Before a Board of Inquiry MacKays to Expressway Proposal

under: the Resource Management Act 1991

in the matter of: Notice of requirement for designation and resource consent applications by the NZ Transport Agency for the MacKays to Peka Peka Expressway Proposal

applicant: NZ Transport Agency Requiring Authority

Statement of evidence of Fraser Colegave (Economics) for the Holdings Limited

Dated: 5 October 2012

1

STATEMENT OF EVIDENCE OF FRASER JAMES COLEGRAVE FOR HOLDINGS LIMITED

QUALIFICATIONS AND EXPERIENCE

1 My full name is Fraser James Colegrave.

2 I hold a First-Class Honours Degree in Economics from the Univeristy of . I am a member of the Association of Economists and a member of the New Zealand Resource Management Law Association.

3 I have over 20 years commerical experience, the last 12 of which I have worked as an economics consultant. I am a founding partner of Covec Limited, an applied economics consultancy based in Auckland.

4 During my time at Covec, I have successfully led and completed over 150 consulting projects. My main field of expertise is land-use economics. I have worked extensively in this area for many of the largest property developers in New Zealand, including Argosy, the Neil Group, Foodstuffs, and Todd Property. I regularly provide expert evidence for council hearings, Environment Court hearings and also hearings before the High Court.

CODE OF CONDUCT

5 I have read the Code of Conduct for Expert Witnesses as contained in the Environment Court Consolidated Practice Note (2011), and I agree to comply with it as if this Inquiry were before the Environment Court. My qualifications as an expert are set out above. I confirm that the issues addressed in this brief of evidence are within my area of expertise. I have not omitted to consider material facts known to me that might alter or detract from the opinions expressed.

SCOPE AND STRUCTURE OF EVIDENCE

6 My evidence focuses on the business floorspace projections used to determine future traffic volumes, and is structured as follows:

6.1 First, I briefly review the projections to set the scene.

6.2 Second, I examine the economic rationale underlying them.

6.3 Third, I review the rate of historic non-residential growth.

6.4 Fourth, I derive my own projections of floorspace growth.

KCAHL M2PP Economic Evidence 05102012 2

6.5 Fifth, I reconcile my projections with those used in the traffic modelling.

6.6 Finally, I offer some concluding remarks.

EXECUTIVE SUMMARY

7 My evidence reviews the various floorspace scenarios used to test the sensitivity of the traffic models (as described in Technical Report 34). It finds that the composite growth scenario, which forms the basis of the traffic assessment, has been derived unilaterally and without any robust supporting analysis, economic or otherwise.

8 In addition, my evidence finds that, notwithstanding the project’s stated focus on enabling economic development, the 780 page assessment of environmental effects (AEE) contains only 5 pages on economic effects. Further, of the 36 technical reports commissioned to inform the AEE, including 11 on social effects, there are none on economics.

9 Given my findings, and to ensure that the project is informed by more detailed analysis, I generate my own projections of non- residential floorspace growth in the to contrast and compare with those used in the AEE. First, however, I review historic district growth to provide context.

10 The review of past floorspace growth reveals a trend of systematic underperformance, caused in part by significant employment leakage. However, it also identifies a marked upswing in the rate of development (per head of additional population) over the last five or six years.

11 To project future non-residential floorspace growth, I review the various methods available, and choose one that is based on the expected rate of population growth. I identify the expected increase in floorspace per capita of population growth, and apply that to Statistics New Zealand’s official population projections. This method projects non-residential floorspace growth of 124,800m2 to 2031 under the low scenario, and 544,000m2 under the high.

12 In my view, the low scenario is unrealistic because it is based on very low population growth. In fact, the low scenario assumes population growth over the next 20 years that is 75% lower than actual growth over the last 20 years. It is also much lower than the population growth used in the traffic modelling, so I disregard it in the remainder of my analysis. This leaves the medium and high scenarios, which give a range of 329,000m2 to 544,000m2.

