Analysing the cost structure of construction sectors considering carbon emission factors

Abstract

As a major engine of economic growth and development, developing nations must have a thriving manufacturing sector. This is due to the fact that the industry makes a nation more competitive, increases productivity, and generates jobs. By expressing cost as a function of six inputs including labour, output, fixed cost, fuel consumed, materials used, and carbon emission, the study aimed to estimate the Translog cost function for India's manufacturing sector using cost factor share equations. With a 99.5% R² value of 0.995 for the cost variation using the chosen inputs, the results demonstrate a strong model fit.  Among the other input values, total output, fuel consumption, and fixed capitals were the most important cost drivers.  The robustness of the results was further supported by the statistical significance of the estimated coefficients with p values less than 0.01. The PCA has successfully reduced multicollinearity, which is frequently seen in Translog models with few observations. In order to improve the sustainability of these manufacturing industries, this study assists policymakers in designing carbon policies and optimizing cost structures.