081a ak cncl - general - capacity and feasibility modelling - hearing presentation

8/20/2019 081a Ak Cncl - General - Capacity and Feasibility Modelling - Hearing Presentation

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Presentation to IHP

Update of Capacity Modelling

Kyle Balderston & Doug Fairgray

for Auckland Council for Topic 081

4 March 2016


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Overview• Prepared in response to IHP Memo (5 November 2015)

•

Key elements sought in Memo: – a revised method to estimate supply that is capable of accommodating the

changes to density rules as proposed by the Council and its forthcoming proposed changes to the spatial application of residential zones.

– An estimate of demand for residential capacity (expressed as dwellingnumbers) throughout the Auckland region, for the period to 2026 and to 2041.

An estimate of overall supply of residential capacity (in tabular form) and a

breakdown of that supply in terms of each type of zone (e.g. Centres, THAB,MHU, Mixed Use, etc.).

– Presentation of supply in the form of “heat maps” or similar (e.g. as at 2026and 2041) to enable easy visualisation of the spatial spread of supply.

– if possible in the time allowed, the estimates of supply be compiled as forecasts, in order for the Panel to be in position to compare supply forecastswith the demand forecasts.”

• Panel advised it seeks “to use the outputs from this work to assess theextent to which the proposed Plan would be adequate to meet forecastdemand for residential capacity for the period to 2026, and to 2041.”


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Contents

1. ACDC Model (purpose, rationale, outputs)2. Estimates of supply (model outputs,

adjustments, supply from other sources)

3. Estimates of Demand (household growth, pluscatch-up of shortfall)

4. Nature of Demand (household types, incomes,

demand by dwelling price)5. Findings to date


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Kyle Balderston

ACDC Model


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ACDC Model

Purpose:“ a revised method to estimate supply that is capable ofaccommodating the changes to density rules as proposed by the Council and its forthcoming proposedchanges to the spatial application of residential zones”

a ‘filter’ on ‘plan enabled’ capacity that indicates, undercurrent conditions, which of those regulatory enabledopportunities might be commercially viable.

Results indicate a higher probability of development(than sites that are not feasible) and show the locationand nature of opportunities ‘unlocked’ by the plan


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Development

that is enabled

Development

that occurs

Not all of what is enabled, happens, but most of what happens, is enabled.

‘Planning’ cant make things happen but is generally a prerequisite, due to the time -cost of

consenting and plan alignment with infrastructure provision.

A small portion of what happens is not enabled.


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All Sites

Tested

Sites withPlan

enabled

Capacity

(CfGS)

Sites that

‘actually’ get

developed in

timeframe

that feasibility

applies to

Sites withCommercially

Feasible &

Plan enabled

Capacity

(ACDC)

Sites with

commerciallyrealisable potential

that is

not plan enabled or

not in model

Probabilistic Filtering


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But what about time?

• ‘Time’ in model only covers development site purchase (@ June 2014Valuations) to Sale of completed developments 18 months later (saleprices and price ceilings calibrated to sales Mid 2014-2015).

• ‘Future’ feasibility not calculated and may be different due to changes inrelativity between purchase price, sale price, improvements, constructioncosts, supply from other developments, demand…

• (Model could do a future feasibility if in/deflation applied to componentsof model and sites assumed to be developed over that period areexcluded)

• Consideration of ‘the future’ therefore requires a consideration widereconomic processes that can be reasonably considered to occur over thetime period being investigated. This may require adjustment of the

‘starting point’ to represent a more ‘normal’ land & house price inflationsituation.