13 While the high scenario growth estimate may seem optimistic, it is important to realise that the M2PP project, and other associated

KCAHL M2PP Economic Evidence 05102012 3

works, are intentionally designed to foster economic growth. At the same time, the district is poised to grow significantly on the back of several large, planned and approved developments. In concert with the M2PP project, these planned developments could propel the district on to a higher growth trajectory than it would have otherwise achieved.

14 Indeed, the economic literature often speaks of a virtuous cycle, in which transport projects improve economic growth, with the resulting economic growth providing more fertile conditions for further transport investment. Through this virtuous cycle, transport projects can work in tandem with other catalysts for economic growth to produce transformational changes to local and regional economies. This will be especially true if the current significant employment leakage can be reversed, at least partially.

15 Recognising the potential synergies between M2PP and planned development, I adopt the midpoint of my medium and high scenarios as my most likely estimate. This amounts to 436,800m2 of non-residential floorspace growth by 2031.

16 Reconciling this figure with the growth scenarios used in the traffic modelling in Technical Report 34, I find that the full growth scenario is far more likely than the composite growth scenario. For instance, the full growth scenario assumes airport growth of 331,648m2 by 2031, and town centre growth of 239,400m2. However, only 111,535m2 of the town centre growth is non-residential. When added to airport growth, the full scenario effectively assumes non- residential floorspace growth of 443,183m2 by 2031, which is only 1.5% higher than my projection.

17 I therefore submit that the full growth scenario provides a more reliable basis for assessment of traffic demand on the local system than the composite growth scenario.

REVIEW OF FLOORSPACE SCENARIOS

18 Three scenarios were used to test the sensitivity of the traffic model to the assumed rate of business floorspace growth. These are shown in Figure B4 on page 142 of Technical Report 34, and are reproduced below.

KCAHL M2PP Economic Evidence 05102012 4

Table 1: GFA Assumptions Underlying Growth Scenarios (m2)

Scenario 2016 2026 2031 Full Growth Airport 87,555 278,584 331,648 PPTC 75,240 239,400 285,000 Total 162,795 517,984 616,648

Composite Growth Airport 43,778 139,292 165,824 PPTC 37,620 119,700 142,500 Total 81,398 258,992 308,324

WTSM Scenario Airport 35,885 85,741 105,162 PPTC 28,797 70,972 88,312 Total 64,682 156,713 193,474

19 The scenarios provide point estimates of additional floorspace growth in 2016, 2026 and 2031 for both the town centre (PPTC) and the airport. Growth in other locations does not appear to have been explicitly considered, or has been grouped in with the town centre (either inadvertently or without explanation).

20 Looking at the righthand column of Table 1, it is clear that the scenarios reflect wildly-varying beliefs about district growth potential. Recognising that the M2PP project is a once-in-a-lifetime opportunity, and that resolving any capacity shortfalls caused by poor planning will be difficult if not prohibitively expensive, it is critical that the projections used to inform the traffic modelling are robust and reliable from the outset.

21 To ensure that this was the case, I carefully reviewed the technical report in which these data appeared to examine their rationale. The results of my investigation are described in the following section.

ECONOMIC RATIONALE FOR SCENARIOS

22 I return to Technical Report 34 to examine the basis on which the various scenarios have been set. I start with the full growth scenario.

23 Reconciling the 2031 full growth figure for the airport (331,648m2 of GFA) with the development thresholds shown for the airport zone in the district plan, it seems apparent that the full growth scenario is intended to reflect the potential built form of the zone. For instance, section D.9.1.5 of the district plan states that development above 339,400m2 is a non-complying activity for the airport zone.

24 Notwithstanding small discrepancies between these two sets of numbers, I consider it highly likely that the full growth scenario is

KCAHL M2PP Economic Evidence 05102012 5

intend to reflect the development potential as demonstrated in the airport’s own masterplan, and as also signalled in the district plan. I therefore do not consider this any further and turn my attention to the full growth scenario for the Paraparaumu town centre (PPTC).

