Eh Sayers Episode 10 - Why Haven't We Ended Poverty Yet?

Release date: October 17, 2022

Catalogue number: 45200003
ISSN: 2816-2250

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It used to be that Statistics Canada didn't measure poverty. Not exactly. Poverty is complex, and there wasn't a single definition that everyone agreed on. So while StatCan did measure low income and other income inequality indicators, it didn't measure poverty per se. That is, until 2018, when the government chose to use the Market Basket Measure, or MBM, as Canada's Official Poverty Line. That means that the government now uses the MBM to track its poverty reduction targets.

But something strange happened during the pandemic: in 2020 the poverty rate fell. And it fell quite a bit. In fact, the poverty rate dropped in one year almost as much as it had in the four preceding years.

But why? What happened? Will the poverty rate continue to fall? And what happens if it hits zero? How would health outcomes change? Education outcomes? People's general happiness and well-being?

Has there ever been a time and place in Canada where the poverty rate was zero? The closest may be the Mincome Experiment of the 1970s in Manitoba. Many Canadians have never heard of this guaranteed income experiment, but it offers a glimpse at what eliminating poverty might look like.

To learn more we spoke with Burton Gustajtis, an economist from Statistics Canada, Evelyn Forget, a Professor of Economics and Community Health Sciences at the University of Manitoba and Kevin Milligan, a Professor of Economics in the Vancouver School of Economics at the University of British Columbia.

Host

Tegan Bridge

Guests

Burton Gustajtis, Evelyn Forget, and Kevin Milligan

Listen to audio

Eh Sayers Episode 10 - Why Haven't We Ended Poverty Yet?- Transcript

(Theme)

Tegan: Welcome to Eh Sayers, a podcast from Statistics Canada, where we meet the people behind the data and explore the stories behind the numbers. I'm your host, Tegan Bridge.

It used to be that Statistics Canada didn't measure poverty. Not exactly. Poverty is complex, and there wasn't a single definition that everyone agreed on. So while StatCan did measure low income and other income inequality indicators, it didn't measure poverty per se. That is, until 2018, when the government chose to use the Market Basket Measure, or MBM, as Canada's Official Poverty Line. That means that the government now uses the MBM to track its poverty reduction targets as well as progress made towards Canada's sustainable development goal for the elimination of poverty.

Something weird happened during the pandemic: in 2020 the poverty rate fell. And it fell quite a bit.

The poverty rate dropped to 6.4%, down from 10.3% in 2019, that's more than a third. In that single year, the rate dropped almost as much as it had in the four preceding years.

But why? What happened? Will the poverty rate continue to fall? And what happens if it hits zero? Could we be on the brink of solving poverty in Canada?

We're going to talk about what happened, but first, it would be helpful to understand what the Market Basket Measure is and how it works.

Burton: My name is Burton Gustajtis. I'm an economist at Statistics Canada.

Burton: In general, the MBM is an absolute measure of low income. It's based on the cost of a specific basket of goods and services mentor represent a modest basic standard of living for a family of four

Tegan: The MBM is like a shopping cart filled with all of the things that you need: food, clothing, footwear, shelter, transportation, and other necessities.

Burton: Each of these components, where appropriate, follow standards created by experts in their given domains. For example, the food component is based on a commonly consumed food item that represents a nutritional diet. Using the 2019 National nutritious food basket developed by Health Canada, and it's consistent with the latest Canada Food Guide.

Tegan: Experts at StatCan then look at that full shopping cart and estimate how much it costs, and that cost becomes the threshold. If you have enough disposable income to purchase that shopping cart of goods, you're living above the poverty line. If you can't, you're below it.

What about people who don't necessarily fit into a family of four structure?

Burton: For different family sizes, we use an equivalization methodology, which is an internationally recognized method of adjusting low income thresholds and income estimates for different family sizes.

Tegan: Is that like an equation?

Burton: Yes, it's called the square root equivalization methodology. So basically, the idea is that the cost for a family increase but at a decreasing rate. So the more people you get in your family, the more expensive your basket will be. But it's not at a, at a linear rate. It's at a decreasing rate.

Tegan: Gotcha. So every additional person that's not like you double the number every single time.

Burton: Yeah, exactly. That's right. Yeah. It increases, but not at a constant but constant rate like that, yeah.

Tegan: So, in addition to having some allowance for different family sizes, there's also a regional component.

Burton: This basket is costed in 53 regions across the provinces.

Tegan: Things can cost different amounts depending on where you live. The same, say, loaf of bread might have a different price if I were to buy it in Halifax, or rural Alberta, or Montréal. So the MBM takes into account the area where people live.

Does the basket change with inflation?

Burton: It does, yeah. So it's an absolute measure of poverty like I mentioned. So the contents of what that means basically is that the contents of the basket are held constant in a base year. Our current base year is 2018. And then it's adjusted annually for inflationary changes, price changes only. The contents of the basket is held constant, but the price is adjusted using the connect consumer prices index.

Tegan: The MBM thresholds are published annually. Therefore, changes in inflation you see from one month to the next are reflected in the annual updating of the MBM items' prices. We did an entire episode this past January, January 2022, about inflation and the CPI, called "Why Should You Care About Inflation?" Check that out to learn more!

Does the Market Basket measure fully capture poverty in Canada?

Burton: That's a good question. Poverty is a complicated concept. It's not just low income defined like the Market Basket Measure. It uhh, it's also, multidimensional. It's, you know, inequalities in the income distribution, being below the poverty line, entry and exit in and out of poverty. It's access to education, a well-paying jobs, social integration. You know, it's not just low income.

Tegan: The Market Basket Measure is a great tool: it's easy to understand, it takes into account differences in geography and allows for some differences in family size, and it's continually being updated, or rebased, which is the technical term, by StatCan and their partners at Employment and Social Development Canada, to ensure that it reflects the up-to-date cost of a basket of goods and services representing a modest, basic standard of living in Canada and to improve the tool and address any potential shortcomings. The Market Basket Measure is useful, but it's not the only way to track poverty. StatCan has a poverty dashboard on the website called the Dimensions of Poverty Hub with 12 additional indicators that you can check out to get a fuller picture.

Now, as I said at the top of the show, the poverty rate had been trending down before the pandemic. Between 2015 and 2019, it dropped from 14.5% to 10.3%, a difference of 4.2 percentage points over four years. What's noteworthy about 2020 is that the poverty rate dropped to 6.4%. Again, that's down from 10.3% in 2019, a difference of 3.9 percentage points, or more than a third. In that single year, the rate dropped almost as much as it had in the four preceding years.

In response to the COVID-19 pandemic, and the shutdowns and restrictions put in place to manage it, the Government of Canada introduced new income supports for individuals as well as businesses, like the Canada Emergency Response Benefit and the Canada Emergency Student Benefit.

Burton: The impact of the pandemic was not felt equally and many families did suffer. What many families do not suffer losses to employment or earnings, rather, earnings employment losses tended to be concentrated among that families and individuals on the lower, but that had lowered market income. So in response to these losses in employment and earnings a number of Canadians turned to the existing and newly announced income support measures that were put in place. These programs provided approximately $82 billion dollars in income and supported about 8.1 1,000,000 Canadian families and unattached individuals in 2020. And overall result of this was that the poverty rate fell by more than 1/3 in 2020. The decreases were universal. They were across all provinces, family types, demographic groups, although I should caution the gaps between the at risk populations and those not typically at risk of poverty remained so that although poverty decrease for everyone, the gaps between the address populations remain the same.

Tegan: It's important to note that these shifts in the poverty rate were caused by temporary government supports, so we can't expect these changes to be permanent.

We learned about the poverty rate's impressive drop, and it really got everybody on the podcast team thinking. What would Canada look like if the poverty rate hit zero? How would health outcomes change? Education outcomes? People's general happiness and well-being?

This made us really curious. Has there ever been a time and place in Canada where the poverty rate was zero? The closest may be the Mincome Experiment. We wanted to learn more, so we knew we needed to find an expert.

Evelyn: My name is Evelyn Forget. I'm a professor in the Department of Community Health Sciences at the University of Manitoba.

Tegan: Could you tell us what was the Mincome experiment?

Evelyn: the Mincome experiment happened in the mid-1970s in Canada at a time when the federal government and the various provincial governments were rethinking a lot of the social programs that were delivered in this country. And what it was guaranteed annual income experiment. That's what it was called at the time. What it meant was that everybody who participated in the experiment would receive a promise that they would receive a certain agreed upon amount of money if they had no other source of income. If they did have another source of income. If, for example, they worked and earned a little bit of money, the benefit would be reduced, but it would be reduced less than proportionately. So the guaranteed income acted both as a supplement to low wage workers and as a replacement for provincial income assistance at the time. There were two sites in Manitoba that were chosen to participate in the experiment. Winnipeg and a small town known as Dauphin Manitoba.

Tegan: Families received money for three years, from 1975 to 1978, and one of the goals was to evaluate the impact of a guaranteed annual income on the work behaviour of recipients, to test the theory that if you give people money they won't have the same incentive to work, and they'll cut their hours at work or even quit their jobs.

And what were the results of this experiment?

Evelyn: During the 1980s, there were a couple of economists at the University of Manitoba who looked at the labor market results. Derek Hum and Wayne Simpson. And they discovered what's been discovered in many other basic income and guaranteed income experiments. And that is that there really isn't much of a labor market response people who were working before the experiments started to pretty much continue to work. People who weren't working ahead of time for the most part didn't start working and didn't stop. So there. There wasn't much of a change in participation in the labor market that was caused by the basic income experiment or the guaranteed annual income experiment.

Tegan: But there were two notable exceptions to this.

Evelyn: There were, in effect, two groups of people who did work less during the experiment. One of those groups of people. Were new mothers. Umm. So if you think again back to the 1970s. Maternity leaves. Were not what they are now. There was no one year parental leave and for the most part, women were guaranteed four weeks off when they gave birth. And there were a lot of new mothers who thought that that was a rather miserly response to childbirth. And I think predictably, many of those families use the Mincome to buy themselves longer parental leaves. But the other group of people who did work less were-- and here the language turns out to be really, really important. And the language that was used in the report was young, unattached males, that is, young men who hadn't yet formed families. They weren't married. They weren't. They weren't living in, in, in committed relationships. They didn't have children, and they work less, and that seemed to feed a lot of the prejudices people had a lot of worries that people had about guaranteed income. And what I was able to do was to go back and to find some of the educational records during the period. And one of the things I showed was that there was. And nice little bubble in high school completion rates exactly during the Mincome experiment. And what that meant was that people who probably wouldn't have finished high school were able to finish high school because their families received Mincome support.

Tegan: People thought that these young men were doing as everyone feared, taking the money and running, but Evelyn's findings suggests that what might have happened instead was that young men who might otherwise have dropped out of high school to help support their families were instead given the opportunity to complete their education and graduate.

Did this experiment have any kind of impact on what kinds of work people did?

Evelyn: Well, I don't have data looking specifically at the kinds of jobs that people were doing. What I have are a lot of anecdotal reports from people who participated in the experiment. And so I was able, for example, to talk to people who use the opportunity to keep small businesses alive or to start small businesses. And I thought that was a really interesting outcome. One woman I talked to living in Dauphin. I have opened a small record shop selling, you know record players and vinyl records during the period. And she said she remembered the Mincome period as being a time when everybody had a little bit of money in their pockets. But there were a lot of stories of people using the Mincome money to invest in small businesses that were already preexisting, Umm, a lot of the people in Dauphin, for example, were farmers or related in some way to agriculture. And so Mincome stabilized their income and allowed them to invest in new equipment to build their businesses.

Tegan: So in terms of people's health, did this have any kind of impact on people's physical or mental health?

Evelyn: One of the reasons I went back looking for the Mincome records was to find out whether people's health improved. I was particularly interested in mental health, but I was interested in health and all kinds of ways. And what I was able, I was very lucky actually, because Manitoba had just moved to Universal health insurance just before the experiment began. And what I was able to do was to track down some of the participants in the Medicare Records and to look at what happened to their health. And so I was able to compare people in the experiment to a match group of people who were living in similar kinds of places the same age and sex, who didn't receive income support. And I was able to show that hospitalization rates fell pretty substantially during the experiment. Overall, the hospitalization rate fell by about 8.5%. And that's a pretty dramatic finding, a big reduction in hospitalization rates. When I looked at it a little bit more closely to find out why hospitalization rates fell, there were really two categories that stood out. The first were accidents and injuries. No, that's a big category that picks up all kinds of acute hospital admissions. You know, people have been in car accidents, accidents of all types and so on. But the other category was mental health. There was a big reduction in hospitalizations related to mental health. So that was one of the big findings, I think during this experiment it was certainly it was certainly an interesting outcome to see from a guaranteed income experiment.

I think we find similar results every time we run the similar kinds of experiments. I think that people's health inevitably improves when their income goes up. I think that's not a surprise. We see it in a lot of different kinds of programs. Umm, I think that one of the things that becomes very obvious to people is that poverty imposes a lot of costs on the economy and on society. And if you can do something that reduces the rate of poverty, you could improve living standards not only for people who are receiving the money, but for everybody who lives in a town. Everybody who lives together. Umm, so I think those things are very positive. But the basic findings I think are things we see over and over and over again. That poverty has a cost. We feel that cost and in very personal terms, in terms of our health, in terms of our wellbeing, that if you give people money for the most part, they spend it on things that improves the quality of life for themselves and their family. They invest in education, they invest in better housing, better food. So in some sense, there are no surprises there.

People who receive money at vulnerable periods in their lives can really make changes that are going to affect their health that are going to affect their lives for years and years and years to come.

Tegan: So, back to the MBM…what would happen if everyone lived above the threshold of the MBM? , by definition that would mean that there would be no poverty. Now, I'm not going to lie. We, and by 'we', I mean the podcast team who are most definitely not experts, might have gotten a bit carried away with this idea.

We asked our StatCan expert about using the Market Basket Measure in a Mincome-like way, and he very kindly explained some of the issues.

Burton: It's a statistical tool meant to be used in parallel with an income concept given the construction of its disposable income like the tenure type adjustments and the fact that, like you mentioned, the costs are not defined independently for different family sizes or constructions. It can't be used in that manner for program eligibility or sending minimum wage or for a basic income concept that it's, it's not, it's a great tool for model, for measuring poverty and income distribution, but it shouldn't be seen as a universal tool that can solve all of these problems.

Tegan: We wanted to learn more about poverty and why it's so complex, and also why we shouldn't try to use the MBM as a universal tool.

Kevin: I'm Kevin Milligan. I'm a professor of economics at the Vancouver School of Economics at the University of British Columbia.

Tegan: The market basket measure is a great reporting tool, but it reports after the fact. So , it isn't used to address need.

Kevin: So just to give an example, you know right now we have a lot of income transfers that are based on your family income and your family circumstance. Think of the Canada Child benefit, think of the GST tax credit, that lower income Canadians get and many of us got when we were students, you know, you got that check every quarter that direct deposit. Those are based on the tax filing schedule and so we just filed our taxes and April 2022. Those benefits are all being adjusted quite shortly in July 2022 for the 12 months from July 2022 to June 2023. So if you think about it, if I lost my job tomorrow, when would my Canada child benefit? When would my GSE tax credit be updated? Well, I file my taxes in April 2023, so July 2023, my check will be updated, which is maybe not great because what if my upgrade income needs are now? So that's one big challenge that you face is that cycle of how things repeated now you could argue that maybe there's ways we can do things more quickly. We could not key things off the income tax cycle and do it in some other way. But that that's the kind of challenge you have to face is how do you actually get checks into people's hands based on their current circumstance? And that's one of the many challenges that we face.

Tegan: The Market Basket Measure doesn't take into account different circumstances, like family shape and size. A family of four could mean two parents and two children, but it could also be one parent and three children. These two families would have very different needs. And that's before you add things like disability to the mix. Kevin explains.

Kevin: Our current system is really strongly based on your needs. So if you're someone who is with a disability, you're gonna have a different kind of income structure. If you're someone and even varies by disability, depends on your family circumstance, depends on a lot of different aspects of your life. So we have a whole panoply of government programs. They're pretty complicated. They often interact in poor ways, and those are not good things. But we have to understand the reason why they exist is that there are a variety of different needs. If we were to replace that whole basket, inference programs with a 'one-size fits all' program. That's kind of a flat check of some kind that doesn't depend on your needs. Then if you think about it, the people who gonna be hurt most are the people with the biggest needs because that one size fits all check is not gonna touch all the bases. That they might have in terms of their needs. And so that's a great challenge for a basic income approach is that if you try to make sure that the people with the highest needs are made whole, that they get the same kind of income transfer, you end up, kind of, well, you have to take into account all of their different kinds of disability, all of their family circumstances, all of their income patterns, and you essentially end up recreating all the complexity of the existing system. So what I'm suggesting here is no magic solution here. Sometimes. Basically income is thought of as a magic solution to things that we can wipe the table with all the complexity. And what I'm asking everyone to think about is the reason why that complexity exists is that people have complicated lives. Doesn't mean we shouldn't push back on the complexity and try to improve it to make the points of access easier for low income Canadians to access their benefits. But it does suggest that there's no magic wand here.

I wouldn't walk into that discussion thinking I'm gonna solve that in a day.

Tegan: Don't get me wrong. All of this isn't a criticism of the Market Basket Measure. It's a tool designed for a specific purpose that doesn't always work when it's taken out of context and applied to a new purpose for which it wasn't designed. The market basket measure is a great tool to measure one key aspect of poverty, but isn't a perfect measurement of all of the areas of need in the country. It's just one indicator, and there are many more.

What are some of the issues that can arise when we only use one measurement to capture something as complex as poverty?

Kevin: The different measures capture different elements of things. So there's nothing measure called the low income measure, which looks at how family is doing relative to the typical family, takes the median family income in Canada and compare draws a line based on that. So that one measure sometimes has kind of a different picture because it bases on kind of compares the low end to the middle. And so what's interesting about that measure is in the 1990s, the median income. The typical family in Canada, their income was actually falling. What that meant was, uh, the low income measure, which was keyed to that median income, was actually getting lower and lower every year, so it was easier to be out of poverty. So we saw poverty measures, poverty outcomes falling based on that one because it was getting easier to pass it. But that doesn't sound like a good thing. If everyone's income is falling. But the low income is falling slightly different speed than the median income. It just doesn't sound good. That's one of the reasons that the Market Basket measure provides a different picture. What's interesting is it doesn't compare like the low to the middle. So that depending on how the middle is doing that change is poverty. It just says, look, what do you need in Canada in 2022 to have an adequate life and so they uh, people StatCan and all of the round tables and discussions have come up with the basket and that doesn't depend on what the median income is doing. It doesn't bounce around it that way. So it's a bit more stable in that way and is arguable. I saw I've measure of deprivation. It's not to say that the low income measure doesn't have its uses just to give an example of that. That is something that's used in international poverty comparisons because whatever is in the Canadian basket for the Market Basket measure makes sense for Canada but might not make sense for Italy. Might not make sense for Japan. They're just gonna have different basket of goods, different cultures, different economies. So international comparisons tend to stick to something like the low income measure, which compares the low to the middle, because that's something you can implement more easily across countries.

Tegan: There's a reason why there are 12 different indicators on the StatCan's poverty hub. One indicator just can't tell the full story on its own.

I feel like I got a little bit of a crash course as a junior policy analyst or something doing this episode.

