briefing note #9 - calgary impact assessment model (ciam ... · (ciam). the simulations estimate...

calgary.ca/economy call 3-1-1

Calgary Impact Assessment Model (CIAM):

Two Simulations

Corporate Economics

December 2010

Briefing Note #9

Corporate Economics

Briefing Note #9 - Calgary Impact Assessment Model (CIAM): Two Simulations

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ii Calgary Impact Assessment Model (CIAM): Two Simulations

Executive Summary

�� The�research�brief�presents�simulation�results�from�the�Calgary�Impact�Assessment�Model�(CIAM).� The� simulations� estimate� the� effects� on� The� City’s� financial� position� from:� (1)�stronger�economic�growth�and�(2)�introduction�of�a�payroll�tax.

�� The� Calgary� Impact� Assessment� Model� is� a� systems� model� that� is� divided� into� five� sub-modules:�population,�employment,�housing,�non-residential�space�and�municipal�services.

�� The�basecase�simulation�was�developed�for�the�period�1990�-�2009.�The�basecase�is�used�as�a�yardstick�against�which�the�various�policy�proposals�are�measured.

�� The�simulation�results�showed�the�following:

�{ A�stronger�economic�growth

�y Population�levels�would�be�higher�when�compared�to�the�basecase.�y Total�operating�expenditures�would�be�higher�when�compared�to�the�basecase.�y Debt�levels�would�be�higher�when�compared�to�the�basecase.

�{ Payroll�tax

�y Total�operating�expenditures�would�be�higher�when�compared�to�the�basecase.�y Debt�levels�would�be�lower�when�compared�to�the�basecase.

Table of Contents

1. Introduction ..........................................................12. Model Structure .....................................................1

2.1.��Population�and�Labour�Market�Modules�..............22.2.��Real�Estate�Module�..................................................32.3.��Municipal�Government�Module�............................42.4.��Main�Assumptions�of�the�Model�...........................5

3. Basecase .................................................................63.1.��Estimation�of�Parameters�........................................63.2.��Collection�of�Historic�Data�.....................................63.3.��The�Calibration�Process�..........................................6

4. Application of the Model ......................................85. Conclusion ...........................................................126. Bibliography ........................................................13

Calgary Impact Assessment Model (CIAM): Two Simulations 1

Overview of the Model

Chart 1Local Economy and the External Environment

MunicipalFinance

MigrationWTI CrudeOil Prices

PopulationEmployment

ResidentialSpace

Non-residential

Space

CityIndex

InterestRates

1. IntroductionThe� research� brief� presents� simulation� results� from� the� Calgary� Impact� Assessment� Model�(CIAM)1.�The�simulations�were�designed�to�estimate�the� impact�of�changes�to�the�economic�growth�rate�and�changes�in�The�City’s�revenue�sources�on�The�City’s�major�financial�indicators.�

The�brief�is�divided�into�four�parts.�The�first�introduces�the�topic�and�lays�out�the�organization�of�the�report.�The�second�describes�the�model�and�its�structure.�The�third�part�describes�the�model’s�basecase.�The�final�section�presents�the�model’s�results.

2. Model StructureThe� model� is� made� up� of� five� key� components:� population,� employment,� housing,� non-residential�space�(including�office,� industrial�and�commercial�space)�and�municipal�services.��

1� Calgary�Impact�Assessment�Model��is�the�result�of�work�that�was�done�at�The�City�of�Edmonton�and�The�City�of�Calgary.�Previous�versions�of�the�model�were�presented�at�different�professional/academic�venues,�including�the�System�Dynamics�Conference�in�Palermo,�Italy�in�2002.�The�current�version�of�the�model�was�calibrated�by�Corporate�Economics�and�reviewed�by�Prof.�Nathaniel�Osgood�from�the�University�of�Saskatchewan.

