DATA ON RESIDENTIAL REAL ESTATE PRICES

REQUEST FOR INFORMATION (RFI) FOR DATA ON RESIDENTIAL REAL ESTATE PRICES FOR
STATISTICS CANADA

Date to Respond by: September 3rd, 2013

This is not a bid solicitation.  Statistics Canada is seeking feedback from the Industry with respect to the availability of data for residential real estate prices and dwelling characteristics.

Contents
1.	Introduction	3
1.1 Background	3
1.2 Overview	3
1.2 Objectives of the RFI	4
2. Instructions to Respondents	4
2.1 Nature of Request for Information	4
2.2 Response Costs	4
2.3 Treatment of Responses	4
2.4 Response Format	5
2.5 Numbering System	5
2.6 Enquiries	6
2.7 Submission of Responses	6
2.8 Contracting Authority	6
3. Questions	6
3.1 Scope	6
3.2 Methodology	8
3.2.1 Weighting	8
3.2.2 Land-Structure split	8
3.2.3 Constant quality price	8
3.3 Data quality and transparency of methods	10
3.3.1 Revisions and adjustments	11
3.4 Contractual agreements and intellectual property	11

1.	Introduction 
1.1 Background

Statistics Canada has been mandated by the government to collect, compile, analyse, abstract, and publish statistical information on the economic, social and general conditions of the country and its citizen.  Statistics Canada has also been charged with promoting the avoidance of duplication in the information collected by departments; and to promote and develop integrate social and economic statistics at the national and at each provincial and territorial levels, and to coordinate plans for the integration of those statistics.  

In January 2011 the Prime Minister launched the Red Tape Reduction Commission.  The Commission was asked to identify irritants to business and to make recommendations to ways to reduce the compliance burden without compromising the environment or health and safety of Canadians.  The recommendations were organized within five categories, of which two have direct implication on how Statistics Canada does business: cut the administrative burden that businesses have to deal with, which included cutting the information demands on businesses; and to cut the hidden burden when businesses have to contend with the demands of many different federal regulators.

This RFI is being put forward so that Statistics Canada can fulfill its mandate while respecting the recommendations put forward by the Red Tape Reduction Commission to avoid duplication and reduce the burden being put on respondents.  

1.2 Overview

Given the important contribution of the residential property market to overall economic activity and its role in trend analysis and policy making, Statistics Canada is assessing the feasibility of developing a more comprehensive residential property price index, which would better align with user needs and international guidelines. The main goal is to develop a residential property price index which includes both new homes and residential properties sold on the resale market. While Statistics Canada’s New Housing Price Index provides sufficient coverage of new homes, there remains a gap in the organization’s coverage of resale homes. Statistics Canada would like to explore the possibility of using existing data to close this gap, rather than imposing additional burden by collecting it. 

Statistics Canada is issuing a Request for Information (RFI) on the availability of data for residential real estate prices and dwelling characteristics. For the purpose of the RFI, residential real estate includes only those properties sold in Canada on the resale market (i.e. not new properties). Of interest are administrative data sets (micro data), which would allow Statistics Canada to produce a residential property price index. Statistics Canada is also interested in information about price indexes for residential real estate which are already being produced, as well as the methodology used to construct them. 

In responding to the RFI, information related to the questions below would be appreciated. Additional information relevant to the development and use of a residential property price index should also be included, particularly if it may impact the extent to which the data/indexes for residential real estate are available for third-party use. If possible, the information provided should be complete and not require referencing other material not included unless there is no other way of providing the information.  Wherever applicable, the information provided should go beyond what may already be publicly available, such as on a website. 

1.3 Objectives of the RFI

The purpose of the RFI is to help Statistics Canada in the evaluation of available price and dwelling characteristics data for residential resale properties, and in assessing the feasibility of developing a broader residential property price index covering both the new and resale housing markets. 

