UNICEF, a branch of the United Nations, has just released an interesting report on child poverty during the Great Recession. The report’s results have been reported widely and are distressing. It shows that since 2008 2.6 million children in rich countries have sunk below the poverty line. In 23 of the 41 countries analysed, child poverty has jumped since 2008. In Ireland, Croatia, Latvia, Greece and Iceland rates rose by over 50%.

Change in child poverty, 2008 to 2012 (anchored in 2008) I should say at the outset that I am generally convinced by what I’ve read in this report. It is a very important topic and one that needs to be debated more. But for people serious about analysing poverty, the report is not good enough. I’ve been puzzling over a few things in particular.

Making assumptions is all well and good in economics research: it is often unavoidable. But researchers usually spend a long time justifying their assumptions, and showing what happens when they make different ones.

But in this report the authors make assumptions that are not adequately justified. Take their definition of “poverty”. Usually academics define poverty as those people with incomes below 60% of their country’s median. That’s a relative measure, of course. Here, though, the authors use income figures from 2008—before the crisis really hit—as a “benchmark” against which to compare the incomes of subsequent years. They do this, they say, because otherwise country-wide falling incomes will mean that the “true” poverty rate could be understated. (In a recession, if everyone’s income is declining, the official poverty rate could be stagnant or even falling, even though in practice many more people are being thrown into penury.)

But this is a kind of absolute measure of poverty, not a relative one. People are judged to be either in or out of poverty by looking at their current income relative to a past threshold. That has the effect of boosting poverty numbers during a recession.

That’s not necessarily a bad thing, for the reasons outlined above. But the authors don’t replicate their finding using alternative definitions of poverty. That does not inspire confidence in the reliability of their results.

There are other incidences in which assumptions are made, but not justified. The authors split the 41 countries analysed into three groups: the “most affected”, “moderately affected” and “least affected” by the recent economic turmoil. They show that the countries most affected by the economic crisis performed worse in terms of child poverty.

Fine. But who is included in each group? They say that Estonia, Hungary, Iceland, Latvia and Lithuania were included in the “most affected” group because they were all “supported by International Monetary Fund (IMF)/EU/European Central Bank programmes”. (As far as I know, neither Estonia nor Lithuania was subject to an IMF programme, but never mind). The other countries included in this group—like Greece and Italy—were included because the cost of insuring their government debt got quite high in 2012.

Clearly, both of the criteria for inclusion in the “most affected” group are rather arbitrary. Why is France not included? Why is Britain, which is experiencing its longest period of pay stagnation since records began in 1855, not included?

This is not to say that either France or Britain should definitely be included in the “most affected” group—just that some explanation as to why they were not is surely justified. A sceptic would claim that the authors put specific countries into specific groups with the intention of showing that the countries “most” affected by the recession did "worst" in terms of child poverty. (I believe this is highly unlikely, but the authors should have addressed this point).

Then there is the data analysis itself. Take Figure 7 of the report, shown below. The chart shows that those countries that saw the biggest increases in poverty headcount also saw the biggest increases in the “poverty gap” (the median income of those below the line, expressed as a percentage of the poverty line). Or does it? After all, the “r-squared” of the correlation—a measure of how strong it is—is very low, at just 0.1426. (The authors don't appear to say whether or not that correlation is statistically significant, either). But there is no commentary on the size of the r-squared: instead there is a trend line slapped on the graph.