December 2022

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CENTRE FOR
THE STUDY
OF LIVING
STANDARDS

The Potential for National Statistics
to Transform Social PolicyPeter Hicks
CSLS Research Report 2022-07
December 2022

The Potential for National Statistics to Transform Social Policy

Table of Contents
I. Abstract ..................................................................................................................................................... 2
II. Executive Summary ................................................................................................................................. 3
III. Introduction............................................................................................................................................. 5
IV. Measuring how Programs Affect the Quality of Life ............................................................................. 5
V. Examples of Future uses in Program and Policy Applications ................................................................ 8

1. Uses in Retrospective Evaluations .......................................................................................... 8
2. Matching People with Available Services .............................................................................. 8
3. Feedback Loops to Support Continuous Improvements in Program Design and Delivery .. 10
4. Future Program Designs and ‘What if’ Analysis .................................................................. 10
5. Policies Aimed at Higher Level Objectives .......................................................................... 11
VI. Traditional System-Wide Analysis will also be Strengthened ............................................................. 12VII. Partnership will be Essential ............................................................................................................... 12

1. Partnerships with Program Departments in all Jurisdictions ................................................ 13
2. Partnerships with Researchers .............................................................................................. 14
3. Flexible approaches are possible .......................................................................................... 14
VIII. Conclusion ......................................................................................................................................... 15
References................................................................................................................................................... 16

1

The Potential for National Statistics to Transform Social Policy
Abstract
Statistics Canada is considering radical improvements to its system of national social
statistics in order to strengthen the evidence base for traditional social research and analysis and,in addition, to enable a major shift towards evidence-driven social policies and programs. These
new uses have the potential to allow social programs to be designed, administered, revised, andevaluated based on evidence of what has worked best for program recipients in similar
circumstances in the past. These include applications that will assist in referring individuals to
those social program interventions that are most likely to meet their own needs and aspirations,regardless of the department or order of government that offers those programs. They will allow
policies to focus on higher order objectives such as improving quality of life at the level ofindividuals.
Existing social statistics are structured according to data sources, such as surveys,
censuses or administrative records. The system being envisaged would be based on an integrated
model of society that shows how individuals interact with social institutions, including social
programs, over the course of their lives. The data will be drawn from multiple sources includingfrom individuals and from many administrative files that can be linked for particular applications
using techniques that protect privacy and confidentiality. Development will be gradual anduneven across the different domains of social policy. Success will rely heavily on new forms ofpartnership among the national statistical office, program departments and the researchcommunity.

2The Potential for National Statistics to Transform Social Policy
Executive Summary
Statistics Canada is planning major changes for the system of national social statistics.
Existing social statistics are still mainly organized in separate compartments based on the sourceof data, such as surveys, censuses and administrative records. The changes being considered
involve a radical shift towards an integrated system based on data on how individuals interact
with each other, and with social institutions and social programs, over the course of their lives.
The data would be drawn from multiples sources including many administrative records as well
as directly from individuals using existing and new surveys, censuses and, perhaps, newer
technologies. These rich data sources could be linked for particular applications using
technologies that protect privacy and confidentiality.
The new approach would greatly strengthen the base of evidence for existing social
research and analysis. The new statistical evidence would be granular and timely. It would allow
deeper analysis of issues related to equality and sustainability, including analysis at the level ofsmall at-risk groups. The longitudinal nature of the data would allow new kinds of causal
analysis. It could, for example, allow comparisons of the previous and subsequent characteristics
and experiences of the participants in particular programs with those of non-participants withsimilar characteristics and in similar situations. This information would allow analysis of which
programs are working best, for whom, and in what circumstances.
The paper provides examples of how the new ‘what is likely to work best’ evidence could,
over time, result in major improvement in the effectiveness of social policies and the efficientadministration of social programs. It shows how the eventual result would be a shift to evidencedriven, transparent, individual-driven policies and programs.
For example, the design of new programs could be greatly improved by the ability to use‘what if’ modelling that would shows the likely effects of using different program design
characteristics or of possible future changes in the characteristics of the individuals being served.
Existing programming could be continuously adapted based on current information about which
program features working best for which clients. Some program evaluations already use ‘what is
likely to work best’ analysis, but their power would be greatly improved by new statistics on amuch wider range of factors that could affect program outcomes.
A particular powerful and visible program application will be ability to use ‘what is likely
to work best’ evidence in referring individuals to the available social interventions that are most
likely to meet their needs and aspirations. In many cases this kind of information could be
provided directly to individual citizens over the internet. As well, a new kind of casemanagement or referral function could emerge that would guide people, particular those at risk,
to mixes of interventions, including those provided different departments and jurisdictions.
More generally, the objective of social policies has always been to improve the quality oflife for society as a whole and for specific individuals. However, it has not been possible todevelop practical, empirically-based planning and accountability systems that could measures
how programs affected quality of life for individual participants. For example, an individual’s
quality of life will be affected by the combined effects of their participation in a range of social
3