25 Reconciling the full growth scenario for PPTC was not easy. There were several issues. First, according to table 8.1 on page 93 of Technical Report 34, PPTC is expected to cater for new development equal to 189,405m2 of GFA by 2026, yet the numbers in Figure B4 (i.e. my Table 1) show 239,400m2 of GFA by that date. The origins of the additional 50,000m2 shown in Figure B4 are unclear.

26 Also unclear is whether the PPTC figures in Figure B4 are intended to include just non-residential development, or to also include residential development. If I assume, as I expect is the case, that the data are also supposed to include residential development, then I am unsure why only three growth nodes are shown in the table. Indeed, according to residential building consent data for the district, as shown below, residential growth has not been confined to the town centre in the past, and almost certainly will be more dispersed in the future. Thus, if the data in figure B4 are intended to cover residential development as well, development beyond the three growth nodes should also be accounted for.

Table 2: New Dwelling Consents by Census Area Unit (1996 to 2012)

Census Area Unit Number 563701 Beach 521 563703 Waikanae East 206 563704 Peka Peka 93 563705 Waikanae Park 124 563706 Waikanae West 277 563920 Kaitawa 118 564022 Otaki Forks 188 564023 120 564400 Otaki 391 565901 North 253 565902 214 565903 Paraparaumu Beach South 701 566000 Paraparaumu Central 1,775 566101 427 566102 251 566200 Paekakariki 48 566302 182 Total 5,889

27 If I continue to assume that figure B4 is intended to include residential and non-residential growth, then the next complication is reconciling the level of residential development shown here with the

KCAHL M2PP Economic Evidence 05102012 6

expected rate of household growth shown in table 4.1 on page 17 (of technical report 34).

28 For example, table 4.1 shows household growth of 4,825 from 2010 to 2026, while table 8.1 shows residential development of 2,489 dwelling units, plus 77,870m2 of medium and higher density residential development (in PPTC). Subtracting the dwelling units (2,489) from predicted household growth (4,825) leaves 2,336 households to be accommodated within PPTC. For this to work, the average dwelling size in PPTC would need to be 77,870m2/2,336 = 33m2. I consider this highly unlikely.

29 While the apparent discrepancies above are of real concern, it is important to recognise that the full growth scenario did not form the basis of the traffic modelling underlying the AEE. Rather, having received information from Kapiti Coast District Council (KCDC) that several large, planned developments were proposed between 2010 and 2026 – none of which were represented in the WTSM – the report authors “considered that a more likely scenario would be that only a certain proportion of each planned development would be operational by 2026.”1

30 This decision is interesting for at least two reasons. First, the large/planned developments identified by KCDC generated traffic growth of 60% which, according to the technical report, was only slightly higher than trend growth of 50%.2 However, because WTSM predicted growth of only 18% over the same period (i.e. more than 2.5 times lower than trend growth), the authors deemed the full development scenario unlikely.

31 With all due respect, the difference between trend growth (50%) and full development growth (60%) seems quite minor, so it is not clear why the full development scenario was not given more credit.

32 Second, this executive decision by the authors – to effectively ignore the full growth scenario outlined by KCDC – is interesting because it creates an onus to derive an alternative scenario that is not only robust and reliable, but which also harnesses the unique opportunity presented by the M2PP project. Striking such a fine balance would surely rely on a significant amount of data and analysis, so I set out to understand exactly how their alternative scenario (i.e. the composite growth scenario) had been derived.

33 I did not need to look far, as a description was provided in appendix 34.G of technical report 34. In short, future traffic was determined

1 Page 18 of technical report 34. 2 Page 27 of technical report 34.

KCAHL M2PP Economic Evidence 05102012 7

based on whether each planned development was inside or outside the WTSM zone. If it was inside the WTSM, as they all were, then the full WTSM growth was taken with only as much development as required to reach 50% of the development total. Put more simply, the composite approach is equal to 50% of the full growth scenario for each planned development.