Kevin: There you go. This is the kind of work a lot of folks in the ESDC and Department of Finance do all the time and trying to design these income programs and it it's a great challenge. It's also very rewarding because when you think about what you're doing, you're trying to help out families who are really in need as best you can. I was using, making great use of Statistics Canada surveys and products to do the best job as we're trying to help design those things. Me on the outside as a researcher and those in government on the inside. But yeah, I think it's a fascinating thing because it's so difficult. It's a real challenge. If it were easy, it'd be done by noon and it would be great. But it's those challenges and trying to find ways of finding wins is a great challenge and one that I have enjoyed working on.

Tegan: As you've said before, if it were easy, somebody would have done it already.

Kevin: Yeah. Yeah, I think that's right.

Tegan: It's difficult to eradicate poverty, but that doesn't mean it's not worth doing. Canada has a poverty reduction strategy in line with the UN's sustainable development goals.

How would eradicating poverty change outcomes for an individual? Well, for somebody who's experiencing poverty, how would that change their lives?

Kevin: So in two ways. So, I would phrase it in terms of having more income for people who are in low income I think it would change in a couple of ways. One is through just the ability to purchase more things that might help out in sustaining there well-being, so this would be better food, better living circumstance, adequate clothing, things like that. But the other more subtle but perhaps also more important, channel is through thinking of the stress that a family undergoes when they don't have enough income when they don't feel like they their kids can keep up with their neighbors in terms of how they're able to participate in things that school, that kind of stress of having a tight budget is has been shown by research to be quite important to one's own well-being and also to the long run impacts of living in poverty. What people remember if they grew up in poverty, is perhaps some hungry nights, but more often than that, it was the uuh, you know, pain in the stress of having a tight budget, whether that led to. I you know, bad behavior in the household or just a shame and embarrassment at school, those memories and the real impact of that is in certain ways even stronger than going at night without a big dinner.

Tegan: In a previous episode, "Unravelling," from season one, our guest, Dr. Kelley, spoke about the impact of stress on kids. Check it out to learn more.

What does it cost not to do our best to eradicate poverty?

Evelyn: Ohh, I think the cost of poverty are immense in this country. Umm, I think, if you start looking at, there's not a single social problem in Canada that's not made worse by poverty. If you look at the healthcare system, for example in 2010. There was a study done on hospitalizations, for example. And I'm looking specifically at what are called ambulatory care sensitive conditions. Now, these are hospitalizations that occur because people didn't receive appropriate primary care. Umm, looking specifically at those kinds of hospitalizations, the authors found that 30 to 40% of hospitalizations are driven by low socioeconomic status. So driven by poverty. If you look at education, a lot of educational funding is required to help children stay current when they change schools. Why don't you children who change schools many times over the course of a year? Why do children change schools? One of the reasons is that parents can't pay the rent and they move. And so you get that kind of mobility among families that and that makes it harder for kids to stay current. And it makes it harder for the educational system to pay for kids. If you look at something like incarceration, 80% of women who are incarcerated. Are incarcerated for poverty related crimes. 80% I mean the cost of incarceration are immense in this country. So we're paying for poverty, we're paying for it in, in, in terms of every social program you can think of. It's not just the money we put out in terms of provincial social assistance or other kinds of programs. It's every single social program that we've gotten place to assist people.

Tegan: And this might be it. Just a question that's not answerable. But how do we measure the worth of breaking the cycle of poverty for a family?

Evelyn: I think that's your rhetorical question to end with. Well, I yeah, I don't have an answer for that. I don't have an answer for that because I think ultimately it's a moral question. It's an ethical question. Umm, you know, it's in the in a sense it, In a sense, I think it undermines the importance of the issue. If I say, well, I benefit, I benefit. If I'm not living. You know next door to people who need help and don't receive it. We all benefit, I think, but we've benefit in in very practical and monetary terms. But we especially benefit, I think, in broader social terms, in terms of the kind of cohesion, the kind of society we want to live in.

Tegan: If someone would like to learn more about the Market Basket measure and how Statcan measure poverty, where can they go?

Burton: So the dimensions of poverty hub at Statistics Canada is a great resource for the latest information on the Market Basket measure and the work that we're doing on creating the Market Basket measure thresholds for the territories that different indicators of poverty that are identified in the opportunity for all Canada's first Poverty reduction document. So I would start there.

Tegan: You've been listening to Eh Sayers. Thank you to our guests, Burton Gustajtis, Evelyn Forget, and Kevin Milligan for sharing their expertise.

You can subscribe to this show wherever you get your podcasts. There, you can also find the French version of our show, called Hé-coutez bien. If you liked this show, please rate, review, and subscribe. Thanks for listening!

Sources

"Dimensions of Poverty Hub." 2018. Statistics Canada. Statistics Canada. December 4, 2018. Dimensions of Poverty Hub

Forget, Evelyn L. 2011. "The Town with No Poverty: The Health Effects of a Canadian Guaranteed Annual Income Field Experiment." Canadian Public Policy 37 (3): 283–305. The Town with No Poverty: The Health Effects of a Canadian Guaranteed Annual Income Field Experiment.

"The Daily — Canadian Income Survey, 2020." 2022. Statistics Canada. March 23, 2022. Canadian Income Survey, 2020.

Download

Eh Sayers Episode 10 - Why Haven't We Ended Poverty Yet? (MP3, 23.2 MB)

Retail Commodity Survey: CVs for Total Sales July 2022

Retail Commodity Survey: CVs for Total Sales July 2022
Table summary
This table displays the results of Retail Commodity Survey: CVs for Total Sales (July 2022). The information is grouped by NAPCS-CANADA (appearing as row headers), and Month (appearing as column headers).
NAPCS-CANADA Month
202204 202205 202206 202207
Total commodities, retail trade commissions and miscellaneous services 0.67 0.63 0.61 0.72
Retail Services (except commissions) [561]  0.67 0.63 0.61 0.71
Food at retail [56111]  0.94 0.56 0.52 1.85
Soft drinks and alcoholic beverages, at retail [56112]  0.63 0.59 0.61 0.71
Cannabis products, at retail [56113] 0.00 0.00 0.00 0.00
Clothing at retail [56121]  1.05 1.00 0.93 0.84
Footwear at retail [56122]  1.76 1.51 1.22 1.55
Jewellery and watches, luggage and briefcases, at retail [56123]  7.38 5.44 5.89 5.00
Home furniture, furnishings, housewares, appliances and electronics, at retail [56131]  1.14 1.31 1.05 1.02
Sporting and leisure products (except publications, audio and video recordings, and game software), at retail [56141]  2.09 1.60 1.93 1.80
Publications at retail [56142] 5.82 5.62 6.05 5.64
Audio and video recordings, and game software, at retail [56143] 0.62 0.31 1.17 1.01
Motor vehicles at retail [56151]  2.33 2.21 2.14 2.32
Recreational vehicles at retail [56152]  5.72 6.99 2.88 3.73
Motor vehicle parts, accessories and supplies, at retail [56153]  1.74 1.83 1.84 1.85
Automotive and household fuels, at retail [56161]  1.68 1.86 1.61 1.65
Home health products at retail [56171]  2.39 2.54 2.58 2.53
Infant care, personal and beauty products, at retail [56172]  2.07 1.97 2.25 1.99
Hardware, tools, renovation and lawn and garden products, at retail [56181]  2.81 1.60 2.41 2.09
Miscellaneous products at retail [56191]  3.02 3.12 2.89 2.40
Total retail trade commissions and miscellaneous services Footnote 1 1.66 1.84 1.88 1.94

Footnotes

Footnote 1

Comprises the following North American Product Classification System (NAPCS): 51411, 51412, 53112, 56211, 57111, 58111, 58121, 58122, 58131, 58141, 72332, 833111, 841, 85131 and 851511.

Return to footnote 1 referrer

In October 2022, questions measuring the Labour Market Indicators were added to the Labour Force Survey as a supplement.

Question wording within the collection application is controlled dynamically based on responses provided throughout the survey.

Labour Market Indicators

ENTRY_Q01 / EQ1 – From the following list, please select the household member that will be completing this questionnaire on behalf of the entire household.

WFH_Q01 / EQ2 – At the present time, in which of the following locations (do/does) (Respondent’s name/this person/you) usually work as part of (his/her/their/your) main job or business?

WFH_Q02 / EQ3 – Last week, what proportion of (his/her/their/your) work hours did (Respondent name/this person/you) work at home as part of (his/her/their/your) main job or business?

INF_Q01 / EQ4 – Over the last month, that is since September 15 to today, how many hours of voluntary ( /paid) overtime or ( /paid) extra hours did (respondent’s name/this person/you) decide to work at any (business/businesses/job/jobs) in response to the recent increase in the cost of living?

INF_Q02 / EQ5 – When did (respondent’s name/this person/you) last receive a raise in (his/her/their/your) main job?

CHS_Q01 / EQ6 – Over the last month, that is since September 15 to today, how difficult or easy was it for your household to meet its financial needs in terms of transportation, housing, food, clothing and other necessary expenses?

CHS_Q02 / EQ7 – Today, could your household cover an unexpected expense of $500 from your household's resources?

Retail Commodity Survey: CVs for Total Sales (Second Quarter 2022)

Retail Commodity Survey: CVs for Total Sales (July 2022)
Table summary
This table displays the results of Retail Commodity Survey: CVs for total sales (second quarter 2022). The information is grouped by NAPCS-CANADA (appearing as row headers), and Quarter (appearing as column headers).
NAPCS-CANADA Quarter
2022Q1 2022Q2
Total commodities, retail trade commissions and miscellaneous services 1.17 0.93
Retail Services (except commissions) [561]  1.20 0.95
Food at retail [56111]  0.97 1.66
Soft drinks and alcoholic beverages, at retail [56112]  0.49 0.68
Cannabis products, at retail [56113] 0.00 0.00
Clothing at retail [56121]  1.25 2.96
Footwear at retail [56122]  1.50 2.61
Jewellery and watches, luggage and briefcases, at retail [56123]  6.58 6.12
Home furniture, furnishings, housewares, appliances and electronics, at retail [56131]  1.45 1.81
Sporting and leisure products (except publications, audio and video recordings, and game software), at retail [56141]  1.96 3.25
Publications at retail [56142] 5.80 7.06
Audio and video recordings, and game software, at retail [56143] 0.50 1.04
Motor vehicles at retail [56151]  1.86 1.78
Recreational vehicles at retail [56152]  3.65 3.02
Motor vehicle parts, accessories and supplies, at retail [56153]  1.62 1.63
Automotive and household fuels, at retail [56161]  1.90 1.60
Home health products at retail [56171]  2.10 2.59
Infant care, personal and beauty products, at retail [56172]  2.20 3.55
Hardware, tools, renovation and lawn and garden products, at retail [56181]  2.14 2.08
Miscellaneous products at retail [56191]  2.00 3.08
Total retail trade commissions and miscellaneous services Footnotes 1 1.76 1.57

Footnotes

Footnote 1

Comprises the following North American Product Classification System (NAPCS): 51411, 51412, 53112, 56211, 57111, 58111, 58121, 58122, 58131, 58141, 72332, 833111, 841, 85131 and 851511.

Return to footnote 1 referrer

Labour Market and Socio-economic Indicators - October 2022

In October 2022, the following questions measuring the Labour Market and Socioeconomic Indicators were added to the Labour Force Survey as a supplement.

The purpose of this survey is to identify changing dynamics within the Canadian labour market, and measure important socioeconomic indicators by gathering data on topics such as type of employment, quality of employment, support payments and unmet health care needs.

Question wording within the collection application is controlled dynamically based on responses provided throughout the survey.

Labour Market and Socio-economic Indicators

ENTRY_Q01 / EQ 1 - From the following list, please select the household member that will be completing this questionnaire on behalf of the entire household.

Employee Block

LMI_Q01 / EQ 2 - Is (respondent name's/this person's/your) main job permanent?

LMI_Q02 / EQ 3 - In what way is (respondent name's/this person's/your) main job not permanent?

LMI_Q03 / EQ 4 - In (his/her/their/your) main job, (are/is) (respondent name/this person/you) paid by a private employment or placement agency that is different from the company (he/she/this person/you) work(s) for?

LMI_Q04 / EQ 5 - What is the total duration of (respondent name's/this person's/your) contract or agreement in (his/her/their/your) main job?

LMI_Q05 / EQ 6 - In (respondent name's/this person's/your) main job, (is/are) (he/she/they/you) guaranteed a minimum number of work hours per pay period?

LMI_Q06 / EQ 7 - What would you say best describes (respondent name's/this person's/your) current situation in (his/her/their/your) main job?

Self-employed Block

LMI_Q07 / EQ 8 – What is the main reason why (respondent name/this person/you) (are/is) self-employed in (his/her/their/your) (main/other) job?

LMI_Q08 / EQ 9 – (Does/do) (respondent name/this person/you) have any partners or co-owners in (his/her/their/your) (main/side) business?

LMI_Q09 / EQ 10 – (Does/Do) (respondent name/this person/you) or (his/her/their/your) (partners/company/partners or company) own or lease a building or space dedicated to (his/her/their/your) (main/side) business?

LMI_Q10 / EQ 11 - In (respondent name's/this person's/your) (main/side) business, is/are (he/she/they/you) required to belong to a professional association or regulatory college to do (his/her/their/your) job?

LMI_Q11 / EQ 12 - Does (respondent name's/this person's/your) (main/side) business operate…?

LMI_Q12 / EQ 13 - What is the current mix of clients in (respondent name's/this person's/your) main business?

LMI_Q13 / EQ 14 - Would (respondent name/this person/you) be able to continue operating (his/her/their/your) main business for the next five years based on returning or existing clients alone?

LMI_Q14 / EQ 15 – To what extent do you agree or disagree with the following statement?
In normal times, it is easy for [Respondent's name/this person/you] to find new clients in [his/her/their/your] main business.

LMI_Q15 / EQ 16 – (Does/Do) (respondent name/this person/you) or (his/her/their/your) (partners/company/partners or company) currently have any contracts with businesses, government agencies, or non-profit organizations as part of (his/her/their/your) main business?

LMI_Q16 / EQ 17 - Thinking of (respondent name's/this person's/your) largest contract, what is the total duration of that contract?

LMI_Q17 / EQ 18 – During the last 12 months, did (respondent name/this person/you) have any full days with no clients or work in (his/her/their/your) main business even though (he/she/they/you) wanted to work?

LMI_Q18 / EQ 19 – What would you say is (respondent name's/this person's/your) plan with (his/her/their/your) main business over the next 12 months?

LMI_Q19 / EQ 20 - What is the main reason (respondent name/this person/you) expect(s) to stop working or close (his/her/their/your) main business?

LFI-CHECK1 / EQ 21 - Last week, did (he/she/this person/you) work at a job or business?

LFI-CHECK2 / EQ 22 - Last week, did (he/she/this person/you) have a job or business from which (he/she/this person/you) (were/was) absent?

LFI-CHECK3 / EQ 23 - Did (he/she/this person/you) have more than one job or business last week?

LFI-CHECK4 / EQ 24 - Was this because (he/she/this person/you) changed employers?

LFI-CHECK5 / EQ 25 - (Has/Have) (respondent name/this person/you) ever worked at a job or business?

LFI-CHECK6 / EQ 26 - When did (respondent name/this person/you) last work?

LMI_Q20 / EQ 27 - Excluding (his/her/their/your) main job or business, (has/have) (respondent's name/this person/you) earned any money by freelancing, doing a paid gig, or completing a short-term job or task during the last 12 months?

LMI_Q21 / EQ 28 - Was this freelancing, paid gig, or short-term task or job one of the jobs (respondent's name/this person/you) had last week, or something else entirely?

LMI_Q22 / EQ 29 - You mentioned earlier that (respondent name/this person/you) had a job or a business during the last 12 months.

In addition to the jobs or businesses (he/she/this person/you) had during this period, did (respondent name/this person/you) earn any money by freelancing, doing a paid gig, or completing any other short-term job or task during the last 12 months?

LMI_Q23 / EQ 30 – (You mentioned earlier that (respondent name/this person/you) did not have a job or a business during the last 12 months.)

(Has/Have) (respondent name/this person/you) earned any money by freelancing, doing a paid gig, or completing any other short-term job or task during the last 12 months?

LMI_Q24 / EQ 31 - When was the last time (respondent name/this person/you) freelanced, did a paid gig, or got paid to do a short-term task or job?

SCC1_Q05 / EQ 32 - In the last 12 months, did (respondent's name/you) receive support payments from a former spouse or partner?

SCC1_Q10 / EQ 33 - What is your best estimate of the amount of support payments (he/she/this person/you) received in the last 12 months?

SCC2_Q05 / EQ 34 - In the last 12 months, did (respondent's name/you) make support payments to a former spouse or partner?

SCC2_Q10 / EQ 35 - What is your best estimate of the total amount (he/she/this person/you) paid in support payments in the last 12 months?

SCC3_Q05 / EQ 36 - In the last 12 months, did (respondent's name/you) pay for child care, so that (he/she/they/you) could work at a paid job?

SCC3_Q10 / EQ 37 - What is your best estimate, of the total amount (he/she/this person/you) paid for child care in the last 12 months?

DSQ_Q01 / EQ 38 - (Do/Does) (respondent's name/you) have any difficulty seeing?

DSQ_Q02 / EQ 39 - (Do/Does) (he/she/this person/you) wear glasses or contact lenses to improve (respondent name's/this person's/your) vision?

DSQ_Q03 / EQ 40 - (Which/With (respondent name's/this person's/your) glasses or contact lenses, which) of the following best describes (respondent's name/your) ability to see?

DSQ_Q04 / EQ 41 - How often does this (difficulty seeing/seeing condition) limit (his/her/their/your) daily activities?

DSQ_Q05 / EQ 42 - (Do/Does) (respondent's name/you) have any difficulty hearing?

DSQ_Q06 / EQ 43 - (Do/Does) (he/she/this person/you) use a hearing aid or cochlear implant?

DSQ_Q07 / EQ 44 - (Which/With) (respondent name's/this person's/your) hearing aid or cochlear implant, which) of the following best describes (respondent's name/your) ability to hear?

DSQ_Q08 / EQ 45 - How often does this (difficulty hearing/hearing condition) limit (his/her/their/your) daily activities?

DSQ_Q09 / EQ 46 - (Do/Does) (respondent's name/you) have any difficulty walking, using stairs, using (his/her/their/your) hands or fingers or doing other physical activities?

DSQ_Q10 / EQ 47 - How much difficulty (do/does) (he/she/this person/you) have walking on a flat surface for 15 minutes without resting?

DSQ_Q11 / EQ 48 - How much difficulty (do/does) (he/she/this person/you) have walking up or down a flight of stairs, about 12 steps without resting?

DSQ_Q12 / EQ 49 - How often (does this difficulty walking/does this difficulty using stairs/do these difficulties) limit (his/her/their/your) daily activities?

DSQ_Q13 / EQ 50 - How much difficulty (do/does) (respondent's name/you) have bending down and picking up an object from the floor?

DSQ_Q14 / EQ 51 - How much difficulty (do/does) (he/she/this person/you) have reaching in any direction, for example, above (his/her/their/your) head?

DSQ_Q15 / EQ 52 - How often (does this difficulty bending down and picking up an object/does this difficulty reaching/do these difficulties) limit (his/her/their/your) daily activities?

DSQ_Q16 / EQ 53 - How much difficulty (do/does) (respondent's name/you) have using (his/her/their/your) fingers to grasp small objects like a pencil or scissors?

