Introduction
Recent years have witnessed a growing optimism about the potential for Indian economic growth. In part, this is fueled by the example of strong sustained growth in China, raising the obvious question of why India cannot do as well. However, the optimism also reflects the fact that India’s growth has accelerated over the past two decades. And while its growth rate remains well below that of China, this favorable performance contrasts with the slowing of growth in other regions. It has also enabled the emergence of a significant middle class in India. Interestingly, India’s economic performance has differed from that of China and other parts of Asia in at least two dimensions. First, India’s success has not been based on strong growth in the manufacturing sector and in exports. Instead, it has reflected very rapid expansion of service-producing industries. Second, it has been associated with relatively modest levels of investment. Even incorporating recent data revisions, India’s physical capital accumulation has not been impressive. And despite substantial increases in the number of Indians attaining higher education, illiteracy rates remain high.
In this paper, we build on a growth accounting framework to empirically examine these dimensions of India’s recent growth. Where has the growth been concentrated, as among agriculture, industry, and the service-producing sectors? What are the major contributors to that growth: increased employment, capital per worker, educational attainment, or improvements in the basic efficiency of resource use (total factor productivity)? We also examine each of the features noted above that distinguish India’s recent performance. Thus, we are particularly interested in the sources of growth in the service-producing industries. Is it sustainable or should India place greater emphasis on the manufacturing sector and the promotion of rapid growth in export markets? We also emphasize the roles of both physical and human capital accumulation. Throughout the analysis, we are particularly concerned about the quality of the available statistical data, and the influence this may have on our conclusions.