34 Arbitrarily cutting each planned development in half obviously has important implications for the traffic modelling, but it also has far more important real-world implications (in my opinion). If this scenario leads to the actual network being of a lower capacity than required for key planned development to reach their full potential, then it will stunt economic growth. To make such an important decision, I would expect to find a comprehensive economic analysis in support and/or cause congestion in the transport network. I therefore set out to understand the economic rationale upon which the 50% reduction for each planned development was based.

35 Working through the rest of appendix 34.G, I was not able to find any further rationale for the design of the composite scenario, so I returned to the larger document of which this technical appendix formed part – the AEE.

36 To my surprise, the AEE itself contained very little economic analysis at all and, as far as I could tell, did not contain any economic analysis to support the composite growth scenario. In fact, of the entire 780 page AEE, only 5 pages were dedicated to economic effects. And the discussion in those 5 pages was fairly broad, and contained very little analysis.

37 To dig a little deeper, I then turned to the various technical reports commissioned by NZTA. However, of the 36 technical reports, including 11 on social effects, there was none on economics. Given the significance of this project, I am at odds to understand this.

38 To summarise, my review of the economic rationale supporting the various growth scenarios revealed a distinct lack of economic analysis. Not only did the composite growth scenario appear arbitrary and lack robust analysis, but the AEE itself was almost completely devoid of economic input. I therefore do not have confidence in the composite scenario on which the AEE was based, and instead derive my own projection to provide an alternative view. First, however, I review the historic growth context.

KCAHL M2PP Economic Evidence 05102012 8

HISTORIC RATE OF NON-RESIDENTIAL GROWTH IN KAPITI

39 I now briefly review historic non-residential floorspace growth before outlining my own projections in the next section.

40 To analyse historic floorspace growth, I retrieved detailed building consent data from Statistics New Zealand’s infoshare service.3 The data show the annual gross floor area (GFA) of new building consents issued by territorial authority (TA) since 1991 by the following nine building types:

40.1 Hostels, boarding houses

40.2 Hotels & other short-term accommodation

40.3 Hospitals, nursing homes

40.4 Education buildings

40.5 Social, cultural, religious buildings

40.6 Shops, restaurants, taverns

40.7 Offices, administration buildings

40.8 Storage buildings

40.9 Factories and industrial buildings

41 To account for differing rates of population growth – a key driver of both residential and non-residential floorspace growth – I divided each TA’s GFA growth since 1991 by its population growth over the same period to form a ratio. The results are shown below.4

3 http://www.stats.govt.nz/infoshare/ 4 Some TAs had very small population growth, or experienced a population decline. They have been excluded, as they skew the results when the results are expressed as a ratio of population change.

KCAHL M2PP Economic Evidence 05102012 9

Figure 1: Ratio of GFA Growth to Population Growth since 1991 by TA

Taupo Matamata-Piako New Plymouth Carterton Dunedin Hastings Central Otago Nelson Lower Hutt Whakatane Palmerston North Manawatu Napier Far North Ashburton Marlborough Kaipara Central Hawke's Bay Hurunui Queenstown-Lakes Upper Hutt Christchurch New Zealand Auckland Hamilton Waipa Tasman Papakura Whangarei Tauranga Waikato Manukau North Shore Western Bay of Plenty Selwyn Franklin Kapiti Coast Rodney Waitakere Waimakariri 0 10 20 30 40 50 60 70 80 90 100 Additional Non Residential GFA per Capita of Additional Population (1991 to 2011)

42 Figure 1 shows that the ratio of non-residential floorspace growth to population growth varies markedly across TAs. The national average is around 39, which means that each additional head of population has resulted in around an additional 39m2 of non-residential floorspace. The corresponding figure for Kapiti is 15m2, which is 2.6 times lower than the national average. This makes it the fourth lowest in New Zealand.

43 To gain a better understanding of Kapiti’s situation, I disaggregated the above data by building type and then compared the resulting figures to the national average. The chart below presents my findings.