programs from all orders of government as well as an even wider range of social factors
unrelated to government programs. The evidence was not there to sort out the effect of any
particular social program. Policies, in consequence, have often tended to reflect the needs andaccountability requirements of those who administer the program, rather than those who use theprogram. The new statistics hold much potential to, over time, sort out the role of different
programs in affecting the lives of participants and, hence, to enable the development ofaccountable, evidence-driven, people-centric policies and programs.
The paper describes why progress in the new directions will be gradual and uneven. An
obvious factor is that a national statistical agency, acting by itself, has neither the mandate nor
the knowledge to engage in direct program applications. Progress will depend heavily on thedevelopment of new partnership relationships among the statistical office, program departments
and the research community. The paper provides examples.

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The Potential for National Statistics to Transform Social Policy1
Introduction
This report contains five major sections. The first section discusses measuring how social
statistics programs affect quality of life. Then, this report provides examples of future uses ofsocial statistics in programs and policy applications. The third section examines how traditional
system-wide analysis will also be strengthened by social statistics. Lastly, this report discusses
how partnerships will be essential and finally moves into the conclusion.
Statistics Canada is considering changes to its social statistics that could, over time,
provide the evidence to radically improve the effectiveness of social policies and programs.
The purpose of this article is to explain to policy-makers, and to social policy analysts
and researchers, how the social statistics of the future have the potential to shed new light on thecauses of social well-being, how that information could in turn help transform social programs
and policies, and why partnerships will be essential to realize the full potential of the newstatistical products.
In addition to their use in policy-making and program administration, the multi-sourced,
integrated system of social statistics that is being envisioned has the potential for payoffs inmany other areas. These are summarized in Box 1 on page 3, along with background information
about the new directions being considered by Statistics Canada.

Measuring how Programs Affect the Quality of Life
Existing social statistics are based onparticular data sources such as surveys,
censuses, and administrative records.
The new developments being consideredby Statistics Canada will draw on datafrom multiple sources to better reflectsocietal interactions in a wide range ofsocial domains. These include health,education, labour markets, income,security, and other domains that
contribute to a high quality of life. The
new data sources include a more flexible
suite of surveys, more detailed
information drawn from administrative
records, and potential new sources based

The data needed to understand how programs affect quality of life
The new capacity for measuring the determinants of a better qualityof life for individuals results from the collection of linkablelongitudinal microdata.
• Microdata are simply the various pieces of information about aparticular individual or a particular program that are collectedfrom the individual or from an administrative data file.
• Longitudinal microdata describe the characteristics of the same
individual at different points in time.
• The adjective ‘linkable’, rather than ‘linked’, refers to the use ofprivacy-protecting statistical techniques that eliminate the needto create a master file that contains linked data about particular
individuals. It also refers to the need for consistent standard
definitions of all the data in the system, a prerequisite for quality
when combining data from various sources.

1

Peter Hicks is a social policy advisor who, in 2020 and 2021, helped Statistics Canada develop its strategic plans
for future directions in social statistics. This article, however, represents his own views, which may not necessarilyreflect the views of Statistics Canada. The authors thanks Michael Wolfson and an anonymous referee for usefulcomments. Email: peterhicks@sympatico.ca

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on social media and related technologies. The sidebar provides a technical description of the datathat will be collected.
The microdata referred to in the sidebar include:••

Characteristics that contribute to an individual’s quality of life including income, wealth,skills, health, safety, social contacts, and perceived well-being.
The characteristics of tax provisions and social programs, including the nature of thebenefits that are delivered and the cost of providing them.

