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Chapter 5Projections of passengermovements on regionalair routes5.1 IntroductionIn the past, BITRE projected future trends of passenger movements for various publictransport modes using a gravity model formulation (BTRE 1998, 2003). The gravitymodel offers an effective methodology to appraise the transport demand betweengeographical areas. It relies on historical origin-destination (OD) information forcalibration. This means that forecasts of future trip distribution are related to thebase distribution used for calibration. However, data constraints in regional areasprevented the possibility of using this approach.With a wealth of 22 years of historical data in passenger movements on regional airroutes, projections were generated using extrapolative methods. In this approach,forecasts for a series are a function solely of time and past values. This chapteroutlines the procedures and assumptions used to generate the projections. It alsopresents the projected trends at a national level and at the level of state and territory.Estimates are presented for passenger movements on regional air routes up to theyear 2016.The projections are neither predictions nor forecasts. Instead, they are conditionalprojections. Rather than attempting to look for what will happen, the projectionsattempt to show an indicative future for passenger movements on regional airroutes if the current situation is extended. In other words, the projection results arepossible future trends based completely on the pattern of past trends. Assuming thecontinuation of past trends, the aim of these analyses is to provide a glimpse into thepossible direction of future trends.5.2 Analysis approachData sourcesThe BITRE regional air transport time series estimates covered more than 90 per centof all data on the passenger movements on regional air routes for the past 22 years.The information is much more comprehensive than survey data and is reasonablyreliable. It provides a good foundation to identify a pattern in the historical data andextrapolate trends into the future.There are a couple of data quality issues that are worth noting. It is inevitable thata minority of the data series appeared to be intermittent and some seemed to belacking patterns over time, particularly at the individual air route level. For thesecases, projections of likely future trends may not be possible or valid.139
BITRE | Report 115MethodologyThe projections of passenger movements on regional air routes were derived usingthe SAS Time Series Forecasting System. The Time Series Forecasting system forecastsfuture values of time series variables by extrapolating trends and patterns in the pastvalues of the series.The system generates forecasts by selecting the best-fitting forecasting model froma list of candidate models (see Appendix D, Section 1). The greatest strength of theTime Series Forecasting system is the wide range of forecasting models it provides toallow for the fitting of various trends (see Appendix D, Section 2). The basic processused in generating projected values involves:• preparing and specifying the input time series data• specifying its periodicity and creating identifications of valid time• fitting forecasting models to each series• producing the forecasts.To select the best-fitting model for each time series on passenger movements,statistical and graphical features (See Appendix D, section 3) were used to select andcustomise forecasting models that best predict the time series.AssumptionsThe extrapolation method assumes that a pattern, which has been established in thepast, will continue and can be extended or extrapolated to provide a likely future. Themethod does not attempt to explain the observed past pattern. It assumes that theembedded factors that shaped the past trend will continue to operate and behave inthe same way for the period of the projection. The future therefore is assumed to bea continuation of the past.5.3 Passenger movement projections on regionalair routes5.3.1 National levelThe total number of passenger movements on regional air routes is projected togrow at an average annual growth rate of 2.5 per cent, from about 16 million in 2005to 21 million in 2016 (Figure 5.1). Total passenger movements on regional air routesbetween major cities and regional areas is projected to grow at an average annualgrowth rate of 2.9 per cent, which is above the overall projection of passengermovements on regional air routes (Figure 5.2). The traffic on these routes is projectedto grow from 14.5 million in 2005 to 19.8 million in 2016. Following a prominentdownward trend for the past few years, the projected growth for passengermovements on regional air routes between regional areas is projected to be about0.01 per cent between 2005 and 2016 (Figure 5.3), with the number of passengermovements projected to increase only marginally.140
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Air transport services inregional A
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© Commonwealth of Australia, 2008I
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At a glance• Revenue passengers c
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2.3.4 Aircraft payload ............
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TablesTable 1.1Box 1.1ivAirports in
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Table 4.20Table 5.1Table 5.2Table 5
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FiguresFigure 1.1 ASGC Remoteness C
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Figure 3.1Figure 3.2Figure 3.3Figur
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Figure 4.14 Intrastate air services
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Executive summaryBackgroundIn recen
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Executive summaryKey findingsHistor
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Executive summaryThese contrasting
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Executive summaryhigh numbers of UC
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Executive summary4. Air services at
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IntroductionChapter 1
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BITRE | Report 115certain regional
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BITRE | Report 1151.4 Project ratio
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BITRE | Report 115Analyses undertak
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Chapter 2Historical trends inregion
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Chapter 3Past performance of air se
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BITRE | Report 115Between 2000 and
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BITRE | Report 115Figure 3.5 Averag
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BITRE | Report 115(b) Number of air
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BITRE | Report 115Most regional air
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BITRE | Report 115Figure 3.13 Route
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BITRE | Report 115As shown in Figur
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BITRE | Report 115Table 3.4Airlines
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BITRE | Report 115Major regional ai
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Appendix BHistorical performance of
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BITRE | Report 115Table B1 Number o
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BITRE | Report 115Table B2 Regional
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BITRE | Report 115Table B2Regional
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BITRE | Report 115Table B3 Route de
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BITRE | Report 115Table B3Route den
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Appendix CAccess to regionalair ser
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Appendix C | Access to regional air
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Appendix C | Access to regional air
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Appendix DForecasting process detai
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Appendix D | Forecasting process de
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Appendix D | Forecasting process de
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GlossaryAircraft movementASGC Remot
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GlossaryIndividual income(weekly)In
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GlossaryState and territory (S/T)St
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AbbreviationsABSACCCACTARIAASGCANSI
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ReferencesABS 2001a, 2001 Census Di
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ReferencesQuiggin, J. 1997, ‘Eval
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