KCAHL M2PP Economic Evidence 05102012 10

Figure 2: Ratio of GFA Growth to Population Growth since 1991 by Building Type

Storage buildings

Factories & industrial

Shops, restaurants, taverns

Offices & administration

Social, cultural, religious

Education buildings

Hotels & Motels etc

Hospitals, nursing homes National Average

Hostels, boarding houses Kapiti Coast District

0 1 2 3 4 5 6 7 8 9 10 Additional Non Residential GFA per Capita of Additional Population (1991 to 2011)

44 Figure 2 reveals a significant deficit in the rate of district floorspace growth for certain building types relative to the national average. The figures for storage buildings, factories and industrial, and offices and administration provide the starkest contrasts. In some cases, the district’s rate of floorspace growth (per capita of additional population) has been four times lower than the national average.

45 To ensure that the data above portrays a reliable view of the district’s past growth, and hence its current economic position, I used another technique called location quotients. These analyse the district’s employment structure to identify sectors where it is a significantly higher or lower proportion than the national average.

46 To be more specific, the location quotient for each sector is calculated by dividing its share of district employment by the corresponding share of national employment. For instance, if a certain sector represents 5% of district employment but 10% of national employment, the location quotient for the district is 5%/10% = 50%.

47 A location quotient of one represents sectors whose employment share matches the national average, and thus in which the district is likely to be self-sufficient. Values less than one represent sectors where the employment share is lower than the national average, where there may be scope to improve self-sufficiency, while values greater than one represent sectors where growth potential may be more limited.

KCAHL M2PP Economic Evidence 05102012 11

48 Consider now the district’s location quotients. These are shown below by 1-digit ANZSIC for 2011.

Figure 3: Kapiti Coast District Location Quotients in 2011 (by 1-Digit ANZSIC)

E Construction G Retail Trade H Accommodation and Food Services Q Health Care and Social Assistance P Education and Training L Rental, Hiring and Real Estate Services S Other Services D Electricity, Gas, Water and Waste Services R Arts and Recreation Services I Transport, Postal and Warehousing C Manufacturing M Professional, Scientific and Technical Services O Public Administration and Safety Opportunities to be J Information Media and Telecommunications more self-sufficient K Financial and Insurance Services A Agriculture, Forestry and Fishing N Administrative and Support Services B Mining F Wholesale Trade

- 0.20 0.40 0.60 0.80 1.00 1.20 1.40 1.60 1.80 2.00 Kapiti District Location Quotients in 2011

49 Figure 3 reveals that the district is more than self-sufficient in a few industries. For instance, the location quotient for construction is 1.72, which means that the district’s construction employment share is 72% higher than the national average. The next highest is retail trade with a location quotient of 1.71. This correlates quite well with the floorspace growth numbers above. For instance, the district’s rate of floorspace growth was closest to the national average for shops, restaurants and taverns, and this happens to be the sector in which the district’s location quotient is the second highest.

50 Moving down the chart, there are a number of green bars where the location quotient is less than one. These represent sectors providing the greatest opportunities to improve self-sufficiency. Again, they correlate quite well to the floorspace data above. For instance, the district’s rate of floorspace growth was very low for storage buildings, factories and industrial, and offices and administration. These are the building types that would house many of the sectors in which the district’s location quotients are the lowest (such as wholesale trade, admin and support services, financial and insurance services, information/media, professional services, manufacturing, and so on).

51 The data above suggest that the district’s past economic growth has not been spectacular, and that there is likely to be significant scope to improve it, at least in certain sectors. One of the most vital steps

KCAHL M2PP Economic Evidence 05102012 12

to securing a brighter economic future for the Kapiti Coast district will be to stem the current outflow of employment. For instance, the recent report on employment areas by Property Economics (PE)for Kapiti Coast District Council (KCDC) revealed that the district had an employment retention rate of 70%, which means that 30% of all workers in the district work elsewhere. This was the sixth worst in the country.

52 To test the impacts of this, I added the commuting data from the Property Economics report to our floorspace dataset above. Then, I used a type of statistical analysis called linear regression to examine the impacts of employment retention on floorspace growth (while also taking account of population growth).

