An Empirical Analysis of Passenger Rail Demand in Pakistan
Journal Title: Research Journal Social Sciences (Online) - Year 2016, Vol 5, Issue 1
Abstract
This study identifies the major determinants of passenger rail demand along with forecasting performance in case of Pakistan. The data set covered annual observations over the period from 1980 to 2012. To examine the short run and long run relationship between passenger rail demand and its determinants, the Autoregressive Distributed Lag (ARDL) model have been used. For comparison of forecasting performance, univariate Autoregressive Integrated Moving Average (ARIMA) and multivariate ARDL forecasted model have been estimated. The passenger kilometers (PKM) is our variable of interest whereas the explanatory variables are total population, GDP per capita, domestic diesel oil prices and fare. The findings of this study indicated that the GDP per capita and population plays pivotal role for increasing passenger rail demand but fare and domestic diesel oil prices have negative relationship. The results postulated that the multivariate ARDL forecasting model is more precise than the univariate ARIMA model. The performance of the predicted models is assessed based on mean absolute error (MAE), mean absolute percentage error (MAPE) and root mean square error (RMSE). On the basis of results government may adopt policies for enhancing GDP, and generating alternative resources for reducing fare and diesel oil prices.
Authors and Affiliations
ALTAF HUSSAIN, Saqlain Raza, Mariuam Shafi
Keywords
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