Appraisal of Factors Influencing Public Transport Patronage in New Zealand

Appraisal of Factors Influencing Public Transport Patronage in New Zealand Dr Judith Wang Research Fellow in Transport Economics The Energy Centre The University of Auckland Business School, New Zealand j.wang@auckland.ac.nz

Important Notice to the Reader The NZ Transport Agency is a Crown entity established under the Land Transport Management Act 2003. The objective of the Agency is to undertake its functions in a way that contributes to an affordable, integrated, safe, responsive and sustainable land transport system. Each year, the NZ Transport Agency funds innovative and relevant research that contributes to this objective. The views expressed in this paper are the outcomes of the independent research, and should not be regarded as being the opinion or responsibility of the NZ Transport Agency. The material contained in the reports should not be construed in any way as policy adopted by the NZ Transport Agency or indeed any agency of the NZ Government. The reports may, however, be used by NZ Government agencies as a reference in the development of policy. While this paper is believed to be correct at the time of its preparation, the NZ Transport Agency and agents involved in their preparation and publication, do not accept any liability for use of the research. People using the research, whether directly or indirectly, should apply and rely on their own skill and judgment. They should not rely on the contents of this paper in isolation from other sources of advice and information. If necessary, they should seek appropriate legal or other expert advice.

1. Introduction 2. The Model 3. Data Analysis and Forecast Models Auckland Wellington Christchurch 4. Elasticity Estimates and Discussion

1. Introduction 2. The Model 3. Data Analysis and Forecast Models Auckland Wellington Christchurch 4. Elasticity Estimates and Discussion

The overall objective of the study was to undertake an in-depth analysis of factors influencing public transport patronage in NZ 1. Identification of the key factors affecting public transport patronage 2. Estimation of the elasticities with respect to each of the key factors identified 3. Development of forecasting models for use by transport operators and transport funding agencies ATRF 2009, Auckland, 1 Oct 2009 Dr Judith Wang 4

Econometric analyses were applied to annual and quarterly national and regional aggregate data for three major regions 3. 1. Major city: Christchurch 2. 1. Auckland (Quarterly, 1996Q1 2008Q2) 2. Wellington (Annually, FY99/00 FY07/08) 3. Canterbury (Quarterly, 1997Q1 2008Q2) ATRF 2009, Auckland, 1 Oct 2009 Dr Judith Wang 5

We considered a set of economic and structural determinants that might have contributed to the changes in trends of PT patronage Dependent variable Patronage (in trips per capita) Economic determinants 1. Service level (in bus/train kilometre per capita) 2. Real fare (in real revenue per passenger) 3. Real income (in real disposable income per capita) Structural determinants 1. Car ownership (in cars per capita by region) 2. Real fuel price ATRF 2009, Auckland, 1 Oct 2009 Dr Judith Wang 6

1. Introduction 2. The Model 3. Data Analysis and Forecast Models Auckland Wellington Christchurch 4. Elasticity Estimates and Discussion

A dynamic model is specified for each city by mode - relating per capita patronage to fares, service level, car ownership, income and fuel price We assume that the long-run equilibrium demand, in passenger trips per capita, can be expressed as a function of service, fare, car ownership, income and petrol price Q f S, F, C, I, O Q X M * X M X M X X M X M t t t t t t t 1 Long-run equilibrium demand Service Fare Car Ownership Income Fuel Price Demand in previous period Assumption: To a certain extent, travel behaviour is a habit Assuming that the function is in linear form, if all variables are transformed in logarithmic forms where ln Q ln S ln F ln C X M X M X M X M X M X M X M X t S t F t C t ln I ln O ln Q X M X M X M X M I t O t t 1 X A, W, C M B, R for Bus and Rail respectively for Auckland, Wellington and Christchurch respectively ATRF 2009, Auckland, 1 Oct 2009 Dr Judith Wang 8