DSQ_Q17 / EQ 54 - How often does this difficulty using (his/her/their/your) fingers limit (his/her/their/your) daily activities?

DSQ_Q18 / EQ 55 - (Do/Does) (respondent's name/you) have pain that is always present?

DSQ_Q19 / EQ 56 - (Do/Does) (he/she/this person/you) ( /also) have periods of pain that reoccur from time to time?

DSQ_Q20 / EQ 57 - How often does this pain limit (his/her/their/your) daily activities?

DSQ_Q21 / EQ 58 - When (respondent's name/you) (are/is) experiencing this pain, how much difficulty (do/does) (he/she/they/you) have with (his/her/their/your) daily activities?

DSQ_Q22 / EQ 59 - (Do/Does) (respondent's name/you) have any difficulty learning, remembering or concentrating?

DSQ_Q23 / EQ 60 - Do you think (respondent's name/you) (has/have) a condition that makes it difficult in general for (him/her/them/you) to learn? This may include learning disabilities such as dyslexia, hyperactivity, attention problems, etc.

DSQ_Q24 / EQ 61 - Has a teacher, doctor or other health care professional ever said that (respondent's name/you) had a learning disability?

DSQ_Q25 / EQ 62 - How often are (his/her/their/your) daily activities limited by this condition?

DSQ_Q26 / EQ 63 - How much difficulty (do/does) (respondent's name/you) have with (his/her/their/your) daily activities because of this condition?

DSQ_Q27 / EQ 64 - Has a doctor, psychologist or other health care professional ever said that (respondent's name/you) had a developmental disability or disorder? This may include Down syndrome, autism, Asperger syndrome, mental impairment due to lack of oxygen at birth, etc.

DSQ_Q28 / EQ 65 - How often are (respondent's name/your) daily activities limited by this condition?

DSQ_Q29 / EQ 66 - How much difficulty (do/does) (respondent's name/you) have with (his/her/their/your) daily activities because of this condition?

DSQ_Q30 / EQ 67 - (Do/Does) (he/she/this person/you) have any ongoing memory problems or periods of confusion?

DSQ_Q31 / EQ 68 - How often are (his/her/their/your) daily activities limited by this problem?

DSQ_Q32 / EQ 69 - How much difficulty (do/does) (respondent's name/you) have with (his/her/their/your) daily activities because of this problem?

DSQ_Q33 / EQ 70 - (Do/Does) (respondent's name/you) have any emotional, psychological or mental health conditions?

DSQ_Q34 / EQ 71 - How often are (his/her/their/your) daily activities limited by this condition?

DSQ_Q35 / EQ 72 - When (respondent's name/you) (are/is) experiencing this condition, how much difficulty (do/does) (he/she/they/you) have with (his/her/their/your) daily activities?

DSQ_Q36 / EQ 73 - (Do/Does) (respondent's name/you) have any other health problem or long-term condition that has lasted or is expected to last for six months or more?

DSQ_Q37 / EQ 74 - How often does this health problem or long-term condition limit (his/her/their/your) daily activities?

DSQ_Q38 / EQ 75 - (Do/Does) (respondent's name/you) have pain that is always present?

DSQ_Q39 / EQ 76 - (Do/Does) (he/she/this person/you) ( /also) have periods of pain that reoccur from time to time?

DSQ_Q40 / EQ 77 - How often does this pain limit (his/her/their/your) daily activities?

DSQ_Q41 / EQ 78 - When (respondent's name/you) (are/is) experiencing this pain, how much difficulty (do/does) (he/she/they/you) have with (his/her/their/your) daily activities?

UNC_Q005 / EQ 79 - During the past 12 months, was there ever a time when (respondent's name/you) felt that (he/she/they/you) needed health care, other than homecare services, but (he/she/they/you) did not receive it?

UNC_Q010 / EQ 80 - Thinking of the most recent time (respondent's name/you) felt this way, why didn't (he/she/they/you) get care?

UNC_Q015 / EQ 81 - Again, thinking of the most recent time, what was the type of care that was needed?

UNC_Q020 / EQ 82 - Did (he/she/this person/you) actively try to obtain the health care that was needed?

UNC_Q025 / EQ 83 - Where did (he/she/this person/you) try to get the service (he/she/they/you) (was/were) seeking?

Canadian Economic News, September 2022 Edition

This module provides a concise summary of selected Canadian economic events, as well as international and financial market developments by calendar month. It is intended to provide contextual information only to support users of the economic data published by Statistics Canada. In identifying major events or developments, Statistics Canada is not suggesting that these have a material impact on the published economic data in a particular reference month.

All information presented here is obtained from publicly available news and information sources, and does not reflect any protected information provided to Statistics Canada by survey respondents.

Hurricane Fiona

  • The Government of Canada announced that Hurricane Fiona, the post-tropical storm, made landfall in Nova Scotia on September 24th bringing damaging winds, flooding, and power outages to much of Atlantic Canada and parts of Quebec.
  • On September 24th, the Government of Nova Scotia announced it had requested the support of the Canadian Armed Forces to assist in clean up and power restoration efforts after Hurricane Fiona. The Government also said it had made a request to the federal government for Federal Disaster Assistance Funding.
  • The Government of Canada announced on September 25th that the Province of Prince Edward Island had requested support from the Canadian Armed Forces to assist in clean up and power restoration.
  • The Government of Newfoundland and Labrador announced on September 25th that following the widespread impacts of Hurricane Fiona on residents, the Provincial Government was moving ahead with emergency response and recovery efforts. The Government said the scale of the storm was unprecedented in this province and the magnitude of the damage was severe, particularly on the southwest coast of the island. The Government of Canada also announced on September 25th that the Canadian Armed Forces was activating resources and personnel in the province to provide physical impact assessments and immediate on-the-ground support to local authorities.
  • The Government of New Brunswick announced on September 25th that significant damage was reported in various communities in the province and that about 12,000 NB Power customers remain without power.

Resources

  • Calgary-based Tamarack Valley Energy Ltd. announced it had entered into a definitive agreement to acquire Deltastream Energy Corporation, also of Calgary, for a total net consideration of $1.425 billion. Tamarack said the acquisition is expected to close prior to the end of October, subject to certain conditions and regulatory approvals.
  • Calgary-based Imperial Oil Limited announced a long-term contract with Air Products Inc. of Pennsylvania to supply low-carbon hydrogen for Imperial's proposed renewable diesel complex at its Strathcona refinery near Edmonton. Imperial said Air Products will provide pipeline supply from its hydrogen plant under construction in Edmonton and that Air Products is increasing overall investment in its Edmonton hydrogen facility to $1.6 billion to support the Imperial contract.
  • Calgary-based Enbridge Inc. and 23 First Nation and Métis communities announced an agreement whereby the communities will acquire, collectively, an 11.57% non-operating interest in seven Enbridge-operated pipelines in the Athabasca region of northern Alberta for $1.12 billion. The parties said that a newly created entity, Athabasca Indigenous Investments, will steward this investment and that the closing of the transaction is expected to occur within the next month.
  • UK-based Rio Tinto Group and Turquoise Hill Resources Ltd. of Montreal announced they had reached an agreement in principle for Rio Tinto to acquire the approximately 49% of the issued and outstanding common shares of Turquoise Hill that Rio Tinto does not currently own for approximately USD $3.3 billion. The companies said the transaction is expected to close in the fourth quarter of 2022, subject to shareholder approval.
  • Toronto-based Agnico Eagle Mines Limited and Teck Resources Limited of Vancouver announced that Agnico Eagle had agreed to subscribe for a 50% interest in Minas de San Nicolás, S.A.P.I. de C.V. (MSN), a wholly owned Teck subsidiary which owns the San Nicolás copper-zinc development project located in Zacatecas, Mexico for USD $580 million of MSN shares, giving Agnico Eagle a 50% interest in MSN. Teck and Agnico Eagle said they anticipate that development capital costs could be in the range of USD $1.0 billion to USD $1.1 billion. The companies said the closing of the transaction is expected to occur in the first half of 2023, subject to customary conditions precedent, including receipt of necessary regulatory approvals.
  • Teck Resources later announced that there had been a structural failure of the plant feed conveyor belt at its Elkview steelmaking coal operation in the Elk Valley of British Columbia and that production will be interrupted for 1-2 months. The company said it expects the impact on 2022 steelmaking coal production will be in the range of 1.5 million tonnes.

Transportation

  • Calgary-based WestJet Airlines Ltd. announced an agreement with Boeing to purchase an additional 42 MAX aircraft, along with options for 22 more. WestJet said the order is in addition to its remaining 23 MAX orders.
  • Mississauga-based Canada Jetlines Operations Ltd. announced on September 22nd it had commenced operations out of its travel hub at Toronto Pearson International Airport with its first scheduled route into Calgary International Airport. The company said it had commenced biweekly flights between Toronto and Calgary and that the frequency will increase to three flights per week in time for the holidays.

Manufacturing

  • Toronto-based De Havilland Aircraft of Canada Limited announced that the site of its new aircraft manufacturing facility will be near Calgary and will consist of a new aircraft assembly facility, runway, parts manufacturing, and distribution centres. De Havilland said it anticipates that once in full operation, there will be up to 1,500 jobs located at De Havilland Field. The company also said it hopes to start construction as early as late 2023 and expects that the first buildings could be operational by 2025.

Other news

  • The Government of Canada announced the removal of all COVID-19 entry restrictions, as well as testing, quarantine, and isolation requirements for anyone entering Canada, effective October 1, 2022. The Government said that on that day, all travellers, regardless of citizenship, will no longer have to:
    • Submit public health information through the ArriveCAN app or website;
    • Provide proof of vaccination;
    • Undergo pre- or on-arrival testing;
    • Carry out COVID-19-related quarantine or isolation;
    • Monitor and report if they develop signs or symptoms of COVID-19 upon arriving to Canada;
    • Undergo health checks for travel on air and rail; or
    • Wear masks on planes and trains.
  • The Government of Canada announced on September 20th that it had introduced legislation that would make life more affordable for Canadians and that measures in these bills would:
    • Double the Goods and Services Tax Credit for six months;
    • Provide a Canada Dental Benefit to children under 12 who do not have access to dental insurance, starting this year; and
    • Provide a one-time top-up to the Canada Housing Benefit to deliver $500 to 1.8 million renters who are struggling with the cost of housing.

    The Government said the support package totals more than $4.5 billion, of which $3.1 billion is in addition to funding previously allocated in Budget 2022.

  • The Bank of Canada increased its target for the overnight rate by 75 basis points to 3.25%. The last change in the target for the overnight rate was a 100 basis points increase in July 2022.
  • Mississauga-based Walmart Canada announced more than $100 million to build a new high-tech sortable fulfillment centre near Montreal in Vaudreuil-Dorion, Quebec, slated to open in 2024. The company said it also plans to update and remodel a record number of stores in a year as part of a multi-year $3.5 billion investment.

United States and other international news

  • On September 29th U.S. President Joseph R. Biden, Jr. declared that a major disaster exists in the State of Florida and ordered Federal aid to supplement State, tribal, and local recovery efforts in the areas affected by Hurricane Ian beginning on September 23, 2022 and continuing.
  • On September 29th President Joseph R. Biden, Jr. declared that an emergency exists in the State of South Carolina and ordered Federal assistance to supplement State, tribal, and local response efforts due to the emergency conditions resulting from Hurricane Ian beginning on September 25, 2022 and continuing.
  • The U.S. Federal Open Market Committee (FOMC) raised the target range for the federal funds rate by 75 basis points to 3.00% to 3.25% and said it anticipates that ongoing increases in the target range will be appropriate. The last change in the target range was a 75 basis points increase in July 2022. The Committee also said it will continue reducing its holdings of Treasury securities and agency debt and agency mortgage-backed securities.
  • The European Central Bank (ECB) announced it had decided to raise the three key ECB interest rates by 75 basis points to 1.25% (main refinancing operations), 1.50% (marginal lending facility), and 0.75% (deposit facility). The last change in these rates was a 50 basis points increase in July 2022.
  • The Bank of England's Monetary Policy Committee (MPC) voted to increase the Bank Rate by 50 basis points to 2.25%. The last change in the Bank Rate was a 50 basis points increase in August 2022. The Committee also voted to reduce the stock of purchased UK government bonds by £80 billion over the next twelve months, to a total of £758 billion.
  • The Bank of Japan (BoJ) announced it will apply a negative interest rate of -0.1% to the Policy-Rate Balances in current accounts held by financial institutions at the BoJ and that it will purchase a necessary amount of Japanese government bonds (JGBs) without setting an upper limit so that 10-year JGB yields will remain at around zero percent.
  • The Reserve Bank of Australia (RBA) increased the target for the cash rate by 50 basis points to 2.35%. The last change in the target for the cash rate was a 50 basis points increase in August 2022.
  • The Monetary Policy and Financial Stability Committee of Norway's Norges Bank raised the policy rate by 50 basis points to 2.25%. The last change in the policy rate was a 50 basis points increase in August 2022.
  • The Executive Board of Sweden's Riksbank raised the repo rate by 100 basis points to 1.75%. The last change in the repo rate was a 50 basis points increase in June 2022.
  • OPEC and non-OPEC members announced they had decided to revert to the production level of August 2022 for the month of October 2022 and that the upward adjustment of 0.1 mb/d to the production level was only intended for the month of September 2022.
  • California-based Adobe Inc. announced it had entered into a definitive merger agreement to acquire Figma, Inc., a collaborative design platform also of California, for approximately USD $20 billion. Adobe said the transaction is expected to close in 2023, subject to the receipt of required regulatory clearances and approvals and the satisfaction of other closing conditions, including the approval of Figma's stockholders.
  • Tennessee-based FedEx Corp. announced it expects to generate total cost savings of USD $2.2 billion to USD $2.7 billion in fiscal 2023 compared to the company's prior plan, by:
    • Reducing flight frequencies and temporarily parking aircraft;
    • Closing select sort operations, suspending certain Sunday operations, and other linehaul expense actions; and
    • Reducing vendor utilization, deferring certain projects, and closing certain FedEx Office and corporate locations.

    FedEx also said that effective January 1, 2023, rates will increase by an average of 6.9%.

  • Illinois-based BP America Inc announced on September 21st that the bp-Husky Toledo Refinery was shut down following a fire at the facility.
  • UK-based Cineworld Group plc announced that it and certain of its subsidiaries had commenced Chapter 11 cases in the United States Bankruptcy Court. Cineworld said it had secured commitments for an approximate USD $1.94 billion in debtor-in-possession financing facility, that it expects to operate its global business and cinemas as usual without interruption, and that it anticipates emerging from Chapter 11 during the first quarter of 2023.
  • Switzerland-based Nord Stream AG announced on September 27th that the significant pressure drop caused by the gas leak on both lines of the gas pipeline registered on September 26th leads to a strong assumption of the pipeline physical damage. Nord Stream said it had started mobilization of all necessary resources for a survey campaign to assess the damages in cooperation exchange with relevant local authorities and that it is not possible to estimate a timeframe for restoring the gas transport infrastructure.

Financial market news

  • West Texas Intermediate crude oil closed at USD $79.49 per barrel on September 30th, down from a closing value of USD $89.55 at the end of August. Western Canadian Select crude oil traded in the USD $55 to $68 per barrel range throughout September. The Canadian dollar closed at 72.96 cents U.S. on September 29th, down from 76.27 cents U.S. at the end of August. The S&P/TSX composite index closed at 18,444.22 on September 30th, down from 19,330.81 at the end of August.

Business or organization information

1. Which of the following categories best describes this business or organization?

  • Government agency
  • Private sector business
  • Non-profit organization
    • Who does this organization primarily serve?
      • Households or individuals
        e.g., child and youth services, community food services, food bank, women's shelter, community housing services, emergency relief services, religious organization, grant and giving services, social advocacy group, arts and recreation group
      • Businesses
        e.g., business association, chamber of commerce, condominium association, environment support or protection services, group benefit carriers (pensions, health, medical)
  • Don't know

Business or organization information

2. In what year was this business or organization first established?

Please provide the year this business or organization first began operations.
Year business or organization was first established:
OR
Don't know

3. Over the last 12 months, did this business or organization conduct any of the following international activities?

Select all that apply.

  • Export or sell goods outside of Canada
    Include both intermediate and final goods.
  • Export or sell services outside of Canada
    Include services delivered virtually and in person.
    e.g., software, cloud services, legal services, environmental services, architectural services, digital advertising
  • Make investments outside of Canada
  • Sell goods to businesses or organizations in Canada who then resold them outside of Canada
  • Import or buy goods from outside of Canada
    Include both intermediate and final goods.
  • Import or buy services from outside of Canada
    Include services received virtually and in person.
    e.g., software, cloud services, legal services, environmental services, architectural services, digital advertising
  • Relocate any business or organizational activities or employees from another country into Canada
  • Exclude temporary foreign workers.
  • Engage in other international business or organizational activities
    OR
  • None of the above

4. Over the next three months, how are each of the following expected to change for this business or organization?

Exclude seasonal factors or conditions.

  • Number of employees
    • Increase
    • Stay about the same
    • Decrease
    • Not applicable
    • Don't know
  • Vacant positions
    • Increase
    • Stay about the same
    • Decrease
    • Not applicable
    • Don't know
  • Sales of goods and services offered by this business or organization
    • Increase
    • Stay about the same
    • Decrease
    • Not applicable
    • Don't know
  • Selling price of goods and services offered by this business or organization
    • Increase
    • Stay about the same
    • Decrease
    • Not applicable
    • Don't know
  • Demand for goods and services offered by this business or organization
    • Increase
    • Stay about the same
    • Decrease
    • Not applicable
    • Don't know
  • Imports
    • Increase
    • Stay about the same
    • Decrease
    • Not applicable
    • Don't know
  • Exports
    • Increase
    • Stay about the same
    • Decrease
    • Not applicable
    • Don't know
  • Operating income
    • Increase
    • Stay about the same
    • Decrease
    • Not applicable
    • Don't know
  • Operating expenses
    • Increase
    • Stay about the same
    • Decrease
    • Not applicable
    • Don't know
  • Profitability
    • Increase
    • Stay about the same
    • Decrease
    • Not applicable
    • Don't know
  • Cash reserves
    • Increase
    • Stay about the same
    • Decrease
    • Not applicable
    • Don't know
  • Capital expenditures
    e.g., machinery, equipment
    • Increase
    • Stay about the same
    • Decrease
    • Not applicable
    • Don't know
  • Training expenditures
    • Increase
    • Stay about the same
    • Decrease
    • Not applicable
    • Don't know
  • Marketing and advertising budget
    • Increase
    • Stay about the same
    • Decrease
    • Not applicable
    • Don't know
  • Expenditures in research and development
    • Increase
    • Stay about the same
    • Decrease
    • Not applicable
    • Don't know

Business or organization obstacles

5. Over the next three months, which of the following are expected to be obstacles for this business or organization?

Select all that apply.

  • Shortage of labour force
  • Recruiting skilled employees
  • Retaining skilled employees
  • Shortage of space or equipment
  • Rising cost of inputs
    An input is an economic resource used in a firm's production process.
    e.g., labour, capital, energy and raw materials
  • Rising costs in real estate, leasing or property taxes
  • Rising inflation
  • Rising interest rates and debt costs
    e.g., borrowing fees, interest payments
  • Difficulty acquiring inputs, products or supplies from within Canada
  • Difficulty acquiring inputs, products or supplies from abroad
  • Maintaining inventory levels
  • Insufficient demand for goods or services offered
  • Fluctuations in consumer demand
  • Attracting new or returning customers
  • Cost of insurance
  • Transportation costs
  • Obtaining financing
  • Increasing competition
  • Challenges related to exporting or selling goods and services outside of Canada
  • Maintaining sufficient cash flow or managing debt
  • Other
    • Specify other:
    OR
  • None of the above

Flow condition: If "Recruiting skilled employees" or "Retaining skilled employees" is selected in Q5, go to Q6. Otherwise, go to Q7.

