DEVELOPMENT OF A REGRESSION MODEL TO FORECAST AIR TRAVEL DEMAND AT BAGHDAD INTERNATIONAL AIRPORT

Abstract

The civil aviation demand forecast is a carefully formed perspective for airport system activities. Its main use is to predict possible needs for the planning and financial management processes for air carriers and civil aviation authorities. It is vital to conduct frequent analyses and projections of demand in order to meet their customers' expectations by balancing supply and demand and staying abreast of the ever-changing aviation industry. The purpose of this paper is to establish a mathematical relationship between the socioeconomic explanatory factors such as (population, Gross Domestic Product (GDP), consumption expenditure, rate of exchange, industry, imports, and exports) and activities (passenger movements and aircraft operations) at Baghdad International Airport in order to develop an econometric model. The required data had been collected for the past ten years. Eight models were developed depending on one or more of the explanatory variables using SPSS software, and they were then subjected to cross-comparison to see which model was more robust. According to the findings of the statistics, the gross domestic product, population size, and consumption expenditure are the most appropriate explanatory variables that have a significant impact on these activities, where they had a high R2 and F-statistics value equal to 90% and 73.442, respectively, for the model of air passengers and GDP and 90% and 48.737 for the model of flight operations and GDP.