Sorry, right-wingers, higher inequality doesn't boost economic growth

Though reducing inequality likely doesn't help that much either

It’s a classic talking point on the right that a country needs more inequality to grow faster. It’s one of the ostensible reasons why the dog-eat-dog US is ahead of egalitarian Europe. The basic idea, which I admit is intuitively plausible, is that relatively high inequality incentivizes effort and specifically rewards risk-taking. It should also just generally channel resources toward the most productive members of society, who then save and invest more. Hence, economic growth should get a boost. Conversely, too much equality dulls the entrepreneurial spirit or makes people slack off.

And it’s true that decades ago, many economists wouldn’t have much an issue with the idea. Arthur Okun and his Equality and Efficiency: The Big Tradeoff are perhaps the most well known in the space. This is how he put it some time ago:

Contrast among American families in living standards and in material wealth reflects a system of rewards and penalties that is intended to encourage effort and channel it into socially productive activity. To the extent the system succeeds, it generates an efficient economy. But that pursuit of efficiency necessarily creates inequalities. In hence, society faces a trade-off between equality and efficiency. Tradeoffs are the central study of the economists. You can’t have your cake and eat it, too, is a good candidate for the fundamental theorem of economic analysis. We can’t have our cake of market efficiency and share it equally.

In a very general sense, there is or was obviously some truth to what he says. It’s also just a bog-standard economic hypothesis (like, for example, the opposite hypothesis that inequality harms growth). Don’t let my juicy right-vs-left ideological framing scare you off. Sure, the idea that inequality helps with growth has a right-wing tone to it; but that says nothing about whether it’s correct or not. Just like the claim that inequality harms growth has a left-wing tone to it; but that shouldn’t repel you from it. What matters is the evidence (if you want more theory, read the footnote).¹ And the actual evidence we have on the inequality-growth relationship hasn’t been kind to “inequality boosts growth” hypothesis over the past few decades. (But it’s also not in any straightforward way true that more inequality means less welfare, as The Spirit Level guys insist!)

Meta-analyses point in the same direction: no or negative relationship

If you’re new to a topic and don’t have much time to examine it properly, relying on meta-analyses is a good first-pass to get a sense for things. If you want a firm grasp of the evidence, you’ll have to go beyond meta-analyses and also wrestle with individual studies, preferably those that are of highest quality. But this is a good start.

Fortunately, there have been three major meta-analyses that were conducted on the inequality–growth relationship in recent time: De Dominicis et al. (2008), Cunha Neves et al. (2016), and most recently Capretti and Tonni (2025).

All three point in the same general direction, which is that the aggregate effect of inequality on growth is either negative or zero. None of them finds an Okun-like positive average effect.

De Dominicis et al. (2008), published in the Scottish Journal of Political Economy, were the first to apply meta-analytic methods to the literature. They found that estimation methods, data quality, and sample coverage systematically affect results, and concluded that the evidence does not indicate a clear positive relationship - if anything, the direction leans negative.

Cunha Neves et al. (2016), in World Development, extended this analysis with more recent studies and broader inequality concepts (not just income, but also land and human capital inequality). Their conclusions were that the effect of inequality on growth is negative. This negative effect is more pronounced in developing countries and over long time horizons. They also found traces of publication bias in the literature - unsurprisingly, authors and journals are more likely to publish statistically significant findings, regardless of direction.

The newest entry, Capretti and Tonni (2025), covers studies published from 1994 to 2025 and collects 531 effect-size estimates from 33 papers. They find an “economically small but statistically significant negative average effect” of income inequality on growth. They also detect selective publication based on statistical significance, though not systematic directional bias (i.e., the literature isn’t systematically pushing negative results over positive ones – it just favors significant results, period).

So the meta-analytic verdict is fairly simple on average: if anything, higher inequality is associated with somewhat lower growth.

Mind the huge heterogeneity

All three meta-analyses emphasize that the heterogeneity of results across individual studies is enormous. The average effect may be mildly negative, but individual estimates scatter wildly from strongly negative to strongly positive. Why? What accounts for this?

Here are some of the most important sources of heterogeneity. It all depends on:

1. Which countries you study. The negative effect of inequality on growth appears stronger in developing countries. In richer economies, the relationship is weaker or sometimes positive. Barro (2000) first documented this pattern, and both Cunha Neves et al. (2016) and Capretti and Tonni (2025) confirm it in their meta-regressions.

2. What time horizon you use. Cross-sectional studies that examine long-run growth (25–40 years) tend to find more negative effects. Short-run panel studies sometimes find positive effects. Forbes (2000), in one of the most influential papers in this literature, showed that inequality appears positively related to growth in the short-to-medium run using panel data with fixed effects. Though this may simply reflect the mechanical effect of the estimator. There might not be any genuine economic effect here.

3. How you measure inequality. Capretti and Tonni (2025) note that inequality measured after taxes and transfers is associated with more negative growth effects than inequality measured before fiscal redistribution. The choice of inequality index can also influence results. The Gini coefficient, income shares, and the Theil index can tell somewhat different stories. This isn’t surprising for at least two reasons. First, as a summary aggregate variable the Gini coefficient is much less sensitive to what’s happening at the extremes of the distribution than, say, the top 1% or 0.1% share of income/wealth. Second, even just descriptively, the income Gini coefficient and top income shares show no rise of within-country inequality over the past few decades (contrary to popular opinion). The less frequently used Theil index does show such a rise.