Labour challenges

6. Compared with 12 months ago, how would this business or organization describe its challenges with recruiting and retaining staff?

  • More challenging than 12 months ago
  • About the same
  • Less challenging than 12 months ago
  • Don't know

Flow condition: If "Difficulty acquiring inputs, products or supplies from within Canada", "Difficulty acquiring inputs, products or supplies from abroad", or "Maintaining inventory levels" is selected in Q5, go to Q7. Otherwise, go to Q12.

Supply chain challenges

7. How long does this business or organization expect the following to continue to be an obstacle?

  • Difficulty acquiring inputs, products or supplies from within Canada
    • Less than 3 months
    • 3 months to less than 6 months
    • 6 months to less than 12 months
    • 12 months or more
    • Don't know
  • Difficulty acquiring inputs, products or supplies from abroad
    • Less than 3 months
    • 3 months to less than 6 months
    • 6 months to less than 12 months
    • 12 months or more
    • Don't know
  • Maintaining inventory levels
    • Less than 3 months
    • 3 months to less than 6 months
    • 6 months to less than 12 months
    • 12 months or more
    • Don't know

8. Over the last three months, how have supply chain challenges experienced by this business or organization changed?

Supply chain challenges include difficulty acquiring inputs, products or supplies from within Canada or abroad and difficulty maintaining inventory levels.
Exclude seasonal factors or conditions.

  • Supply chain challenges have worsened
    • Which of the following factors have contributed to these challenges?
      Select all that apply.
      • Increased prices of inputs, products or supplies
      • Increased delays in deliveries of inputs, products or supplies
      • Supply shortages resulted in fewer inputs, products or supplies being available
      • Supply shortages resulted in no inputs, products or supplies available
      • Other
        • Specify other:
        OR
      • Don't know
  • Supply chain challenges have remained about the same
  • Supply chain challenges have improved

9. Over the next three months, how does this business or organization expect supply chain challenges to change?

Supply chain challenges include difficulty acquiring inputs, products or supplies from within Canada or abroad and difficulty maintaining inventory levels.
Exclude seasonal factors or conditions.

  • Supply chain challenges are expected to worsen
  • Supply chain challenges are expected to remain about the same
  • Supply chain challenges are expected to improve

Supply chain

10. Over the next 12 months, does this business or organization plan to make any of the following adjustments to its supply chain?

Select all that apply.

  • Relocate supply chain activities to Canada
  • Relocate supply chain activities outside of Canada
  • Substitute inputs, products or supplies with alternate inputs, products or supplies
  • Shift to local suppliers
  • Partner with new suppliers
  • Work with suppliers to improve timeliness
  • Implement technological improvements
  • Invest in research and development projects to identify alternate inputs, products, supplies, or production processes
  • Other
    • Specify other:
    OR
  • Don't know
    OR
  • None of the above

Display condition: If "Maintaining inventory levels" is selected in Q5, go to Q11. Otherwise, go to Q12.

11. Over the next three months, in response to an expected difficulty maintaining inventory levels, which of the following does this business or organization plan to do?

Select all that apply.

  • Raise selling prices for goods and services offered
  • Accept backorders for goods or delay date of services
  • Stop taking sales orders
  • Increase promotion for alternative goods with greater availability
  • Find alternate inputs
  • Improve or speed up production process
  • Improve inventory tracking to plan timing of purchases
  • Other
    • Specify other:
    OR
  • Don't know
    OR
  • None of the above

Flow condition: If the business or organization is a private sector business or non-profit organization, go to Q12. Otherwise, go to Q13.
Display condition: If the business or organization is a non-profit organization, do not display "Transfer the business" or "Sell the business".

Expectations for the next year

12. Over the next 12 months, does this business or organization plan to do any of the following?

Select all that apply.

  • Expand current location of this business or organization
  • Expand operations of this business or organization internationally
  • Expand operations of this business or organization into a new province or territory within Canada
  • Move operations of this business or organization to another province or territory within Canada entirely
  • Expand this business or organization to other locations within the same province
  • Expand this business or organization without increasing physical space
    i.e., hiring more staff who will work remotely
  • Restructure this business or organization
  • Restructuring involves changing the financial, operational, legal or other structures of the business or organization to make it more efficient or more profitable.
  • Acquire other businesses, organizations or franchises
  • Invest in other businesses or organizations
  • Merge with other businesses or organizations
  • Scale down operations of this business or organization to within a single province or territory within Canada
  • Transfer the business
  • Sell the business
    OR
  • Close the business or organization
    OR
  • Don't know
    OR
  • None of the above

Input costs

13. Over the next 12 months, how likely is this business or organization to pass on any increases in its costs to customers?

e.g., costs related to increases in wages, inputs, products, supplies, taxes, rents, and carbon prices.

  • Very likely
  • Somewhat likely
  • Somewhat unlikely
  • Very unlikely
  • Don't know

Retirement

14. What percentage of employees does this business or organization expect to voluntarily retire over the next 12 months?

Exclude layoffs.
Provide your best estimate rounded to the nearest percentage.
Percentage of employees expected to retire over the next 12 months:
OR
Don't know

Flow condition: If the percentage of employees expected to retire over the next 12 months is greater than 0% in Q14, go to Q15. Otherwise, go to Q16.

15. Does this business or organization have plans in place to address expected retirements?

e.g., hiring staff to fill vacancies due to retirements, training staff to take over responsibilities of retiring staff

  • Yes
  • No
  • Don't know

Wages

16. Over the next 12 months, does this business or organization expect the average wages paid to change?

  • Average wages are expected to increase
    • By what percentage are average wages expected to increase?
      Provide your best estimate rounded to the nearest percentage.
      • Percentage:
        OR
      • Don't know
  • Average wages are expected to decrease
    • By what percentage are average wages expected to decrease?
      Provide your best estimate rounded to the nearest percentage.
      • Percentage:
        OR
      • Don't know
  • Average wages are expected to stay approximately the same
  • Not applicable
    e.g., This business or organization does not pay wages

17. To what extent does this business or organization consider inflation when setting wages and salaries?

  • A large extent
  • A medium extent
  • A small extent
  • Not at all
  • Don't know

Recruitment, retention and training

18. Does this business or organization currently do or plan to do any of the following over the next 12 months?

Select all that apply.

  • Increase wages offered to new employees
  • Increase wages offered to existing employees
  • Increase benefits offered to new employees
  • Increase benefits offered to existing employees
  • Offer signing bonuses or incentives to new employees
  • Offer option to work remotely
  • Offer flexible scheduling
  • Apply for learning and development programs provided by governments in order to upskill or reskill current employees
  • Work with education and training institutions to offer work-integrated learning programs such as co-ops, internships, and apprenticeships
  • Provide tuition support to employees to take courses or programs
  • Provide employees with paid time to engage in learning and development programs
  • Provide training to employees to take other positions within this business or organization
  • Encourage employees to participate in on-the-job training
  • Encourage employees to acquire micro-credentials which help individuals develop job-related competencies
    Micro-credentials are short, concentrated groups of courses that are based on industry needs. They are generally offered in shorter or more flexible timespans and tend to be more narrowly focused in comparison with traditional degrees and certificates. Some micro-credentials may be stackable and can be combined to form a part of a larger credential.
    OR
  • None of the above

Volunteering

19. Does this business or organization have, or intend to recruit, volunteers?

  • Yes
    • Which of the following is this business or organization facing in volunteer recruitment and retention?
      Select all that apply.
      • Shortage of new volunteers
      • Volunteer retention
      • Volunteers not able to commit long term
      • High volunteer burnout and stress
      • Lack of time or resources for this business or organization to recruit volunteers
      • Other
        • Specify other:
        OR
      • No issues – No new volunteers are required
        OR
      • No issues – While some previous volunteers have not returned, this business or organization has been successful in recruiting new volunteers for all available roles
        OR
      • Don't know
  • No
  • Don't know

Display condition: If "Yes" is selected in Q19, go to Q20. Otherwise, go to Q21.

20. Volunteer recruitment and retention challenges have had which of the following impacts or expected impacts on this business or organization?

Select all that apply.

  • Paid employees working increased hours to take on volunteer roles
  • Employee burnout
  • Reduction of programs and services offered
  • Cancellation of programs and services offered
  • Adapting current volunteer tasks to meet operational requirements
    e.g., volunteers take on more responsibilities
  • Other
    • Specify other:
    OR
  • Don't know
    OR
  • There has been no impact on this business or organization

Technology and automation

21. Over the next 12 months, does this business or organization plan to adopt or incorporate any of the following technologies?

Exclude technologies already adopted.
Select all that apply.

  • Software or hardware using artificial intelligence
    e.g., machine learning, predictive technology, virtual personal assistants, online customer support bots, image or speech recognition
  • Robotics
  • Automation of certain tasks
    e.g., through the use of robots or computer algorithms
  • Cloud computing
    Cloud computing: services that are used over the internet to access software, computing power, or storage capacity.
    e.g., Microsoft 365®, Google Cloud™, Dropbox™
  • Collaboration tools
    e.g., Zoom™, Microsoft Teams™, Slack™
  • Security software tools
    e.g., anti-virus, anti-spyware, anti-malware, firewalls
  • Software or databases for purposes other than telework and online sales
  • Digital technology to move business operations or sales online (for purposes other than teleworking or remote working)
  • Other
    • Specify other:
    OR
  • None of the above

Flow condition: If at least one technology or "Other" is selected in Q21, go to Q22. Otherwise, go to Q23.

22. Using a scale from 1 to 5, where 1 means "not at all challenging" and 5 means "extremely challenging", how challenging are the following for this business or organization when adopting or incorporating technologies?

  • Reorienting business strategy and processes
    • 1 – Not at all challenging
    • 2
    • 3
    • 4
    • 5 – Extremely challenging
    • Not relevant
  • Retraining employees with skills to use new technologies and processes
    • 1 – Not at all challenging
    • 2
    • 3
    • 4
    • 5 – Extremely challenging
    • Not relevant
  • Hiring workers with skills in technologies
    • 1 – Not at all challenging
    • 2
    • 3
    • 4
    • 5 – Extremely challenging
    • Not relevant
  • Finding suitable hardware or software vendors
    • 1 – Not at all challenging
    • 2
    • 3
    • 4
    • 5 – Extremely challenging
    • Not relevant
  • Ensuring high-speed connectivity
    • 1 – Not at all challenging
    • 2
    • 3
    • 4
    • 5 – Extremely challenging
    • Not relevant
  • Integrating new digital technologies into this business' or organization's existing technology infrastructure
    • 1 – Not at all challenging
    • 2
    • 3
    • 4
    • 5 – Extremely challenging
    • Not relevant
  • Having access to financial resources to invest in new technologies
    • 1 – Not at all challenging
    • 2
    • 3
    • 4
    • 5 – Extremely challenging
    • Not relevant
  • Ensuring security and privacy of data
    • 1 – Not at all challenging
    • 2
    • 3
    • 4
    • 5 – Extremely challenging
    • Not relevant

Lending

23. Over the last 12 months, did this business or organization apply for a new line of credit, a new term loan, a new non-residential mortgage, or refinancing of an existing non-residential mortgage?

Include commercial mortgages.
Exclude residential mortgages.

  • Yes
    • Was the largest request made approved, either fully or partially?
      • Yes
      • No
        • What reasons were given by the credit provider for turning down the request?
          Select all that apply.
          • Insufficient sales or cash flow
          • Insufficient collateral
          • Poor or lack of credit experience or history
          • Project was considered too risky
          • Business or organization operates in an unstable industry
          • Other
            OR
          • No reason given by credit provider
            OR
          • Don't know
      • This business or organization is still waiting for the outcome
      • The request was withdrawn by the business or organization
      • Don't know
  • No
    • Which of the following were reasons this business or organization did not apply for a business loan?
      Select all that apply.
      • This business or organization did not require a loan
      • Thought the request would be turned down
      • Interest rates or cost of borrowing are too high
      • Concern about the economy or inflation
      • Applying for financing is too difficult or time consuming
      • Unaware of financing sources (private or government) that are available to this business or organization
      • Other
        OR
      • Don't know
  • Don't know

Liquidity

24. Does this business or organization have the cash or liquid assets required to operate for the next three months?

  • Yes
  • No
    • Will this business or organization be able to acquire the cash or liquid assets required?
      • Yes
      • No
      • Don't know
  • Don't know

Debt

25. Over the next three months, does this business or organization plan to apply for a new line of credit, a new term loan, a new non-residential mortgage, or refinancing of an existing non-residential mortgage?

Include commercial mortgages.
Exclude residential mortgages.

  • Yes
  • No
    • Does this business or organization have the ability to take on more debt?
      • Yes
      • No
        • For which of the following reasons is this business or organization unable to take on more debt?
          Select all that apply.
          • Cash flow
          • Lack of confidence or uncertainty in future sales
          • Request would be turned down
          • Too difficult or time consuming to apply
          • Interest rates are unfavourable
          • Payment terms are unfavourable
          • Credit rating
          • Other
            • Specify other:
            OR
          • Don't know
      • Don't know
  • Don't know

26. Which of the following best describes the current debt level of this business or organization?

  • Greater than the debt level just prior to the onset of the COVID-19 pandemic
  • About the same as it was just prior to the start of the COVID-19 pandemic
  • Below the debt level just before the start of the COVID-19 pandemic
  • Don't know
  • Not applicable
    e.g., The business or organization did not exist prior to the COVID-19 pandemic

27. Over the next 12 months, to what extent does this business or organization foresee challenges in repaying funding received from repayable government support programs put in place because of the COVID-19 pandemic?

Examples of repayable government support programs include the Canada Emergency Business Account (CEBA) or the Indigenous Business Initiative (sometimes referred to as the Emergency Loan Program (ELP), issued through an Aboriginal Financial Institutions (AFI) or Métis Capital Corporations (MCCs)).

  • Not a challenge
  • A minor challenge
  • A major challenge
  • Don't know
  • This business or organization did not receive any repayable funding from government support programs related to the COVID-19 pandemic

Working arrangements

28. Over the next three months, what percentage of the employees of this business or organization is anticipated to do each of the following?

Exclude staff that are primarily engaged in providing driving or delivery services or staff that primarily work at client premises.

Provide your best estimate rounded to the nearest percentage.
If the percentages are unknown, leave the question blank.

  • Work on-site exclusively
    Percentage of employees:
  • Work on-site most hours
    Percentage of employees:
  • Work the same amount of hours on-site and remotely
    Percentage of employees:
  • Work remotely most hours
    Percentage of employees:
  • Work remotely exclusively
    Percentage of employees:

Future outlook

29. Over the next 12 months, what is the future outlook for this business or organization?

  • Very optimistic
  • Somewhat optimistic
  • Somewhat pessimistic
  • Very pessimistic
  • Don't know

Flow condition: If the business or organization is a private sector business, go to Q30. Otherwise, go to "Contact person".

Ownership

(i) The groups identified within the following questions are included in order to gain a better understanding of businesses owned by members of various communities across Canada.

30. What percentage of this business or organization is owned by women?

Provide your best estimate rounded to the nearest percentage.

Percentage:
OR
Don't know

31. What percentage of this business or organization is owned by First Nations, Métis or Inuit peoples?

Provide your best estimate rounded to the nearest percentage.

Percentage:
OR
Don't know

32. What percentage of this business or organization is owned by immigrants to Canada?

Provide your best estimate rounded to the nearest percentage.

Percentage:
OR
Don't know

33. What percentage of this business or organization is owned by persons with a disability?

Include visible and non-visible disabilities.

Provide your best estimate rounded to the nearest percentage.

Percentage:
OR
Don't know

34. What percentage of this business or organization is owned by LGBTQ2 individuals?

The term LGBTQ2 refers to persons who identify as lesbian, gay, bisexual, transgender, queer and/or two-spirited.

Provide your best estimate rounded to the nearest percentage.

Percentage:
OR
Don't know

35. What percentage of this business or organization is owned by members of visible minorities?

A member of a visible minority in Canada may be defined as someone (other than an Indigenous person) who is non-white in colour or race, regardless of place of birth.

Provide your best estimate rounded to the nearest percentage.

Percentage:
OR
Don't know

Flow condition: If more than 50% of this business or organization is owned by members of visible minorities, go to Q36. Otherwise, go to "Contact person".

36. It was indicated that at least 51% of this business or organization is owned by members of visible minorities. Please select the categories that describe the owner or owners.

Select all that apply.

  • South Asian
    e.g., East Indian, Pakistani, Sri Lankan
  • Chinese
  • Black
  • Filipino
  • Latin American
  • Arab
  • Southeast Asian
    e.g., Vietnamese, Cambodian, Laotian, Thai
  • West Asian
    e.g., Afghan, Iranian
  • Korean
  • Japanese
  • Other group
    • Specify other group:
    OR
  • Prefer not to say

MLflow Tracking: An efficient way of tracking modeling experiments

By: Mihir Gajjar, Statistics Canada
Contributors: Reginald Maltais, Allie Maclsaac, Claudia Mokbel and Jeremy Solomon, Statistics Canada

MLflow is an open source platform that manages the machine learning lifecycle, including experimentation, reproducibility, deployment and a central model registry. MLflow offers four components:

  • MLflow Tracking: Record and query experiments—code, data, configuration parameters and results.
  • MLflow Projects: Package data science code in a format to reproduce runs on any platform.
  • MLflow Models: Deploy machine learning models in diverse serving environments.
  • Model Registry: Store, annotate, discover and manage models in a central repository.

This article focuses on MLflow Tracking. The MLflow website has details on the remaining three components.

Benefits of MLFlow

MLflow Tracking provides a solution that can be scaled from your local machine to the entire enterprise. This allows data scientists to get started on their local machine while organizations can implement a solution that ensures long term maintainability and transparency in a central repository.

MLflow Tracking provides consistent and transparent tracking by:

  • Tracking parameters and the corresponding results for the modeling experiments programmatically and comparing them using a user interface.
  • Recovering the model having the best results along with its corresponding code for different metrics of interest across experiments for different projects.
  • Looking back through time to find experiments conducted with certain parameter values.
  • Enabling team members to experiment and share results collaboratively.
  • Exposing the status of multiple projects in a singular interface for management along with all their details (parameters, output plots, metrics, etc.).
  • Allowing tracking across runs and parameters through a single notebook, reducing time spent managing code and different notebook versions.
  • Providing an interface for tracking both Python and R based experiments.

How do I flow between my experiments with MLflow?

This article focuses on using MLflow with Python. The MLflow QuickStart document has examples of its use with R for a local installation on a single machine. Organizations wishing to deploy MLflow across teams could also refer to the QuickStart document.

This article will explore an example of using MLflow with Python; however, to get the best understanding of how MLFlow works, it's useful to go through each step on your machine.

