Abstract
This study examines long term forecasting of international air travel demand in Nigeria. Yearly data from 2001 to 2017 were collected from secondary sources. Ordinary Least Square (OLS) regression was used to forecast the ten years (2018 to 2028) demand for international air passenger travel in Nigeria. The demand for international air passenger in Nigeria from year 2001 to 2017 was compared with the forecast. Calculation reveals that the coefficient of determination R2 is 0.815, while the computed reveals that the coefficient of determination R2 is 0.769, this difference can be attributed to approximations to two decimal places for calculated test. The calculated test and computed test reveals that the error term is minimal and the explanation level is high; hence the prediction or forecast is reliable. The forecast for years 2020, 2025 and 2028 are 5,282,453, 6,342,519, and 6,978,559 respectively which are about 48 percent increase, 78 percent increase, and 95 percent increase respectively from demand in year 2017. The forecast of ten years from year 2018 to year 2028 reveals that there will be more increase in the demand for international air passenger travel in Nigeria. The implication of this increment is that existing air transport infrastructures should be upgraded, and new infrastructures should be procured and installed; airport and airline operations should be reviewed and strategized such that they will meet the expectations of airline and airport users. Other concerned business stakeholders should use this data to plan and invest as there is high tendency for profit making.
Highlights
1.1 Background of the Study There will always be demand for movement as the importance of transportation cannot be far-fetched from or beyond the following; economic purpose, social integration and spatial interaction, (Adeniran, 2016) without which poverty is inevitable
This study adopts Ordinary Least Square (OLS) regression approach, as it is often used for trend forecasting. 1.2 Aim and Objectives The aim of this paper is to examine the dynamics for evaluating different forecasting methods for international air passenger demand in Nigeria
It assumes that the past rate of growth or change will continue (John, 2007). 2.3Ordinary Least Square (OLS) Regression The least squares method is a form of mathematical regression analysis that finds the line of best fit for a dataset, providing a visual demonstration of the relationship between the data points
Summary
1.1 Background of the Study There will always be demand for movement as the importance of transportation cannot be far-fetched from or beyond the following; economic purpose, social integration and spatial interaction, (Adeniran, 2016) without which poverty is inevitable. This connote the axiom of Wilfred Owen, a renowned transport analyst who states that “Immobility Perpetuate Poverty”. The demand for transport is a derived one which is driven by the needs and desires to attain some other final objectives.
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