the effect of rail infrastructure development on economic growth
TRANSCRIPT
The effect of Rail infrastructure development on
economic growth in Regional Victoria
Milan Jovetic
MATH 1332 Minor Thesis
Project aim:
• The aim of this project is to asses the impact of rail infrastructure investment on the regional economy of Victoria and evaluate economic convergence between Metropolitan and Regional areas in Victoria.
2
MATH 1332 Minor Thesis
BAT
BGO
GEL TRN
SER
ACCESSIBILITY:
• Better accessibility reduces the transport cost and presents local companies and individuals with an opportunity to present their products in much larger markets.
• Accessibility indicators:
• No. of train services
• Travel time
• Patronage
5
MATH 1332 Minor Thesis
No. of train services and Travel time to Melbourne :
6
MATH 1332 Minor Thesis
20
03
-10
20
03
-12
20
04
-02
20
04
-04
20
04
-06
20
04
-08
20
04
-10
20
04
-12
20
05
-02
20
05
-04
20
05
-06
20
05
-08
20
05
-10
20
05
-12
20
06
-02
20
06
-04
20
06
-06
20
06
-08
20
06
-10
20
06
-12
20
07
-02
20
07
-04
20
07
-06
20
07
-08
20
07
-10
20
07
-12
20
08
-02
20
08
-04
20
08
-06
20
08
-08
20
08
-10
20
08
-12
20
09
-02
20
09
-04
20
09
-06
20
09
-08
20
09
-10
20
09
-12
20
10
-02
20
10
-04
20
10
-06
20
10
-08
20
10
-10
20
10
-12
20
11
-02
20
11
-04
20
11
-06
20
11
-08
20
11
-10
20
11
-12
20
12
-02
20
12
-04
5
9
13
17
21
25
29
33
(Bendigo - MLB)
(Ballarat - MLB)
(Geelong - MLB)
(Seymour - MLB)
(Traralgon - MLB)
Average No. of train servicesN
o. o
f tr
ain
se
rvic
es
20
03
-10
20
03
-12
20
04
-02
20
04
-04
20
04
-06
20
04
-08
20
04
-10
20
04
-12
20
05
-02
20
05
-04
20
05
-06
20
05
-08
20
05
-10
20
05
-12
20
06
-02
20
06
-04
20
06
-06
20
06
-08
20
06
-10
20
06
-12
20
07
-02
20
07
-04
20
07
-06
20
07
-08
20
07
-10
20
07
-12
20
08
-02
20
08
-04
20
08
-06
20
08
-08
20
08
-10
20
08
-12
20
09
-02
20
09
-04
20
09
-06
20
09
-08
20
09
-10
20
09
-12
20
10
-02
20
10
-04
20
10
-06
20
10
-08
20
10
-10
20
10
-12
20
11
-02
20
11
-04
20
11
-06
20
11
-08
20
11
-10
20
11
-12
20
12
-02
20
12
-04
50
60
70
80
90
100
110
120
130
140
150
(Bendigo - MLB)
(Ballarat - MLB)
(Geelong - MLB)
(Seymour - MLB)
(Traralgon - MLB)
Average travel time to Melbourne
Tra
ve
l tim
e t
o M
elb
ou
rne
(m
in)
No. of train services and patronage :
7
MATH 1332 Minor Thesis
20
03-1
02
003
-12
20
04-0
22
004
-04
20
04-0
62
004
-08
20
04-1
02
004
-12
20
05-0
22
005
-04
20
05-0
62
005
-08
20
05-1
02
005
-12
20
06-0
22
006
-04
20
06-0
62
006
-08
20
06-1
02
006
-12
20
07-0
22
007
-04
20
07-0
62
007
-08
20
07-1
02
007
-12
20
08-0
22
008
-04
20
08-0
62
008
-08
20
08-1
02
008
-12
20
09-0
22
009
-04
20
09-0
62
009
-08
20
09-1
02
009
-12
20
10-0
22
010
-04
20
10-0
62
010
-08
20
10-1
02
010
-12
20
11-0
22
011
-04
20
11-0
62
011
-08
20
11-1
02
011
-12
20
12-0
22
012
-04
789
1011121314151617181920
1.0
1.5
2.0
2.5
3.0
3.5
4.0
Average No of train services
Yearly pa-tronage (mil-
lions)
Bendigo corridor - Average No. of train services and patronageN
o. o
f tr
ain
se
