INDIAN AUTOMOTIVE COMPONENT INDUSTRY: PROFITABILITY, R&D DETERMINANTS AND EXPORT PERFORMANCE

Abstract

The Indian automotive market has risen to become the world's fourth largest, with the component industry accounting for a sizable chunk of the pie. The Indian automotive component industry has risen at a rapid pace, with overall industrial revenues growing at a compound annual growth rate (CAGR) of 14.46 percent, from US $3.66 billion to US $46.28 billion over the last decade. The component business now exports more than a quarter of its output, reflecting its growing integration into the global supply chain. The economy-wide liberalisation in the country in the early nineties led to the entry of several overseas players into the Indian market, thereby altering the competitive landscape in this industry. Consequently, the existing players responded to this new reality by adopting catching-up strategies or emulating the strategies followed by the overseas players operating in the country. As a result, spending on in-house R&D increased dramatically from 2000 to 2018, with an annual CAGR of 15.63 percent. The broad literature survey indicates that there is a general dearth of studies on individual industries in emerging economies, which face a different set of challenges in comparison with industries in advanced countries. A large majority of the previously published research on profitability in India has focused on the effects of pro-market policies or foreign ownership. The effect of business group affiliation on profitability is largely underexplored in industry-specific settings. With respect to studies related to firm-level research efforts, the influence of business group affiliation on firm-level research efforts is typically overlooked, particularly in industry-specific settings, and studies on component industries in the post-reform period are quite scarce. With regards to export performance, previous research on the component industry focused on cross-sectional data, which ignored the effect of business group affiliation on firm-level exports. The CMIE PROWESS database provided the majority of the data required to examine R&D, profitability, and export performance in the Indian automotive component industry (Centre for Monitoring Indian Economy). The CMIE Prowess database was supplemented with industry-level data from the Central Statistics Office of India's Annual Survey of Industries, CMIE's Industry Outlook database, and the Automotive Component Manufacturers Association's annual reports (ACMA). The research used a sample of 78 domestic automotive component firms for the period 2000-2018. An unbalanced panel dataset of 78 enterprises was created to investigate the profitability determinants of the sample component firms. This research applies the procedure suggested by Blundell and Bond (1998) within the Generalized Method of Moments (GMM) framework, as the model specification panel data is dynamic in nature, which renders both fixed and random effect models biased and inconsistent. The research used two accounting measures as surrogates for profitability, namely Return on Assets (ROA) and Return on Capital Employed (ROCE). The determinants of R & D expenditure are identified with the help of the panel Tobit model with robust standard errors estimated using the MLE. The research uses R & D intensity to surrogate the R & D expenditure of the sampled firms. The determinants of export performance are examined with the help of the panel Tobit model, with robust standard errors estimated with MLE and McDonald and Moffitt decomposition (1980). The research uses export intensity as a proxy for the export performance of the sample firms. The GMM estimation reveals that the profit persistence in the industry is moderate to high. Furthermore, this study discovered that past R&D intensity, labour productivity growth, firm size, export intensity, overseas investments, and business group firms with overseas investments all have a positive and significant impact on current profitability. Some variables, such as A&M intensity, capital intensity, the firm’s leverage, the firm’s age, and business group affiliation, have been found to have exercised negative influence. The results of panel Tobit estimates find a non-linear inverted "U" shaped relationship between a firm’s size and R&D expenditure. The estimation also shows that a variety of independent variables, including a firm’s age, overseas investment, and affiliation with a business group, have a positive and contributory effect on the industry's research activities. Other variables found to have a negative impact include market power, export intensity, the firm’s leverage, and business group affiliates with an overseas presence. The results of the panel Tobit estimates for identifying the determinants of export performance reveal that technology imports, a firm’s age, overseas investment, and affiliation with a business group significantly affect an industry’s export performance. However, some variables, such as past R & D intensity, firm size, companies with overseas investment, and being part of a group, have been found to have had a detrimental effect. In sum, being outward-oriented in terms of overseas investment and being affiliated with a business group make a significant difference concerning innovative behaviour and export success.