The objective of the RFI is to provide an opportunity for those interested to share information they feel Statistics Canada should be aware of for the development of a residential property price index. The information provided will be reviewed by Statistics Canada, as part of a process to determine whether available data could be used by Statistics Canada to measure price changes in residential real estate, rather than collecting new data. Further consultations or bid solicitations may follow.  
2. Instructions to Respondents

The following sub-sections provide specific instructions for respondents.
2.1 Nature of Request for Information
This is not a bid solicitation. This RFI will not result in the award of any contract; therefore, potential suppliers of any goods or services described in this RFI should not earmark stock or facilities, nor allocate resources, as a result of any information contained in this RFI. Also, the procurement of any of the goods and services described in this RFI will not necessarily follow this RFI. This RFI is simply intended to solicit feedback from industry with respect to the contents of this RFI.
2.2 Response Costs

Statistics Canada will not reimburse any respondent for expenses incurred in responding to this RFI.
2.3 Treatment of Responses

Use of Responses: Responses will not be formally evaluated. However, the responses received may be used by Statistics Canada to develop, evaluate or modify plans towards the development of a residential property price index. Statistics Canada will review all responses received by the RFI closing date. Statistics Canada may, in its discretion, review responses received after the RFI closing date.
Review Team: A review team composed of representatives from Statistics Canada will review the responses. Statistics Canada reserves the right to hire any independent consultant, or use any government resources that it considers necessary to review any response. Not all members of the review team will necessarily review all responses.
Confidentiality: Respondents should mark any portions of their response that they consider proprietary or confidential. Statistics Canada and its consultants will treat those portions of the responses as confidential to the extent permitted by the Access to Information Act.
Post-Submission Review Meetings: Statistics Canada may request individual Post-Submission Review Meetings with respondents to provide clarity on information provided. If required, these will be held at the most appropriate location, to be determined at a later date. The intent of these meetings will be to provide an opportunity for a face-to-face discussion with respondents. Although respondents may request a meeting, and their request will be considered, Statistics Canada will determine whether it requires additional information from any given respondent and will schedule meetings accordingly. All such requests, by respondents, should be forwarded to the Contracting Authority.
2.4 Response Format

Section 3 contains specific questions that are consecutively numbered. Respondents are asked to submit responses indexed by the specific RFI question number. Respondents are asked to repeat the question prior to their response for reviewer convenience.
Respondents are requested to submit one softcopy, in PDF format, of their response.
a)  Cover Page: If the response includes multiple volumes, respondents are requested to indicate on the front cover page of each volume the title of the response, the solicitation number, the volume number and the full legal name of the respondent. 
b)  Title Page: The first page of each volume of the response, after the cover page, should be the title page, which should contain: 
•	The title of the respondent’s response and the volume number;
•	The name and address of the respondent;
•	The name, address and telephone number of the respondent’s contact;
•	The date; and 
•	The solicitation number. 

2.5 Numbering System 

Each question has its own unique number. It is prefixed with “Q-“ followed by a sequence number (e.g. Q-1). Respondents are requested to prepare their response using a numbering system corresponding to the one in this RFI. All references to descriptive material, technical manuals, and any brochures included as part of the response, should be referenced accordingly. 
2.6 Enquiries 

Because this is not a bid solicitation, Statistics Canada will not necessarily respond to all enquiries in writing or by circulating answers to all potential suppliers. However, respondents with questions regarding this RFI may direct their enquiries to the Contracting Authority identified herein. 
2.7 Submission of Responses 

Respondents should send responses electronically via e-mail to the Contracting Authority's address identified herein by the date specified on the front page of the RFI. All requested information is to be provided to the Contracting Authority on or before the closing date. Statistics Canada reserves the right to accept late responses at its sole discretion.  
2.8 Contracting Authority 

Contracting Authority: X
E-mail Address: XXVV.XXVV@statcan.gc.ca 
Telephone No.: 
Facsimile No.:
3. Questions

This section solicits specific feedback on available data for residential real estate prices and dwelling characteristics. For the purpose of the RFI, residential real estate refers to residential property sold on the resale market. 
3.1 Scope 

Statistics Canada is looking for data on prices and characteristics of residential properties sold on the resale market. The data would be used by Statistics Canada to create a residential property price index.    