rvic
es
Yea
rly
pat
ron
age
(mil
lio
ns)
20
03
-10
20
04
-01
20
04
-04
20
04
-07
20
04
-10
20
05
-01
20
05
-04
20
05
-07
20
05
-10
20
06
-01
20
06
-04
20
06
-07
20
06
-10
20
07
-01
20
07
-04
20
07
-07
20
07
-10
20
08
-01
20
08
-04
20
08
-07
20
08
-10
20
09
-01
20
09
-04
20
09
-07
20
09
-10
20
10
-01
20
10
-04
20
10
-07
20
10
-10
20
11
-01
20
11
-04
20
11
-07
20
11
-10
20
12
-01
20
12
-04
5
7
9
11
13
15
17
19
21
23
25
1.00
1.05
1.10
1.15
1.20
1.25
1.30
1.35
1.40
1.45
1.50Average No of train services
Yearly pa-tronage (mil-
lions)
Seymour corridor - Average No. of train services and Yearly patronage
No
. o
f tr
ain
ser
vice
s
Yea
rly
pat
ron
age
(mil
lio
ns)
Yearly patronage :
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MATH 1332 Minor Thesis
Regional Train Yearly Patronage (in millions)_Vline
YearGeelong Corridor
(Y_Actual)
Growth %
Ballarat Corridor
(Y_Actual)
Growth %
Bendigo corridor
(Y_Actual)
Growth %
Seymour Corridor
(Y_Actual)
Growth %
Traralgon Corridor
(Y_Actual)
Growth %
FY 2005-06 2.03 1.37 1.47 1.05 0.82
FY 2006-07 2.57 26.6 1.88 37.2 2.20 49.7 1.15 9.5 1.05 28.0
FY 2007-08 3.08 19.8 2.39 27.1 2.78 26.4 1.21 5.2 1.54 46.7
FY 2008-09 3.38 9.7 2.68 12.1 3.06 10.1 1.17 -3.3 1.77 14.9
FY 2009-10 3.47 2.7 2.82 5.2 3.15 2.9 1.22 4.3 1.91 7.9
FY 2010-11 3.77 8.6 3.10 9.9 3.36 6.7 1.32 8.2 1.95 2.1
FY 2005/06 - 2010/11 85.7
126.3
128.6
25.7
137.8
No. of train services and Travel time to Melbourne :
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MATH 1332 Minor Thesis
20102009200820072006
20.0
17.5
15.0
12.5
10.0
7.5
5.0
Year
No. of tr
ain
trips
per
resi
dent
BarwonCentral HighlandsLoddonGoulburnGippsland
Variable
No of train trips per resident vs Year
Coef R-Sq Central Highlands (Ballarat corridor) 1.58 91.90%Loddon (Bendigo corridor) 1.24 84.80%Gippsland (Traralgon corridor) 1.09 80.20%Barwon (Geelong corridor) 0.786 89.20%Goulburn (Seymour corridor) 0.096 43.70%
Economic growth indicators
Economic situation in Victorian regions is assessed by utilizing following variables:
• No. of income earners • Average wage and salary income
• Average value of private sector house
• No. of building approvals • Unemployment
10
MATH 1332 Minor Thesis
No. of wage and salary earners
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MATH 1332 Minor Thesis
% of wage and salary earners within working age population living in combined districts
Melbourne
Train Lines
No Train lines
60.0
61.0
62.0
63.0
64.0
65.0
66.0
67.0
68.0
69.0
70.0
2006 2007 2008 2009
%
Melbourne Train Lines No Train lines
No. of wage and salary earners
12
MATH 1332 Minor Thesis
No. of wage and salary earners (Convergence)
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MATH 1332 Minor Thesis
4544434241403938
1
0
-1
-2
-3
No. of Wage and salary earners in 2006 (%)
Av g
row
th r
ate
(2006 -
2009)
(%)
Gippsland (Traralgon)
East Gippsland
Ovens-Murray
Goulburn (Seymour)
Loddon (Bendigo)
Mallee
Wimmera
Central Highlands (Ballarat)
Western Dist.