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$0

$500,000

$1,000,000

$1,500,000

$2,000,000

$2,500,000

$3,000,000

$3,500,000

$4,000,000

2 0 1 4

2 0 1 6

2 0 1 8

2 0 2 0

2 0 2 2

2 0 2 4

2 0 2 6

2 0 2 8

2 0 3 0

2 0 3 2

2 0 3 4

2 0 3 6

2 0 3 8

2 0 4 0

2 0 4 2

2 0 4 4

2 0 4 6

2 0 4 8

2 0 5 0

Year

Development Costs Vs Expected Sale Price and Profit ($)

Infrastructure CostsOther CostsConstruction CostsExisting Improvement ValueLand Value

0%

5%

10%

15%

20%

25%

2 0 1 4

2 0 1 6

2 0 1 8

2 0 2 0

2 0 2 2

2 0 2 4

2 0 2 6

2 0 2 8

2 0 3 0

2 0 3 2

2 0 3 4

2 0 3 6

2 0 3 8

2 0 4 0

2 0 4 2

2 0 4 4

2 0 4 6

2 0 4 8

2 0 5 0

% M a r g i n

Year

Development Profit Margin (%) vs

Required Profit Margin (%)

Profit Margin % ($Profit/$Revenue)

Minimum Required Profit Margin %

Starting Year Values

2014 2044

Total Construction Costs $ 425,154.00 $ 770,107.62

Land Value $ 455,000.00 $ 1,277,091.14

Improvement Value $ 120,000.00 $ 82,030.42

Other Costs $ 80,000.00 $ 144,908.93

Infrastructure Costs $ 50,000.00 $ 90,568.08

Overall Development Cost $ 1,130,154.00 $ 2,364,706.18

Expected Sale Price $ 1,220,000.00 $ 3,004,690.29

Profit ($) (Costs less Sales Revenue) $ 89,846.00 $ 639,984.11

Profit % ($Profit/$Revenue)

7.4%

21.3%

Minimum Required Profit: 2014 2044

20.0% No Go Go

Earliest Year Development achievesRequired Profit

2040


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Feasible Development Model

Existing Costs and Prices

Model

Future Costs and Prices

Model

(ROI)

Current Costs and

Sale Prices

Expected Rates ofInflation in Costs

and Sale Prices

Not done in model

(see DF Demand vs Supply)

Completed & in model

Capacity for

Growth Model

(Enabled

development and

base parcel data)


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Model Evolution• V1 – PAUP inputs, 64k (013 E.G. Report)

• V1 – ACAP inputs, 181k (apply exact same 013 E.G.method to new enabled opportunities from density rule changes)

• V2 – ACAP Inputs, 108 – 144k (PF/AT quick reviewresults in imposition of price ceilings to remove sales of largeexpensive dwellings in low value areas (as per supplied LUTs) +

some minor adjustments)• V3.6 ACAP Inputs, 198-256k (9 developments per site,

calibrated dwelling size and prices to to Price ceilings/sales records,accidentally impose PF noted corrections for houses and terraces toapartments)

• V3.7 ACAP Inputs, 224-308k (as per 3.6 but re-corrected apartments)


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Headline Totals

• ACAP based Results are arguably more noticeable for their similarity thandifferences

• PAUP to ACAP rules have IMO made a more significant difference than iterations tomodel (as should be expected), however Model v3 is much ‘better’ than v1 and v2.

• V2 to V3 iteration change results from 9:1 difference in developments tested andbetter sizing houses to ceilings.


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Spatial results (Capacity)V1 PAUP V1 ACAP V2 HPC

V3.7 Max

Return

•

Much as per the Totals, spatial Results are arguably more noticeable for theirsimilarity than differences.

• Consistency of spatial distribution of both ‘clusters of potential’ and areas wherelimited development appears possible under the regulatory and commercial

• ACAP rule change increases concentration of opportunity for small scaledevelopments (density relaxation) but not location. Only spatial zone changes willalter spatial distribution of opportunities.


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Sales Location (Value) and feasible

developments


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Land Value to Floorspace Price

Denser developments are able to moderate the cost of new floorspace on expensive land (compared toless dense developments) but are more expensive on lower value land. The simple best fit curve slopeand relative position are a function of regulation, and model assumptions.


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V3 Results super summary

• How much – quite a lot

• Where – donut with a candle in the middle

•

What price – good range, limited cheaperdwellings (role of inputs? Test ‘very small’

typologies?)

• What size – good range, mostly larger (but

closely linked to price)


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What else can we use model to

investigate?• High level spatial form – how does PAUP align to:

– AP development strategy?

