5 The second group of models focuses on the effect of inequality on policy decisions – either through voting or through lobbying. Alesina and Rodrik (1994) and Persson and Tabellini (1994) use standard median voter models to predict that societies with a larger gap between median and mean incomes (a plausible measure of inequality) would choose higher rates of redistributive taxation. If taxes distort private investment decisions, then greater inequality might lead to lower growth rates through higher distortive taxation. Bénabou (2000) proposes an alternative set up where inequality distorts public policy by leading to inefficiently low – rather than high – taxes. This mechanism requires that voting power increase with wealth, so that the pivotal voter has higher than median wealth. It also requires that public investment (e.g. educational subsidies) have positive spillovers, so that taxes finance efficient public expenditures. These conditions are not sufficient for, but may lead to, multiple equilibria that depend on the initial distribution.<sup>5</sup> Inequality may also matter for political processes other than elections. Esteban and Ray (2000) suggested that the rich might find it easier to lobby the government, and distort resource allocation from the social optimal towards the kinds of expenditures they prefer. Campante and Ferreira (2007) construct a model where the outcome of lobbying is generally not Pareto efficient: resource allocation can be distorted away from the social optimal, and this may benefit poorer or richer groups, depending on their relative productivity levels in economic and political activities.<sup>6</sup> These various predictions have been put to the test a number of times, typically by including a measure of initial inequality in the standard cross-country growth regression of Barro (1991). In a first phase of the literature, both Alesina and Rodrik (1994) and Persson and Tabellini (1994) reported results from such an exercise. Alesina and Rodrik (1994) regressed the annual growth rate in per capita GDP on the Gini coefficients (for income or land) in 1960, for different country samples, using both OLS and twostage least squares (TSLS) regressions.<sup>7</sup> Their inequality data come from secondary sources, namely compilations of income Gini coefficients from Jain (1975) and Fields (1989), and of land coefficients from Taylor and Hudson (1972). Both of these studies found a negative and statistically significant coefficient for initial inequality in the growth regression. Alesina and Rodrik report a particularly robust correlation between land inequality and subsequent growth, significant at the 1% level, and implying that an increase of one standard deviation in land inequality would lead to a decline of 0.8 percentage points in annual growth rates. Deininger and Squire (1998), using a larger (and arguably higher-quality) crosscountry inequality dataset they compiled, report the same basic finding of a negative effect of initial inequality on growth.

This Deininger and Squire (1996) dataset, introduced in the late 1990s, contained inequality data points for many more countries and, most importantly, at various points in time. This allowed Li and Zou (1998) and Forbes (2000) to run the same growth regression as the earlier papers on a panel, rather than a cross-section, of countries – ushering in “Phase 2” of the literature on inequality and growth. Forbes

> 5 The mechanism proposed by Bénabou (2000) has the advantage that it is more consistent with the evidence that high inequality countries tend to tax less, rather than more, than less unequal countries. See also Ferreira (2001). 6 The theoretical literature on the links between inequality and growth has been extensively reviewed, and we do not attempt to review it comprehensively here again. For some of the best surveys, see Aghion et al. (1999), Bertola (2000) and Voitchovsky (2009).

> 7 Literacy rates in 1960, infant mortality rates in 1965, secondary enrollment in 1960, fertility in 1965 and an Africa dummy are used as instruments for inequality in the TSLS first-stage.