Two-dimensional methodological issues in

Canadian municipal infrastructure time series.

Marie-Claude Duval, Peter Elliott

Statistics Canada

ICES III Presentation / June 20, 2007

Overview

Background

Data Sources

Challenges

Methodology

Conclusion and lessons learned

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Background

Importance and current state of Canada’s public physical infrastructure

Infrastructure Canada required information in support of their research and public policy requirements

Project mandate: develop historical data series in current and constant dollars of capital investment and stock, by:

asset and province, federal, provincial and municipal governments, 1961-2005

function and province, municipal governments, 1988-2005

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Background (cont’d) – Assets - examples

Code: Description: 1017 Parking Lots and Garages

1019 Indoor Recreational Buildings

1213 Waste Disposal Facilities

2202 Roads

2601 Sewage Treatment

8001 Computers

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Background (cont’d) – Functions

Code/Description:

1 General Government Services

2 Protection of Persons & Property (police, firefighting)

3 Transportation and Communication (roads, snow removal, parking)

4 Environment (water supply, sewage & garbage collection & disposal)

5 Health

6 Social Services (welfare)

7 Resource conservation & Industrial development (Industrial parks, tourism)

8 Regional Planning & Development

9 Recreation & Culture (sport facilities, libraries)

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Data Sources Annual Capital Investment by Asset and Province, Current $:

1. ICSP - Investment and Capital Stock Program (Stocks) - 1871-2003, asset and industry detail (Canada), aggreg (prov)

2. CES - Capital Expenditures Survey (Flows) - 1988-2003 by province and asset detail; - pre-1988 less detail (building & engineering asset; no industry)

3. PISP - Public Institutions Statistical Program (Functions) - 1993-2003 data series by province, function and asset; Pre-1993: partial data available; used other sources

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Challenges – ICSP, CES, PISP

1. Data coherence Slightly different universes (industry coding) Asset disconnects between CES and PISP (concordances) Acceptable asset-function combinations ICSP adjustments (e.g. software, residential infrastructure)

2. Data Base Creation Back-cast to 1871 to generate stocks (data gaps, imputation) Level of details required by asset, function and province in

order to derive data in constant dollars.

3. Benchmarking Respect ICSP control totals – by asset and by province – Respect local government data trends by asset and province

and by function and province (PISP).

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Methodology

Goal: Develop coherent and consistent database

on capital investment in current dollars from 1871 to 2003:

Part 1 - by asset and province;

Part 2 - by asset, function and province

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Methodology

Use of the following data sources:

Controls = Investment and Capital Stock Program (ICSP)

Source 1 = Capital Expenditures Survey (CES)

Source 2 = Public Institutions Statistical Program (PISP)

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Methodology

Assumptions:

All information known at the requested level is better than no information.

The two sources are relevant even if different and were reconciled to be comparable.

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Methodology

Part 1:

Provide estimates on capital investment by asset and province

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Methodology Part 1 – Capital Investments by asset and province

Constraints:

Respect total by asset and total by province (controls).

Try to respect local government data trends by asset and province (source 2).

Capital Investment from two different sources (source 1 and source 2) might be different between them as well as with the controls.

Lack of data from sources 1 and 2 for some years.

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Methodology Part 1 – Capital Investments by asset and province

Process:

For each year, use raking ratio estimator to derive capital investment by asset and province using data from source 1 and source 2 and by respecting control total by asset and control total by province (controls).

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Methodology Part 1 – Capital investments by asset and province

1. Control data are the marginals: Ca,.= Capital investment by asset

C.,p= Capital investment by province

Asset Province

... Que Ont ... Total

1006 C1006,.

1008 C1008,.

... ...

Total ... C.,que C.,ont ... C

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Methodology Part 1 - Capital investments by asset and province

2a. Use data from source 1 in the cells : Ca, p, S1

Asset Province

... Que Ont ... Total

1006 .... C1006,que,S1 C1006,ont,S1 C1006,.

1008 .... C1008,que,S1 C1008,ont,S1 .... C1008,.

... ... .... ...

Total ... C.,que C.,ont ... C

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Methodology Part 1 - Capital investments by asset and province

2b. Adjust the cell values to preserve the controls. Raking ratio estimator (Ca,p,S1,rr)

Asset Province

... Que Ont ... Total

1006 .... C1006,que,S1,rr C1006,ont,S1,rr C1006,.

1008 .... C1008,que,S1,rr C1008,ont,S1,rr .... C1008,.

... ... .... ...