Install MLflow

MLflow can be installed as a standard Python package by typing the following command in a terminal window:

$ pip install mlflow

After the command has finished executing, you can type mlflow in your terminal and explore the available options. For example, you can try: mlflow –version to see the version installed

Launch MLflow server

It's recommended to have a centralized MLflow server for an individual, team or organization so that runs for different projects can be logged in one central place, segregated by experiments (different experiments for different projects). This will be covered in more detail later in this article. To quickly get started with the tool, you can skip the server launch and still log the runs. By doing this, the runs are stored in a directory called "MLruns" located in the same directory as the code. You can later open MLflow UI in the same path and visualize the logged runs.

The runs can be logged to an MLflow server running locally or remotely by setting the appropriate tracking URI (uniform resource identifier). Setting the appropriate logging location is explained later.

If, however, you prefer to start the server right away, you can do so by issuing the following command:

$ mlflow server

The terminal will display information similar to what is below, which shows the server is listening at localhost port 5000This address is useful for accessing the MLflow user interface (UI). Feel free to explore the subtle difference between MLflow UI and MLflow server in the MLflow Tracking documentation.

[2021-07-09 16:17:11 –0400] [58373] [INFO] Starting gunicorn 20.1.0
[2021-07-09 16:17:11 –0400] [58373] [INFO] Listening at: http://127.0.0.1:5000 (58373)
[2021-07-09 16:17:11 –0400] [58373] [INFO] Using worker: sync
[2021-07-09 16:17:11 –0400] [58374] [INFO] Booting worker with pid: 58374
[2021-07-09 16:17:11 –0400] [58375] [INFO] Booting worker with pid: 58375
[2021-07-09 16:17:11 –0400] [58376] [INFO] Booting worker with pid: 58376
[2021-07-09 16:17:11 –0400] [58377] [INFO] Booting worker with pid: 58377

Logging data to MLflow

There are two main concepts in MLflow tracking: experiments and runs. The data logged during an experiment is recorded as a run in MLflow. The runs can be organized into experiments, which groups together runs for a specific task. One can visualize, search, compare, and download run artifacts and metadata for the runs logged in an MLflow experiment.

Data in an experiment can be logged as a run in MLflow using MLflow Python, R, Java packages, or through the REST API (application programming interface).

This article will demonstrate modeling for one of the "Getting started with NLP (natural language processing)" competitions on Kaggle called "Natural Language Processing with Disaster Tweets." A Jupyter notebook and the MLflow Python API will be used for logging data to MLflow. The focus will be on demonstrating how to log data to MLflow during modeling, rather than getting the best modeling results.

First, let's start with the usual modeling process, which includes imports, reading the data, text pre-processing, tf-idf (term frequency-inverse document frequency) features and support vector machine (SVM) model. At the end, there will be a section called "MLflow logging."

Note: The NLP pipeline is kept as simple as possible so that the focus is on MLflow logging. Some of the usual steps, like exploratory data analysis, are not relevant for this purpose and will be left out. The preferred way of logging data to MLflow is by leaving a chunk of code at the end to log. You can also configure MLflow at the beginning of the code and log data throughout the code, when the data or variable is available to log. An advantage to logging all the data together at the end using a single cell is that the entire pipeline would finish successfully, and the run will log the data (given the code for MLflow logging has no bugs). If the data are logged throughout the code and the code execution stops for any reason, the data logging will be incomplete. However, if there's a scenario where a code has more than one code chunk, which takes a significant amount of time to execute, then logging throughout the code, in multiple locations, may actually be beneficial.

Importing the libraries

Start by importing all the required libraries for the example:

# To create unique run name.
import time
# To load data in pandas dataframe.
import pandas as pd

# NLP libraries

# To perform lemmatization
from nltk import WordNetLemmatizer
# To split text into words
from nltk. tokenize import word_tokenize
# To remove the stopwords
from nltk.corpus import stopwords

# Scikit-learn libraries

# To use the SVC model
from sklearn.svm import SVC
# To evaluate model performance
from sklearn.model_selection import cross_validate, StratifiedkFold
# To perform Tf-idf vectorization
from sklearn.feature_extraction.text import TfidfVectorizer
# To get the performance metrics
from sklearn.metrics import f1_score, make_scorer
# For logging and tracking experiments
import mlflow

Create a unique run name

MLflow tracks multiple runs of an experiment through a run name parameter. The run name can be set to any value, but should be unique so you can identify it amongst different runs later. Below, a timestamp is used to guarantee a unique name.

run_name = str(int(time.time()))
print('Run name: ', run_name)

Gives:

Run name: 1625604741

Reading the data

Load the training and test data from the CSV files provided by the example.

# Kaggle competition data download link: https://www.kaggle.com/c/nlp-getting-started/data
train_data = pd.read_csv("./data/train.csv")
test_data = pd.read_csv("./data/test.csv")

By executing the following piece of code in a cell:

train_data

A sample of the training data that was just loaded can be seen in Figure 1.

Figure 1: A preview of the training data that was loaded.

Figure 1: A preview of the training data that was loaded.

Figure 1: A preview of the training data that was loaded.

The top and bottom five entries of the CSV file. It contains the columns: id, keyword, location, text and target. The text column contains the tweet itself and the target column, the class.

Figure 1: A preview of the training data that was loaded.
  id keyboard location text target
0 1 NaN Nan Our Deeds are the Reason of this #earthquake M… 1
1 4 NaN Nan Forest fire near La Ronge Sask. Canada 1
2 5 NaN Nan All residents asked to 'shelter in place' are… 1
3 6 NaN Nan 13,000 people receive #wildfires evacuation or… 1
4 7 NaN Nan Just got sent this photo from Ruby #Alaska as… 1
... ... ... ... ... ...
7608 10869 NaN Nan Two giant cranes holding a bridge collapse int… 1
7609 10870 NaN Nan @aria_ahrary @TheTawniest The out of control w… 1
7610 10871 NaN Nan M1.94 [01:04 UTC] ?5km S of Volcano Hawaii. Htt… 1
7611 10872 NaN Nan Police investigating after an e-bike collided… 1
7612 10873 NaN Nan The Latest: More Homes Razed by Northern Calif… 1

7613 rows x 5 columns

The training data are about 70% of the total data.

print('The length of the training data is %d' % len(train_data))
print('The length of the test data is %d' % len(test_data))

Output:

The length of the training data is 7613
The length of the test data is 3263

Text pre-processing

Depending on the task at hand, different types of preprocessing steps might be required to make the machine learning model learn better features. Preprocessing can normalize the input, remove some of the common words if required so that the model does not learn them as features, make logical and meaningful changes that can lead to the model performing and generalizing better. The following demonstrates how performing some pre-processing steps can help the model grab the right features when learning:

def clean_text(text):
    # split into words
    tokens = word_tokenize(text)
    # remove all tokens that are not alphanumeric. Can also use .isalpha() here if do not want to keep numbers.
    words = [word for word in tokens if word.isalnum()]
    # remove stopwords
    stop_words = stopwords.words('english')
    words = [word for word in words if word not in stop_words]
    # performing lemmatization
    wordnet_lemmatizer = WordNetLemmatizer()
    words = [wordnet_lemmatizer.lemmatize(word) for word in words]
    # Converting list of words to string
    words = ' '.join(words)
    return words

train_data['cleaned_text'] = train_data['text'].apply(clean_text)

Comparing the original text to the cleaned text, non-words have been removed:

train_data['text'].iloc[100]

'.@NorwayMFA #Bahrain police had previously died in a road accident they were not killed by explosion https://t.co/gFJfgTodad'

train_data['cleaned_text'].iloc[100]rain_data['text'].iloc[100]

'NorwayMFA Bahrain police previously died road accident killed explosion http'

Reading the text above, one can say that, yes, it does contain information about a disaster and hence should be classified as one. To confirm this with the data, print out the label present in the CSV file for this tweet:

train_data['target'].iloc[100]

Output:

1

Tf-idf features

Next, we are converting a collection of raw documents to a matrix of TF-IDF features to feed into the model. For more information about tf-idf, please refer to tf–idf - Wikipedia and scikit-learn sklearn.feature_extraction.text documentation.

ngram_range=(1,1)
max_features=100
norm='l2'

tfidf_vectorizer = TfidfVectorizer(ngram_range=ngram_range, max_features=max_features, norm=norm)

train_data_tfidf = tfidf_vectorizer.fit_transform(train_data['cleaned_text'])
train_data_tfidf

Output:

<7613x100 sparse matrix of type '<class 'numpy.float64'>'
with 15838 stored elements in Compressed Sparse Row format>

tfidf_vectorizer.get_feature_names()[:10]

Output:

['accident',
'amp',
'and',
'as',
'attack',
'back',
'best',
'body',
'bomb',
'building']

SVC model

The next step to perform the modeling is to fit a model and evaluate the performance.

Stratified K-Folds cross-validator is used to evaluate the model. See scikit learn sklearn.model_selection for more information.

strat_k_fold = StratifiedKFold(n_splits=5, shuffle=True, random_state=42)

Making a scorer function using the f1-score metric to pass it as a parameter in the SVC model.

scoring_function_f1 = make_scorer(f1_score, pos_label=1, average='binary')

Now comes an important step of fitting the model to the data. This example uses the SVC classifier. See scikit learn sklearn.svm.svc for more information.

C = 1.0
kernel='poly'
max_iter=-1
random_state=42

svc = SVC(C=C, kernel=kernel, max_iter=max_iter, random_state=random_state) 
cv_results = cross_validate(estimator=svc, X=train_data_tfidf, y=train_data['target'], scoring=scoring_function_f1, cv=strat_k_fold, n_jobs=-1, return_train_score=True)
cv_results

Output:

{'fit_time': array([0.99043322, 0.99829006, 0.94024873, 0.97373009, 0.96771407]),
'score_time': array([0.13656974, 0.1343472 , 0.13345313, 0.13198996, 0.13271189]),
'test_score': array([0.60486891, 0.65035517, 0.5557656 , 0.5426945 , 0.63071895]),
'train_score': array([0.71281362, 0.76168757, 0.71334394, 0.7291713 , 0.75554698])}

def mean_sd_cv_results(cv_results, metric='F1'):
    print(f"{metric} Train CV results: {cv_results['train_score'].mean().round(3)} +- {cv_results['train_score'].std().round(3)}")
    print(f"{metric} Val CV results: {cv_results['test_score'].mean().round(3)} +- {cv_results['test_score'].std().round(3)}")

mean_sd_cv_results(cv_results)

F1 Train CV results: 0.735 +- 0.021
F1 Val CV results: 0.597 +- 0.042

Note: The code below is executed as a shell command by adding the exclamation mark: '!' in the beginning of the code in a Jupyter cell.

! Jupyter nbconvert --to html mlflow-example-real-or-not-disaster-tweets-modeling-SVC.ipynb

[NbConvertApp] Converting notebook mlflow-example-real-or-not-disaster-tweets-modeling-SVC.ipynb to html
[NbConvertApp] Writing 610630 bytes to mlflow-example-real-or-not-disaster-tweets-modeling-SVC.html

Logging to MLflow

First, set the server URI. As the server is running locally, set the tracking URI to localhost port 5000. The tracking URI can be set to a remote server as well (see Where Runs are Recorded).

server_uri = 'http://127.0.0.1:5000'
mlflow.set_tracking_uri(server_uri)

To organize the runs, an experiment was created and set where the runs will be logged. The "set_experiment" method will create a new run with the given string name and set it as the current experiment where the runs will be logged.

mlflow.set_experiment('nlp_with_disaster_tweets')

Finally, start a run and log data to MLflow.

# MLflow logging.
with mlflow.start_run(run_name=run_name) as run:

    # Logging tags
    # run_name.
    mlflow.set_tag(key='Run name', value=run_name)
    # Goal.
    mlflow.set_tag(key='Goal', value='Check model performance and decide whether we require further pre-processing/hyper-parameter tuning.')
    # Modeling exp.
    mlflow.set_tag(key='Modeling technique', value='SVC')

    # Logging parameters
    mlflow.log_param(key='ngram_range', value=ngram_range)
    mlflow.log_param(key='max_features', value=max_features)
    mlflow.log_param(key='norm', value=norm)
    mlflow.log_param(key='C', value=C)
    mlflow.log_param(key='kernel', value=kernel)
    mlflow.log_param(key='max_iter', value=max_iter)
    mlflow.log_param(key='random_state', value=random_state)

    # Logging the SVC model.
    mlflow.sklearn.log_model(sk_model=svc, artifact_path='svc_model')
   
    # Logging metrics.
    # mean F1-score - train.
    mlflow.log_metric(key='mean F1-score - train', value=cv_results['train_score'].mean().round(3))
    # mean F1-score - val.
    mlflow.log_metric(key='mean F1-score - val', value=cv_results['test_score'].mean().round(3))
    # std F1-score - train.
    mlflow.log_metric(key='std F1-score - train', value=cv_results['train_score'].std().round(3))
    # std F1-score - val.
    mlflow.log_metric(key='std F1-score - val', value=cv_results['test_score'].std().round(3))
   
    # Logging the notebook.
    # Nb.
    mlflow.log_artifact(local_path='real-or-not-disaster-tweets-modeling-SVC.ipynb', artifact_path='Notebook')
    # Nb in HTML.
    mlflow.log_artifact(local_path='real-or-not-disaster-tweets-modeling-SVC.html', artifact_path='Notebook')

In the code above, you begin a run with a run_name and then log the following:

  1. Tags: A key-value pair. Both the key and the value are strings. For instance, this can be used to log the goal of the run where the key would be 'Goal:' and the value can be 'To try out the performance of Random Forest Classifier with default parameters.'
  2. Parameters: Also, a key-value pair and can be used to log the model parameters.
  3. Model: Can be used to log the model. Here you are logging a scikit-learn model as an MLflow artifact, but we can also log a model for other supported machine learning libraries using the corresponding MLflow module.
  4. Metrics: A key-value pair. The key data type is "string" and it can have the metric name. The value parameter has a data type "float". The third optional parameter is "step" which is an integer that represents any measurement of training progress – number of training iterations, number of epochs, etc.
  5. Artifacts: A local file or directory can be logged as an artifact for the current run. In this example, we're logging using the notebook so that they're accessible for future runs. By doing this, you can save a plot like "loss curve" or "accuracy curve" in the code and log them as an artifact in MLflow.

There you have it—you successfully logged data for a run in MLflow! The next step is to visualize the logged data.

MLflow UI

If you scroll back to Figure 1, you'll remember that you launched the server and it was listening at localhost port 5000. Open this address in your preferred browser to access the MLflow UI. Once the MLflow UI is visible, you can use the interface to look at the experiment data that was logged. The experiments created appear in the sidebar of the UI, and the logged tags, parameters, model and metrics are shown in the columns.

Figure 2: MLflow UI

Figure 2: MLflow UI

Figure 2: MLflow UI

Figure 2 shows the MLflow UI. The experiment which was set above i.e. nlp_with_disaster_tweets is opened and the run that you logged earlier along with the details such as run name, parameters and metrics. It also shows the location where the artifacts are stored. You can click on the logged run to explore it in further detail.

Text in image: MLflow Expriements Models

Nlp_with_disaster_tweets (1. Click on this experiment)

Experiment ID: 1, Artifact Location: ./miruns/1 (Location of the logged artifacts)

Notes: None

2. Explore the logged data

Figure 2: MLflow UI
  Parameters Metrics Tags
Start Time Run Name User Source Version Model C Kernel max_feature Mean F1-s Mean F1-s Std F1-s Modeling t
2021-07-09 16:27:58 16258… Mihir ipykerne - sklearn 1.0 poly 100 0.735 0.597 0.021 SVC

3. The run that we logged using the Python API. Click on the link to open the run

To explore a specific run in greater detail, click on the relevant run in the Start Time column. This will allow you to explore a logged run in detail. The run name is shown and you can add any notes for the run such as logged parameters, metrics, tags and artifacts. The data logged using the Python API for this run are shown here.

The files logged as artifacts can be downloaded, which can be useful if you want to retrieve the code later. Since the code that generates results for every run is saved, you don't need to create multiple copies of the same code and can experiment using a single skeleton notebook by changing the code between runs.

The logged trained model can be loaded in a future experiment using the Python API from the logged run.

Figure 3: Exploring the logged artifacts in a run

Figure 3: Exploring the logged artifacts in a run

Figure 3: Exploring the logged artifacts in a run

Figure 3 explores the logged artifacts. The logged files (notebook and the model) are shown. The description of the model also provides code to load the logged model in Python.
Text in image:

Tags

Figure 3: Exploring the logged artifacts in a run
Name Value Actions
Goal Check model performance and decide whether we require further pre-processing hyper-parameter tuning. Edit – delete icons
Modeling technique SVC Edit – delete icons
Run name 16525862471 Edit – delete icons

Add Tag
Name – Value – Add

Artifacts
Notebook

  • Real-or-not-disaster-tweets-modeling-SVC.html
  • Real-or-not-disaster-tweets-modeling-SVC.ipynb

svc_model

  • MLmodel
  • conda.yaml
  • model.pld

Full Path: ./miruns/1/fcdc8362b2fe74329a4128fa522d80cb/artifacts/svc_model
Size: 0B

MLflow Model
The code snippets below demonstrate how to make predictions using the logged model

Model schema
Input and output schema for your model. Learn more
Name – Type
No Schema.

To demonstrate the run comparison functionality, more modeling experiments were performed and logged to MLflow by changing a few parameters in the same jupyter notebook. Feel free to change some parameters and log more runs to MLflow.

Figure 4 shows the different logged runs. You can filter, keep the columns you want, and compare the parameters or metrics between different runs. To perform a detailed comparison, you can select the runs you want to compare and click on the "Compare" button highlighted in the figure below.

Figure 4: Customizing and comparing different runs using MLflow UI

Figure 4: Customizing and comparing different runs using MLflow UI

Figure 4: Customizing and comparing different runs using MLflow UI

In MLflow UI, one can customize the columns being shown, filter and search for different runs based on the logged data and can easily compare the different logged runs based on the visible columns. You can also compare different logged runs in greater detail by selecting them and clicking on the "Compare" button.

Text in image: 
1. Can filter and keep the columns of interest
Columns: Start Time, User, Run Name, Source, Version, Models, Parameters, Metrics, Tags
2. Can compare different runs
3. Different runs logged. Select the runs you want to compare
Showing 5 matching runs. Compare, Delete, Download, CSV
4. Click Compare 

Figure 4: Customizing and comparing different runs using MLflow UI
  Parameters Metrics Tags
Start Time Run Name User Source Version Model C Kernel max_fe Mean F1-s Mean F1-s Std F1-s Modeling Run name Goal
2021-07-12 14:48:54 1626115725 Mihir ipykerne - sklearn 1.0 Poly 500 0.93 0.694 0.001 SVC 16261157 Check mo…
2021-07-12 14:48:16 1626115688 Mihir ipykerne - sklearn 1.0 Poly 500 0.931 0.693 0.001 SVC 16261156 Check mo…
2021-07-12 14:48:50 1626115602 Mihir ipykerne - sklearn 1.0 Poly 500 0.933 0.694 0.002 SVC 16261156 Check mo…
2021-07-12 14:48:01 1626115552 Mihir ipykerne - sklearn 1.0 Poly 500 0.876 0.649 0.002 SVC 16261155 Check mo…
2021-07-09 16:27:58 1625002471 Mihir ipykerne - sklearn 1.0 Poly 500 0.735 0.597 0.021 SVC 16258624 Check mo…

After clicking the "Compare" button, a table-like comparison between different runs will be generated, (as shown in Figure 5) allowing you to easily compare logged data across different runs. The parameters that differ across the runs are highlighted in yellow. This gives the user an idea of how model performance has changed over time based on the change in parameters.