2 Calgary Impact Assessment Model (CIAM): Two Simulations

Population

Chart 2Components of Population Growth

Labour Market

Chart 3Drivers of the Labour Market

2.1. PopulationandLabourMarketModules

Population� is� the�main�driver�of� the�model�and� is�constantly�changing� through�changes�migration�and� ageing.� It� is� estimated� by� the� cohort survival� methodology� which� allows� for� an� accounting� of�population�by�its�various�age�components:�births,�deaths�and�migration.�Migration�occurs�when�there�is�a�imbalance�between�the�demand�and�supply�for�labour.�Usually�the�demand�for�labour�exceeds�supply�during�periods�of�increased�economic�activity�and�this�results�in�in-migration.�The�contrary�occurs�during�periods�of�economic�slowdown.�Most�individuals�who�move�into�the�region�are�generally�in�the�younger�age�cohorts�and�many�women�are�in�the�childbearing�age�groups.�The�absence�of�migration�over� an� extended� period� of� time� could� lead� to� a� decline� in� the� level� of� population.� Consequently,�positive�net�migration�can�cause�the�population�to�renew�itself.�

Net Migration = In Migration - Out Migration

Natural Increase = Births - Deaths

In Migration

Births Deaths

Out Migration

Population

+

+

++

++

+

++

RelativeWage Rate

Population

NetMigration

LabourForce

Difference inUnemployment

Rate

Employment

WageRate

NationalUnemployment

Rate

LocalUnemployment

Rate

Births

Deaths

InterestRates

WTI CrudeOil Prices

+


Real Estate

Chart 4Drivers of the Residential Housing Market

2.2. RealEstateModule

The�real�estate�module�is�divided�into�residential�and�non-residential�housing.�The�stock�of�space�is�increased�by�construction�and�decreased�by�demolition.�The�market�price�of�space�is�an�important�driver�of�the�demand�for�space.�A�change�in�the�market�price�influences�the�qualifying�income/space�required�per�worker.�A�change�in�the�vacancy�rate�impacts�the�expected�construction�or�sellers�price�of�space.�

HousingStarts

Fraction ofFamilies

Qualified

SellersPrice

QualifyingIncome

HousingStock

IncomeQualifiedDemand

MarketPrice

DevelopmentCosts

PropertyTax

Payment

VacancyRate

TotalFamilies

Supply Demand


Municipal Finance

Chart 5Components of Municipal Capital

2.3. MunicipalGovernmentModule

Municipal�finance�is�a�complex�system.�The�municipality�draws�revenues�from�residential�and�non-residential�assessment,�government�transfers�and�user�fees.�This�amount�is�used�to�provide�services�to�its�citizens�and�to�partly�finance�capital.�Businesses�and�migrants�are�attracted�by�the�availability�of�services,�employment�and�affordable�housing.�

RequiredStock

Standard per Capita

Population

AvailableFunds

DepreciationInvestmentStock

Gap

Delay

Average Lifeof Stock

+

++

+

+


2.4. MainAssumptionsoftheModel

The�equations�below�contain�the�model’s�basic�assumptions:

1.� Demand�for�Services�=�ƒ(Population,�Standards)

2.� Supply�of�Services�=�ƒ(Employees,�Municipal�Capital)

3.� Infrastructure�Gap�=�Demand�for�Services�-�Supply�of�Services

4.� Cost�of�Infrastructure�Gap�=�Infrastructure�Gap�*�Unit�Cost

5.� Municipal�Capital�=� Integ� (Municipal� Investment� -�Municipal�Capital�Depreciation,�Initial�Capital�Stock)

6.� Municipal�Investment�=�Min.�(Cost�of�Infrastructure�Gap,�Funds�Available�for�Capital)

7.� Municipal�Employees�=�ƒ(Supply�of�Service,�Municipal�Capital)

8.� Municipal�Operating�Cost�=�Labour�Cost�+�Non-Labour�Cost

9.� Labour�Cost�=�Municipal�Employees�*�Average�Labour�Cost

10.� Non-Labour�Cost�=�ƒ(Municipal�Capital)


3. BasecaseThe�main�purpose�of�the�basecase�is�to�provide�a�yardstick�to�rank�the�policy�simulation.�Consequently,�it�is�possible�to�say�whether�or�not�the�policy�option�would�leave�The�City�the�same,�worse�off�or�better�off.

