Determinants of Petrol Prices in India: A Regression Model with De-Autocorrelated Time-Series Data

Abstract

The control that the Central Government of India had for many years over the petrol prices, kept the life of the common man, who was dependent on the prices of essential commodities for day to day existence, at ease. The liberalization policy allowing determination of petrol prices by the oil marketing companies based on the international market prices is now affecting the prices of all essential commodities with cascading effects. This paper attempts to discover how strongly various manifest factors govern the petrol prices in India on a month-to-month basis. A regression model is built using time-series data on monthly petrol prices and other lagged variables including petrol consumption, import and export of petroleum products, etc. spread over the period 2010 to 2018. Various transformations are performed on the variables to get a more accurate model. The auto-correlation present in the data is suitably handled and finally a regression model is built with the de-autocorrelated data.Contribution/ Originality: This paper's primary contribution is the identification of the main factors, among those considered, that affect petrol prices in India. This objective is achieved using a regression model with monthly time series data wherein the autocorrelation is removed for more reliable results. The path that is followed to get improvements to the model by making transformations on the dependent and independent variables, multicollinearity redressal and de-autocorrelation is an interesting and unconventional feature of this paper.

Public Policy of Green Practices by Restaurants and Hotels: Case of Ecotourism in Ranong Province, Thailand

“…AVE above 0.5 confirmed the convergent validity. (Hair et al, 2012;Henseler, Ringle, & Sinkovics, 2009;Siddiqui & Siddiqui, 2019;Sultana, Koli, & Firoj, 2019;Syahnaz, Nursal, & Komariah, 2019;Tarus, Tenai, & Komen, 2019;Theodore & William, 2019;Tong & Baslom, 2019;Zahra, Hameed, Fiaz, & Basheer, 2019). Five direct effect was proposed.…”