Figure 5: Comparing logged runs in MLflow UI in detail

Figure 5: Comparing logged runs in MLflow UI in detail

Figure 5: Comparing logged runs in MLflow UI in detail

Figure 5 compares different logged runs in MLflow in detail. The tags, parameters and metrics are in different rows and the runs are in different columns. This allows a user to compare details of interest for different runs in a single window. The parameters which are different in different runs are highlighted in yellow. For example, in the experiments the parameters max_features and ngram_range were changed for different runs and hence they are highlighted in yellow in the image above.

Text in image:
Nlp_with_disaster_tweets > Comparing 5 Runs

Figure 5: Comparing logged runs in MLflow UI in detail
Run ID: 7a1448a5f88147c093
c357d787dbe3		 264533b107b04be3
bd4981560bad0397		 7670578718b3477abb
798d7e404fed6c		 D2372d5873f2435c
94dc7e633a611889		 Fdc8362b2f37432f9
a4128fa522d80cb
Run Name 1626115725 1626115688 1626115602 1626115552 16265862471
Start Time 2021-07-12 14:48:54 2021-07-12 14:48:16 2021-07-12 14:48:50 2021-07-12 14:46:01 2021-07-09 16:27:58
Parameters
C 1.0 1.0 1.0 1.0 1.0
Kernel Poly Poly Poly Poly Poly
Max_features 500 500 500 500 500
Max_iter -1 -1 -1 -1 -1
Ngram_range (1.3) (1.2) (1.1) (1.1) (1.1)
Norm 12 12 12 12 12
random_state 42 42 42 42 42
Metrics
Mean f1-score-train 0.93 0.931 0.933 0.876 0.735
Mean f1-score-val 0.694 0.693 0.694 0.649 0.597
std f1-score-train 0.001 0.001 0.002 0.002 0.021
std f1-score-val 0.008 0.009 0.01 0.013 0.042

Changes in the parameters and metrics across different runs can also be laid-out in a Scatter Plot. The values of the x-axis and y-axis can be set to any parameter or metric allowing the user to analyze the changes. In Figure 6, the reader can analyze the change in validation, in this case the mean F1-score, over different values for the parameter 'max_features'. If you hover over a data point, you can see details about that run.

Figure 6: Configuring the scatter plot to visualize the effects of different parameter configurations in the logged runs

Figure 6: Configuring the scatter plot to visualize the effects of different parameter configurations in the logged runs

Figure 6: Configuring the scatter plot to visualize the effects of different parameter configurations in the logged runs

A demonstration of MLflow's capability of plotting a graph using details from different runs. You can select a particular parameter on X-axis and a metric you want to monitor on the Y-axis; this will create a scatter plot with the details on the corresponding axis on the go and you will be able to visualize the effects of the parameter on the metric to get an idea about how the parameter is affecting the metric.

Text in image:
Scatter Plot
X-Axis: max_features
Y-Axis: mean F1-score-val

Figure 6: Configuring the scatter plot to visualize the effects of different parameter configurations in the logged runs
Run Name 1626115552
Start Time 2021-07-12 14:46:01
C 1.0
Kernel Poly
Max_features 500
Max_iter -1
Ngram_range (1.1)
Norm 12
random_state 42
Mean f1-score-train 0.876
Mean f1-score-val 0.649
std f1-score-train 0.002
std f1-score-val 0.013

The Parallel Coordinates Plot is also useful, as it shows the viewer the effect of the selected parameters on the desired metrics at a glance.

Figure 7: Configuring the parallel coordinates plot to visualize the effects of different parameters on the metrics of interest

Figure 7: Configuring the parallel coordinates plot to visualize the effects of different parameters on the metrics of interest

Figure 7: Configuring the parallel coordinates plot to visualize the effects of different parameters on the metrics of interest

In this image a parallel coordinates plot is configured. You can select different parameters and metrics using the provided input windows, based on which the parallel coordinates plot is updated. This plot can provide an idea about the results you get using different configurations in the experiments. It can help in comparing different configurations and selecting the parameters that perform better.

Text in image:
Scatter Plot – Contour Plot – Parallel Coordinates Plot
Paramters: random_state, norm, max_iter, max_features, C, kernel, ngram_range
Metrics: mean F1-score-val

Figure 7: Configuring the parallel coordinates plot to visualize the effects of different parameters on the metrics of interest
random_state norm Max_iter Max_features C Kernel ngram_range Mean F1-score-val  
46.20000   -1.10000 500.00000 1.10000     0.69400  
46.0000   -1.10000 500.00000 1.10000   (1.3) 0.68000 0.68
45.0000     450.00000          
44.0000   -1.05000 400.00000 1.05000     0.66000 0.66
43.0000     350.00000          
42.0000   -1.0000 300.00000 1.00000 poly (1.2) 0.64000 0.64
41.0000     250.00000          
40.0000   -0.95000 200.00000 0.95000     0.62000 0.62
39.0000     150.00000          
38.0000   -0.9000 100.00000 0.90000   (1.1) 0.60000 0.6
37.80000   -0.90000 100.0000 0.9000     0.59700  

Other interesting stuff in MLflow tracking:

There are other important points to note with MLflow tracking:

  • The runs can be exported to a CSV file directly using the MLflow UI.
  • All functions in the tracking UI can be accessed programmatically—you can query and compare runs with code, load artifacts from logged runs or run automated parameter search algorithms by querying the metrics from logged runs to decide the new parameters. You can also log new data to an already logged run in an experiment after loading it programmatically (visit Querying Runs Programmatically for more information).
  • By using the MLflow UI, users can search for runs having specific data values using the search bar. An example of this would be to use metrics.rmse < 1 and params.model='tree'. This is very helpful when you need to dig up a run with specific parameters executed in the past.
  • The Jupyter notebook used as an example in this blog post can be found on GitHub.

Feel free to contact us at statcan.dsnfps-rsdfpf.statcan@statcan.gc.ca and let me know about other interesting features or use case you like to use that you feel could have been mentioned. We will also have an opportunity for you to Meet the Data Scientist to discuss MLFlow in greater detail. See below for more details.

Register for the Data Science Network's Meet the Data Scientist Presentation

If you have any questions about this article or would like to discuss this further, we invite you to our new Meet the Data Scientist presentation series where the author will be presenting this topic to DSN readers and members.

Tuesday, October 18
2:00 to 3:00 p.m. EDT
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Register for the Data Science Network's Meet the Data Scientist Presentation. We hope to see you there!

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Eh Sayers Episode 9 - Sylvia Ostry: Lessons From A Legend

Release date: October 7, 2022

Catalogue number: 45200003
ISSN: 2816-2250

Sylvia Ostry

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If this is the first time you're hearing about Sylvia Ostry, buckle up.

Ostry was appointed Canada's first and only female chief statistician in 1972, but she didn't get there by playing by the rules. She was ambitious but grew up in a world where many thought that it was shameful to be female and have a career.

Sylvia was a Jewish woman in economics, and even after she earned a Ph.D. from the University of Cambridge, she was denied a job with the United Nations because of her gender. Nevertheless, she had a storied career, becoming the Chairman of the Economic Council of Canada then the Chief Economist at the OECD. But we're not focusing on her career highlights. We're going behind the scenes to look at how she challenged herself to succeed, becoming both a respected economist and mother, and how she handled setbacks, and discrimination, all while staying true to herself and demonstrating the integrity for which she's remembered today.

We're celebrating the 50th anniversary of Sylvia Ostry's appointment as chief statistician. In this episode of Eh Sayers, featuring interviews with her sons, Adam Ostry and Jonathan Ostry, we are pleased to introduce you to this remarkable woman and to share with you eight pieces of advice inspired by her life.

Host

Tegan Bridge

Guests

Adam Ostry, Jonathan Ostry

Listen to audio

Eh Sayers Episode 9 - Sylvia Ostry: Lessons From A Legend - Transcript

Tegan: Welcome to Eh Sayers, a podcast from Statistics Canada, where we meet the people behind the data and explore the stories behind the numbers. I'm your host Tegan Bridge.

In 1972, Sylvia Ostry became the first, and (so far!) only, female Chief Statistician of Canada. 50 years ago, the world was a different place. NASA was launching their Space Shuttle Program and the Godfather was in movie theaters.

The workplace was changing, with more and more women working outside the home than ever before. In 1972, 45% of women aged 25 to 54 participated in the labour market, that is, were employed or looking for a job. While that might seem like a relatively small percentage today, it represented a huge shift at the time. A decade earlier, in 1962, it was only 32%. That's a 40% increase in just ten years.

In 1952, while Sylvia became a lecturer at McGill, women in her home province of Manitoba were given the right to be jury members. Sylvia began working as the Director of Special Manpower Studies and Consultation at StatCan in 1965. Just one year before that, in 1964, women were given the right to open a bank account without their husband's signature. And in 1971, the year before Sylvia was made Chief Statistician, Manitoba stopped firing female municipal employees after they married.

When Sylvia Ostry was appointed head of the Economic Council of Canada, the Globe and Mail published an announcement at the bottom of the fifth page of the women's section.

Sylvia passed away in 2020, and to celebrate her, we're taking a look back at her life to see what we can learn from her.

You'll be hearing Sylvia's voice through clips from an interview she gave to Bronwyn Bragg and Mary Breen, recorded on May 28th, 2008.

So, here are 8 pieces of advice from the life of Sylvia Ostry.

(Chime)

Number one. Challenge yourself.

When you think about people who led remarkable lives, it's difficult to imagine who they were before they made it. Before they were successful.

Sylvia Ostry came from humble roots.

Adam: So, my name is Adam Ostry and Sylvia Ostry was my mother.

She was a pioneer, you know. Um. My her parents, now her mother had graduated from normal school in Winnipeg. She was an immigrant from England. She was born in in London. Tottenham Court Road. Can't get more working class than that in the 19-- in the 1890s. She, you know, she came from nothing. They had no money. They were penniless immigrants. My grandfather made money and then lost it during the depression and never really gained it back. You know my and my grandmother. Her mother was ended up being a she was a primary school teacher after having gone to normal school in Winnipeg. But that was it. She was the first uh, her and her brother were the first people to go on to graduate school and to get doctorates at universities. I mean. And then she rose to the top through sheer hard work.

Tegan: Sylvia Ostry challenged herself. She was intelligent and a hard worker, and she challenged herself to succeed.

In her own words;

Sylvia Ostry: at the University of Manitoba to get into medical school it was very difficult, it was a first-class medical school but it covered the whole of western Canada, there was no other medical school at that time and it was very difficult for a woman, I don't remember how many there were since the beginning not more than a handful, and it was much more difficult to be a Jew, so to be a female Jew really appealed to me that I would get in. I had two friends in high school very bright, and we sat down and said look we're going to do our pre-med and we'll going to get the highest marks in Western Canada, because we'll organize ourselves to study and we'll share notes and we'll get money and hire a special people that can teach us and we'll go one, two, three and I said, if they keep us out, we'll sue them, which sounds very strange at that time but I felt very strongly about that, but we did that.

Adam: The things that she respected the things that that she respected the most in people were talent and intelligence, integrity, so honesty, and hard work and discipline. So you know if given the opportunity to or one of her favorite expressions was to goof off, that's a very kind of 1950s expression, goof off, and she would invariably accuse me of goofing off when I wasn't doing my homework or wasn't working. But you know she when given the opportunity to goof off or to work she would invariably choose work.

(Chime)

Tegan: Number two. Follow your passions, even if they take you in an unexpected direction. Maybe especially then.

I think that quitting gets a bad rep. Have you heard of the sunk cost fallacy? Basically, it's when people tend to keep going with something if they've invested a lot of time, effort, or money into it, even if it no longer serves them or it's something they don't want anymore. You can apply this to things like relationships or jobs. I would like to actually encourage you to utilize strategic quitting. And I think Sylvia would too.

Sylvia realized during a visit to her brother, who was studying at Queen's University, that she wanted to study social sciences. The conversations she saw the students having about things like art, politics, and the economy were much more interesting to her than her studies in medicine. She wanted to join them. But to do that, she would have to quit medical school.

Sylvia Ostry: The first year was very boring, just anatomy and physiology and biochemistry and I got a 99 in biochemistry and the other two but that summer I went to see my brother who was at Queens and I spent the summer in Kingston and it was though I had gone to Mars, I had never met people who read books and talked about history and all I'd ever done was study.

I went to see the Dean of the medical school and I said, I really feel badly but I want to leave medical school because its so boring and he exploded and he screamed, you're the best example of why we will not let women in medical school, how correct we were to keep you out, you realize that you are keeping a man out and I said I know I'm sorry but I want to study something else. And he said, that's a lie, you're like all women, you're dropping out so you can go out and get married. I said, it's not true, I'm going to be a doctor, but it'll be a PhD, not a medical doctor. He said, that's a lie and I went out.

Jonathan: my name is Jonathan Ostry. I'm the younger son of Sylvia and Bernard Ostry.

She started off thinking she wanted to be a physician, a doctor, a medical doctor. And I think what had drove her in that direction is, you know, always choose the thing that is the most difficult, the most impossible and see if you can kick the ball through the goal post just for the heck of kicking the ball rather than specifically because this is your passion. And you know, she realized this this really wasn't her passion. And she had chosen this, this direction merely for the reason that I just said. And that was a a very poor reason to kind of motivate what you are gonna do for your life. Right. And so she decided she wanted to go into economics.

Tegan: For Sylvia, the most important thing wasn't necessarily what she was taking. It wasn't the topic of study. It was instead:

Sylvia Ostry: the concentration on learning and I came to McGill and I didn't want to take economics, I didn't care what I took but what happened was they said take economics we think you can do two years and…

Jonathan: I never really thought of my mother as an economist. I mean, she is an economist by training, but you know. But, you know, the is my mother, an economist, did I think of her as an economist? I really thought of her and my father as people who knew everything about everything.

(Chime)

Tegan: Number three. Refuse to accept the limitations put on you by other people.

Sylvia faced discrimination all her life. Even after earning a PhD, she was denied a job at the UN because she was a woman.

Sylvia Ostry: My initial thing was that I wanted to be a development economist and I went to the UN and I had my PhD and I went to see the person who was in charge of it all and I said I have all the qualifications and I would love to work here and he said, look, I might as well be clear to you, no government in the developing countries will hire a woman, and he said you'd better find another career, it's amazing how people could say things like that but it was honest and so when I went to McGill I had to find another, and I was very interested in labor economics so that's what I worked on.

Adam: My mother fought the good fight. She had, she had career disappointments. I mean, my mother wanted to be. My mother wanted to be Deputy Minister of Finance and then governor of the bank, you know. And she was a product of her time, and there was no way they were going to give those jobs to a woman. And she knew it. She was told that. You know, and it's uh. It's. It's. I... she made the best of... You know there's an old expression. You dance with the guy that brung you. And the fact is, is that what she made the best of the of the hand she was dealt,

Tegan: Although she was refused by the UN, she didn't let that stop her. Sylvia didn't quit when she was faced with a roadblock. She found her own way to succeed and refused to accept the limitations put on her by others. And you shouldn't either!

Jonathan: As an economist she had nine lives, right? She didn't just change from medicine to economics. She did her PhD at Cambridge on what today would be considered the most arcane obscure topic. she wrote, her thesis on the sort of this Soviet planning Soviet economic planning as it pertained to newly independent India. She didn't. She didn't work on Marx economics or development economics or Soviet planning. She went to the Oxford Institute of Statistics and Economics and she did other things. She became a labor economist. And then she became an expert on the Canadian labour market and all the challenges for the Canadian economy. She was chair of the Economic Council, Canada. She became an expert on regulatory and microeconomics when she was deputy at consumer and Corporate affairs. And then she became a formal global expert on international trade, which is a completely different topic. She so she reinvented herself. Yeah, in many in many different ways. She had the inner confidence and strength. To know that she could do it.

(Chime)

Tegan: Number four. When faced with a problem, try changing your perspective.

Prior to Sylvia's tenure as Director of Special Manpower Studies and Consultation, StatCan studied the labour supply by focusing on how many men were working and how many men wanted to work.

Sylvia Ostry: The first job they gave me at Statistics Canada was terrific, they gave me, it's a wonderful title today but it didn't bother me, called special manpower studies but it was very interesting they let me attach separate questionnaires to the household survey so I could get information on a whole range of things that nobody else had and we produced and I was able to hire academics and we produced some incredible studies, so I loved the job, it was really fascinating, and indeed some of my early publications were very important in the US, we developed new ways of looking at things, we developed ways, I wanted to develop measures on the amount of demand and not just supply.

Tegan: Sylvia wanted to look at labour supply from another angle. She wanted to look at the participation of workers in the labour market and why someone would choose not to participate in the labour market, not get a job, whether they might want to work under different conditions.

The Manpower Studies gave Sylvia the resources to study the Canadian labour force more closely, in a way that had not been done before. StatCan had been measuring the labour supply for a long time, but manpower was a bit literal and focused on men. Sylvia saw the value in expanding our research by including other groups in new measurements. Sylvia reimagined how we'd think of labour, of manpower, to expand the analysis to include not just men, but women as well. She studied the participation of women in the labour market- the question of what made a woman choose to work, or not to work, and the effect of factors like education, husband's earnings, and children on that decision. This was a big deal at a time when, in the words of economist Joan McFarland, "most of the analysis in economics… ignored the role of women in the economy altogether."

Sylvia Ostry studied the lifetime productivity of a person and the lost output from their premature death or retirement. The labour force participation and potential earnings of both the economic man and the economic woman are included, the first Canadian study of its kind.

Sylvia issued a challenge to traditional economics to change its perspective, not just looking at men but at women, and in doing so, increased our understanding of labour economics.

(Chime)

Tegan: Number five. Live by your own definition of success.

Sylvia Ostry herself was a mother and she also had a career, something other people sometimes judged her for.

Bronwyn: What did the people close to you – your friends and family and wider social network – what did they think of your choices?

Sylvia: Well, in Ottawa I was told that a large number of women were shocked and horrified that I was working they thought that was just appalling, I had children and I was working full-time. They never said this to me, but I heard this from a number of people. The only time there was anything overt was when I was appointed to the OECD, this was '79, I'm told that the wife of the Ambassador told her husband that I was not allowed to enter the Embassy because I was such a disgrace that she could not have me. I was married, I had two children, how could I come to a place like the OECD and be head of it? The chief economist and it was just disgraceful for a woman to be working

Jonathan: You know, when my mother went to the OECD as its chief economist, there were a number of firsts, and maybe and maybe more firsts than when my mother became chief statistician because she became chief statistician in Canada. Which was her country. Uhmm, and you know, you can say that because it's her country, there's a certain comfort level from rising in your country. But when she got the job at the OECD, most people in Paris were absolutely incredulous because first of all, that job had always really been the purview of the of a European citizen, a citizen of Europe. And Canadians or Americans, but you know, Canada was like a backwater and what is this Canadian woman coming to Paris for? That's one. So that was one thing. The other, there was very much, it was a quite a misogynist environment. And I can certainly well appreciate that my mother would have heard whispers and you know in the in the corridors about God, this, what is this woman doing here? That's so it's Canadian, there's woman and just this sense, that boy, she's not one of us. I mean it. It's just so many, well, probably being Jewish. So. So, you know, it's just like, you know, not part of that club and so and so you'll talk about being out of your comfort zone.

Tegan: We all get to decide for ourselves what success looks like. And if you would like to follow in Sylvia's footsteps and define success as raising two children and also becoming the Chief Economist at the OECD, yes! More power to you. You go Glen Coco.