3.1. EstimationofParameters

The�estimation�of�the�model�required�data�of�adequate�quantity�and�quality2.�The�model�estimation�process�relied�on�a�variety�of�data�sources�and�methods.�These�can�be�group�into�three�categories:�data�collection,�calibration�and�expert�validation.�

3.2. CollectionofHistoricData

Time�series�data�was�gathered�for�the�period�1990�to�2009�from�a�variety�of�sources�including�The�City�of�Calgary’s�published�and�unpublished�records�(annual�reports).�In�cases�where�there�were�gaps�in�a�particular�time�series,�the�gaps�were�filled�through�estimation.

3.3. TheCalibrationProcess

The�model�was�estimated�for�the�period�1990�–�2009�using�Vensim’s©�5.5�optimization�routine.�This�was�an�iterative�process�which�involved�repeated�modifications�to�the�model’s�parameters.�The�objective�was�to�select�those�parameters�that�allowed�the�model�to�generate�results�that�were�as�close�as�possible�to�the�historic�data.�Following�each�change,�a�new�model�solution�was�computed�and�the�simulation�error�for�the�particular�series�was�tabulated.�This�process�was�repeated�until�an�acceptable�error�was�achieved.�Examples�of�the�simulated�values�collected�against�the�historic�data�are�shown�in�figures�6�to�8.

2� This� part� of� the� estimation� process� consisted� of� collaborating� with� Prof.� Osgood� from� the� University� of� Saskatchewan� and�presenting� the�model�and� its� results� to� selected�groups�of�The�City�of�Calgary’s�employees�and�asking� them�to�express� their�opinions�on�the�model’s�logical�structure,�assumptions�and�quantitative�results.�Specifically,�they�were�asked�whether�or�not�they�agreed�with�the�model’s�structure,�assumptions�and�results�and�if�not�to�state�the�reasons�for�their�objections.�In�addition,�they�were�invited�to�make�suggestions�for�model�improvement.


Municipal Operating Costs

Chart 6 Chart 7Labour Cost

$millions

Total Expenditures

$millions

Sources: Finance & Supply, Corporate Economics Sources: Finance & Supply, Corporate Economics

Debt and Number of Employees

Chart 8 Chart 9Debt

$millions

Total FTEs

persons


400

600

800

1,000

1,200

1,400Labour Cost [Model]Labour Cost [History]

0

200

400

600

800

1,000

1,200

1,400

1990

1992

1994

1996

1998

2000

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2004

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2008

Labour Cost [Model]Labour Cost [History]

Sources: Finance & Supply, Corporate Economics

1,000

1,500

2,000

2,500

3,000Debt [Model]

Debt [History]

0

500

1,000

1,500

2,000

2,500

3,000

1990

1992

1994

1996

1998

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2004

2006

2008

Debt [Model]

Debt [History]


1,000

1,500

2,000

2,500Total expenditure [Model]

Total expenditure [History]

0

500

1,000

1,500

2,000

2,500

1990

1992

1994

1996

1998

2000

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2004

2006

2008

Total expenditure [Model]

Total expenditure [History]


11,000

12,000

13,000

14,000

15,000

16,000Total FTE's [Model]Total FTE's [History]

9,000

10,000

11,000

12,000

13,000

14,000

15,000

16,000

1990

1992

1994

1996

1998

2000

2002

2004

2006

2008

Total FTE's [Model]Total FTE's [History]



4. Application of the ModelThe�model�was�used�to�simulate�the�effects�of�the�following:�(1)�higher�oil�prices�and�(2)�the�imposition�of�a�one�per�cent�payroll�tax.�The�effects�of�these�changes�were�measured�by�comparing�how�a�given�variable�would�change�when�compared�against�its�baseline�value.�The�baseline�values�were�the�estimated�values�from�the�1990-2009�period.�The�study�therefore�asked�the�question,�how�history�would�have�been�different�if�a�particular�policy�was�in�place.�This�approach�(ex-post)�is�far�superior�to�the�alternative�approach�(ex-ante)�because�the�analyst�is�able�to�avoid�challenges�about�the�reasonableness�of�various�assumptions�surrounding�the�basecase.�

1. Higher economic growth.

�� Higher� economic� growth� was� achieved� over� the� 1990-2009� period� by� assuming� higher� oil�prices.