Total ... C.,que C.,ont ... C

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Methodology Part 1 - Capital investments by asset and province

2c. If no data available at the cell level, calculate the expected values by asset and province Ca,p,S1,e=Ca.*C.p /C

Asset Province

... Que Ont ... Total

1006 .... C1006,que,S1,e C1006,ont,S1, e C1006,.

1008 .... C1008,que,S1, e C1008,ont,S1, e C1008,.

... ...

Total ... C.,que C.,ont ... C

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Methodology Part 1 - Capital investments by asset and

province

3. Redo the steps 2a to 2c using Source 2 data.4. Take the mean of the two values obtained in

steps 2 and 3.

2

CCC rr S2, ,p a,rr S1,p, a,

rr p, a,

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Methodology Part 1 - Capital investments by asset and

province

5. Analysis Analysis using the time series. Biggest differences between the raking ratio values from

Source 1 and Source 2. Biggest differences between the raw data from Source 1

and Source 2.

6. Apply corrections if necessary. 7. Redo the raking ratio. 8. Repeat steps 5 to 7 until the results are satisfactory.

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Examples Ontario, asset 8001 (computers & related

equipment)

RAW DATA (source 1, source 2) RAKING RATIO (source 1, source 2, mean)

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Examples Ontario, asset 2602 (Sanitary & Storm

Sewers) RAW DATA (source 1, source 2) RAKING RATIO (source 1, source 2, mean)

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Methodology

Part 2:

Provide estimates on capital investment by asset, function and province

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Methodology Part 2 – Capital investment by asset, function and

province

Constraints:

Respect totals by asset and province derived in Part 1.

Try to respect local government data trends by function and province (source 2).

Capital Investment from source 2 might be different then the one derived in part 1.

Lack of data from source 2 for some years.

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Methodology Part 2 – Capital Investments by asset, function

and province

Process:

For each year, use ratio estimator to derive capital investment by asset, function and province using data from source 2 by respecting estimates by asset and province derived in part 1.

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Methodology Part 2 - Capital investment by asset, function and

province

rrp,a,S2p,a,

S2p,f,a,

rp,f,a, C C

C

C

1. Ratio estimator:

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Methodology Part 2 - Capital investment by asset, function and

province

2. If data from source 2 not available, use the mean of the ratio for years when source 2 is available:

3. Analysis and corrections by function and province. Similar to part 1.

C rrp,a,S2p,a,

S2p,f,a,rp,f,a, C

CC

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Examples Ontario, function 72 (regional planning and

development)

RAW DATA, RATIO ESTIMATOR

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Examples Alberta, function 22 (policing)

RAW DATA, RATIO ESTIMATOR

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Methodology Step 1 of the project completed:

Capital investment by asset and province and capital investment by asset, function and province from 1871 to 2003 in current dollars.

The subsequent steps performed to the data (but out of scope for this presentation) included:

Derive capital investment in constant dollars. Derive stocks in current and constant dollars. Estimates for years 2004 and 2005 Estimates for other government levels.

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Conclusion and lessons learned

Working with different sources, over a long period of time with many constraints, is feasible BUT:

Constraints to preserve totals:

Use of a raking ratio estimator

Use all sources available as long as they are relevant and comparable.

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Conclusion and lessons learned

Working with different sources, over a long period of time with many constraints, is feasible BUT:

Data quality issues:

CONSISTENCY : Make sure to work with comparable sources. If not, apply adjustments to reconcile them (such as different coverage, different assets, differences over time....)

RELIABILITY : Data confrontation is important to validate the

results and the data used (ex: time series, outliers,...).

LACK OF DATA : Strategy in place in case of lack of data.

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Conclusion and lessons learned

Working with different sources, over a long period of time with many constraints, is feasible BUT:

Analysis of the results

Use of experts who know the topic.

Use of tools to validate the results (ex: time series, outliers,...).

Correct the data and repeat the process when necessary.

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For more information / Pour plus d’information:

Papers / Articles:Papers / Articles: Daily (June 30, 2006) www.statcan.ca STC Analytical Paper – The Age of Public Infrastructure in

Canada (V. Gaudreault & P. Lemire, January 2006, cat no. 11-621-MIE – no. 035 )

STC Contacts: Methodology - Marie-Claude Duval, 613-951-7308

Gerrit Faber, 613-951-9438 ICSP, CES – Irfan Hashmi, 613-951-3363 PISP – Aldo Diaz, 613-951-8563

Peter Elliott, 613-951-4551