Q-1 What transactional level micro data are available for residential real estate property prices and characteristics? Under what conditions would Statistics Canada be permitted to access the source micro data in order to produce and publish a residential property price index?  Please indicate an estimate of cost. 

Q-2 What is the frequency of the micro data collection by the primary source (e.g., real-time, weekly, monthly, quarterly, yearly)? What is the time lag between when the data are collected and when they could be made available to Statistics Canada? At what point is the transaction price of the dwelling sold reported to the primary source (i.e. at point of sale, only after all conditions are removed, only upon registration of the property?) 

Q-3 Please provide a listing of all available data fields/variables on the micro data set.  For example: transaction price, house size, land size, etc. 

Q-4 What is the current coverage of the available micro data? Please include geography (i.e. national, provincial, territorial, regional, municipal) and dwelling types (i.e. single detached, semi-detached, townhome/strata, row unit and apartment-condominium), and any information about plans for expanding the coverage. 

Q-5 If the micro data cannot be accessed by Statistics Canada, are custom runs on the underlying micro data possible, for example to produce a price index using different weights (e.g., stock weighted instead of sales weighted), excluding new homes, by type of dwelling, etc.? Please indicate an estimate of the cost for this type of work.

Statistics Canada is also interested in information about price indexes which are already being produced for residential properties sold on the resale market. The index(es) could be used by Statistics Canada in the development of a residential property price index.
 
Q-6 What price indexes are available for residential real estate property? Under what conditions would Statistics Canada be permitted to use the index to produce and publish a residential property price index?  Please indicate an estimate of cost. 

Q-7 What is the frequency of the underlying transactional level micro data collection by the primary source (e.g., real-time, weekly, monthly, quarterly, yearly)? What is the time lag between when the data are collected and when the index could be made available to Statistics Canada? 

Q-8 Please provide a listing of all available data fields/variables used to produce the index.  For example: transaction price, house size, land size, etc. 

Q-9 What is the current coverage of the available index? Please include geography (i.e. national, provincial, territorial, regional) and dwelling types (i.e. single detached, semi-detached, townhome/strata, row unit and apartment-condominium), and any information about plans for expanding the coverage. 

Q-10 If the index covers less than the entire resale market, how are estimates adjusted or weighted in order to account for under-coverage?   Please include information about the source of the weights, and the frequency with which weights are updated or re-evaluated.  

Q-11 Are custom runs on the underlying micro data possible, for example to produce a price index using different weights (e.g., stock weighted instead of sales weighted), excluding new homes, by type of dwelling, etc.? Please indicate an estimate of the cost for this type of work.

3.2 Methodology

3.2.1 Weighting
Different methods of weight aggregation for residential real estate price indexes are used depending on the intended purpose of the index; one method represents the stock of residential housing at a particular moment in time and another method represents sales that took place during a particular period of time.  
Q-12 What method of aggregating price index components is used in the available index?  Please submit a detailed description of the following: how prices are weighted by dwelling type, by sub-section of the city, at the city level and at the composite level. 
3.2.2 Land-Structure split

One requirement of a residential property price index is that it can be split into a land component and a structure component.  The price of land is not always available, but methods exist to derive it from the total. 

Q-13 Can the available index be split into a land and a structure component? If yes, please describe the method(s) that allow the index to be split by land and structure. 

3.2.3 Constant quality price

The measurement of housing prices over time is not an easy task.  With the exception of new housing development projects, it is rare that two houses with the same characteristics will be sold in the same location month after month.  To ensure that constant quality price indexes are constructed, different methods can be used to address this issue, including a matched model, hedonic regression, repeat sales, model pricing and appraisal methods. 

Q-14 Which methodology for quality adjustment is used in the index? How long has it been in place and how often is it reviewed? 

Do you quality adjust using a repeat sales method (wholly or in combination with another quality adjustment method)? If yes, please answer Q-15.