4. Which statistical method you employ. Fixed-effects estimators, GMM, OLS, and instrumental-variable approaches produce different results. This is expected, as some of the methods are more or less likely to be able to account for (sources of) endogeneity, like reverse causation and omitted-variable bias. In any case, De Dominicis et al. (2008) identified the econometric estimator as the main driver of variation, while Cunha Neves et al. (2016) put more weight on the data structure (panel vs. cross-section). Capretti and Tonni (2025) find that both are important.

But perhaps rising inequality goes with growth at least at low starting levels?

Instead of claiming that inequality is straightforwardly good for growth, more nuanced accounts hold that the relationship is nonlinear – for instance, shaped like an inverted U. At very low levels of inequality, some increase might stimulate growth by providing appropriate incentives. But beyond a certain threshold, inequality does nothing or even becomes harmful, perhaps through credit constraints on the poor, political instability, or underprovision of public goods.

This idea has theoretical appeal and some empirical support. Banerjee and Duflo (2003) documented an inverted-U relationship in a cross-country setting. Balcilar et al. (2021), using a semiparametric model on data from 63 countries, found that inequality has a positive effect on growth up to a Gini threshold of roughly 36, beyond which the effect turns negative.

But the literature on nonlinear effects is itself quite mixed. Some studies find no evidence of a threshold at all. Among those that do, the estimated turning point varies considerably. Hailemariam and Dzhumashev (2020) identify a threshold Gini of about 41 for developing countries, which is quite a bit higher than Balcilar et al.’s estimate. Brueckner and Lederman (2018), instead of estimating a Gini threshold directly, find that the relationship depends on initial income levels. That is, inequality boosts transitional growth in low-income countries but significantly harms it in high-income ones. For the median country in the world (with a GDP per capita around $10,000 in PPP terms in 2015), a one-point increase in the Gini was associated with more than one percentage point lower growth over five years.

For developed countries specifically, some studies place the beneficial threshold at very low Gini values – around 24 or so – meaning that only at exceptionally egalitarian levels does a bit more inequality help. That’s the Gini threshold provided by Hailemariam and Dzhumashev (in contrast to the 41 figure for developing societies). Once you pass this very modest level, the effect turns neutral or negative. Other studies place the threshold higher, around 30–35, which would leave somewhat more room for inequality to be growth-enhancing in middle-inequality countries.

Here’s a simple scatterplot so you get a feel for how unequal different societies are (income inequality).

People on the left and right are likely both wrong

I think if we’re being honest, currently existing evidence doesn’t support the right-wing idea that inequality should be raised or tolerated so that appropriate incentives are in place for improving economic growth. At the same time, the left-wing worry that somewhat higher levels of inequality will definitely be very damaging for growth isn’t warranted either. It might be true, but not in all contexts; and the negative effect, if it exists, is likely modest.

This more or less meshes with the evidence we have specifically on tax cuts for the rich. It simply isn’t the case that they translate into more growth. As a recent meta-analysis on corporate tax cuts puts it:

The empirical literature on the impact of corporate taxes on economic growth reaches ambiguous conclusions: corporate tax cuts increase, reduce, or do not significantly affect growth. We apply meta-regression methods to a novel data set with 441 estimates from 42 primary studies. There is evidence for publication selectivity in favour of reporting growth-enhancing effects of corporate tax cuts. Correcting for this bias, we cannot reject the hypothesis of a zero effect of corporate taxes on growth. Several factors influence reported estimates, including researcher choices concerning the measurement of growth and corporate taxes, and controlling for other budgetary components.

Or take a look at this 2022 paper on how major tax cuts for the rich affect inequality and growth in OECD countries. As one would expect, tax cuts boost top 1% income shares, i.e., increase inequality.

Digitized from Hope and Limberg (2020).

But they don’t do anything for economic growth. They neither boost nor hurt it. Below.

Digitized from Hope and Limberg (2020).

1. Here’s quick theoretical rundown of both sides of the debate from a recent paper (I’m omitting all the references for clarity):

[I]nequality can impact economic growth negatively via two main channels. First, in an economy with relatively high levels of inequality, there are bound to be tendencies toward rent-seeking, abuse of political power for self-enrichment, and distrust of the incumbent government. Alternatively, voters may deem the levels of inequality to be unacceptable and proceed to insist on higher taxation and regulation. In both cases, this creates a hostile environment for investment, and ultimately leads to low growth. Second, financial and credit market imperfections as well as unequal distribution of natural resources […] are a hindrance to the needy to borrow for investment in physical and human capital. In such environments, inequality is considered to perpetuate low growth.

There are two main transmission mechanisms for the positive relationship between income inequality and economic growth. First, the classical argument is that inequality channels resources toward the rich, whose marginal propensity to save is higher than that of the poor. This increases an economy’s aggregate savings, leading to accumulation of physical capital and ultimately higher economic growth. Second, inequality incentivizes individuals or a society to work harder, save, and invest in both human capital and productive industries in order to improve incomes, all of which have a positive impact on economic growth.