The longitudinal nature of the data holds the potential to enable the kind of causal analysis
that was formerly limited to independently-designed experiments, trials and evaluations that used
control or comparison group techniques. That is, the future statistical system could allow
comparisons of the previous and subsequent characteristics and experiences of the participants inparticular programs with those of non-participants with similar characteristics and in similar
situations. This information would allow analysis of which programs are working best, forwhom, and in what circumstances.
Causal analysis based on longitudinal microdata is already in use in related applications. For
example, Employment and Social Development Canada has developed techniques that use datafrom multiple sources to infer the impact of adult training and other employability interventions
on the subsequent employment and income of those who participated in those programs, as wellas their subsequent use of income security programs. This information has been used in referring
clients to available interventions and in sophisticated evaluations of the provincial and territorial
programs that deliver these services.
Through tools such as its Social Policy Simulation Database and Model (SPSD/M), Statistics
Canada already provides users with the statistical capacity to examine the effects of a variety ofincome support programs. These include refundable tax credits and pensions whose outcomescan be measured in terms of changes in income such as reducing poverty, maintaining living
standards or reducing income inequality. The new capacity would, over time, allow a comparable
examination of the effects of programs that provide services and of mixes of income support andservices. It would allow an examination of the effects of programs on a broad range of qualityof-life outcomes, not only income.
The use of the conditional tense throughout this article reflects three important caveats about
future directions.
•First, and obviously, are the inevitable risks in attempting to predict what will happen in
an uncertain future. The pace of change in social statistics is particularly striking as is
illustrated by recent developments such as the use of waste water as a source of healthstatistics, the use of web-scraping techniques for statistical purposes, the widespread useof personal monitoring devices which have much potential as a source of future statistics,
and the increasingly sophisticated techniques being used in big data analysis.

•

Second, Statistics Canada is, justifiably, cautious in moving in directions that, if not
managed carefully, could be seen to be intrusive and that might erode trust in thestatistical system. Statistics Canada is using world-leading techniques to assess the social
acceptability of statistical initiatives. It is referred to as the Necessity and Proportionality
Framework and is designed to protect privacy and confidentiality, provide transparency
and to balance issues related to response burden and the importance of the statistics that6are produced. The use of this framework means that progress on some fronts may beslower than that suggested by analysis based only on technological considerations andthat some initiatives may not advance at all if there are concerns about their social
acceptability.
Box 1. Future Statistical Directions
The Statistics Canada initiative is described in two
technical reports which are found on their website:

addition of new kinds of data that explore even moredimensions of the quality of life in a way that can be
integrated with existing data. An example would be dataobtained from a sample of individuals who volunteered
to provide information collected using personalmonitoring devices, on the proviso that this information
would never be made public. These could gather detailed
information about health status, mobility, stress, andsocial contacts.
Current stage of development
Some of the features of the new system are already in place:• The System of National Quality-Of-Life Statistics:
Future Directions which outlines the rationale for theapproach and describes the features of the proposedsystem as they might look some five to ten years in the
future. It describes the changes that need to take place in
the inputs to the system (the many new sources of datathat will be used), the processes used to analyse the vast
amount of new data in ways that protect privacy, the
new statistical products that need to be available, andthe new uses of those data products, including direct
uses by citizens.

• Statistics Canada has many linkable databases drawn
from different administrative and survey sources that
describe the characteristics of individuals.

• The System of National Quality-Of-Life Statistics:
Conceptual Framework which provides historicalbackground to the proposed approach and describes
standard ways of describing inputs to the new system(individual data items from multiple sources) and how
they are consistently used to produce outputs(indicators, dashboards, supporting tables and microdata
files).
The potential power of a multi-source system
The current article describes the payoffs of the shift to a
multiple-source, more integrated, statistical system inproviding new kinds of causal evidence to support policymaking. The two reports above describe additional payoffs
from such a shift:• Several techniques are used, and more are being
developed, to protect privacy when information isgathered from various sources, including stripping out
individual identifiers, data masking and the creation ofsynthetic individuals.
• Data from tax files is used to supplement informationcollected from individuals on surveys and censuses.
Crowd-sourcing and web-scraping have been used asdata sources.
• A strong capacity has been developed for modelling(SPSD/M) the impacts of major tax provisions andspending programs that determine disposable incomesof individuals, without providing personal information
about any particular individual.

• Information about a much wider range of social topics
can be produced, with the results becoming available
quickly and at a fine level of detail.

• A more flexible household survey capacity has beendeveloped that provides new information quickly.

• Consistently-defined and partially-overlapping
microdata gathered from many sources enable thestatistical system to create reassuringly strong quality
control mechanisms, along the lines of double-entry
bookkeeping systems.