� Policy.�This�simulation�examines�the�financial�impact�on�the�municipality�if�the�price�of�West�Texas�Intermediate�(WTI)�crude�oil�would�have�been�20 per cent higher�during�the�analysis�period�(1990�-�2009).�

� Assumption.� The� model� assumes� that� crude� oil� price� would� have� an� impact� on� total�employment�since�Calgary�is�home�to�most�of�the�energy�companies�operating�in�Alberta.

� Results.�Higher�crude�oil�prices�would�have�placed�additional�pressure�on�The�City’s�budget:

�{ Total�population�would�have�grown�faster�relative�to�the�basecase.�An�increase�in�crude�oil�prices�would�have�increased�economic�activity�in�the�province�and�this�would�demand�an� increase� level�of� employment.� Increased�economic�activity� in� the�city�would�attract�migrants�from�outside�the�region�and�this�would�have�increased�total�population.

�{ Total� operating� expenditures� would� have� been� higher� than� the� basecase.� Providing�services� to� a� higher� level� of� population� would� have� required� increased� investment� in�capital,�causing�operating�expenditures�to�increase.

�{ Total�debt�would�have�been�higher�relative� to� the�basecase�as�The�City�finances�capital�through�taxes�and�debt.�This�scenario�would�require�an�increase�in�borrowing�to�finance�the�increased�level�of�capital�due�to�an�increase�in�population.

�{ The�simulation�shows�higher�economic�growth�and�has�a�more�adverse�effect�on�The�City’s�financial�position.

�{ Total�gap�would�grow�faster�under�this�scenario.�The�City�would�have�been�unable�to�close�the�gap�as�population�growth�would�have�outpaced�investment�in�capital.�


Total Population and Municipal Expenditures

Chart 10 Chart 11Population

thousands of persons

Total Expenditures

$millions


Total Debt and Gap

Chart 12 Chart 13Debt

$millions

Total Gap

$millinos


400

600

800

1,000

1,200

1,400Population [Model]Population [WTI Price]

0

200

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1,400

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Population [Model]Population [WTI Price]


1,000

1,500

2,000

2,500Debt [Model]Debt [WTI Price]

0

500

1,000

1,500

2,000

2,500

1990

1992

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Debt [Model]Debt [WTI Price]


1,000

1,500

2,000

2,500Total expenditure [Model]Total expenditure [WTI Price]

0

500

1,000

1,500

2,000

2,500

1990

1992

1994

1996

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Total expenditure [Model]Total expenditure [WTI Price]


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900Total Gap [Model]Total Gap [WTI Price]

0

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900

1990

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Total Gap [Model]Total Gap [WTI Price]



2. Impose a one per cent payroll tax on total wage bill.

�� The�simulation�in�the�previous�section�shows�that�The�City�does�not�benefit�from�economic�growth.� The� current� simulation� illustrates� how� this� could� be� rectified� by� using� a� growth�sensitive�revenue�source.

� Policy.�This� scenario�examines� the�financial� impact�on� the�municipality� if�The�City�would�have�received�1 per cent�of�the�total�wage�bill�in�Calgary�during�the�analysis�period�(1990�-�2009).�This�revenue�would�have�been�distributed�evenly�between�financing�capital�projects�and�non-tax�revenues.�

� Assumption.�The�model�assumes�that�an�increase� in�funding�and�revenues�would�increase�investment�in�capital�and�reduce�The�City’s�total�debt.

� Results.�Increased�level�of�funding�and�revenues�would�have�placed�less�pressure�on�The�City’s�budget:

�{ Total� tax� financing� would� have� increased� significantly� compared� to� the� basecase.� This�would�allow�The�City�to�fund�major�capital�projects�and�thereby�reducing�the�total�gap.