– Councils stated rezoning principles?

– Infrastructure capacity & planning

– etc.

• Location based assessments (e.g. # or % of development within x distance of y features, or within area z)

• Quick assessments of relative capacity value of potential zonechange submissions (based on results from ‘similar’ locations)

• ‘Slice and dice’ (highly atomistic geography and multiple criteria re

zone, price, size, type, land area etc.)• Economic assessments

• Much more yet to be thought of.


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Quick assessment example

“The Zone-U-Lator”

PAUP Average Residential Zone Density DATA ONLY.xlsx

http://localhost/var/www/apps/conversion/tmp/scratch_3/PAUP%20Average%20Residential%20Zone%20Density%20DATA%20ONLY.xlsxhttp://localhost/var/www/apps/conversion/tmp/scratch_3/PAUP%20Average%20Residential%20Zone%20Density%20DATA%20ONLY.xlsx


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Spatial Results (Heatmaps)

+

Existing Relative dwelling density Feasible capacity relative density

Existing Relative dwelling density compared to change (capacity) in relative

density if all feasible developments were realised.


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ACDC Model Further Evolution• ‘perpetual beta’ – new/more data/information requires

constant update

• Perceptions and the relative importance of‘consistency’ vs ‘good enough’ vs ‘chasing ‘accuracy’’;

• Development of suppressed ‘Future’ component based

on exogenously input ROI assumptions;• Discussions with economic modellers re potential GEM

and/or spatial economic models (AMM) etc. (calculateROI dynamically );

•

Significant interest re application to NPS on UrbanDevelopment

• Group should be proud of what it has collectivelyachieved under difficult circumstances.


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Dr Doug Fairgray

Using the ACDC and other information

to consider overall developmentcapacity, over time


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Dwelling Capacity utilising ACDC

Model captures a key commercial process

(residential development) at a single point in time Process is influenced by economic conditions at

that point, and longer term economic trends

Use model outputs as snapshot of start point, butseek to remove distortion due to specific /unusual economic conditions – hence adjustment

Important to interpret outputs carefully

ACDC a ‘snap-shot’ model - does not allow for feedbackeffects (as economic model would)

Base process relatively consistent over time, outputsvary with circumstances and trend


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Dwelling Capacity - Adjusted• Adjusted downward for effects of high dwelling price inflation to 2015

•Allows some inflation effect (at long term mean)

• Places greater weight on gains from intensification itself

• Same method as in 059-063 and January 28 evidence


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ACDC Range of Indicators

Dwelling typology Dwelling price

Size

By location

Overall numbers are useful, but key importance is

ability to understand the characteristics and

implications of the new dwelling estate


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Dwelling Capacity to 2026 - Medium

Model outputs adjusted, mean of selections

Increase in feasible capacity over time (as per mean historic rates) Add other sources to create full regional picture, over time

SOURCE OF CAPACITY Inside MUL Outside MUL TOTAL

Residential Zones 148,000 16,000 164,000

Business Zones 54,000 4,000 58,000

Total Developable Capacity1

202,000 20,000 222,000

Increase in Feasible Capacity 2

89,000 4,000 93,000

Special Areas 10,000 4,000 14,000 Rural Areas - 5,000 5,000

Housing NZ 10,000 - 10,000

Future Urban Zone - 55,000 55,000

TOTAL 311,000 88,000 399,000

1: Currently viable ACDC15 v3.7 Model, adjusted downward for price inflation 2014 to 20152: From Fairgray EIC on Topic 059-063 EIC Tables 4.4, 6.1, 6.2, 6.4 and 6.5


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Dwelling Capacity to 2026 - Low Model outputs - lowest 3 selections, then factored down, and