• Data describing small, and often vulnerable, populationgroups is becoming increasingly available through what
is called the Disaggregated Data Action Plan.
• A Quality of Life Hub can now be accessed on theStatistics Canada website that, in its current version,contains key indicators of social well-being and thatwill, in the future, provide additional data and ways ofvisualizing the data.

• Powerful new statistical products, including tables anddashboards of indicators, can be tailor-made to meet awide range of policy and program agendas.
• Linkable microdata from multiple sources allow for the•Third, in many areas, progress will depend on the support of other organizations that may
have competing goals. This is particularly the case for social programs which are, inmany cases, delivered by the provinces and territories. Arrangements for the sharing and7use of statistical evidence in these areas have typically been shaped by broader
jurisdictional as well as by data considerations. The need for new partnershiparrangements is discussed later in this article.

Examples of Future uses in Program and Policy Applications
This section of the article describes the program-related uses of the social statistics that
could become available in the future, including uses by governments, by non-governmental
agencies that deliver social services, and by the individuals who benefit from these programs.
Statistical information about likely impacts can be used as programs are designed and as they
develop and are adjusted over time. That information can also allow policy objectives to be
reframed in a way that is more closely aligned to their ultimate objective of enhancing quality oflife.

Uses in Retrospective Evaluations
The comparison group techniques referred to above are already used in some evaluationsof program effectiveness. However, there will be major additional benefits if national statistics
also support the use of these techniques.
For example, evaluations can benefit from the availability of information about a wider
range of factors that can affect outcomes. In the case of employability interventions, this could
include information about changes in the local job markets where individuals live. As well,evaluators would have access not only to information about the particular program intervention
in question, but also to information about the individual’s participation in other interventions that
could shape outcomes, both previous and subsequent to the program being evaluated.
Other benefits relate to timeliness, ease of use and support of multiple applications.
Traditional evaluations involving comparison groups are often complex to design and conduct.
They often require the use of multiple administrative files to examine how the future unfolds forboth program participants and non-participants. They are typically undertaken infrequently,
require a high level of expertise to conduct, and have results that are often only available someyears after the interventions took place. Incorporating this capacity within the system of national
statistics would allow the data to be produced quickly and inexpensively, including in a wide
variety of related applications.

Matching People with Available Services
Access to many social programs is straightforward or automatic, as is the case with those thatprovide refundable tax credits, Old Age Security, or services such as elementary and secondary
education. However, there is still a vast array of community, health, and other social services
where enrolment is not automatic and that are accessed on a one-by-one basis by individuals whohear about them from various sources, often based on recommendations from people they know.
Often eligibility criteria are complex with no simple way of determining which of the options
that are theoretically open would best meet the needs of that individual.
In some cases, the organization offering the service provides a referral function to help peoplechoose among the options they offer. Other agencies may have a gate-keeping, triage function
8

when the number of applicants exceeds the availability of the service being provided. In still
another model, individuals are referred to a service by a third party such as a case manager,
counsellor, or family doctor. And, of course, in many cases people do not access services
because they do not know they exist.
Over time, all of the ways of accessing services could be supported by a new system of nationalsocial statistics. Using techniques similar to those used in the retrospective evaluations discussed
above, the system could provide information to service delivery agencies and their clients on
which of the available services are likely to obtain the best results for particular individuals
based on what has worked best in
similar circumstances in the past. The
New referral tools could build public support and trust
results would be made available overIf developed carefully, consistent with Statistics Canada’s social
the internet to the referral agent and/or
acceptability criteria, the referral tools described in the text could build
the individual applicant at the time
public support and trust for both the programs that use them and forwhen the actual choices were being
the statistical system.
made.
The new information is likely toreshape the way in which people arematched with programs:••

It would support the growth of
an independent casemanagement function whereindividuals with the greatest
needs are referred to the service
most likely to be effective (or,often, a combination of services
and income supports) bycounsellors who have access toevidence on what is likely towork best, regardless of whooffers the service.

• They would result in programming that is both efficient and more
responsive to the diverse needs of individual Canadians, including
those who now feel alienated by standard, often-fragmented
programs that do not reflect their individual circumstances.