With a dynamic model, we can estimate both the short-run and long-run elasticities at the same time Elasticity Definition Estimation Coefficients Short-run Long-run Service elasticity of demand Percentage change in Patronage per capita Percentage change in Service X M S 1 X M S X M Fare elasticity of demand Percentage change in Patronage per capita Percentage change in Fare X M F 1 X M F X M Car ownership elasticity of demand Percentage change in Patronage per capita Percentage change in Car ownership per capita X M C 1 X M C X M Income elasticity of demand Percentage change in Patronage per capita Percentage change in Real income per capita X M I 1 X M I X M Fuel price elasticity of demand Percentage change in Patronage per capita Percentage change in Fuel price X M O 1 X M O X M ATRF 2009, Auckland, 1 Oct 2009 Dr Judith Wang 9

The significance of an influencing factor was determined by hypothesis testing We determine the level of significance of a variable by testing the null hypothesis of the coefficient of the variable being zero For example, to determine the significance of fares Null hypothesis patronage ln Q ln S ln F ln C Alternative hypothesis X M X M X M X M X M X M X M X t S t F t C t ln I ln O ln Q X M X M X M X M I t O t t 1 : X M H 0 0 F H a X M : 0 F Fare did not have significant influence on Fare did have significant influence If we can reject the null hypothesis, that means there was no evidence that this factor did not have significant influence ATRF 2009, Auckland, 1 Oct 2009 Dr Judith Wang 10

A forecast model is satisfactory only if all the influencing factors are statistically significant Eliminate insignificant factor(s) All factors are significant Include all factors Test significance All factors are NOT significant Include only Service + Fare Test significance Include other factors ATRF 2009, Auckland, 1 Oct 2009 Dr Judith Wang 11

1. Introduction 2. The Model 3. Data Analysis and Forecast Models Auckland Wellington Christchurch 4. Elasticity Estimates and Discussion

Bus patronage/capita/quarter 3 4 5 6 0.4 0.6 0.8 1.0 1.2 Rail patronage/capita/quarter Bus patronage in Auckland has been increasing since 1999 while rail patronage has been increasing only since 2003 Bus and Rail Patronage per Capita in Auckland 1996-2008 Bus Patronage per Capita in Auckland Rail Patronage per Capita in Auckland 1996 1998 2000 2002 2004 2006 2008 Time ATRF 2009, Auckland, 1 Oct 2009 Dr Judith Wang 13

Bus patronage/capita/quarter 3 4 5 6 3.5 4.0 4.5 5.0 5.5 6.0 Bus-km/capita/quarter Bus services has been significantly improved in response to the increase in demand since 1999 Bus Patronage and Bus-kilometres per Capita in Auckland 1996-2008 Bus Patronage per Capita in Auckland Bus-km per Capita in Auckland 1996 1998 2000 2002 2004 2006 2008 Time ATRF 2009, Auckland, 1 Oct 2009 Dr Judith Wang 14

Bus patronage/capita/quarter 3 4 5 6 1.5 1.6 1.7 1.8 1.9 2.0 NZD per passenger Deregulation of bus services induced a significant increase in fare but bus patronage continued to climb despite the fare increase Bus Patronage per Capita and Revenue per Bus Passenger in Auckland 1996-2008 Bus Patronage per Capita in Auckland Real Revenue per Bus Passenger in Auckland 1996 1998 2000 2002 2004 2006 2008 Time ATRF 2009, Auckland, 1 Oct 2009 Dr Judith Wang 15

Rail patronage/capita/quarter 0.4 0.6 0.8 1.0 1.2 0.20 0.25 0.30 0.35 Rail-km/capita/quarter Rail patronage has been on a steep climb since the opening of Britomart in 2003 and rail service has been tremendously improved Rail Patronage and train-kilometres per Capita in Auckland 1996-2008 Rail Patronage per Capita in Auckland Rail-km per Capita in Auckland 1996 1998 2000 2002 2004 2006 2008 Time ATRF 2009, Auckland, 1 Oct 2009 Dr Judith Wang 16