Lesser increase in feasible capacity over time

18% (-58,000) lower than medium estimate

Low end of range from other sources

SOURCE OF CAPACITY Inside MUL Outside MUL TOTAL

Low Estimate

Total Developable Capacity1

175,000 18,000 193,000

Increase in Feasible Capacity 2

61,000 3,000 64,000

Special Areas 10,000 4,000 14,000

Rural Areas - 5,000 5,000 Housing NZ 8,000 - 8,000

Future Urban Zone - 49,000 49,000

TOTAL 254,000 79,000 333,000

1: Currently viable ACDC15 v3.7 Model, adjusted downward for price inflation 2014 to 2015

2: From Fairgray EIC on Topic 059-063 EIC Tables 4.4, 6.1, 6.2, 6.4 and 6.5


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Demand for Dwellings

Demand based on households = dwellings (1:1) Projected household growth by StatisticsNZ (2015)

Substantial growth in both Medium and High projections..

..plus dwelling shortfall (2013)

Additional dwellings = growth plus shortfall


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Housing Demand and Capacity to 2026 Table 5.7, examines margin of capacity over demand

Expressed as dwellings, % of demand and years’ of growth

Compares medium capacity and medium growth, through to lowcapacity and high growth

Indicates reasonable margin to 2026 (low capacity and high growth)

SCENARIO Inside MULOutside

MULTotal Inside MUL

Outside

MULTotal Inside MUL

Outside

MULTotal

Surplus/Shortfall Margin (%) Margin (Years)Medium Capacity

Medium Growth

70:30 Outcome 202,000 42,000 244,000 185% 91% 157% 24.1 11.9 20.5

60:40 Outcome 218,000 26,000 244,000 234% 42% 157% 30.5 5.5 20.5

High Growth

70:30 Outcome 174,000 29,000 203,000 127% 49% 104% 16.5 6.4 13.5

60:40 Outcome 193,000 10,000 203,000 164% 13% 104% 21.3 1.7 13.5

Low Capacity

Medium Growth

70:30 Outcome 146,000 33,000 179,000 134% 72% 115% 17.4 9.3 15.0

60:40 Outcome 162,000 17,000 179,000 174% 27% 115% 22.7 3.6 15.0

High Growth

70:30 Outcome 118,000 20,000 138,000 86% 34% 70% 11.2 4.4 9.2

60:40 Outcome 137,000 1,000 138,000 116% 1% 70% 15.1 0.2 9.2


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High Level Comparison

Capacity through intensification plus other sources indicates that

capacity in total is greater than projected demand to 2026

Caveats

Forward-looking assessment has a range of uncertainties, especially

2026+

Longevity of strong in-migration growth is not known

Ability of construction sector to deliver

Effects of the SHAs

Differing views on the ACDC Model

Total capacity is only one part of the full picture

Nature of capacity, including prices

Location of capacity


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Nature of Demand for Dwellings

Consider detail as well as the high-level outcome• Households have varying needs and ability to pay for

housing

• Affordability is an important issue

• Location affects affordability of living

• Auckland market has not delivered lower cost dwellings

(for a variety of reasons)


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Assessing Net Demand for Dwellings by

Price/Value Band

(Section 6 of EIC)• Identify key segments of market & projected growth

• Estimates of demand by dwelling price band

• Add in lower income hshlds not active in market• Allow for effect of market ‘churn’, affects dwelling

availability

•Estimate net demand by price band


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Demand for Dwellings by Price Band to 2016

Medium growth - demand throughout price spectrum

Particular demand in lower end of market - under $500,000

1,700 to 2,700 dwellings pa

Additional demand to catch up past shortfall (another 1,100 pa)


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Demand for Dwellings by Price Band to 2016

High growth also has particular demand in lower end of market

2,600 to 3,800 dwellings pa Additional demand to catch up past shortfall (another 1,100 pa)


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Demand and Potential Supply

ACDC output allows comparison of feasible capacity with current($2015) sales by price band

PAUP provisions suggest a price structure generally compatible…

…however, a substantial gap in the lower price bands


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Some Implications

• Gap apparent in dwelling lower price bands

• Consistent with Auckland’s recent history - dwellingsupply, market and sector structures

• …and with ACDC Model inputs (limited dwellingoptions in


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End

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081a ak cncl - general - capacity and feasibility modelling - hearing presentation

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