• Individuals would, over time, have access to a quite new ‘what is
likely to work best’ statistical information product that would help
them in making life choices. People would be able to see thebenefits of the statistical system in a much more direct way than iscurrently possible. This could, in turn, help improve response rates
to surveys and encourage participation in newer forms of datacollection such as the privacy-protected use of personal monitoring
devices.
• People would have a greater voice in the design of the programs
that affect them. The referral tools being discussed here should be
developed through the use of pilot studies that would involve
consultation with the individuals who participate in those pilots andwith community and other groups who advocate on behalf of people
who are not well served by existing siloed programming. Similarly,
ongoing programming would evolve, as described later in the text,
based on feedback loops that include input from people who
participated in those programs.

The same information would
allow individuals, acting on
their own, to learn what
services exist and which are
likely to work best for them given their needs and interests.

In other words, most people would have direct access to better evidence when choosing services,
thereby reducing the need for a separate referral function. On the other hand, those who need themost assistance would be supported by a more knowledgeable counsellors who can access awider range of services, including practical limitations in accessing some services such as longwaiting lists. As shown in the sidebar, these are changes that could, over time, result in deep
improvements in the way in which governments support citizens in improving the quality of life
in Canada.
It will be important to manage expectations about the use of this kind of technique for matchingspecific people with programs using predictive analytics. It will be useful in many applications
9

but not all. Some potential applications may never even be tested if they fail to meet the criteriaof social acceptability discussed earlier.
As well, the complexities and uncertainties that exist in the real world will often be too great toallow good quality ‘what is likely to work best’ calculations for particular individuals atparticular points in time. However, even here, agencies that offer, for example, labour market
information will be able to provide useful aggregated information obtained from the statisticalsystem. In the case of the employability interventions referred to earlier, it would be possible forindividuals to receive labour market information over the internet about job vacancies, futureskill needs and available training options, as well as information about which kinds of jobseeking or training have, on average, worked best in the past. These averages will often be
available for local areas and small population groupings that are of most direct interest to theindividual in question.

Feedback Loops to Support Continuous Improvements in Program Design and
Delivery
The statistical techniques used to help match specific people with specific services could also be
used to provide program agencies with the information needed to improve the efficiency andeffectiveness of program designs and to improve service quality. Feedback loops would provide
program managers and designers with current information on what aspects of programs areworking best for whom and at what cost. Program participants could also be asked to provide
feedback.
Such feedback would support continuous evidence-driven incremental changes in program
designs and delivery mechanisms. This would be in contrast to traditional arrangements where
programs which often remain unchanged for lengthy periods of time. Today, when reform isclearly needed, entirely new programs are often introduced, often with benefits that are not fully
integrated with programming provided by other agencies.

Future Program Designs and ‘What if’ Analysis
The statistical techniques used in the retrospective and current applications above could also be
used to plan and design future programs given assumptions about future needs andcircumstances. That is, there would be a capacity to undertake powerful ‘what if’ analysis to
examine the effects of different program designs and different assumptions about future
conditions. This would be similar to the existing microsimulation capacity that allows ‘what if’
analysis of income support programs. It would, of course, be more powerful in that it could beapplied to service programming. It would also allow analysis of the effects on a range of higherlevel outcomes, in addition to changes in income.
Particularly important, such applications have the potential to allow planning and design work totake account of the effects of potential changes on other related programming – helping breakthrough the rigidities of existing program and jurisdictional silos.
As is the case with all the program applications discussed in this article, progress in developing
statistical information about the combined effects of different programs options will be gradual.
This is unfamiliar territory both for those who fund and manage existing programs and foranalysts and researchers in different disciplines. Crossing entrenched program and jurisdictional
10

boundaries will require new partnership arrangements. As will be discussed later, the national
statistical agency could play a strong role in developing these partnerships.

Policies Aimed at Higher Level Objectives
It is not only the design and delivery of programs that will be improved by a new approach tosocial statistics. The ability to measure the effects of programming on quality of life would also
allow the underlying policies to be framed in terms of higher-level objectives, closer to the true
purpose of those policies.
At least at the level of rhetoric, the social policy literature is clear on needed future directions.
For example:•

Social interventions should support people in the diverse ways in which they develop
their capacities and seek well-being over the course of life. For example, the literatureoften calls for a shift from disease-centred healthcare to people-centred health andwellness – or from curriculum-centred classroom education to student-centred learning.

•

The interventions provided by different agencies and jurisdictions should be integrated
and readily accessed in a way that respects human diversity and dignity. This is incontrast to much existing programming which has often been designed to provide
accountability and efficiency within the various program silos – resulting in a system
where it is often left to individuals to navigate a labyrinth of uncoordinated andoverlapping income support and service programs.

