Angus Deaton, the Princeton University economist, wrote in the opening paragraph of his acceptance speech for the 2015 Nobel Prize in economics that:
Measurement, even without understanding of mechanisms, can be of great importance in and of itself—policy change is frequently based on it—and is necessary if not sufficient for any reasoned assessment of policies, including the many that are advocated for the reduction of national or global poverty. We are wise to remember the importance of good data, and not to neglect the challenges that measurement continuously poses (Deaton 2016, page 1221).
This nicely sums up the tone of a previous post, that a conversation about Canadian public policy directed to poverty has not been well served by the confusing and conflicting information provided by official statistics.
Just how should we measure poverty in a way that is most helpful for public policy?
The two most commonly used poverty rates produced by Statistics Canada tell very different stories. The patterns are curious, and confusing. The two statistics—the poverty rate according to the Low Income Cut-off and that according to the Low Income Measure—track each other rather closely up to the early 1990s, then diverge quite markedly as the Low Income Cut-off falls steadily to an unprecedented low, while the Low Income Measure drifts upward. Which statistic should we believe?
The cyclical patterns also differ, with the Low Income Measure registering higher poverty during recessions only before the 1990s, and in a way that is more muted and lagging the movement in the Low Income Cut-off. It also signals a rise in poverty only well after the onset of the 1990/92 recession, and both measures show no upturn in poverty during the Great Recession, which began in 2008 and led to a significant fall in employment.
For something that is central to so many policy debates, the Canadian “poverty” rate is notoriously confusing, and it is easy to imagine that public policy may be misled. The first step in devising a poverty reduction strategy is understanding what these numbers mean, and whether they are useful. Is poverty at unprecedented lows, or has it been stuck at high levels for decades? Both views can’t be right, but they can both be wrong.