Barwon (Geelong)
Melbourne
Convergance of No. of wage and salary earners (2006 - 2009)
Average wage and salary income
14
MATH 1332 Minor Thesis
Average wage and salary income (across entire population living in the district)
Melbourne
Train Lines
No Train l ines
30,000
32,000
34,000
36,000
38,000
40,000
42,000
44,000
46,000
48,000
50,000
2006 2007 2008 2009
$
Melbourne Train Lines No Train l ines
General Linear Model: Average Wage and salary income versus Area, Year
Factor Type Levels ValuesArea fixed 3 1, 2, 3Year fixed 4 1, 2, 3, 4
Analysis of Variance for Average Wage and salary income,using Adjusted SS for Tests
Source DF Seq SS Adj SS Adj MS F PArea 2 402579992 402579992 201289996 63.34 0.000Year 3 138857589 87656582 29218861 9.19 0.000Area*Year 6 483207 483207 80535 0.03 1.000Error 32 101692982 101692982 3177906Total 43 643613771
Average wage and salary income
15
MATH 1332 Minor Thesis
One-way ANOVA: Average Wage and salary income versus Area
Source DF SS MS F PArea 2 402579992 201289996 34.24 0.000Error 41 241033779 5878873Total 43 643613771
S = 2425 R-Sq = 62.55% R-Sq(adj) = 60.72%
Individual 95% CIs For Mean Based on Pooled StDevLevel N Mean StDev ---------+---------+---------+---------+1 4 44333 2355 (-----*-----)2 20 36951 2421 (-*--)3 20 33681 2439 (--*--) ---------+---------+---------+---------+ 36000 40000 44000 48000Pooled StDev = 2425
Tukey 95% Simultaneous Confidence IntervalsAll Pairwise Comparisons among Levels of Area
Individual confidence level = 98.06%
Area = 1(Melbourne) subtracted from:
Area Lower Center Upper --------+---------+---------+---------+-2 -10612 -7382 -4151 (-----*------)3 -13882 -10652 -7421 (------*-----) --------+---------+---------+---------+- -10000 -5000 0 5000Area = 2(Trains) subtracted from:
Area Lower Center Upper --------+---------+---------+---------+-3 -5135 -3270 -1405 (--*---) --------+---------+---------+---------+- -10000 -5000 0 5000
Average wage and salary income (Convergence)
16
MATH 1332 Minor Thesis
42000400003800036000340003200030000
17
16
15
14
13
Av. Wage and salary income in 2006 ($)
Av g
row
th r
ate
(2006 -
2009)
(%)
Gippsland (Traralgon corridor)
East Gippsland
Ovens-Murray
Goulburn (Seymour corridor)
Loddon (Bendigo corridor)
Mallee
Wimmera
Central Highlands (Ballarat corridor)
Western Dist.Barwon (Geelong corridor))
Melbourne
Convergance of Average wage and salary income (2006 - 2009)
Average value of private sector house
17
MATH 1332 Minor Thesis
Average value of private sector house
Melbourne
Train Lines
No Train l ines
190
200
210
220
230
240
250
2006 2007 2008 2009 2010
$ ('000)
Melbourne Train Lines No Train l ines
Average value of private sector house
18
MATH 1332 Minor Thesis
One-way ANOVA: Average value of private sector versus Area
Source DF SS MS F PArea 2 2325 1162 4.07 0.023Error 52 14858 286Total 54 17183
S = 16.90 R-Sq = 13.53% R-Sq(adj) = 10.20%
Individual 95% CIs For Mean Based on Pooled StDevLevel N Mean StDev ---------+---------+---------+---------+1 5 235.94 13.00 (------------*-----------)2 25 212.32 16.77 (-----*-----)3 25 216.02 17.60 (-----*-----) ---------+---------+---------+---------+ 216 228 240 252Pooled StDev = 16.90
Tukey 95% Simultaneous Confidence IntervalsAll Pairwise Comparisons among Levels of Area
Individual confidence level = 98.05%
Area = 1(Melbourne) subtracted from:
Area Lower Center Upper ---------+---------+---------+---------+2 -43.58 -23.62 -3.65 (------------*-------------)3 -39.89 -19.92 0.05 (-------------*------------) ---------+---------+---------+---------+ -30 -15 0 15
Area = 2(Trains) subtracted from:
Area Lower Center Upper ---------+---------+---------+---------+3 -7.83 3.70 15.22 (------*-------) ---------+---------+---------+---------+ -30 -15 0 15
Average value of private sector house (Convergence)
19
MATH 1332 Minor Thesis
Regression Analysis: Average growth rate (2006- 2010) versus Average value of private house in 2006
The regression equation isAverage growth rate 2006-2010 = 25.5 - 0.0740 Average value of private sector
Predictor Coef SE Coef T PConstant 25.53 17.36 1.47 0.175Average value of private sector -0.07403 0.08631 -0.86 0.413
S = 3.67413 R-Sq = 7.6% R-Sq(adj) = 0.0%
220210200190180
16
14
12
10
8
6
4
2
Average value of private sector house in 2006 ($ '000)
Avera
ge g
row
th r
ate
2006-2
010 (
%) Gippsland (Traralgon corridor)
East Gippsland
Ovens-Murray
Goulburn (Seymour corridor)
Loddon (Bendigo corridor)
Mallee
Wimmera
Central Highlands (Ballarat corridor)
Western Dist.
