Assessing the Impact of Automation on Traditional Industries in India: An Econometric Time-Series Analysis of Employment, Productivity and Structural Transformation
Abstract : Automation has emerged as a transformative force reshaping industrial structures across developing and advanced economies. In the context of India, where traditional industries such as textiles, manufacturing, agriculture-processing, and mining employ a significant portion of the labor force, the integration of automation technologies presents both opportunities and challenges. This study examines the long-run and short-run impact of automation on employment levels, labor productivity, and structural transformation in India using secondary time-series data from 2000–2024. Econometric techniques including Augmented Dickey–Fuller (ADF) unit root testing, Johansen Cointegration, Vector Error Correction Model (VECM), Granger Causality, and Autoregressive Distributed Lag (ARDL) modeling were applied. The findings reveal that automation significantly enhances productivity in the long run while exerting short-term displacement effects on employment in traditional sectors. Structural transformation toward capital-intensive production is statistically evident. The results contribute to policy debates concerning skill development, labor transition, and inclusive industrial modernization.
Keywords : Automation, Traditional Industries, Employment, Productivity, Structural Transformation, Econometric Analysis, India, Time-Series.
Cite : Prakash, A. (2026). Assessing the Impact of Automation on Traditional Industries in India: An Econometric Time-Series Analysis of Employment, Productivity and Structural Transformation (1st ed., pp. 1-6). Noble Science Press. https://noblesciencepress.org/chapter/nspebgtrdbaip2026ch-01
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