•

Planning, budgeting, and accountability arrangements should be transparent, incorporate
the views of those who will be affected by the policy, and designed to show how
programs contribute to the various dimensions of the quality of life.
•

This is in contrast to existing arrangements which are often limited to tracking
costs and monitoring outputs (such as the number of participants served).

•

Existing performance measures are mainly limited to the economic, dollar-based,
dimensions of quality of life and often ignore those dimensions related to health,skills, security, social contacts, and perceived well-being.

•

Current decision-making about policy directions and program designs is often felt
to be opaque, without input from the individuals who are the intended
beneficiaries.

There has been much reform effort over the decades to promote these newer directions.
However, progress has been slow and many of the expectations surrounding past reforms havenot been met. A basic problem has been that the underlying data have not been available tosupport planning, budgeting and accountability systems that reflect the higher-order goals thatare real purpose of the policies in question.
The system of social statistics that is being proposed would provide detailed measures not only
about the immediate costs and effects of programs but also about their longer-term effects of on
the quality of life of individual program recipients. It would enable comparisons of different
programs based on their costs and longer-term outcomes. That is, it would enable thedevelopment of the planning, budgeting, and accountability regimes that are needed to support
people-centred, integrated, evidence-driven social policies.
11

It will, of course, take time to develop the needed data. Progress is likely to be uneven acrossdifferent social policy areas. It will require political will to develop ways of designing anddelivering programs that transcend traditional boundaries.

Traditional System-Wide Analysis will also be Strengthened
In addition to the new program and policy applications discussed above, the future directions insocial statistics that are being considered have the potential to strengthen the traditional work ofnational statistical offices in supporting the social analysis and research carried out by
governments, interest groups, think tanks, and researchers. Researchers inside Statistics Canada
can play a leading role in undertaking such analysis. For example, a 2022 Statistics Canada
research report, The impact of firm closures and job loss on participation in gig work: A causal
analysis, uses the potential of longitudinal data drawn from multiple sources (in this caseincluding census records) to carry out causal analysis.
In particular, the new statistics will support deeper and more integrated analysis of both equality
and sustainability:•

A social statistics system based on linkable, longitudinal microdata is well suited tosupport analysis of the many forms of inequality that exist among individuals and the roleof social programs in lessening (or reenforcing) those inequalities.

•

Data showing the effects of social programs and institutions on the subsequent lives ofindividuals can also be used in analysis of different dimensions of sustainability such as
the causes of change in levels of human, financial and social capital.

•

Microdata will enable analysis at the level of small population groups and small
geographic areas, better reflecting the diversity of the population.

•

Linkable, longitudinal microdata will allow analysis that crosses traditional boundaries,
for example showing how the health, educational, labour market and family dimensionsof life are inter-related.

Partnership will be Essential
The proposed use of the statistical system to produce evidence about how social interventions
affect quality of life is likely to result in a blurring of the mandates of the statistical office and ofboth program deliverers and the traditional analytic/research community.
For example, the traditional role of the national statistical office is to offer potential users a set of
products, such as tables or ways of accessing microdata files, along with needed explanatory
material. Users could apply those products as they saw fit, typically with minimal further input
from the statistical agency. The future is likely to see more partnership arrangements where boththe statistical office and the program organization, and researchers, work together in designing,
testing and, in some cases, in the ongoing operation of applications that make use of the newstatistical products that are being proposed.

12Partnerships with Program Departments in all Jurisdictions
The potential for using statistical information in the program and policy applications discussed
above requires consistently-defined information about the characteristics of programs andprogram participants and consistent ways of measuring outcomes.
The existing statistical system does a good job in supporting such consistent analysis of theincome support programs and tax measures of all jurisdictions. The products, or benefits, ofincome support programs are easy to describe and measure. However, the benefits of service
programs, such as those that provide education or social services, will need to be described in aconsistent fashion and at a much finer level of detail than now exists.
Developing and collecting such consistent, detailed information about service programs can only
be done in partnership with the agencies, mainly in provincial/territorial jurisdiction, whichadminister these programs. The value of pan-Canadian approaches to sharing administrative data
about services has long been recognized. In many social areas, sharing arrangements alreadyexist between Statistics Canada and the provinces and territories. There will, however, be large
payoffs, as well as operational challenges, in developing new arrangements where administrativeand other data can be directly used in improving the programs that supplied that data.
The nature of the partnership arrangements will depend on the application in question. For
example, Box 2 describes the consideration that should be taken into account in developing
partnerships to support ‘what is likely to work best’ referral applications.
Box 2. Partnership with Program Agencies in Referral Applications
Likely the most complex partnership arrangements will bewith the program agencies (mainly in areas of provincial andterritorial jurisdiction) that will use ‘what is likely to work
best’ data in referring people to their services.