Barwon (Geelong corridor)
Melbourne
Convergance of private house value across statistical districts
No. of building approvals
20
MATH 1332 Minor Thesis
Building appovals - Total dwelling units per thousand people
Melbourne
Train Lines
No Train lines
5.0
6.0
7.0
8.0
9.0
10.0
11.0
12.0
2006 2007 2008 2009 2010
No.
Melbourne Train Lines No Train lines
No. of building approvals
21
MATH 1332 Minor Thesis
One-way ANOVA: No of building approvals versus Area
Source DF SS MS F PArea 2 84.81 42.40 13.55 0.000Error 52 162.78 3.13Total 54 247.58
S = 1.769 R-Sq = 34.25% R-Sq(adj) = 31.72%
Individual 95% CIs For Mean Based on Pooled StDevLevel N Mean StDev -----+---------+---------+---------+----1 5 8.125 1.422 (-------------*------------)2 25 8.715 1.800 (-----*-----)3 25 6.144 1.790 (-----*-----) -----+---------+---------+---------+---- 6.0 7.2 8.4 9.6Pooled StDev = 1.769
Tukey 95% Simultaneous Confidence IntervalsAll Pairwise Comparisons among Levels of Area
Individual confidence level = 98.05%
Area = 1(Melbourne) subtracted from:Area Lower Center Upper +---------+---------+---------+---------2 -1.501 0.589 2.679 (----------*---------)3 -4.071 -1.981 0.109 (---------*----------) +---------+---------+---------+--------- -4.0 -2.0 0.0 2.0
Area = 2(Trains) subtracted from:Area Lower Center Upper +---------+---------+---------+---------3 -3.777 -2.571 -1.364 (-----*-----) +---------+---------+---------+--------- -4.0 -2.0 0.0 2.0
No. of building approvals (Convergence)
22
MATH 1332 Minor Thesis
Regression Analysis: Av growth rate (2006-2010) versus No of building approvals in 2006/1000 residents
The regression equation is:Av growth rate (2006 - 2010) = 0.4 + 2.86 No of building approvals in 2006
Predictor Coef SE Coef T PConstant 0.43 30.75 0.01 0.989No of building approvals in 2006 2.863 3.996 0.72 0.492
S = 20.9572 R-Sq = 5.4% R-Sq(adj) = 0.0%
1110987654
60
50
40
30
20
10
0
-10
No of building approvals in 2006 / 1000 residents
Avera
ge g
row
th r
ate
(2006 -
2010)
(%)
Gippsland (Traralgon corridor)
East Gippsland
Ovens-Murray
Goulburn (Seymour corridor)
Loddon (Bendigo corridor)
MalleeWimmera
Central Highlands (Ballarat corridor)
Western Dist.
Barwon (Geelong corridor)
Melbourne
Convergance of building approvals for all dwelling units (2006 - 2010)
Unemployment
23
MATH 1332 Minor Thesis
Unemployment rate (2006 - 2010)
Melbourne
Train Lines
No Train l ines
4.0
5.0
6.0
7.0
2006 2007 2008 2009 2010
%
Melbourne Train Lines No Train l ines
General Linear Model: Unemployment Rates (%) versus Area, Year Factor Type Levels ValuesArea fixed 3 1, 2, 3Year fixed 5 1, 2, 3, 4, 5
Analysis of Variance for Unemployment Rates (%), using Adjusted SS for Tests
Source DF Seq SS Adj SS Adj MS F PArea 2 4.211 4.211 2.106 1.88 0.166Year 4 12.864 5.793 1.448 1.29 0.289Area*Year 8 0.856 0.856 0.107 0.10 0.999Error 40 44.756 44.756 1.119Total 54 62.687
S = 1.05778 R-Sq = 28.60% R-Sq(adj) = 3.62%
SUMMARY
24
MATH 1332 Minor Thesis
CONCLUSION
Presented analysis results strongly suggest the following:
• Population living in regions of Victoria with established train services is, on average, presented with better opportunity to obtain employment, reach a higher wage and salary income and consequently buy or build a house.
• Further development of more comprehensive rail network in regional
Victoria might be used as a means of achieving economic convergence and provide an environment for more uniform economic development across state.
25
MATH 1332 Minor Thesis