�{ Total� operating� expenditures� would� have� been� higher� than� the� basecase.� Providing�services� to� a� higher� level� of� population� would� have� required� increased� investment� in�capital,�causing�operating�expenditures�to�increase.

�{ Total� debt� would� have� been� lower� relative� to� the� basecase� as� The� City� finances� capital�through�an�increase�in�funding.�This�scenario�would�require�a�decrease�in�borrowing.

�{ Total�gap�would�grow�slower�under�this�scenario.�The�City�would�have�been�able�to�close�some�of�the�gap.�


Financing of Capital and Operating Expenditures

Chart 14 Chart 15Tax Financing

$millions

Total Expenditures

$millions


Total Debt and Gap

Chart 16 Chart 17Debt

$millions

Total Gap

$millions


100

150

200

250Tax Financing [Model]Tax Financing [Payroll Taxes]

0

50

100

150

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250

1990

1992

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2000

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2008

Tax Financing [Model]Tax Financing [Payroll Taxes]


1,000

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2,000

2,500Debt [Model]

Debt [Payroll Taxes]

0

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1,000

1,500

2,000

2,500

1990

1992

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1996

1998

2000

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2004

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2008

Debt [Model]

Debt [Payroll Taxes]


1,000

1,500

2,000

2,500Total expenditure [Model]Total expenditure [Payroll Taxes]

0

500

1,000

1,500

2,000

2,500

1990

1992

1994

1996

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2000

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2004

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2008

Total expenditure [Model]Total expenditure [Payroll Taxes]


300

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900Total Gap [Model]Total Gap [Payroll Taxes]

0

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1990

1992

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2008

Total Gap [Model]Total Gap [Payroll Taxes]



5. ConclusionThis� paper� provides� a� summary� of� Calgary� Impact� Assessment� Model� (CIAM)� and� the� results� of�the� two�applications�of� the�model.�Each� simulation� is� judged�against�a�basecase.�The�first� scenario�assumes�higher�crude�oil�prices�during�the�study�period.�The�results�show�increased�economic�activity�which� lead� to� an� increase� in� the� demand� for� labour,� consequently� increasing� migration� and� total�population.�But,�providing�services�to�a�larger�population�base�requires�a�larger�infrastructure�stock.�The�municipality’s�level�of�debt�and�operating�expenditures�would�increase�under�this�scenario,�while�the�difference�between�required�and�actual�capital�would�also�widen�since�The�City�is�restricted�in�its�level�of�funding.�The�municipality�finances�capital�through�a�combination�of�debt�and�tax�revenues.�

The�second�simulation�assumes�a�1�per�cent�payroll�tax�levied�from�the�total�wage�bill�in�Calgary.�This�amount�would�be�distributed�evenly�between�financing�capital�projects� and�non-tax� revenues.�The�simulation�shows�that�tax�financing�increases�during�the�study�period,�which�allow�the�municipality�to�reduce�its�level�of�debt,�consequently�reducing�the�gap.�

The� two� scenarios� confirm� the� notion� that� the� municipality� does� not� fully� capture� the� benefits� of�increased�economic�activity.�Policies�focusing�on�providing�the�local�government�with�additional�tax�revenues�place�less�pressure�on�The�City’s�debt�position�and�therefore�reduces�the�gap�between�required�and�actual�infrastructure.�

Model documentation:

Volume 1:�Report�by�Dr.�Nathaniel�Osgood,�University�of�Saskatchewan.

Volume 2:�Model�description

Volume 3:�Model�equations

Volume 4:�Model�constants

Volume 5:�Tables�used�in�the�model


6. BibliographyAlfeld� LE,� Graham� AK.1974.� Introduction� to� Urban� Dynamics,� Chapter� 10:� The� URBAN2� Model,�Cambridge,�Massachusetts:�Wright–Allan�Press,�Inc.

Alfeld�LE,�Meadows�DL.�1974.�A�Systems�Approach�to�Urban�Revival.�In�N.J.�Mass,�(Ed).�Readings�in�Urban�Dynamics�Vol.�1.�Cambridge,�Massachusetts:�Wright–Allan�Press,�Inc.