• In some cases, it might also be best placed to
manage follow-up surveys with program
participants, where it could be seen a neutral,
trusted player.

• The program department in question would, of course,
continue to be responsible for the entire operation of that
program. It has the mandate and budget for delivering
the service or income support in question, for identifying
what services are potentially available, for making actualreferrals, for providing advice to clients, and formaintaining administrative data.

• In all cases, it will want to highlight its independentrole in ensuring the social acceptability of thestatistical dimensions of the application, including
protecting privacy and confidentiality.

• However, the statistical office should also play an
independent supporting role in the development of thepractical referral tools. It has the mandate and capacity tomaintain, process and protect much of the data used in
making the ‘what is likely to work best’ calculations.
These data will often be obtained from sensitive sources
such as surveys, tax files and the administrative records
of other departments or jurisdictions.
• The statistical office will often be best placed todevelop and explain the quality of these calculations
and how they should be interpreted by users.

• There will be a large overlap in the ‘what is likely towork best’ data and referral calculations used in social
programs administered by different agencies. The
direct involvement of the statistical agency can ensure
the needed consistency and can assist in the efficient
sharing of data and experience across a variety of
applications in different agencies.
• Both the program and statistical agencies will also use
the same micro databases and techniques in otherapplications within their mandates. These include, forexample, evaluation and program design applicationsin program departments, and producing a range ofaggregated social statistics in the case of the statisticalagency.

A main message from Box 2 is that a single program or jurisdiction, acting in isolation, could not
realize the full payoffs of the newly-available ‘what is likely to work best’ evidence described in13this article. The national statistical office, or its equivalent, must be directly involved. Only it has
the expertise and authority to develop the needed socially-accepted statistical tools and to ensurethat statistical evidence developed in one area can also be used in a wide range of otherapplications.

Partnerships with Researchers
In addition to partnerships with program organizations, it will be important to develop strong
partnership arrangements with analysts and researchers in academia, think tanks, program
departments, and international organizations to develop the statistical tools and processes thatwill be needed to fully realize the potential of the proposed new directions.
Box 3 describes two complex, longer-term examples. However, partnership is also needed on a
range of more immediate tasks. For example, the background papers referred to in Box 1 show
why shifting to a multisource system requires the development of standard, or ideal, definitionsof all variables in the social statistic system – definitions that are based on a model of society,without any reference to the source of that data. In the case of existing data, this will largely be amechanical exercise since it will be important to ensure the continuity of existing time series.
However, the external research community, including those in different academic disciplines,
should be involved in this process since the standard definitions chosen will influence the content
of data that will be collected in the future.
Partnership arrangements with external research community can also be used to help address a
key resource problem. This is the lack of staff with the skills needed to carry out the complex
technical work associated with development and application of the new statistical tools. We areat a stage of development where users of the new analytic tools will need a set of skills that issimilar to the skills needed to develop those tools. There would be high payoffs frompartnerships that would result in sharing of existing expertise and increasing the supply of skilled
analysts for the future.