53 The results were highly statistically significant. In fact, they showed that, holding all other factors constant, each employee retained by a district increased its floorspace growth by 15m2 over the last 20 years. Given that Kapiti district is currently leaking around 6,100 workers (according to the PE report), this means that the district’s past floorspace growth could have been nearly 100,000m2 more without leakage. Perhaps even more importantly, it means that reducing the leakage in future will enable the district to support much higher floorspace growth than conventional projections suggest. I return to this point shortly.

54 In summary, district non-residential growth has been low by national standards, particularly in floorspace terms. The high rate of employment leakage is partly to blame.

PROJECTED NON-RESIDENTIAL FLOORSPACE GROWTH

55 I now perform a projection of district non-residential floorspace against which the reasonableness (or otherwise) of the projections used for traffic modelling are later assessed.

56 There are a few ways to forecast floorspace growth. The first is to convert population growth to employment growth, and to then convert this to floorspace growth. Despite some intuitive appeal, however, this can be inaccurate. It relies on a series of nested assumptions that expose the analysis to the risk of compounding errors, and it is less direct than it needs to be.

57 At the other end of the spectrum, floorspace growth can be forecast simply by extrapolating past trends. While fairly straightforward, this can also be unreliable because it implicitly assumes that all underlying factors will continue to behave the same as they have in the past. This is seldom the case.

58 Falling somewhere in the middle is my preferred method. This projects non-residential floorspace growth on the basis of population

KCAHL M2PP Economic Evidence 05102012 13

growth without first converting to employment. Not only is this more direct than the first method, and hence reduces the scope for compounding errors, but it also helps capture supply and demand dynamics that shape non-residential growth.

59 That is to say, on the one hand local population provides an important source of final demand for goods and services, from which the demand for floorspace is partly derived. On the other hand, population is a proxy for employment, and thus also helps capture supply-side effects.

60 Whichever method is chosen, the results must be put in context of forthcoming changes to the local environment, as these will generally not be captured by the raw projections themselves. There are several factors that might need to be accounted for, and failure to do so may result in poor planning decisions. I return to this point shortly.

61 To generate initial floorspace projections using my preferred method, I need estimates of (i) population growth, and (ii) growth in floorspace per head of additional population. I start with population growth.

62 To determine likely population growth, I have used Statistics New Zealand’s official population projections.5 These are tabulated below and include low, medium and high scenarios.

Table 3: Kapiti Coast District Official Population Projections (from Statistics NZ)

Series 2011 2016 2021 2026 2031 Growth Low 49,400 50,800 51,800 52,700 53,300 3,900 Medium 50,600 53,400 56,000 58,500 60,900 10,300 High 51,800 56,000 60,300 64,600 68,800 17,000

63 To determine the amount of floorspace that is likely to be developed per head of population, I have relied on the information presented in Figure 1. However, since these data provide only point estimates for 20 years of underlying growth, it is important to first analyse these in more detail to ensure that any underlying changes are not overlooked.

64 To that end, the following graph shows cumulative growth in non- residential floorspace since as a function of cumulative population growth for the district since 1991. Also shown in red is the

5 http://www.stats.govt.nz/tools_and_services/tools/TableBuilder/population- projections-tables.aspx

KCAHL M2PP Economic Evidence 05102012 14

corresponding national trend over the same period, which has been calibrated to district population growth to provide a direct comparison.

Figure 4: Cumulative Floorspace Growth vs Cumulative Population Growth since 1991 700,000 National Average GFA growth = 39 x Pop growth 600,000 R² = 0.99

500,000

400,000

300,000

200,000

Kapiti Coast District Cumulative Non Residential GFA Growth (since 1991)Growth GFA Non Residential Cumulative 100,000 GFA Growth = 13 x Pop Growth R² = 0.94

- - 2,000 4,000 6,000 8,000 10,000 12,000 14,000 16,000 Cumulative Population Growth (since 1991)

65 The straight lines that run through each set of data represent linear trendlines, and capture the overall pattern of growth since 1991. Both fit their respective datasets well, as shown by the R2 figure. This measures the so-called “goodness of fit”, with an R2 of 1 indicating a perfect linear correlation.