Rail patronage/capita/quarter 0.4 0.6 0.8 1.0 1.2 2.3 2.4 2.5 2.6 2.7 2.8 NZD per passenger Despite significant increase in rail fare, rail patronage has been climbing steeply Rail Patronage per Capita and Revenue per Rail Passenger in Auckland 1996-2008 Rail Patronage per Capita in Auckland Real Revenue per Rail Passenger in Auckland 1996 1998 2000 2002 2004 2006 2008 Time ATRF 2009, Auckland, 1 Oct 2009 Dr Judith Wang 17

NZD/capita/quarter 6.0 6.5 7.0 7.5 Car ownership/capita 0.48 0.50 0.52 0.54 Car ownership has been on the rise with increase in income Real Disposable Income and Car Ownership per Capita in Auckland 1996-2008 Real Disposable Income per Capita Car Ownership per Capita in Auckland 1996 1998 2000 2002 2004 2006 2008 Time ATRF 2009, Auckland, 1 Oct 2009 Dr Judith Wang 18

cents per litre 100 120 140 160 180 Car ownership/capita 0.48 0.50 0.52 0.54 Car ownership s increasing trend has flattened while fuel price has been volatile and rapidly increasing in recent years Fuel Price and Car Ownership per Capita in Auckland 1996-2008 Fuel Price Car Ownership per Capita in Auckland 1996 1998 2000 2002 2004 2006 2008 Time ATRF 2009, Auckland, 1 Oct 2009 Dr Judith Wang 19

cents per litre 100 120 140 160 180 PT journeys/capita 4 5 6 7 8 The increase and fluctuations in fuel price in recent years did have a positive impact on PT patronage Fuel Price and PT Patronage per Capita in Auckland 1996-2008 Fuel Price PT Patronage per Capita 1996 1998 2000 2002 2004 2006 2008 Time ATRF 2009, Auckland, 1 Oct 2009 Dr Judith Wang 20

Two models were identified for Auckland Bus Patronage Forecast Auckland Bus Patronage Model (1999Q3-2008Q2) Service + Car ownership+ Q4 Seasonal dummy ln Q 0.8046 0.4977 ln S 1.3239ln C A B A B A t t t AB 0.5071ln Q 0.0661D t 1 4t Auckland Bus Patronage Model (2003Q3-2008Q2) Service + Car ownership + Fuel price+ Q4 Seasonal dummy A B A B A ln Q 1.9306 0.4603ln S 1.9618ln C 0.2040ln O t t t t AB 0.3677 ln Q 0.0478D t 1 4t ATRF 2009, Auckland, 1 Oct 2009 Dr Judith Wang

Two models were identified for Auckland Bus Patronage Forecast Bus Pax Per Capita 6,8 6,6 6,4 6,2 6,0 5,8 5,6 5,4 5,2 5,0 4,8 4,6 4,4 4,2 4,0 3,8 3,6 3,4 3,2 3,0 Observed Patronage per Capita per Quarter on Contract Bus Services Best Fitted Model 99-08 R-square = 0.9562 Best Fitted Model 03-08 R-square = 0.9829 This period is not considered because it has a different trend. Possible reasons are: 1. In 1990 s Car prices fell by 50% as Japanese second hand imports entered the market. In 1998 Tarrifs removed from cars 2. Deregulation of bus services in 1989 1996 Q1 to 1999 Q2 The opening of the CBD railway station Britomart in 2003 and subsequent improvement of rail services has induced modal shifts and marked the beginning of a changed trend 2,8 1996 1997 1998 1999 2000 2001 2002 2003 Year 2004 2005 2006 2007 2008 2009 ATRF 2009, Auckland, 1 Oct 2009 Dr Judith Wang 22

