Income inequality has become the watchword of the current era. It is often used as a shorthand explanation for wealth concentration, economic stagnation, declining social mobility, various social ills ranging from the decline of civic engagement to the opioid crisis, and for the populist politics that have blossomed in the US and Europe. In his fascinating talk, Brian Nolan, Professor of Social Policy at the University of Oxford, took a hard look at the evidence for these purported consequences of inequality, and in most cases found it lacking or inconclusive. But does data have the final word?
Take Brexit, for example. Many have argued that rising British income inequality was responsible for driving populist feeling. But Prof. Nolan showed that while inequality spiked sharply during the Thatcher era, it remained stable thereafter, meaning that the level of inequality did not, in a strict sense, correlate with the rise of populism. Yet Prof. Nolan didn’t discount the possibility that the data might not be telling the whole story. He acknowledged that there may be lagging or indirect effects, and it is possible that the spurt of inequality in the 80s sowed the seeds for the present wave of populism in ways that sociologists are still studying. Certainly the fact that, as he cited, education and geography are the strongest predictors for how people voted suggests that labor market competitiveness and uneven regional economic development — which are manifestations of inequality — rallied support for the “Leave” campaign.
On Growth and Inequality
According to Prof. Nolan, the claim that rising inequality slows economic growth is not robustly substantiated by the evidence. In my view, this causal relationship is not only unsupported by data but might also be conceptually flawed. Let’s say inequality does slow down growth: we are still left to explain what forces are creating inequality in the first place. And the possible answers to that question — financialization, stagnant wages, etc. — are all markers of a sedate economy. Thus, our hypothesis would be that inequality is both driven by and driving slow growth, in which case the impact of inequality on growth is a feedback effect, and we ought to focus primarily on the puzzle of slowed economic growth.
This puzzle cuts to the heart of a debate in the field of economics about the theories used to understand the workings of the economy. As Prof. Nolan pointed out, policymakers at the IMF and the OECD now argue that inequality can be addressed through market correcting tweaks, and have therefore begun developing policies intended to foster “inclusive growth.” But is inequality a bug or a feature of our capitalist economy? It might be more likely that slowed growth, like income inequality, is inherent to capitalism. In that case, are redistribution and other such schemes the solution? If the gears of the capitalist economy are in a secular slowdown, they might not provide more than a short-term reprieve.