Convergence or Divergence in the Manufacturing Sector Since 1980’s? Evidence from the Indian Sub Nationals
Authors: Shergill Amrita , Arora Sakshi 
Published: June 2023

Purpose: The objective of this study was to divulges into understanding the inter-state disparities across the sixteen major Indian states in the registered manufacturing sector by analyzing it’s pattern and traversing over the years initiating from 1980-1981 to 2015-2016.

Theoretical framework: The Indian economic development pattern is not only unusual, but also rare, when one compares it to the economic development paths followed by other developing and developed countries. The countries such as Singapore, Taiwan, South Korea and China achieved economic growth by initially giving priority to the manufacturing sector. It was after producing tangible outputs and generating innovations in the manufacturing sector that in the above mentioned countries, the services sector emerged as the biggest and leading sector in economic growth. The economic literature also shows a strong correlation between the growth of the manufacturing output and the growth of GDP (Thirlwall, A. P. 1983). The growth of the manufacturing sector sucks labour resources from other sectors where disguised unemployment exist; which contributes to the growth of the capital employed in the industry, while the productivity of other sectors is not adversely affected (N. Marconi et. al,2016) In other words, a strong and growing manufacturing sector is necessary for economic growth and development. However, in India the services sector emerged as the biggest and fast growing sector in the very beginning, and the manufacturing sector's contribution to economic growth has been relatively small.

Design/methodology/approach: To bring about the pattern of the size of the manufacturing sector the data has been analyzed by tabulation, calculating averages, coefficients of variations, bar diagrams and line graphs so that a clear picture is exemplified. To look into the impact of geographical location the data has been divided into two regional schemes which have been analyzed using the dummy variable regression technique (ANOVA), and lastly to highlight if there exists convergence or divergence across the states over the aforementioned time period the technique of σ – convergence and β-convergence have been applied.

Findings: The results of σ – convergence based on coefficient of variation clearly show that the size of manufacturing sector, in terms of both the indicators of size, diverged among states over 1980-1981 to 2015-2016 period. At least it is sure that no convergence occurred over this period. Furthermore, the results of the β-convergence based on growth rates of the two indicators give conflicting conclusions. The value of gross output per-capita indicated divergence over the reference period; but SDP share indicator suggested convergence over the same period. Taking both σ- convergence and β-convergence together, one may suggest that these do not indicate to any tendency towards convergence over this period. Therefore the objective of this paper was to analyse the change in the size of manufacturing sector across the states over the 1980-81 /2015-16 period on the basis of two indicators; share of manufacturing sector in SDP and value of gross manufacturing output per capita. The analysis revealed that the pattern changed somewhat over this period. Some states improved their ranking e.g. Gujarat and H.P. and ranking of some others worsened e.g. Maharashtra, Bihar etc. The analysis also revealed that there was no significant difference in the SDP share and value of gross output per capita of manufacturing sector between coastal / non coastal and northern/southern states. The analysis of convergence / divergence across the states over the 1980-81/ 2015-16 revealed that convergence did not occur; rather there was some tendency towards divergence.

Research, Practical & Social implications: Future research should focus on the reducing the disparities among the Indian states via exploring other important variables in the manufacturing sector. It can be further extended by using panel data analysis. Also, Policy implication suggested for the laggard states has been to identify the caveats and implementation of policies for them should be at national level to bolster the overall growth of the manufacturing sector.