Q-15 Please describe the specific methodology and procedures of the repeat sales method, including steps taken to mitigate influencing factors (e.g., renovations, housing depreciation).  How are month-to-month index values calculated?  How are structural changes in the industry noted and accounted for in future estimates (e.g., changing desirability of specific neighbourhoods). Please provide examples wherever possible. 

Do you quality adjust using a hedonic method (wholly or in combination with another quality adjustment method)? If yes, please answer Q-16.

Q-16 Please describe the specific methodology and procedures of the hedonic method. How is the model specified? What is its functional form and the method of estimation (e.g., OLS, GLS, bootstrapping, etc.)? Please provide examples wherever possible. In addition: 
•	What type of hedonic model is used? Does it use panel data with or without time dummies?  
•	If a hedonic imputation model is used, please provide details, including about prior stratification and number of observations.  
•	If summary regressions are run, how many years do the data span and what can be said about the appropriateness of this time span?  
•	Is one hedonic regression run on the entire dataset or are separate regressions run on criteria that can be described in detail, such as to reduce heterogeneity?  
•	If the method relies on “benchmark” models where average criteria of a neighbourhood get used, please describe how the benchmark was determined (including for land).  How often is the benchmark model reviewed/modified? 
•	How are month-to-month index values calculated? How are structural changes in the industry noted and accounted for in future estimates?

Do you quality adjust using a mixed method (e.g., a hybrid method that combines features of hedonics and repeat sales)? If yes, in addition to the above, please also answer Q-17.

Q-17 Please describe the rationale for using a mixed or hybrid model, and its mechanics in terms of processing, quality adjustment, imputation methods and index generation.

Do you quality adjust using a method other than the ones listed above? If yes, please answer Q-18.

Q-18 If a method other than one listed here is used, please describe the methodology in detail, including how a constant quality index is achieved.  
3.3 Data quality and transparency of methods
Statistics Canada, as a professional agency in charge of producing official statistics, has the responsibility to inform users of the concepts and methodology used in collecting, processing and analyzing its data, of the accuracy of these data, and of any other features that affect their quality or "fitness for use". 
The Policy on Informing Users of Data Quality and Methodology stipulates that ‘Statistics Canada will make available to users indicators of the quality of the data it disseminates and descriptions of the underlying concepts and methodology’.   
Q-19 How are the following quality dimensions measured for the available data/index: relevance, accuracy, timeliness, accessibility, interpretability and coherence? Please describe the steps taken to ensure the quality of the micro data, including data editing and imputation. 

Q-20 Could Statistics Canada be granted regular access to the data/index to certify the quality and methods? Could Statistics Canada publish documentation for users under the Policy on Informing Users of Data Quality and Methodology (this includes, where applicable, notes to users, data sources, concepts and variables, data accuracy (coverage error), additional documentation?

Q-21 In the case of data, could Statistics Canada be granted regular access to information on: 
•	the data sources;
•	the purpose for which the data were originally collected;
•	the merits and shortcomings of the data for the statistical purpose for which they are used (in terms of conceptual and coverage biases);
•	how the data are processed after being received, and what if anything is done to correct problems in the original data set;
•	the reliability of the estimates, including caveats where necessary? 

Q-22 In the case of index numbers of prices, could Statistics Canada be 
granted regular access to information on: 
•	any substitutions made in developing the estimates; 
•	product changes and changes in product quality;
•	precise definitions of the underlying economic concepts that the index numbers are intended to measure;
•	the methodology adopted (index formula, weighting system, computation of the index at various aggregation levels, basing, re-basing, linking of indexes)?

 3.3.1 Revisions and adjustments 

	Q-23 What revision policies are currently in place for the available data/index? Please include information about what data are subject to revision and why, as well as a description of benchmarking, calendarization or seasonal adjustments made to the data and their impact. 

3.4 Contractual agreements and intellectual property

Q-24 What type of long-term arrangements are in place with data providers to ensure the continuity of data delivery?

Q-25 Please describe any issues related to intellectual property of the underlying micro data or index, and how those could be addressed.  For example, are there any clauses in agreements with data providers that could prevent sharing of micro data with a third party organization such as Statistics Canada?