Look at the changes, not at the levels

A few people have asked me recently for my view on “The Spirit Level” by Richard Wilkinson and Kate Pickett, which is apparently having some impact in policy circles. John Kay’s view in the FT comes closest to my own:

a larger source of irritation is the authors’ apparent belief that the application of regression methods to economic and social statistics is as novel to social science as it apparently is to medicine. The evidence presented in the book is mostly a series of scatter diagrams, with a regression line drawn through them. No data is provided on the estimated equations, or on relevant statistical tests. If you remove the bold lines from the diagram, the pattern of points mostly looks random, and the data dominated by a few outliers.

The United States, the most unequal of the countries considered, scores poorly on virtually all the social indicators used. Japan, rated one of the most equal, has long life expectancy, a small prison population and low levels of violence. Within Europe the Scandinavian countries are generally distinguished by high levels of both equality and social performance. These observations probably account for most of Wilkinson and Pickett’s findings.

I’m about as anti-inequality an economist as you’ll find. But my own empirical work on the issue has convinced me that when you look at within-country changes, the picture that emerges is very different to what you see when you look at a snapshot across countries over time. For example, it’s certainly true that in unequal countries, lifespans are shorter and infant mortality is higher. But here’s what you get if you compare changes in inequality with changes in mortality (from a paper with Tim Smeeding and Christopher Jencks).


Note: Changes in infant mortality are scaled in reverse, to allow comparability with life expectancy measures. LE is life expectancy at birth (years). IM is infant mortality (deaths per 1000). All changes are expressed on a ‘per decade’ basis (ie. annualized and multiplied by 10). We exclude the three poorest countries in the OECD (Mexico and Poland; and Turkey for lack of data), and the richest (Luxembourg). Countries and years covered are Australia (AUS) 1981-2001, Belgium (BEL) 1985-2000, Canada (CAN) 1981-2000, France (FRA) 1981-2000, Germany (DEU) 1981-2000, Italy (ITA) 1986-2000, Netherlands (NLD) 1983-99, Norway (NOR) 1979-2000, Spain (ESP) 1980-2000, Sweden (SWE) 1981-2000, Switzerland (CHE) 1982-2000, the United Kingdom (GBR) 1979-99, and the United States (USA) 1979-2000.

Yup, the graph slopes up. In other words, countries that experienced big increases in inequality saw bigger improvements in health than those where inequality stayed stable or fell. In most cases, the effect isn’t significant, but the data certainly don’t support the hypothesis that rising inequality harms population health.

From a policy standpoint, specifications based on changes must surely be more compelling than specifications based on cross-country snapshots at a point in time. Australia can never literally become the Netherlands, but we can see what happens when our level of inequality rises and theirs falls.

After working on inequality and mortality, I have had similar experiences in looking at data on inequality and savings with Alberto Posso (we find no relationship), and in looking at inequality and growth with Dan Andrews and Christopher Jencks (we find that inequality has no impact on growth over the period 1905-2000, and conclude that inequality is good for growth over the period 1960-2000). In both cases, I had begun the project secretly hoping to find that inequality was bad, and wound up reluctantly reporting no such thing.

All this has made me think that the ‘instrumental’ reasons for worrying about inequality tend to be pretty flimsy, and that the best reason to care about inequality is the declining marginal utility of income (a dollar brings less happiness to a millionaire than a pauper). Inequality matters, but let’s not overegg the pudding.

Update: Dalton Conley has an interesting ‘why should we care about inequality’ piece in American Prospect that touches on some of these themes.

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9 Responses to Look at the changes, not at the levels

  1. Ben says:

    For me, the main reason to care about inequality is that it is unjust. Poor people are sicker and die younger in most countries. My understanding is that this is so irrespective of the poor’s absolute income (as opposed to relative). Whilst this is not an “instrumental” reason to avoid inequality, it is an important one. BMJ meta-analysis looked at your question this year with very different results:


    However, most studies used seem to be cross-sectional (rather than following changes over time as you have rightly expressed a preference for). I am aware that some have suggested a lag factor might be at play. I’ll go look through your paper with Smeeding & Jencks to see what time period was covered.

  2. Cathal Kelly says:

    A coincidence in timing, but Andrews, Jencks and Leigh is cited today here: http://crookedtimber.org/2009/12/17/bookblogging-the-failure-of-trickle-down/

  3. SJ says:

    Crossposted at JQ:

    Leigh’s paper can be found here.

    I challenge anyone qualified in econometrics to examine Figure 2, and agree with the fitted curves.

  4. SJ says:

    Sorry, Andrew, I forgot to give the back link to JQ

  5. Jon says:

    Increasing inequality is associated with increased growth and no decline in health/mortality outcomes. Well, that is great news and really a complete vindication of the free market/laissez faire doctrines of the last few decades. Thank you! As to any argument around the declining marginal utility of income – well, so what, really? . A reminder perhaps to keep up the donations to the poor but clearly no grounds for contemplating any sort of policy changes or bleeding heart distributive justice issues – not at the risk of compromising growth.

  6. Andrew Leigh says:

    SJ, I think you’ve gotten things a bit muddled. Figure 2 simply charts GDP and life expectancy (no tricks – it’s just raw data). As I recall, we don’t make much of it in the text.

    If you want to understand inequality and life expectancy, you’ll find that in Figure 3.

    Bottom line – in levels, inequality makes you sick. In changes (which is what policy can affect), inequality makes you healthier – but the relationship isn’t significant at conventional levels, so our interpretation is that there’s no proven relationship either way.

  7. SJ says:

    “SJ, I think you’ve gotten things a bit muddled. Figure 2 simply charts GDP and life expectancy (no tricks – it’s just raw data). As I recall, we don’t make much of it in the text.”

    Well, if I was just trying show raw data, I probably wouldn’t have drawn a strange looking curve through it. Nevertheless, I accept your position that “we don’t make much of it in the text”. Please accept my apologies.

  8. Alan says:

    What is striking about this discussion is the seeming
    blindness to environmental and resource issues. The bottom
    line there (wrt the topic of the post, and discussion) is that
    the rich and very-rich are consuming everyone’s future, in
    a very big way. (I would include the U.S. middle class in
    the category of “rich”.) The most compelling objective
    argument against great inequality in income or wealth
    is not actually an argument against those things *per se*,
    it is an argument against extreme consumption which is
    (it should be obvious by now) unsustainable.

    SEE (book):
    How the Rich are Destroying the Earth
    by: Herv? Kempf

    “The book’s central thesis [is] that the ‘oligarchy,’ a global
    stateless class composed of the hyper-rich and the ‘new
    Nomenklatura,’ is responsible for our species’ headlong rush
    to environmental destruction, both indirectly, through the
    rest of society’s attempts to imitate and emulate their
    wasteful habits of conspicuous consumption, and directly,
    through their control of the levers of power, all presently
    fixed at the ‘Catastrophe’ setting’.”

    for more snippets and notes, go here:

  9. Andrew Leigh says:

    SJ, apology happily accepted. I agree that the curve looks odd, but that’s because it’s a locally weighted regression that is doing its best to follow the data. It gets pulled down at the end because of a couple of rich nations – including the US (I’d guess because of inadequate healthcare & racial heterogeneity, but there’s a fierce debate on this). When you plot all the world’s nations, the so-called “Preston Curve” looks smoother than if you just do it for the OECD, as we did.

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