Two models were identified for Auckland Rail Patronage Forecast Auckland Rail Patronage Model (2003Q3-2008Q2) Model 1 - Service + Fare + Income+ Q4 Seasonal dummy A R A R A R ln Q 1.1448 0.9946ln S 0.9672ln F 1.606ln I t t t t AR 0.2957 ln Q 0.1325D t 1 4t Auckland Rail Patronage Model (2003Q3-2008Q2) Model 2 - Service + Fare+ Q4 Seasonal dummy ln Q 1.6913 0.8827 ln S 0.6755ln F A R A R A R t t t AR 0.4584ln Q 0.1478D t 1 4t ATRF 2009, Auckland, 1 Oct 2009 Dr Judith Wang

Two models were identified for Auckland Rail Patronage Forecast Rail Pax Per Capita 1,35 1,30 1,25 1,20 1,15 1,10 1,05 1,00 0,95 0,90 0,85 0,80 0,75 0,70 0,65 0,60 0,55 0,50 0,45 0,40 Observed Patronage per Capita per Quarter Best Fitted Model 1 R-square = 0.9867 Best Fitted Model 2 R-square = 0.9785 The rail market in Auckland had been stagnant for many many years 1996 Q1 to 2003 Q2 The opening of the CBD railway station Britomart in 2003 and subsequent improvement of rail services has induced modal shifts and marked the beginning of a changed trend 0,35 1996 1997 1998 1999 2000 2001 2002 2003 Year 2004 2005 2006 2007 2008 2009 ATRF 2009, Auckland, 1 Oct 2009 Dr Judith Wang 24

1. Introduction 2. The Model 3. Data Analysis and Forecast Models Auckland Wellington Christchurch 4. Elasticity Estimates and Discussion

One model was identified for Wellington Bus Patronage Forecast Bus Pax Per Capita 50,5 50,0 49,5 49,0 48,5 48,0 47,5 47,0 46,5 46,0 45,5 45,0 44,5 44,0 43,5 43,0 42,5 Observed Patronage per Capita per Annum Best Fitted Model 98-08 R-square = 0.9006 ln Q 2.0590 0.2312ln F 0.4934ln Q W B W B W B t t t Fare is a significant factor 42,0 41,5 41,0 2000 2001 2002 2003 2004 Financial Year 2005 2006 2007 2008 ATRF 2009, Auckland, 1 Oct 2009 Dr Judith Wang 26 1

Two models were identified for Wellington Rail Patronage Forecast Wellington Rail Patronage Forecast Model Model 1 - Service + Car ownership + Fuel price W R W R W ln Q 1.3759 0.7424ln S 0.3246ln C 0.1303ln O t t t t 0.6889ln Q W R t 1 Wellington Rail Patronage Forecast Model Model 2 - Service + Income + Fuel price W R W R ln Q 0.4663 0.7847 ln S 0.2176ln I 0.1212ln O t t t t 0.6900ln Q W R t 1 ATRF 2009, Auckland, 1 Oct 2009 Dr Judith Wang

Two models were identified for Wellington Rail Patronage Forecast Rail Pax Per Capita 24,6 24,4 24,2 24,0 Observed Patronage per Capita per Annum Best Fitted Model 1 R-square = 0.9846 Best Fitted Model 2 R-square = 0.9873 23,8 23,6 23,4 23,2 23,0 22,8 22,6 22,4 22,2 22,0 21,8 21,6 21,4 21,2 2000 2001 2002 2003 2004 2005 2006 2007 2008 Financial Year ATRF 2009, Auckland, 1 Oct 2009 Dr Judith Wang 28

1. Introduction 2. The Model 3. Data Analysis and Forecast Models Auckland Wellington Christchurch 4. Elasticity Estimates and Discussion