Arthur�W�B.1994.�Increasing�Returns�and�Path�Dependence�in�the�Economy.�Ann�Arbor:�University�of�Michigan�Press.

Atkinson� G,� � Oleson� T.� 1996.� Urban� Sprawl� as� a� Path� Dependent� Process.� Journal� of� Economic�Literature,�Vol.�XXX,�No.�2.

Bruce�D,��Carruthers�N.�1994.�Financial�Simulation�Model:�FINSIM�Model�Development�and�Results.�Calgary,�Alberta:�The�City�of�Calgary.

1978.�The�Fiscal�Impact�Handbook.�New�Brunswick

Burchell�RW,�Listokin�D.1990.�Infrastructure�Costs,�Fiscal�Impacts,�and�Proffer�Charges.�Report�to�the�Planning�Department�of�the�City�of�Virginia�Beach,�Virginia.

Burchell�RW,�Listokin�D.1992.�Fiscal�Impact�Procedures�and�State�of�the�Art:� �The�Subset�Question�of�the�Costs�and�Revenues�of�Open�Space�and�Agricultural�Lands,�paper�presented�at�the�conference�Does�Land�Conservation�Pay?�Determining�The�Fiscal�Implications�of�Preserving�Open�Land,�Lincoln�Institute�of�Land�Policy,�Cambridge,�Massachusetts.

City� of� Edmonton.� 1980.� Fiscal� Impact� Analysis:� Interim� Report� #1.� Edmonton,� Alberta:� City� of�Edmonton.

City� of� Edmonton.� 2000.� 2001-2010� Long-Range� Financial� Plan,� Edmonton,� Alberta:� The� City� of�Edmonton�Corporate�Services�Department.

Ford�A.�1976.�Users�Guide�to�the�Boom�1�Model�(LA-6396-MS).�Los�Alamos,�New�Mexico:�Los�Alamos�Scientific�Laboratory.

Forrester�J�W.�1961.�Industrial�Dynamics.�Cambridge:�Productivity�Press.

Forrester�J�W.�1968.�Principles�of�Systems.�Cambridge:�Productivity�Press.

Forrester�J�W.�1969.�Urban�Dynamics.�Cambridge:�Productivity�Press.

Gale�DE.�1973.�The�Municipal�Impact�Evaluation�System:��Computer�Assisted�Cost/Revenue�Analysis�of�Urban�Development/�PAS�Report�294.�Washington,�D.C.:��Planning�Advisory�Service.

Hamilton�HR.�et�al.�1963.�Systems�Simulation�for�Regional�Analysis:�An�Application�to�River-Basin�Planning.�York,�Pennsylvania:�The�Maple�Press�Company.


Hunt�JD.�1993.�Calgary�GoPlan:��The�Role�of�Modelling�in�Transportation�Planning,�BGS-N015-07-93.�Calgary,�Alberta:�City�of�Calgary.

Isserman�A.�et�al.�“Regional�Labour�Market�Analysis”.�In�Peter�Nijkamp�(1986),�(Ed.),�Handbook�of�Regional�and�Urban�Economics,�Vol.�1:�Regional�Economics.�Amsterdam,�North-Holland.

Jozsa��J.�et�al.�1981.�Projections�of�Regional�and�Sub-Regional�Socio-Economic�Impacts�of�a�Resource�Development�Project.�Halifax.�Nova�Scotia:�Canadian�Regional�Science�Association�Annual�Meetings,�May�22.

Maciariello� JA.� 1975.� Dynamic� Benefit� Cost� Analysis:� Evaluation� of� Public� Policy� in� a� Dynamic�UrbanModel.�Lexington,�Massachusetts:�D.C.�Heath�and��Company.

Mass�NJ.�1978.�Business�Structure�and�Economic�Activity�in�Urban�Dynamics.�In�N.J.�Mass�(1978),�(Ed).�Readings�in�Urban�Dynamics�Vol.1.�Cambridge,�Massachusetts:�Wright–Allan�Press,�Inc.