(Chime)

Tegan: Number six. When prejudice closes a door, break that door down.

You might have heard the expression "when one door closes another opens." Maybe that's true. But. It's also true that sometimes doors are closed because of prejudice. And when those doors close, you kick them wide open. This maxim could apply metaphorically to many stories from Sylvia's life, but sometimes we actually mean it pretty literally.

Sylvia Ostry: The funniest thing was when Flo Byrd had her first meeting to discuss the Royal Commission on Women, it was held at a very fancy club in Ottawa and I was coming into have lunch with her and I was stopped at the entrance and I said, I'm sorry, I have a luncheon meeting with Senator Byrd. They said, you can't come in this door, I said what do you mean I can't come in this door? Not allowed, as a woman, you have to go in the side door. So I burst out laughing, I said, that's good cause we're having a meeting on a Royal Commission for Women and I'll make sure that this place is either closed or you open the front door.

(Chime)

Tegan: Number seven. Surround yourself with people who love and support you.

You know what they say. Haters gonna hate (hate hate hate). But take it from Sylvia. Surrounding yourself with people who love and support you makes all the difference. For Sylvia, it was her husband, Bernard.

Sylvia Ostry: My husband was just the most extraordinary man and as I said I had known him since I was five years old.

Adam: She wouldn't have survived without my father the ones that my father, my mother was. My mother was blessed with having my father as her husband, my father loved my mother, adored my mother, worshipped the ground she walked on uh for all sorts of reasons. My mother was. My mother never forgot the degree to which she was loved by him. Umm. And you know her two children were privileged to have grown up and to have been raised by two people who loved The way my parents loved each other. my family, my, my, my parents stayed married to each other for 50 years. And it was, uh, my mother, my mother, my mother expressed her love for my father in differently than the way my father expressed his love for my mother. I mean, my father's collecting of Art Nouveau and Art Deco furniture and objets d'art, which you could now see in the Royal Ontario Museum is a testament to his love for her. He did that not because he was interested in the period. He did that because she was. She had an intellectual interest in the Vimar Republican and French Art Deco. She was interested in the period she was interested in the in the political [unintelligible] and turmoil that was going on in the 20s and 30s and in Western Europe, notably France and Germany. 28:43 Umm. And so my father decided that he would begin surrounding her with the tangible illustrations of that period. That was the way he expressed his love for her. In all her major, major career um decisions in life she couldn't do anything without first consulting with him. And if you look at the career path, I don't think you'll find any examples of the husband consciously giving up career opportunities so that his wife could pursue her career. Even today, I dare say that there are the examples are few and far between.

Sylvia Ostry: I was appointed Chairman of the Economic Council and I was at the office one morning when I got a call from Paris and the assistant to the Director General, phoned and said the head of the economics department is leaving, he's retiring and we'd be very interested in interviewing you and the Director General wants to know if you'll come to Paris. And I was staggered and I said, well, I could get back to you on Friday, this was Wednesday and I came home that night and I had this insane call from Paris and I described it and I said I'll be polite and wait till Friday, and then I'll tell them and he said are you crazy? I said, what do you mean? He said, you'll never have another offer like this for the rest of your life that's a crucial job, he was right, it was very important at that time, I said what do you want me to do, I can't do it, he said yes you can, you're going to go and I'll work something out. That's what he was like. I couldn't be where I am without him.

(Chime)

Tegan: Number eight. Work hard.

Our last piece of advice comes straight from Sylvia Ostry herself.

Bronwyn: I was wondering if I could ask you if you have any advice for young women?

Sylvia: Yeah. I think my advice is what I did myself: You must be determined to be the best in what you do and you have to be disciplined and you have to work hard. I know it sounds platitudinous but that's what I did. I never thought about power, getting jobs or anything, I just wanted to do better than anyone else. And I was like that from when the time I was in grade 1.

Adam: Sylvia Ostry was a complicated and complex human being. She was highly intelligent. She was driven by her need to work. She expressed her identity through her work. And she devoted her life to. To work . She was full of integrity. She. She was brutally honest, first with herself and then demanded no less from others, starting from starting with her children. And so as a mother, she taught me, she tried anyway to teach me very early the discipline of work and of being honest with yourself in terms of what you can and cannot do. She believed very strongly in in trying to be the best that you could be and trying to. She always had a an expression that she would use with me whenever I would collapse and say that I couldn't do it she would get very upset and angry and say that you're not working hard enough. And if I had a goal that that I would then say I would never be able to she always said your reach should exceed your grasp. And then she lived by that credo for her entire life.

Jonathan: Sylvia dedicated her life to improving the welfare of Canadians. She was, you know, a not only a great intellectual, very broad in terms of, you know, her areas of expertise but also not interested in knowledge for knowledge's sake. She was interested in how to leverage knowledge to uh to guide policy with the ultimate purpose of the well being of Canadians or in a in a larger canvas. The world. And this is what she devoted her life to.

Adam: She committed, she devoted her entire life, her entire working life, to public service. There is no nobler calling and she as an is an exemplar of that. And I think that, you know, Canada recognized that. She died a companion of the order. But you know, she um if people remember her, I hope people remember her for her contribution to making Canada a better place in which to live.

(Outro)

Tegan: You've been listening to Eh Sayers. Thank you to Sylvia Ostry's sons, Adam Ostry and Jonathan Ostry, for their special contribution to this episode. Thank you to Joan McFarland for help with some of the economic concepts. To the librarians at Library and Archives, who helped us with the research. And to University of Ottawa Library Archives and Special Collections, who gave us permission to include excerpts from Bronwyn Bragg and Mary Been's 2008 interview with Sylvia Ostry.

You can subscribe to this show wherever you get your podcasts. There you can also find the French version of our show, called Hé-coutez bien. If you liked this show, please rate, review, and subscribe. Thanks for listening!

Sources

"Canadian Women's History." 2013. PSAC NCR. Public Service Alliance of Canada. January 9, 2013.

McFarland, Joan. 1976. "Economics and Women: A Critique of the Scope of Traditional Analysis and Research." Atlantis: Critical Studies in Gender, Culture and Social Justice 1 (2): 26–41.

Ostry, Sylvia. 2008. Sylvia Ostry Interview by Bronwyn Bragg and Mary Been. University of Ottawa Library Archives and Special Collections.

"The Surge of Women in the Workforce." 2018. Statistics Canada. May 17, 2018.

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Eh Sayers Episode 9 - Sylvia Ostry: Lessons From A Legend (MP3, 21.97 MB)

Financial statements, March 31, 2022

Statement of Management Responsibility Including Internal Control over Financial Reporting

Responsibility for the integrity and objectivity of the accompanying financial statements for the year ended March 31, 2022, and all information contained in these statements rests with the management of Statistics Canada (the agency). These financial statements have been prepared by management using the Government of Canada's accounting policies, which are based on Canadian public sector accounting standards.

Management is responsible for the integrity and objectivity of the information in these financial statements. Some of the information in the financial statements is based on management's best estimates and judgment, and gives due consideration to materiality. To fulfill its accounting and reporting responsibilities, management maintains a set of accounts that provides a centralized record of the agency's financial transactions. Financial information submitted in the preparation of the Public Accounts of Canada, and included in the agency's Departmental Results Report, is consistent with these financial statements.

Management is also responsible for maintaining an effective system of internal control over financial reporting (ICFR) designed to provide reasonable assurance that financial information is reliable, that assets are safeguarded, and that transactions are properly authorized and recorded in accordance with the Financial Administration Act and other applicable legislation, regulations, authorities and policies.

Management seeks to ensure the objectivity and integrity of data in its financial statements through careful selection, training and development of qualified staff; through organizational arrangements that provide appropriate divisions of responsibility; through communication programs aimed at ensuring that regulations, policies, standards, and managerial authorities are understood throughout the agency and through conducting an annual risk-based assessment of the effectiveness of the system of ICFR.

The system of ICFR is designed to mitigate risks to a reasonable level based on an ongoing process to identify key risks, to assess the effectiveness of associated key controls, and to make any necessary adjustments.

A risk-based assessment of the system of ICFR for the year ended March 31, 2022 was completed in accordance with the Treasury Board Policy on Financial Management and the results and action plans are summarized in the annex, which can be found at the end of the notes to these financial statements.

The effectiveness and adequacy of the agency's system of internal control is reviewed by the work of internal finance staff, who conduct periodic assessments of different areas of the agency's operations, and by the Departmental Audit Committee (DAC), who provide advice to the Chief Statistician on the adequacy and effectiveness of the agency's risk management, control and governance frameworks and processes.

The financial statements of Statistics Canada have not been audited.

Anil Arora
Chief Statistician

Ottawa, Canada
September 9, 2022

Ziad Shadid
Acting Chief Financial Officer

Ottawa, Canada
September 9, 2022

Statement of Financial Position (Unaudited)
As at March 31
(in thousands of dollars)
  2022 2021
Liabilities
Accounts payable and accrued liabilities (note 4)
 77,932 89,631
Vacation pay and compensatory leave
 47,857 53,069
Deferred revenue (note 5)
 67 149
Employee future benefits (note 6)
 16,669 18,070
Total net liabilities 142,525 160,919
Financial assets
Due from Consolidated Revenue Fund
 60,417 71,876
Accounts receivable and advances (note 7)
 9,063 6,571
Total gross financial assets 69,480 78,447
Financial assets held on behalf of Government
Accounts receivable and advances (note 7)
 -2,401 -1,305
Total Financial assets held on behalf of Government -2,401 -1,305
Total net financial assets 67,079 77,142
Departmental net debt 75,446 83,777
Non-financial assets
Prepaid expenses
 5,686 7,934
Consumable supplies
 1,723 1,931
Tangible capital assets (note 8)
 163,499 160,365
Total non-financial assets 170,908 170,230
Departmental net financial position 95,462 86,453

Contractual obligations and contractual rights (note 9)
Contingent liabilities and contingent assets (note 10)

The accompanying notes form an integral part of these financial statements.

Anil Arora
Chief Statistician

Ottawa, Canada
September 9, 2022

Ziad Shadid
Acting Chief Financial Officer

Ottawa, Canada
September 9, 2022

Statement of Operations and Departmental Net Financial Position (Unaudited)
For the Year Ended March 31
(in thousands of dollars)
  2022 Planned Results 2022 2021
Expenses
Statistical Information
 977,075 1,003,974 763,439
Internal services
 71,099 94,882 88,974
Total expenses 1,048,174 1,098,856 852,413
Revenues
Special statistical services
 138,000 150,045 140,726
Other revenues
 100 28 28
Revenues earned on behalf of Government
 -18,100 -22,083 -20,507
Total revenues 120,000 127,990 120,247
Net cost of operations before government funding and transfers 928,174 970,866 732,166
Government funding and transfers
Net cash provided by Government of Canada
   891,098 603,079
Change in due from Consolidated Revenue Fund
   -11,459 16,003
Services provided without charge by other federal government departments (note 11a)
   100,165 92,622
Transfer of the transition payments for implementing salary payments in arrears
   0 -2
Transfer of assets to other federal government departments
   71 151
Net cost (revenue) of operations after government funding and transfers   -9,009 20,313
Departmental net financial position - Beginning of year   86,453 106,766
Departmental net financial position - End of year   95,462 86,453

Segmented information (note 12)

The accompanying notes form an integral part of these financial statements.
Statement of Change in Departmental Net Debt (Unaudited)
For the Year Ended March 31
(in thousands of dollars)
  2022 2021
Net cost (revenue) of operations after government funding and transfers -9,009 20,313
Change due to tangible capital assets
Acquisition of tangible capital assets (note 8)
 29,540 29,018
Amortization of tangible capital assets (note 8)
 -26,209 -31,457
Net loss on disposal of tangible capital assets including adjustments
 -197 -433
Transfer of tangible capital assets to other federal government departments
 0 0
Total change due to tangible capital assets 3,134 -2,872
Change due to consumable supplies -208 370
Change due to prepaid expenses -2,248 2,083
Net increase (decrease) in departmental net debt -8,331 19,894
Departmental net debt - Beginning of year 83,777 63,883
Departmental net debt - End of year 75,446 83,777
The accompanying notes form an integral part of these financial statements.
Statement of Cash Flows (Unaudited)
For the Year Ended March 31
(in thousands of dollars)
  2022 2021
Operating activities
Net cost of operations before government funding and transfers 970,866 732,166
Non-cash items:
Amortization of tangible capital assets (note 8)
 -26,209 -31,457
Loss on disposal of tangible capital assets
 -197 -433
Services provided without charge by other federal government departments (note 11a)
 -100,165 -92,622
Transfer of emergency salary advances to other federal government departments
 -71 -152
Transition payments for implementing salary payments in arrears
 0 2
Variations in Statement of Financial Position:
Increase (decrease) in accounts receivable and advances
 1,397 -5,816
Increase (decrease) in prepaid expenses
 -2,248 2,083
Increase (decrease) in consumable supplies
 -208 370
Decrease (increase) in accounts payable and accrued liabilities
 11,699 -14,600
Decrease (increase) in vacation pay and compensatory leave
 5,212 -18,395
Decrease in deferred revenue
 82 465
Decrease in employee future benefits
 1,401 2,450
Cash used in operating activities 861,559 574,061
Capital investing activities
Acquisitions of tangible capital assets, excluding capital leases (note 8)
 29,540 29,018
Cash used in capital investing activities 29,540 29,018
Financing activities
Payments of lease obligation for tangible capital assets
 0 0
Cash used in financing activities 0 0
Net cash provided by Government of Canada 891,099 603,079

The accompanying notes form an integral part of these financial statements.

Notes to the Financial Statements (Unaudited)
For the Year Ended March 31

1. Authority and objectives

Statistics Canada (the agency) was established in 1918, pursuant to the Statistics Act. The agency received full departmental status by order-in-council in 1965.

The agency is a division of the public service named in Schedule I.1 of the Financial Administration Act. The minister responsible for Statistics Canada is the Minister of Innovation, Science and Economic Development, who represents the agency in Parliament and in Cabinet.

The agency's mandate derives primarily from the Statistics Act. The act requires the agency — under the direction of the minister — to collect, compile, analyze, and publish statistical information on the economic, social, and general conditions of the country and its citizens. Statistics Canada has a mandate to coordinate and manage the country's statistical system.

The agency's mandate has two primary objectives:

  • Provide statistical information and analysis of the economic and social structure and functioning of Canadian society as a basis for the development, operation and evaluation of public policies and programs. This information is used for public and private decision-making, and for the general benefit of all Canadians.
  • Promote the quality, coherence, and international comparability of Canada's statistics through collaboration with other federal departments and agencies, with the provinces and territories, and in accordance with sound scientific standards and practices.

The agency reports on the two core responsibilities described below.

Statistical information - The agency has a responsibility to produce objective high-quality statistical information for the whole of Canada. The statistical information produced relates to the commercial, industrial, financial, social, economic, environmental and general activities and conditions of the people of Canada.

Internal services - Internal services are groups of related activities and resources that are administered to support the needs of programs and other corporate obligations of an organization.

2. Summary of significant accounting policies

These financial statements have been prepared using the agency's accounting policies stated below, which are based on Canadian public sector accounting standards. The presentation and results using the stated accounting policies do not result in any significant differences from Canadian public sector accounting standards.

The significant accounting policies are as follows:

(a) Parliamentary authorities

The agency is financed by the Government of Canada through Parliamentary authorities. Financial reporting of authorities provided to the agency do not parallel financial reporting according to generally accepted accounting principles since authorities are primarily based on cash flow requirements. Consequently, items recognized in the Statement of Financial Position and in the Statement of Operations and Departmental Net Financial Position are not necessarily the same as those provided through authorities from Parliament. Note 3 provides a reconciliation between the bases of reporting. The planned results amounts in the "Expenses" and "Revenues" sections of the Statement of Operations and Departmental Net Financial Position are the amounts reported in the Future-oriented Statement of Operations included in the 2021-22 Departmental Plan. Planned results are not presented in the "Government funding and transfers" section of the Statement of Operations and Departmental Net Financial Position and in the Statement of Change in Departmental Net Debt because these amounts were not included in the 2021-22 Departmental Plan.

(b) Net cash provided by Government

The agency operates within the Consolidated Revenue Fund (CRF), which is administered by the Receiver General for Canada. All cash received by the agency is deposited into the CRF, and all cash disbursements made by the agency are paid from the CRF. The net cash provided by the Government is the difference between all cash receipts and all cash disbursements, including transactions between federal government departments.

(c) Amounts due from or to the CRF

Amounts due from or to the CRF are the result of timing differences at year-end between the time when a transaction affects authorities and when it is processed through the CRF. Amounts due from the CRF represent the net amount of cash that the agency is entitled to draw from the CRF without further authorities to discharge its liabilities.

(d) Revenues

  • Revenues received for special statistical services are recorded as deferred revenue upon receipt. These amounts are recognized as revenue in the period in which the services are rendered and related expenses are incurred.
  • Other revenues are recognized in the period the event giving rise to the revenues occurred.
  • Revenues that are non-respendable are not available to discharge the agency's liabilities. While the Chief Statistician; is expected to maintain accounting control, he has no authority regarding the disposition of non-respendable revenues. As a result, non-respendable revenues are considered to be earned on behalf of the Government of Canada and are therefore presented as a reduction of the entity's gross revenues.

(e) Expenses

  • Transfer payments are recorded as an expense in the year the transfer is authorized and all eligibility criteria have been met by the recipient.
  • Vacation pay and compensatory leave are accrued as the benefits are earned by employees under their respective terms of employment.
  • Services provided without charge by other federal government departments for accommodation, employer contributions to the health and dental insurance plans, and workers' compensation are recorded as operating expenses at their carrying value.

(f) Employee future benefits

  1. Pension benefits — Eligible employees participate in the Public Service Pension Plan, a multi-employer pension plan administered by the Government. The agency's contributions to the Plan are charged to expenses in the year incurred and represent the total departmental obligation to the Plan. The agency's responsibility with regard to the Plan is limited to its contributions. Actuarial surpluses or deficiencies are recognized in the financial statements of the Government of Canada, as the Plan's sponsor.
  2. Severance benefits — The accumulation of severance benefits for voluntary departures ceased for applicable employee groups. The remaining obligation for employees who did not withdraw benefits is calculated using information derived from the results of the actuarially determined liability for employee severance benefits for the Government as a whole.

(g) Accounts receivable

Accounts receivable are initially recorded at cost. When necessary, an allowance for valuation is recorded to reduce the carrying value of accounts receivable to amounts that approximate their net recoverable value.

(h) Non-financial assets

  • All tangible capital assets and leasehold improvements having an initial cost of $10,000 or more are recorded at their acquisition cost. Tangible capital assets do not include immovable assets located on reserves as defined in the Indian Act, works of art, museum collection and Crown land to which no acquisition cost is attributable; and intangible assets.
  • Consumable supplies include items held for future program delivery and are not intended for resale. These supplies are recorded at the acquisition cost. If there is no longer a service potential, the supplies are valued at the lower of cost or net realizable value.

(i) Contingent liabilities

Contingent liabilities are potential liabilities which may become actual liabilities when one or more future events occur or fail to occur. If the future event is likely to occur or fail to occur, and a reasonable estimate of the loss can be made, a provision is accrued and an expense recorded to other expenses. If the likelihood is not determinable or an amount cannot be reasonably estimated, the contingency is disclosed in the notes to the financial statements.