66 Also of note is the recent upswing in the district figures. This has dragged the trendline up so that all the data points to 2005 fall below the line, and all the rest sit above it.

67 The fact that the data are positioned this way around the trendline is likely to mean that there has been a structural shift in the underlying rate of growth. In other words, the rate of growth over the last five or so years is likely to be significantly different from that which had prevailed in the past. As a result, generating floorspace projections from the 20-year trendline above is likely to understate growth.

68 To accommodate the recent increase in floorspace growth (per head of additional population) and thus ensure a more accurate projection, I have fitted a piecewise function to the district data. This essentially splits the Kapiti figures into two sets, and then fits separate trendlines to each. This way, the new trend that has emerged over the last five years is isolated and can be used as a

KCAHL M2PP Economic Evidence 05102012 15

basis for projection. The figure below shows the piecewise function and associated trendlines.

Figure 5: Piecewise function Linking Floorspace Growth with Population Growth since 1991

700,000 National Average GFA growth = 39 x Pop growth R² = 0.99 600,000

500,000

400,000

300,000 Kapiti Coast (since 2006) GFA Growth = 32 x Pop Growth R² = 0.96 200,000 Kapiti Coast (to 2005) GFA Growth = 11x Pop Growth R² = 0.99

Cumulative Non Residential GFA Growth (since 1991)Growth GFA Non Residential Cumulative 100,000

- - 2,000 4,000 6,000 8,000 10,000 12,000 14,000 16,000 Cumulative Population Growth (since 1991)

69 This piecewise function has improved the goodness of fit for both portions of the dataset, as illustrated by the improvement in R2. Whereas before the R2 was 0.94, it is now 0.99 and 0.96 respectively. In addition, the data are now falling below and above each line with more regularity, which means that the trend is more illustrative of the overall pattern. I therefore deem this a more suitable basis for projecting floorspace growth.

70 The next step is to combine the population projections with the trend from 2006 (i.e that there is an additional 32m2 per ahead of additional population) to yield raw estimates of floorspace growth. To that end, the following table shows the cumulative floorspace growth projections associated with each population scenario.

Table 4: Projected Non-Residential Floorspace Growth (m2)

Series 2016 2021 2026 2031 Low 44,800 76,800 105,600 124,800 Medium 89,600 172,800 252,800 329,600 High 134,400 272,000 409,600 544,000

71 Table 4 shows that district non-residential floorspace could grow by 124,800m2 under the low scenario to 544,000m2 under the high. This is quite a large range. However, in my view, the low projection is unrealistic, because it assumes very low population growth. In fact, the low projection assumes population growth over the next 20

KCAHL M2PP Economic Evidence 05102012 16

years that is 75% lower than actual population growth over the previous 20 years.

72 Given the significant improvements that M2PP will make to the local and regional road network, making the district more attractive to live, the low scenario seems implausible. I therefore ignore it in the remainder of my analysis.6

73 By contrast, the medium and high figures seem to provide an accurate reflection of future growth potential. While the high figure may seem a stretch to some, I consider it credible given the following other factors that will likely lead to even faster growth in future.

74 First, not only will the various state highway projects make the district a more attractive place to live, and hence indirectly create demand for new floorspace, but they will also make the district a more attractive place to invest. This is explicitly recognised in most regional and national transport strategies, with one of NZTA’s overarching objectives for state highway projects being “to support economic growth and productivity throughout New Zealand.”7

75 Similar statements are peppered throughout the assessment of environmental effects (AEE) for the project, which clearly highlights the project’s focus on enabling economic growth. Consider the following highlights:

75.1 Page 35 of the AEE identifies ‘project benefits’. The first sentence states that “completing this project will assist regional and national economic growth, as well as delivering a range of other benefits.” This suggests that economic growth is one of the most significant benefits of the project, if not the most significant.

75.2 Page 36 of the AEE identifies ‘project objectives’, the first of which is “to enhance inter-regional and national economic growth and productivity.” Again, this places significant emphasis on the effects that the project will have on economic growth, including floorspace growth.