Flexible approaches are possible
Establishing the partnership arrangements discussed here – and developing complex statistical
tools such as those described in Box 3 – will be difficult and will take time. Fortunately, thiswork can be conducted gradually and flexibly. The speed of reform can be quite different indifferent areas of social statistics. In some areas, such as statistics related to income, or theassessment of employability programs referred to earlier, much of the development work has
already taken place. In other applications, development will continue for many years, reflecting
the priorities associated with the uses of the new data and the resources available to conduct theneeded development work.
A system based on microdata is inherently flexible. It makes efficient use of whatever data are
there, from all sources, including data that is limited to certain groups or geographic areas orreference periods. The same items of data can be classified in different ways depending on theintended use, both existing uses and new uses. A microdata system allows for trial-and-error
learning where this is appropriate, including the use of pilot studies. It is consistent with different
partnership arrangements.
And, as also described in Box 3, lessons can be learned from similarly difficult challenges thathave been addressed in the past.
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Box 3. Partnership in Developing Statistical Tools
The box describes two of the most complex statistical projects
that will be needed over the coming years and shows why
partnerships with the research, pan-Canadian and international
communities will be needed for successful implementation.
Linking data about activities to measures of quality of life
There will be a new need to classify the detailed activities inpeople’s lives in a way that allows analysis of the effects of
those activities on different dimensions of the quality of life.
For example, they would show how the various activities thattake place during the course of a day or year add to, or
subtract for, people’s human capital (particularly their healthand skills) and social capital.
The resulting system for classifying activities would provide aparallel to existing economic classifications that show how
dollar transactions are linked to changes in an individual’s
financial capital and economic well-being.
Developing standard ways of linking activities to various
forms of human and social capital would be most useful insocial research generally, not only in policy applications.
Accordingly, there could be high payoffs from strong
partnerships with the broader research and academic
communities and with international bodies in theirdevelopment.
There is also a need for more frequent collection of highquality information about these detailed individual activities.
Part of the solution may be more frequent time use surveys.
However, new approaches will likely also be needed,
including exploring the use of personal monitoring devices to
produce information related to physical activity, the locationof activities, interactions with others, stress, and other healthmeasures. Partnership with organizations who have had moreexperience in these applications could be useful.
Linking point-in-time and lifecourse data
A barrier to integrated social policy analysis is that:• Most data sources provide information about thecharacteristics and activities of individuals orfamilies/households at particular points in time.
• The jurisdictional boundaries of social policies are,however, mainly organized around life-trajectories.
Education policy deals with the time that individuals
spend over life in learning settings. Labour market policy
relates to life in employment. Health policy mainly deals
with time spent in sickness or disability. In principle,
those policies should be supported by data that takes
lifecourse trajectories into account.
Classification systems need to be developed to show how
point-in-time data can be consistently linked to the various
lifecourse trajectories.
Consistent ways of coding microdata about people’s activities
and transactions to different trajectories in their lives could,
over time, open up potentially important new forms ofanalysis. For example, it could help in examining how
programs in different areas of social policy (e.g., health,education, security) and different programming instruments(such as income transfers, service provision and regulatory
approaches) interact in their effects on quality of life ofindividuals over the course of their lives.
Again, these are complex topics that cross existing academic
disciplines and policy silos and that have implications forinternational statistical standards and classifications.
However, there are precedents
The statistical challenges described above, and throughout the
text, are unquestionably complex. However, it is also
important to note that national social statistics systems havedealt with similarly complex problems in the past. Lessons
can be learned from this past experience.
An example is the development and collection of highlydetailed, internationally-consistent measures literacy,
numeracy, and other basic skills. This work was based on
partnerships that included national statistical agencies,
international bodies, program departments, independent
researchers and, in Canada, the pan-Canadian organization,
the Council of Ministers of Education, Canada.
Similarly complex systems have been developed in the healtharea for classifying diseases and health interventions, again
involving partnerships that included national statisticalagencies, international statistical bodies and, in Canada, thepan-Canadian organization, the Canadian Institute for Health
Information.

Conclusion
The tradition function of national social statistics is to describe Canada’s society and to support
excellent social analysis and research. The message of this article is that the future directions
being proposed can not only strengthen that traditional function but also can play an important,direct role in transforming social programs and policies. As consequence, changes in the15

statistical system hold the potential to, over time, lead to significant, measurable improvementsin the quality of life in Canada.
However, Statistics Canada has neither the mandate nor the resources, by itself, to realize thispotential. Success will depend critically on the active support of partners in program agencies inall jurisdictions and in the research community. It will also depend on the support of the central
agencies of government in fostering these partnerships and providing appropriate resources.

References
Hicks, P. (2022, January 31). The System of National Quality-of-Life Statistics: Future
Directions. Analytical Studies: Methods and References. Retrieved December 12, 2022,
from https://www150.statcan.gc.ca/n1/pub/11-633-x/11-633-x2021006-eng.htm
Hicks, P. (2022, June 1). The System of National Quality-of-Life Statistics: Conceptual
Framework. Analytical Studies: Methods and References. Retrieved December 12, 2022,
from https://www150.statcan.gc.ca/n1/pub/11-633-x/11-633-x2022002-eng.htm
Jeon, S. H., & Ostrovsky, Y. (2022, September 27). The impact of firm closures and job loss onparticipation in gig work: A causal analysis. Analytical Studies Branch Research Paper
Series. Retrieved December 12, 2022, fromhttps://www150.statcan.gc.ca/n1/pub/11f0019m/11f0019m2022001-eng.htm

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