Two models were identified for Christchurch Bus Patronage Forecast Christchurch Fitted Bus Patronage Forecast Model (1998Q1-2008Q2) Service only+ Q4 Seasonal dummy C B C B C B ln Q 0.1147 0.0708ln S 0.0898ln Q 0.8863D t t t 1 4t Christchurch Fitted Bus Patronage Forecast Model (2004Q1-2008Q2) Fare + Fuel price + Q4 Seasonal dummy C B C B ln Q 0.1731 0.2620ln F 0.2785ln O t t t C B 0.2373ln Q 0.0429D t 1 4t ATRF 2009, Auckland, 1 Oct 2009 Dr Judith Wang

Two models were identified for Christchurch Bus Patronage Forecast Bus Pax Per Capita 8,0 7,8 7,6 7,4 7,2 7,0 6,8 6,6 6,4 6,2 6,0 5,8 5,6 5,4 5,2 Observed Patronage per Capita per Quarter Best Fitted Model 98-08 R-square = 0.9861 Best Fitted Model 04-08 R-square = 0.8717 Cash Gold Coin fare in 1998 marked the beginning of a new trend Metrostar cross-suburban service introduced in Nov 2004 The introduction of the Metrocard in July 2003 also had significant impact on patronage Norther Star bus service introduced in Nov 2006 5,0 Orbiter ring route weekday 4,8 frequency increased from a 15-min 4,6 headway to 10-min in 2001 4,4 Orbiter ring route 4,2 introduced in 1999 4,0 1996 1997 1998 1999 2000 2001 2002 2003 Year 2004 2005 2006 2007 2008 2009 ATRF 2009, Auckland, 1 Oct 2009 Dr Judith Wang 31

1. Introduction 2. The Model 3. Data Analysis and Forecast Models Auckland Wellington Christchurch 4. Elasticity Estimates and Discussion

The three cities all have different characteristics and the drivers behind the trends were also different Influencing Factor Auckland Wellington Bus Rail Bus Rail Christchurch Service positive positive n/a positive positive Fare n/a negative negative n/a negative Car Ownership negative n/a n/a negative n/a Income n/a positive n/a negative n/a Fuel Price positive n/a n/a positive positive ATRF 2009, Auckland, 1 Oct 2009 Dr Judith Wang 33

A summary of best estimates of elasticities Influencing Factor Auckland Wellington Bus Rail Bus Rail Christchurch Service 0.46 (0.73) 0.88 (1.63) n/a 0.74 (2.39) 0.07 (0.62) Fare n/a -0.68 (-1.25) -0.23 (-0.46) n/a -0.26 (-0.34) Car Ownership -1.96 (-3.10) n/a n/a -0.32 (-1.04) n/a Income n/a 1.61 (2.28) n/a -0.22(-0.70) n/a Fuel Price 0.20 (0.32) n/a n/a 0.13 (0.42) 0.28 (0.37) Key: Short-run (Long-run) ATRF 2009, Auckland, 1 Oct 2009 Dr Judith Wang 34

Service was identified as the key driving factor among all five factors considered It had significant influence in all cities and in almost all modes except Wellington bus and the elasticity estimates were all positive Influencing Factor Auckland Wellington Bus Rail Bus Rail Christchurch Service 0.46 (0.73) 0.88 (1.63) n/a 0.74 (2.39) 0.07 (0.62) Fare n/a -0.68 (-1.25) -0.23 (-0.46) n/a -0.26 (-0.34) Car Ownership -1.96 (-3.10) n/a n/a -0.32 (-1.04) n/a Income n/a 1.61 (2.28) n/a -0.22(-0.70) n/a Fuel Price 0.20 (0.32) n/a n/a 0.13 (0.42) 0.28 (0.37) Key: Short-run (Long-run) ATRF 2009, Auckland, 1 Oct 2009 Dr Judith Wang 35

