responsible for views expressed in the paper.