Basically, when governments around the world want to evaluate how prepared their citizens are for retirement, they have two criteria. One is poverty. The second is that they want to see how well Canadian, American, or Australian workers will sustain their living standards in retirement.
Unfortunately, the target they use right now is to say, can they replace 70% of their employment earnings? For a long time we've realized that this is a completely inadequate benchmark. It actually makes no sense. When I did an extremely large research review of all the studies that have ever been done, I found that there was no scientific demonstration anywhere in the world that showed that people who replaced 70% of their income actually do sustain their living standards in retirement.
I present a new, alternative measure that basically says people want to sustain their living standards, which means they actually want to have enough money to buy the same level of goods and services after retirement as they do before retirement. That's what our living standards are really made up of: how much money we have to spend.
In terms of data, going back to the CPP question, that's critical because that's what the CPP is there for, to help people sustain their living standards. Currently, I'm testing the CPP enhancements using the model that the government developed—because it's outside their mandate to use this model—to understand who in Canada is actually benefiting from the CPP enhancements and by how much. Is it high-income Canadians or low-income Canadians?
My concern is that I hear of meetings such as this in industry, in the academic world, and everywhere. People have a lot of questions, and there are no answers. If you go to the United States, the government supports universities or different groups to actually develop very sophisticated models. They can then draw on this expertise and have the authoritative models to answer these questions. We don't have this in Canada. It's literally pennies for the government to continue to support the models where we can take all the data that we have available, put it together, and actually understand where the CPP enhancement went right and where it went wrong. Should it or should it not have been doubled?
I've now talked to leading Canadian thinkers across Canada. What's interesting in the results that happened in the CPP enhancement is that they actually weren't that punitive for low-income Canadians. This is very contrary to what's in the media. The problem is that people who speak in the media are researchers looking at it from a very narrow dataset. Once you look at data of all Canadians, across time, across their working careers, you get very different results. I really believe that before we put forward policy changes we have to understand how it's going to unfold into the future. It cannot just be an ideological debate and having people come together and put together whatever is popular at the time. We need to have informed evidence coming from authoritative sources.
It's funny, but I've spoken 20 times to industry and academia over the last three months. I'm constantly travelling and talking. To be honest, I just talk about my work and I'm never selling an idea. However, I am selling an idea today. I implore you, if there's one thing I can get across today, basically it's that the government needs to put some money back into the analytical tools.
It doesn't have to be housed in government. We can house it outside of government, in the university. It's going to be lot cheaper and will make it more accessible to all the academics across Canada, and for all the special interest groups to actually test their ideas and get real answers. Then, when government has questions, they can draw on this expertise and we can argue based on some baseline numbers. Right now, we don't even know what these numbers are, and neither does the government, I'm afraid, because, again, they cut the model.