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Estimation of freight demand at Mumbai Port using regression and time series models


Forecasting future freight demand at a seaport is important for its planning and development. India has 13 major ports which handle 75% of the total seaport freight. Among the 13 major ports, Mumbai Port, ranked at number three in the country for the year 2013-14, handles about 11% of the total freight at major seaports in India. The focus of this paper is on developing inbound and outbound demand forecasting models for Mumbai Port. The models are developed using additive regression and time series techniques. In regression analysis economic indicators, Gross Domestic Product (GDP) and Crude Oil Production (CRLP) are found to be significant. The multivariate models performed better than the univariate models. The validation of time-series models resulted in error of less than 5%. Both multivariate regression and time-series models are used to forecast freight demand for the years 2014- 15 through 2017-18. The regression models are producing more optimistic forecasts than the time series models. The elasticity analysis suggested that Mumbai’s inbound freight will be growing almost with India’s GDP growth rate, the outbound freight, however, will experience slower growth than that of inbound.

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Correspondence to Gopal R. Patil.

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Patil, G.R., Sahu, P.K. Estimation of freight demand at Mumbai Port using regression and time series models. KSCE J Civ Eng 20, 2022–2032 (2016).

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