A Cross-Industry Efficiency Analysis and Contribution of the Information and Technology Sector to Indian Economic Growth

Abstract:     
This paper investigates the contribution of the service sector, especially the information and communication services to Indian Economic growth using a growth accounting analysis and data from the CMIE database. For the calculation of the contribution of inputs in the growth accounting framework Jorgenson et, al. (2005) advise the use of capital or labour services since not only the quality but also the productivity of various types of capital or labour input, such as low- versus high-skilled, will differ. Standard measures of labour input, such as numbers employed or hours worked, will not account for such differences. Hence they prefer measures of labour input which take the heterogeneity of the labour force into account. According to Timmer et, al. (2007, p. 5) these measures are called labour services or capital services, as they allow for differences in the amount of services delivered per unit of labour or capital in the growth accounting approach. The present study follows the Data Envelopment Analysis (DEA) methodology to unearth the efficiencies of the IT industry of India. The results suggest that In these three years the mean PTE score was about 0.6, indicating thereby companies are 40% pure technical inefficient. Pure technical inefficiency in the Indian software industry may be attributed to the poor infrastructure, mainly power supply. Infrastructure bottleneck and frequent power cut leads to delays and productivity loss in the silicon city of India, i.e. Bangaluru. Percentage of efficient companies in terms of PTE scores was lowest in the year 2003-04 (20.83%) and highest in the year 2005-06 (40.28%). Percentage of efficient companies in PTE score followed a cyclical pattern as well. Indian software companies are becoming more scale inefficient over the years. It was observed that the PI companies have relatively high OTE score as compared to PF and group owned companies. For example, average OTE score for the study period for all the PI companies stood at 0.482 where as the mean OTE scores for PF owned companies and group owned companies were found to be 0.372 and 0.336 respectively. Mean OTE score for PI companies were found to be highest for all the years and lowest for group owned companies expect for the year 1999-2000 when mean OTE score of PF companies was lowest. These scores highlighted that the inefficiency levels in the PI, PF and Group owned companies were 51.8%, 62.8%, and 66.4% respectively, thereby suggesting that although the levels of inefficiencies are very high across all companies yet private Indian companies appeared to be performing better than other two. It is observed that OTE scores of all the three categories of companies have recorded the same pattern. This may be due to external environmental factors have its bearing on OTE of the companies.

Number of Pages in PDF File: 15

Keywords: ICT, IT sector, Efficiency Analysis, Multi Factor Productivity

JEL Classification: O52, J24, L80, L84

working papers series