Meadows�D.H.�1980.�The�Unavoidable�A�Priori.�Edward�B.�Roberts�(Ed).�Managerial�Applications�of�System�Dynamics.�Cambridge,�Massachusetts:�MIT�Press.

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P.O. Box 2100, Stn. M, #8311, Calgary, AB, Canada T2P 2M5


Q3 2010

Calgary & Region Economic Outlook 2000-2020


VOLUME 2

ENERGY MARKETS AND THE ECONOMY

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EXECUTIVE BRIEFING Commentary on Calgary’s statistics for the month of DECEMBER 2008

THE CITY OF CALGARY January 28, 2009 | Corporate Economics | For inquires call Patrick Walters: 403-268-1335

Why the corporation should care?

Money offered by Federal Budget to build certain infrastructure is badly needed in Calgary (i.e. social housing). It also provides a great economic opportunity at the time of crisis.

The problem is that it has also double whammy effect on the municipal fi nances. The cites have to shuffl e previously accepted decisions about capital spending and go deeper into debt (to much the offer).

Hot Topics

The information in this report is generally of a forecast nature. The City of Calgary accepts no liability.

Global crisis – saga continuesThe distinct characteristics of this crisis are: speed of changes and lack of reliable information.

Many countries around the world experience recession; for example European Union, and Russia. In relatively good condition are countries with less developed banking system where the ‘new-fi nancial-instruments’ related to the U.S. sub-prime mortgages were absent.

The world is very inter-connected and countries such as China and India are also affected.

The one leading indicator for the global economy that is believed to be a reliable index of change, free of manipulation, is the Baltic Dry Index (BDI). It measures the demand versus the supply of dry bulk carriers. In short: “People don’t book freighters unless they have cargo to move.” This indicator slid dramatically since mid July 2008 and stayed at below 1,000-level for the last three months.

Canada & AlbertaThe good news is that the budget proposed by Harper’s government was passed and the political impasse in Canada was solved. The 2009 Federal Budget made commitments to large municipalities such as:

$4 Billion over 2 years for rehabilitation projects,

$1 Billion Green Infrastructure Fund, no details on this yet,

$500 million over 2 years for recreational infrastructure on a 50/50 cost sharing basis,

$2 billion gas tax transfer to municipalities is made permanent,

up to $500 million for Public Transit Infrastructure (mostly already allocated to Toronto, Montreal and Vancouver) and

$400 million for Police recruitment

Baltic Dry Index (BDI) Jan 2008-Jan 2009

0

2,000

4,000

6,000

8,000

10,000

12,000

14,000

Jan-

08

Feb-

08

Mar

-08

Apr

-08

May

-08

Jun-

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Aug

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Sep

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Oct

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Nov

-08

Dec

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Jan-

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Source: The Baltic Exchange, Corporate Economics

Forecasting Canada’s Growth

The Federal Budget The Conference Board of Canada International Monetary Fund

0.9% 0.5% 1.2%

2.4% 3.6% 1.6%

P.O. Box 2100, Stn. M, #8311, Calgary, AB, Canada T2P 2M5 | Email: [email protected] | Tel: 403.268.8690

Calgary Census Metropolitan Area (CMA)

February 18, 2010Patrick Walters, City Economist | Wendy Fan, Corporate Economist

Inflation ReviewJ A N UA RY

2010


Major Contributors to Calgary's Inflation Rates(12-Month-Moving-Average)

Jan-05 Jul-05 Jan-06 Jul-06 Jan-07 Jul-07 Jan-08 Jul-08 Jan-09 Jul-09 Jan-10

12-M

onth

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Infla

tion

Rat

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)

-2

-1

0

1

2

3

4

5

6All-items FoodShelter Gasoline

Source: Statistics Canada, Corporate Economics, February 2010

Inflation Still Moderate in January 2010

Inflation Rates(12-Month-Moving-Average or average inflation rate for the past 12 months)