Bus fare was a significant influencing factor in both Wellington and Christchurch but not in Auckland Auckland had a higher proportion of public transport dependent population. As a result, it appeared that fare did not have a significant influence on bus patronage in Auckland Despite the increase in fares, the increase in fuel price was more significant. In other words, public transport was still relatively cheap as compared to driving. As a result, the increase in patronage was influenced by the increase in fuel price but not influenced by fare for Auckland bus and Wellington rail. Influencing Factor Auckland Wellington Bus Rail Bus Rail Christchurch Service 0.46 (0.73) 0.88 (1.63) n/a 0.74 (2.39) 0.07 (0.62) Fare n/a -0.68 (-1.25) -0.23 (-0.46) n/a -0.26 (-0.34) Car Ownership -1.96 (-3.10) n/a n/a -0.32 (-1.04) n/a Income n/a 1.61 (2.28) n/a -0.22(-0.70) n/a Fuel Price 0.20 (0.32) n/a n/a 0.13 (0.42) 0.28 (0.37) Key: Short-run (Long-run) ATRF 2009, Auckland, 1 Oct 2009 Dr Judith Wang 36

Income was found to have a positive effect on Auckland rail patronage and on the contrary a negative effect on Wellington rail patronage, while international estimates were negative The change in rail market as a result of the tremendous investment in infrastructure and service improvement. A higher proportion of commuters with higher income were attracted to use rail service since the opening of Britomart in 2003 Influencing Factor Auckland Wellington Bus Rail Bus Rail Christchurch Service 0.46 (0.73) 0.88 (1.63) n/a 0.74 (2.39) 0.07 (0.62) Fare n/a -0.68 (-1.25) -0.23 (-0.46) n/a -0.26 (-0.34) Car Ownership -1.96 (-3.10) n/a n/a -0.32 (-1.04) n/a Income n/a 1.61 (2.28) n/a -0.22(-0.70) n/a Fuel Price 0.20 (0.32) n/a n/a 0.13 (0.42) 0.28 (0.37) Key: Short-run (Long-run) ATRF 2009, Auckland, 1 Oct 2009 Dr Judith Wang 37

A higher proportion of commuters with higher income were attracted to use rail service since the opening of Britomart in 2003 Millions 4,5 4,0 3,5 3,0 Rail Patronage by Passenger Type Auckland Adult Concession Student Other (Monthly Passes, Day Passes) 1% 2% 3% 100% 4% 3% 6% 5% 5% 90% 80% 70% Composition of Rail Patronage by Passenger Type Auckland 36% 32% 28% 25% 4% 5% 23% 5% 6% 5% 7% 22% 21% 100% 2,5 60% 2,0 1,5 50% 40% 30% 59% 60% 64% 66% 68% 68% 66% 1,0 20% 0,5 10% 0,0 2002 2003 2004 2005 2006 2007 2008 FY 0% 2002 2003 2004 2005 2006 2007 2008 FY ATRF 2009, Auckland, 1 Oct 2009 Dr Judith Wang 38

Rail service and fare elasticities were higher than the corresponding estimates for bus in Auckland and in other cities Auckland s public transport system, especially the rail system, had gone through tremendous improvement over the last decade. As a result, the service and fare elasticities were higher (more elastic) than in other cities Influencing Factor Auckland Wellington Bus Rail Bus Rail Christchurch Service 0.46 (0.73) 0.88 (1.63) n/a 0.74 (2.39) 0.07 (0.62) Fare n/a -0.68 (-1.25) -0.23 (-0.46) n/a -0.26 (-0.34) Car Ownership -1.96 (-3.10) n/a n/a -0.32 (-1.04) n/a Income n/a 1.61 (2.28) n/a -0.22(-0.70) n/a Fuel Price 0.20 (0.32) n/a n/a 0.13 (0.42) 0.28 (0.37) Key: Short-run (Long-run) ATRF 2009, Auckland, 1 Oct 2009 Dr Judith Wang 39