(j) Contingent assets

Contingent assets are possible assets which may become actual assets when one or more future events occur or fail to occur. If the future even is likely to occur or fail to occur, the contingent asset is disclosed in the notes to the financial statements.

(k) Transactions involving foreign currencies

Transactions involving foreign currencies are translated into Canadian dollar equivalents using rates of exchange in effect at the time of those transactions. Gains and losses resulting from foreign currency transactions are reported on the Statement of Operations and Departmental Net Financial Position according to the activities to which they relate.

(l) Measurement uncertainty

The preparation of these financial statements requires management to make estimates and assumptions that affect the reported and disclosed amounts of assets, liabilities, revenues and expenses reported in the financial statements and accompanying notes at March 31. The estimates are based on facts and circumstances, historical experience, general economic conditions and reflect the Government's best estimate of the related amount at the end of the reporting period. The most significant items where estimates are used are the liability for employee future benefits and the useful life of tangible capital assets. Actual results could significantly differ from those estimated. Management's estimates are reviewed periodically and, as adjustments become necessary, they are recorded in the financial statements in the year they become known.

(m) Related party transactions

Related party transactions, other than inter-entity transactions, are recorded at the exchange amount. Inter-entity transactions are transactions between commonly controlled entities. Inter-entity transactions, other than restructuring transactions, are recorded on a gross basis and are measured at the carrying amount, except for the following:

  1. Services provided on a recovery basis are recognized as revenues and expenses on a gross basis and measured at the exchange amount.
  2. Certain services received on a without charge basis are recorded for departmental financial statement purposes at the carrying amount.

3. Parliamentary authorities

The agency receives most of its funding through annual parliamentary authorities. Items recognized in the Statement of Operations and Departmental Net Financial Position and the Statement of Financial Position in one year may be funded through parliamentary authorities in prior, current, or future years. Accordingly, the agency has different net results of operations for the year on a government funding basis than on an accrual accounting basis. The differences are reconciled in the following tables:

(a) Reconciliation of net cost of operations to current year authorities used

Reconciliation of net cost of operations to current year authorities used
  2022 2021
(in thousands of dollars)
Net cost of operations before government funding and transfers 970,866 732,166
Adjustments for items affecting net cost of operations but not affecting authorities:
Amortization of tangible capital assets
 -26,209 -31,457
Loss on disposal of tangible capital assets
 -197 -433
Services provided without charge by other federal government departments
 -100,165 -92,622
Decrease (increase) in vacation pay and compensatory leave
 5,212 -18,394
Decrease in employee future benefits
 1,401 2,450
Refund of prior years' expenditures
 2,716 1,091
Increase in respendable revenues
 398 0
Consumption of prepaid expenses
 -12,285 -12,020
Consumption of supplies
 -208 0
Bad debt expense
 -1 -13
Increase in accrued salary receivable
 864 195
Total items affecting net cost of operations but not affecting authorities
 -128,474 -151,203
Adjustments for items not affecting net cost of operations but affecting authorities:
Acquisition of tangible capital assets, excluding capital leases
 29,540 29,018
Decrease in respendable accounts receivable
 0 -3,754
Acquisition of prepaid expenses
 10,037 14,103
Acquisition of consumable supplies
 0 370
Increase in salary receivable
 1,378 513
Increase in salary advances
 17 7
Transition payments for implementing salary payments in arrears
 0 2
Payments for pay equity settlement
 19 97
Total items not affecting net cost of operations but affecting authorities
 40,991 40,356
Current year authorities used 883,383 621,319

(b) Authorities provided and used

Authorities provided and used
  2022 2021
(in thousands of dollars)
Authorities provided:
Vote 1 - Operating expenditures
 854,035 588,445
Statutory amounts
 90,714 83,531
Total authorities provided 944,749 671,976
Less:
Lapsed: Operating expenditures
 -61,366 -50,657
Current year authorities used 883,383 621,319

4. Accounts payable and accrued liabilities

The following table presents details of the agency's accounts payable and accrued liabilities:

Accounts payable and accrued liabilities
  2022 2021
(in thousands of dollars)
Accounts payable - Other federal government departments and agencies 13,306 11,666
Accounts payable - External parties 30,238 41,672
Accrued salaries and wages 34,388 36,293
Total accounts payables and accrued liabilities 77,932 89,631

5. Deferred revenue

The agency has the authority to expend revenue received during the fiscal year. Deferred revenue represents the balance at year-end of unearned revenues stemming from amounts received from external parties, which are restricted for specific statistical services. Revenue is recognized in the period in which these expenditures are incurred or in which the service is performed. Details of the transactions related to this account are as follows:

Deferred revenue
  2022 2021
(in thousands of dollars)
Opening balance 149 614
Amount received 149,963 140,261
Revenues recognized -150,045 -140,726
Net closing balance 67 149

6. Employee future benefits

(a) Pension benefits

The agency's employees participate in the Public Service Pension Plan ("the Plan"), which is sponsored and administered by the Government of Canada. Pension benefits accrue up to a maximum period of 35 years at a rate of 2 percent per year of pensionable service, times the average of the best five consecutive years of earnings. The benefits are integrated with Canada/Québec Pension Plan benefits and they are indexed to inflation.

Both the employees and the agency contribute to the cost of the Plan. Due to the amendment of the Public Service Superannuation Act following the implementation of provisions related to Economic Action Plan 2012, employee contributors have been divided into two groups – Group 1 relates to existing plan members as of December 31, 2012, and Group 2 relates to members who joined the Plan as of January 1, 2013. Each group has a distinct contribution rate.

The 2021-2022 expense amounts to $61,274 thousand ($56,996 thousand in 2020-2021). For Group 1 members, the expense represents approximately 1.01 times (1.01 times in 2020-2021) the employee contributions and, for Group 2 members, approximately 1.00 times (1.00 times in 2020-2021) the employee contributions.

The agency's responsibility with regard to the Plan is limited to its contributions. Actuarial surpluses or deficiencies are recognized in the Consolidated Financial Statements of the Government of Canada, as the Plan's sponsor.

(b) Severance benefits

Severance benefits provided to the agency's employees were previously based on an employee's eligibility, years of service and salary at termination of employment. However, since 2011 the accumulation of severance benefits for voluntary departures progressively ceased for substantially all employees. Employees subject to these changes were given the option to be paid the full or partial value of benefits earned to date or collect the full or remaining value of benefits upon departure from the public service. By March 31, 2022, substantially all settlements for immediate cash out were completed. Severance benefits are unfunded and, consequently, the outstanding obligation will be paid from future authorities.

The changes in the obligations during the year were as follows:

Severance benefits
  2022 2021
(in thousands of dollars)
Accrued benefit obligation - Beginning of year 18,070 20,520
Expense or adjustment for the year 172 -380
Benefits paid during the year -1,573 -2,070
Accrued benefit obligation - End of year 16,669 18,070

7. Accounts receivable and advances

The following table presents details of the agency's accounts receivable and advances balances:

Accounts receivable and advances
  2022 2021
(in thousands of dollars)
Receivables - Other federal government departments and agencies 2,554 2,896
Receivables - External parties 6,194 3,501
Employees advances 317 174
Subtotal 9,065 6,571
Allowance for doubtful accounts on receivables from external parties -2 -1
Gross accounts receivable and advances 9,063 6,570
Accounts receivable held on behalf of Government -2,401 -1,305
Net accounts receivable and advances 6,662 5,265

8. Tangible capital assets

Amortization of tangible capital assets is done on a straight-line basis over the estimated useful life of the asset as follows:

Amortization of tangible capital assets
Asset class Amortization period
Computer hardware 5 years
Computer software 5 years
Other equipment 5 years
Motor vehicles 7 years
Leasehold improvements 25 years
Assets under construction Once available for use
Software under development Once available for use

Assets under construction and software assets under development are recorded in the applicable asset class in the year that they become available for use and are not amortized until they are available for use.

Tangible capital assets
Capital Asset Class Cost Accumulated Amortization Net Book Value
Opening Balance Acquisitions Disposals and Write-Offs AdjustmentsFootnote 1 Closing Balance Opening Balance Amortization Disposals and Write-Offs AdjustmentsFootnote 1 Closing Balance 2022 2021
(in thousands of dollars)
Computer hardware 2,629 80 -518 0 2,191 2,181 128 -487 0 1,822 369 448
Computer software 345,377 1,865 -191 31,245 378,296 268,466 24,573 -85 0 292,953 85,342 76,911
Other equipment 4,166 68 -878 0 3,356 3,129 445 -839 0 2,736 621 1,037
Motor vehicles 2,849 0 -21 0 2,828 2,654 62 -21 0 2,695 133 195
Leasehold improvements 24,987 176 0 78 25,241 10,361 1,001 0 0 11,362 13,879 14,626
Assets under construction 207 404 0 -99 512 0 0 0 0 0 512 207
Software under development 66,941 26,947 0 -31,245 62,643 0 0 0 0 0 62,643 66,941
Total 447,156 29,540 -1,608 -21 475,067 286,791 26,209 -1,432 0 311,568 163,499 160,365
Footnote 1

Included in adjustments are the following: software assets under development of $31,245 thousand that were transferred to computer software upon completion of the assets; assets under construction of $78 thousand that were transferred to leasehold improvements upon completion of construction and $21 thousand that was expensed due to projects being cancelled.

Return to the first footnote 1 referrer

9. Contractual obligations and contractual rights

(a) Contractual obligations

The nature of the agency's activities may result in some large multi-year contracts and obligations whereby the agency will be obligated to make future payments when the services/goods are received. Significant contractual obligations that can be reasonably estimated are summarized as follows:

Contractual obligations
  2023 2024 2025 2026 2027 and subsequent Total
(in thousands of dollars)
Acquisition of goods and services 4,300 3,651 3,656 0 0 11,607
Total 4,300 3,651 3,656  0  0 11,607

(b) Contractual rights

The activities of the agency sometimes involve the negotiation of contracts or agreements with outside parties that result in the agency having rights to both assets and revenues in the future. They involve sales of goods and services. The agency does not have significant contractual rights to disclose as at March 31, 2022.

10. Contingent liabilities and contingent assets

(a) Contingent liabilities

Contingent liabilities arise in the normal course of operations and their ultimate disposition is unknown.

Claims and litigations

The agency records an allowance for claims and litigations where it is likely that there will be a future payment and a reasonable estimate of the loss can be made. In 2021-2022, the agency did not have any contingent liabilities.

(b) Contingent assets

The agency discloses contingent assets that are likely to be realized. In 2021-2022, the agency did not have any contingent assets.

11. Related party transactions

The agency is related as a result of common ownership to all government departments, agencies, and Crown corporations. Related parties also include individuals who are members of key management personnel or close family members of those individuals, and entities controlled by, or under shared control of, a member of key management personnel or a close family member of that individual.

The agency enters into transactions with these entities in the normal course of business and on normal trade terms.

(a) Common services provided without charge by other federal government departments

During the year, the agency received services without charge from certain common service organizations related to accommodation, the employer's contribution to the health and dental insurance plans and workers' compensation coverage. These services provided without charge have been recorded at the carrying value in the agency's Statement of Operations and Departmental Net Financial Position as follows:

Common services provided without charge by other federal government departments
  2022 2021
(in thousands of dollars)
Accommodation 42,077 43,549
Employer's contribution to the health and dental insurance plans 58,037 49,017
Worker's compensation 51 56
Total 100,165 92,622

The Government has centralized some of its administrative activities for efficiency, cost-effectiveness purposes and economic delivery of programs to the public. As a result, the Government uses central agencies and common service organizations so that one department performs services for all other departments and agencies without charge. The costs of these services, such as the payroll and cheque issuance services provided by Public Services and Procurement Canada and audit services provided by the Office of the Auditor General are not included in the agency's Statement of Operations and Departmental Net Financial Position.

(b) Other transactions with other federal government departments and agencies

Other transactions with other federal government departments and agencies
  2022 2021
(in thousands of dollars)
Accounts receivable 2,554 2,896
Accounts payable 13,306 11,666
Expenses 23,515 19,041
Revenues 111,601 105,272

Expenses and revenues disclosed in (b) exclude common services provided without charge, which are already disclosed in (a).

12. Segmented information

Presentation by segment is based on the agency's core responsibilities. The presentation by segment is based on the same accounting policies as described in the Summary of significant accounting policies in note 2. The following table presents the expenses incurred and revenues generated for the main core responsibilities, by major object of expense and by major type of revenue. The segment results for the period are as follows:

Segmented information
  Statistical Information Internal services 2022 Total 2021 Total
(in thousands of dollars)
Transfer payments
Grant to the Organization for Economic Co-operation and Development
 0 0 0 0
Total transfer payments 0 0 0 0
Operating expenses
Salaries and employee benefits
 674,915 71,859 746,774 685,891
Accommodation
 39,084 2,993 42,077 43,549
Professional and special services
 159,197 7,636 166,833 38,045
Transportation and postage
 60,305 1,235 61,540 10,591
Amortization
 25,543 666 26,209 31,457
Repairs and maintenance
 750 536 1,286 812
Materials and supplies
 5,001 4,478 9,479 10,819
Rentals
 21,514 5,349 26,863 23,140
Communication and printing
 17,450 120 17,570 7,705
Loss on disposal of tangible capital assets
 176 0  176 240
Bad debts
 1 0  1 13
Other
 38 10 48 151
Total operating expenses 1,003,974 94,882 1,098,856 852,413
Total expenses 1,003,974 94,882 1,098,856 852,413
Revenues
Special statistical services
 150,045 0 150,045 140,726
Other revenues
 28 0 28 28
Revenues earned on behalf of Government
 -22,083 0 -22,083 -20,507
Total revenues 127,990 0 127,990 120,247
Net cost from continuing operations 875,984 94,882 970,866 732,166

Annex to the Statement of Management Responsibility Including Internal Control over Financial Reporting of Statistics Canada for Fiscal Year 2021-2022 (Unaudited)

1. Introduction

This document is attached to Statistics Canada's (StatCan) Statement of Management Responsibility Including Internal Control over Financial Reporting for the 2021-2022 fiscal year. This annex provides summary information on the measures taken by StatCan to maintain an effective system of internal control over financial reporting (ICFR), including information on internal control management, assessment results and related action plans.

Detailed information on the agency's authority, mandate and core responsibilities can be found in the 2022-2023 Departmental Plan and the 2021-22 Departmental Results Report.

2. Departmental system of internal control over financial reporting

2.1 Internal control management

StatCan has a well-established governance and accountability structure to support departmental assessment efforts and oversight of its system of internal control. A departmental internal control management framework, approved by the Chief Statistician and the Chief Financial Officer (CFO), is in place and includes:

  • organizational accountability structures as they relate to internal control management to support sound financial management, including roles and responsibilities of senior managers for control management in their areas of responsibility;
  • values and ethics considerations;
  • ongoing communication and training on statutory requirements, and policies and procedures for sound financial management and control; and
  • regular updates to, and monitoring at least on a semi-annual basis, of internal control management as well as the provision of related assessment results and action plans to the Chief Statistician, senior departmental management and the Departmental Audit Committee (DAC).

The DAC provides advice to the Chief Statistician on the adequacy and effectiveness of the agency's risk management, control and governance frameworks and processes.

2.2 Service arrangements relevant to financial statements

StatCan relies on other organizations for the processing certain transactions that are recorded in its financial statements, as follows:

2.2.1 Common service arrangements
  • Public Services and Procurement Canada (PSPC) centrally administers the payment of salaries, the procurement of certain goods and services, and provides accommodation services;
  • Shared Services Canada (SSC) provides information technology (IT) infrastructure services;
  • The Department of Justice Canada provides legal services; and
  • The Treasury Board of Canada Secretariat (TBS) provides information on public service insurance and centrally administers payment of the employer's share of contribution toward statutory employee benefit plans.
2.2.2 Specific arrangements
  • PSPC provides StatCan with the Common Departmental Financial System platform to capture and report financial and materiel management transactions.

Readers of this annex may refer to the annexes of the above-noted departments for a greater understanding of the systems of internal control over financial reporting (ICFR) related to these specific services.

3. StatCan assessment results during fiscal year 2021-2022

StatCan adopted an ongoing, rotational, risk-based monitoring approach to support testing of internal control over financial reporting. In 2021, StatCan updated its Internal Control over Financial Management Risk-based Monitoring Strategy, which replaced its previous version from 2017. According to the new strategy, the ongoing monitoring cycle was extended to a four-year period and the plan is adjusted through an annual risk assessment process.

The following table summarizes the status of the ongoing monitoring activities according to the previous fiscal year's rotational plan.

Progress during the 2021-2022 fiscal year
Previous fiscal year's rotational ongoing monitoring plan for current fiscal year Status
Financial Close and Reporting Completed as planned; remedial actions started.
Entity Level Controls: (Fraud Controls) Draft framework completed as planned; no remedial actions required.
Operating Expenditures Completed as planned; no remedial actions required.
IT General Controls On track with minor delays: operating effectiveness delayed to Q1. 2022-23.

In addition to the ongoing monitoring plan for ICFR, in 2021-2022 StatCan conducted operating effectiveness testing on Costing, Forecasting, Budgeting and CFO Attestation as part of the broader Internal Control over Financial Management (ICFM) business processes.

New or significantly amended key controls are summarized in section 3.1. The areas of the departmental system of internal controls that were reviewed this fiscal year are summarized in section 3.2.

3.1 New or significantly amended key controls

Following the risk assessment and considering the impact of the pandemic, a new sub-process was created under Capital Assets, to assess the stewardship of IT assets in employees' homes. This sub-process will be assessed in 2022-23.

3.2 Ongoing monitoring program

As part of its rotational ongoing monitoring plan, the agency completed its reassessment of Entity Level Controls (ELCs) and controls within specific business processes. Senior management received reports on the results of testing and developed action plans where necessary. For the most part, the key controls that were tested performed as intended. An example of ELCs is the fraud detection controls mentioned in s.3 above.

4. Action plan for the next fiscal year (2022-2023) and subsequent fiscal years

The table below shows the agency's rotational ongoing monitoring plan over the next three years. An annual risk assessment is conducted to validate the high-risk controls and to adjust the on-going monitoring plan as required. Action plans from previous years will be followed-up on to ensure that remedial actions have been taken.

Ongoing monitoring plan for financial reporting
Internal Control over Financial Reporting Fiscal Year 2022–2023 Fiscal Year 2023–2024 Fiscal Year 2024–2025
Entity level controls Yes No Yes
IT general controls under agency management Yes Yes No
Capital assets Yes No No
Financial close and reporting Yes Yes No
Interviewers' payroll No Yes Yes
Operating expenditures No No Yes
Revenues No Yes No
Payroll and benefits Yes No Yes
Ongoing monitoring plan for financial management
Internal Control over Financial Management Stage of monitoring
Fiscal Year 2022–2023 Fiscal Year 2023–2024 Fiscal Year 2024–2025
Budgeting Ongoing Monitoring Ongoing Monitoring Ongoing Monitoring
Costing Ongoing Monitoring Ongoing Monitoring Ongoing Monitoring
Forecasting Ongoing Monitoring Ongoing Monitoring Ongoing Monitoring
Payroll Ongoing Monitoring Ongoing Monitoring Ongoing Monitoring
CFO Attestation of Cabinet and TB Submissions Ongoing Monitoring Ongoing Monitoring Ongoing Monitoring
Investment Planning Design & Operating Effectiveness Ongoing Monitoring Ongoing Monitoring
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