Relative Importance

(%)*Jan-10 Dec-09 Jan-09

Calgary: All-items 100 (0.0) (0.1) 3.1

Calgary: All-items excluding food and energy 75.2 1.3 0.8 2.0

Food 15.5 4.2 4.8 3.8

Shelter 27.7 (2.8) (2.5) 7.3

Owned accommodation 17.9 0.0 0.5 6.3

Water, fuel and electricity 5.6 (18.6) (18.5) 13.3

Household operations, furnishing and equipment 11.4 2.8 2.8 0.6

Clothing and footwear 5.2 0.3 0.4 (2.4)

Transportation 19.5 (3.9) (4.9) 0.8

Gasoline 4.5 (17.1) (19.9) 8.9

Health and personal care 4.5 4.8 4.5 2.2

Recreation, education and reading 12.9 1.1 1.0 0.2

Alcoholic beverages and tobacco products 3.3 3.8 3.7 3.0

Alberta: All-items 100 (0.1) (0.1) 3.0

Alberta: All-items excluding food and energy 75.2 1.4 1.4 1.9

Canada: All-items 100 0.4 0.3 2.3

Canada: All-items excluding food and energy 73.6 1.1 1.8 1.2

Source: Statistics Canada, Corporate Economics, February 2010 * 2005 CPI basket weights at April 2007 prices, Alberta and Canada, effective May 2007

CPI began picking up from the slow pace experienced in 2009

Inflation rate continued to increase in January 2010. Compared to a year ago, consumer price indexes climbed 1.9 per cent in Canada, 1.7 per cent in Alberta, and 1.4 per cent in Calgary. Stronger demand led to higher commodity prices which resulted in increases in consumer prices. It was the third consecutive month since gasoline prices have exerted upward pressure on CPI. However, core inflation continues to be well within the central bank’s target and the remaining output gap and the drag from strong Canadian dollar will restrain inflation.

Factors affecting recent inflation trend

The overall inflation in Calgary is a weighted index of price changes of various goods and services based on their relative importance in the CPI basket. From the graph below, we can see the trend of shelter costs is highly correlated with the trend of the overall inflation. Shelter costs take up 27.7% of the weight in the CPI basket, which explained over half of the changes in the decline of Calgary’s consumer prices from its 2007 peak. Food and gasoline are also highly weighted in the CPI

basket. The pick up of the prices of both food and gasoline put upward pressure on the inflation rate, which, however, is dominated by the downward pressure from the shelter costs. The CPI in Calgary would remain moderate until the economy returns to its full capacity.

Major contributors to Calgary’s 12-month-moving-average inflation

Shelter: The 2.8 per cent decrease in shelter costs in January 2010 offset 0.8 per cent of Calgary’s overall inflation. The decline was caused by lower mortgage interest costs and natural gas prices.

Food: Food prices rose 4.2 per cent in January 2010, which was lower than the 4.8 per cent increase in last December. The total contribution of food prices to Calgary’s overall inflation in January was 0.7 per cent.

Transportation: The 12-month-moving-average transportation prices decreased by 3.9 per cent in January 2010, which offset 0.8 per cent of the overall inflation in Calgary. The downward pressure was mostly caused by gasoline price which dropped by 17.1 per cent at the 12-month-moving-average level.

Next release: March 19, 2010

Who We AreOver the past ten years Corporate Economics has researched dozens of economic topics and developed reliable methods of forecasting and analysis. Monitoring economic trends allows us to develop unique insights on how external events are impacting the local economy and the Municipal Corporation. We provide services in four areas: forecasting, information provision, consulting and policy analysis.

For more information, please contact:

Patrick Walters

403.268.1335

[email protected]

Many of our publications are available on the internet at www.calgary.ca/economy.

Stanley Kongnetiman

403.268.5059

[email protected]

Wendy Fan

403.268.8690

[email protected]

Calgary Impact Assessment Model (CIAM)

Corporate Research Analyst: Estella Scruggs

The City of Calgary provides this information in good faith. However, the aforementioned organization makes no representation, warranty or condition, statutory express or implied, takes no responsibility for any errors and omissions which may contained herein and accepts no liability for any loss arising from any use or reliance on this report.

briefing note #9 - calgary impact assessment model (ciam ... · (ciam). the simulations estimate...

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