76 The economic literature agrees that carefully-selected and well- designed transport projects can have significant impacts on economic development. Many speak of a virtuous cycle, in which transport projects improve economic growth, with the resulting

6 I note that I am not alone in making this judgment call, either. For instance, the report on employment areas by Property Economics for KCDC also assumed population growth of 10,000 people over the next 20 years. This is almost identical to the medium scenario above, and more than 2.5 times greater than the low scenario.

7 http://www.nzta.govt.nz/network/projects/results.html

KCAHL M2PP Economic Evidence 05102012 17

economic growth providing more fertile conditions for further transport investment. Through this virtuous cycle, transport projects can work in tandem with other catalysts for economic growth to produce transformational changes to local and regional economies.

77 The other major factor that is likely to lead to higher than usual growth is the presence of a new strategic growth node, the airport, whose owners are willing and ready to bring land to market in a timely and efficient manner. While initial uptake has been a little slower than desired, partly due to the GFC and also because time was taken to find a suitable equity partner, the future prospects look good indeed.

78 The reason is that are no longer considered places just where people and goods are transported. They are also gaining increasing recognition as strategic locations for a range of economic activities. This has led to the emergence of two new urban planning terms: ‘airport city’ and ‘aerotropolis’.

79 The term airport city relates to business development within the immediate confines of an airport, while aerotropolis extends this to include peripheral development. The following diagram illustrates them both.

Figure 6: Schematic Overview of Airport City and Aerotropolis (from Karsarda)

KCAHL M2PP Economic Evidence 05102012 18

80 While this diagram depicts development on a scale that is unlikely to ever occur at Kapiti Coast Airport, the sentiment holds weight. A wide range of economic activities will eagerly locate around the airport given an opportunity to do so.

81 Some readers may question the relevance of an aerotropolis to Paraparaumu or even New Zealand, and assume that it applies only to much larger international cities. However, this is not the case. For instance, recent master plans for embrace this concept, and associated press releases frequently cite the term aerotropolis. The truth is that an aerotropolis can flourish around almost any airport, and there are significant gains from doing so.

82 According to Dr John Kasarda – pioneer of the term aerotropolis - one of the key challenges is the need for careful master planning from the outset. In mature cities, where infrastructure networks and zonings are already established, this can be tricky. However, for Kapiti, the opportunity still exists to design the local and regional roading network to optimise its potential.

83 Finally, as noted earlier, the district’s current rate of employment leakage is likely to have significantly reduced its floorspace growth in the past. To the extent that the airport development, and other initiatives, can help stem or reduce this, there will be additional opportunities for growth over and above those ordinarily afforded by population growth.

84 Put simply, if potential synergies between the M2PP project and associated large-scale developments are realised, the district has a very strong chance of achieving economic growth at a level not previously witnessed in the district. I therefore consider the most likely estimate of future floorspace growth to be the midpoint of my medium and high estimates, which results in projected growth to 2031 of 436,800m2.

85 Reconciling this figure with the growth scenarios used in the traffic modelling, I find that the full growth scenario is far more likely than the composite growth scenario. For instance, the full growth scenario assumes airport growth of 331,648m2 by 2031, and town centre growth of 239,400m2. However, only 111,535m2 of the town centre growth is non-residential. When added to airport growth, the full scenario effectively assumes non-residential floorspace growth of 443,183m2 by 2031, which is only 1.5% higher than my projection.

86 I therefore submit that the full growth scenario provides a more reliable basis for assessment than the composite growth scenario

CONCLUSIONS

87 This evidence has reviewed the floorspace growth scenarios used for sensitivity testing, and has revealed a number of issues. It has also

KCAHL M2PP Economic Evidence 05102012 19

derived its own projections from first principles, and then put the results in context of key emerging trends and developments. It finds that the full growth scenario is likely to be far more reflective of future growth than the composite scenario, and that decisions based on the latter are likely to forego important economic development opportunities afforded by the M2PP project.

______Fraser Colegrave October 2012

KCAHL M2PP Economic Evidence 05102012