The fluctuations in fuel price in recent years had a positive impact on PT patronage in all three cities, although not on all modes The estimated fuel price elasticity in Christchurch was higher than in Auckland and Wellington: Christchurch had the highest car ownership per capita among the three cities but relatively cheaper bus fares and a more convenient ticketing system This implied a higher substitution effect between bus and car in Christchurch as compared to other cities Influencing Factor Auckland Wellington Bus Rail Bus Rail Christchurch Service 0.46 (0.73) 0.88 (1.63) n/a 0.74 (2.39) 0.07 (0.62) Fare n/a -0.68 (-1.25) -0.23 (-0.46) n/a -0.26 (-0.34) Car Ownership -1.96 (-3.10) n/a n/a -0.32 (-1.04) n/a Income n/a 1.61 (2.28) n/a -0.22(-0.70) n/a Fuel Price 0.20 (0.32) n/a n/a 0.13 (0.42) 0.28 (0.37) Key: Short-run (Long-run) ATRF 2009, Auckland, 1 Oct 2009 Dr Judith Wang 40

NZD/capita/quarter 0.45 0.50 0.55 0.60 Christchurch has always had the highest car ownership among the three cities Christchurch Auckland Wellington 1996 1998 2000 2002 2004 2006 2008 ATRF 2009, Auckland, 1 Oct 2009 Dr Judith Wang Time

In the long run, the most effective policy to encourage use of public transport could be by controlling car ownership or its use Car ownership was the most elastic among all the factors identified and fuel price was found to have significant influence in Auckland and Christchurch bus patronage but only in the latest four or five years Influencing Factor Auckland Wellington Bus Rail Bus Rail Christchurch Service 0.46 (0.73) 0.88 (1.63) n/a 0.74 (2.39) 0.07 (0.62) Fare n/a -0.68 (-1.25) -0.23 (-0.46) n/a -0.26 (-0.34) Car Ownership -1.96 (-3.10) n/a n/a -0.32 (-1.04) n/a Income n/a 1.61 (2.28) n/a -0.22(-0.70) n/a Fuel Price 0.20 (0.32) n/a n/a 0.13 (0.42) 0.28 (0.37) Key: Short-run (Long-run) ATRF 2009, Auckland, 1 Oct 2009 Dr Judith Wang 42

The elasticity estimates for Wellington were lower (less elastic) than those for Auckland and Christchurch in general The market in Wellington was quite different from Auckland and Christchurch: Wellington has the highest public transport use among the three cities Wellington also had the highest walk modal share as the CBD employment area is more compact and walkable The council also had a committed parking restraint policy in CBD Influencing Factor Auckland Wellington Bus Rail Bus Rail Christchurch Service 0.46 (0.73) 0.88 (1.63) n/a 0.74 (2.39) 0.07 (0.62) Fare n/a -0.68 (-1.25) -0.23 (-0.46) n/a -0.26 (-0.34) Car Ownership -1.96 (-3.10) n/a n/a -0.32 (-1.04) n/a Income n/a 1.61 (2.28) n/a -0.22(-0.70) n/a Fuel Price 0.20 (0.32) n/a n/a 0.13 (0.42) 0.28 (0.37) Key: Short-run (Long-run) ATRF 2009, Auckland, 1 Oct 2009 Dr Judith Wang 43

Concluding Remarks Our methodology and analysis in this study was limited by data availability Auckland Wellington Christchurch Bus data: contract services only Rail data: service measured in train-km Only annual information available Service data: approximation from time table Fare data: only available from 2004 Partial Adjustment Model is the best model given the data limitation Econometric analysis can be a powerful tool for forecasting but more effort is required in maintaining a database of good quality information ATRF 2009, Auckland, 1 Oct 2009 Dr Judith Wang

Thank you! Any questions? Dr Judith Wang Research Fellow in Transport Economics The Energy Centre The University of Auckland Business School, New Zealand j.wang@auckland.ac.nz ATRF 2009, Auckland, 1 Oct 2009 Dr Judith Wang