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Impact of Vertical Integration on Market Power in Indian Manufacturing Sector During the Post-Reform Period

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Abstract

In the context of declining degrees of vertical integration in major industries of Indian manufacturing sector during the post-reform period, the present paper is an attempt to examine how such “vertical disintegration” has affected firms’ market power and its implications for competition policy. Using panel dataset of 49 majors industries of Indian manufacturing sector for the period 2003–04 to 2010–11 and applying the system generalized method of moments approach to estimate of dynamic panel data models, the paper finds that vertical integration does not cause any significant impact on average market power of firms in an industry. Instead, it is influenced by market size, and selling and technology-related efforts. While selling intensity has a positive impact on market power, the impact of market size and technology intensity is found to be negative. Notably, like vertical integration, market concentration, import to export ratio, and capital intensity also do not have any significant impact on market power. The findings of this paper, therefore, have important implications for competition law and policy in general and policies and regulation relating to technology development and international trade in particular.

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Notes

  1. However, if the upstream and downstream markets become more competitive, such a situation may not arise.

  2. This is so particularly when the downstream firms are unaware of the price mark-up by the upstream firm and is referred to as vertical externality (Tirole 1988).

  3. In addition, firms consider vertical integration whenever there are uncertainties in the supply of inputs (Carlton 1979). Vertical integration can also benefit an infant industry which produces a new downstream input as the demand for such inputs in open market may be limited for survival of these infant industries (Stigler 1951).

  4. Analyzing impact of multimarket vertical merger on prices of retail gasoline, Hastings (2004) found evidences of higher retail prices following decline in market share of retailers that are not integrated.

  5. However, Rosengren and James (1994) and Asker (2004) did not find any support for the theory of foreclosure.

  6. The anti-trust laws of the USA were critical on vertical mergers on the ground that such combinations can reduce competition by limiting access to resources in input markets, reducing number of competitors, and leveraging monopoly power across markets.

  7. A number of studies in recent years have used dynamic framework to analyze industry level market power (e.g., Mishra 2008) or firm-level profit margins (Kambhampati and Parikh 2005) in Indian context

  8. These measures of vertical integration were first propounded by Adelman (1955). Although they have various limitations (Nugent and Hamblin 1996), these measures, especially the ratio of value added to sales have been widely used in empirical research on vertical integration. A number of studies (e.g., Adelman 1955; Gort 1962; Nelson 1963; Laffer 1969; Tucker and Wilder 1977) have used ratio of value added to sales as a measure of vertical integration with some variations.

  9. The details are available at Mishra et al. (2011) and Mishra and Rao (2014).

  10. Robust conclusions on relationship between vertical integration and market power require defining market at relevant level, whereas it is not clear what should be the appropriate level of relevant market. This may have serious implications on the findings given that competition is localized in many markets. Given data limitations and non-availability of location-specific information, the paper addresses this problem in two ways—(i) by using more disaggregate classification of industries (at 3-digit level), and (ii) using two alternative additive measures of market concentration. Consistent findings across alternative indices at disaggregate level are expected to give robust conclusions in this regard. Further, the HHI is considered as a standard measure of market concentration and used widely in empirical research.

  11. Three-year moving averages of the variables reduce their temporal variations. Hence, one may expect that such inter-locking would make the variables independent of the random disturbance term.

  12. Using such average measure of the dependent variable is very important in a multidimensional framework, as in such a framework, the adjustment process is likely to be slow and a single lag dependent variable based on annual values as an explanatory variable may not be enough to capture the entire dynamics of the model.

  13. For the details on GRS, see Ginevicius and Cibra (2009).

  14. High advertising intensity of existing firms may require the potential entrants to incur disproportionately high advertising expenses to win over the incumbents, and this may discourage entry.

  15. There are evidences (e.g., Scherer and Ross 1990) of positive relationship between profit margin and advertising intensity.

  16. It is observed that expenditure on distribution and marketing activities results in higher profitability (Majumdar 1997).

  17. There are evidences (e.g., Mishra and Chandra 2010; Mishra and Vikas 2010) of no significant impact of innovation on firms’ profitability in Indian pharmaceutical industry.

  18. Since industry is the unit of observation in the present context, endogeneity problem is unlikely to be acute (Salinger et al. 1990).

  19. The use of such dynamic models is favored, especially, for panels that have a large number of cross-sectional units with a small number of time periods, as we have in the present case. This is so because their estimation methods do not require larger time periods to obtain consistent parameter estimates.

  20. Use of lagged value is a widely used practice to control the endogeneity problem (e.g., Gupta 2005; Aschhoff and Schmidt 2008; Clemens et al. 2012). Since the present paper estimates dynamic model, lagged explanatory variables capture both short and long-term effects, and hence are expected to be valid instruments. More importantly, since the three-year moving averages of the variables are used, such measures also add deeper lags in the process. Further, the method of system GMM adds both lagged vales of the variables and their differences as the instruments. This improves efficiency of the estimates as well.

  21. It is also found that there is no severe multicollinearity as the variance inflation factors (VIFs) are very low.

  22. These contradictions may also largely be due to model specification and period of analysis. For example, while both Kambhampati and Parikh (2005) and Mishra (2008) have added majority of the variables as the independent variables like the present paper, impact of vertical integration is not controlled in either of these two studies. Hence, inclusion of vertical integration in the present paper makes marked departure from nay of the existing studies and this is reflected in the findings. Further, while Kambhampati and Parikh (2005) and Mishra (2008) focused in the 1990s and applied Arellano and Bond (1991) dynamic panel data estimation techniques, the present paper covers the decade of 2000s and applies the system GMM of Arellano and Bover (1995) and Blundell and Bond (1998). Such differences in period of coverage and estimation techniques might have bearings on the findings of the present paper vis-à-vis the earlier studies.

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  1. Economics, Indian Institute of Management Ahmedabad, Ahmedabad, 380 015, India

    Rakesh Basant

  2. Department of Humanities and Social Sciences, Indian Institute of Technology Kharagpur, Kharagpur, 721 302, India

    Pulak Mishra

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Basant, R., Mishra, P. Impact of Vertical Integration on Market Power in Indian Manufacturing Sector During the Post-Reform Period. J Ind Compet Trade 19, 561–581 (2019). https://doi.org/10.1007/s10842-019-00294-4

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