voter theorem is absent. However, it is not clear that this would fully neutralize the relevance of income distribution; even dictators cannot entirely ignore their citizens’ wishes.<sup>9</sup> A more compelling reason to question this hypothesis is that the evidence suggests that poorer countries tend to have more unequal distributions.<sup>10</sup> The (small) literature on the role of distribution in influencing public spending has almost solely used the Gini index (as in, for example, Shelton 2007), rather than skewness, but the two are likely to be highly correlated. Empirically, we find that skewness is actually a more common feature of income distributions in low-income countries than in high-income ones; we find that the correlation coefficient between (log) GDP per capita and the ratio of the mean to the median incomes is -0.405.<sup>11</sup> Thus, if anything, the political economy of redistribution (or at least the median-voter version) implies <u>more redistributive effort in poorer countries. So, we appear to know enough already to reject</u> this hypothesis as an explanation of the rising SPEC, and we will not test it further.

**_Distribution 2: The unequal growth hypothesis._** _Economic growth in market economies tends to be inequality increasing. This leads to political demands for redistributive SP policies._ The idea that higher inequality creates demands for redistribution is familiar from the political economy literature (including, for example, Alesina and Rodrik 1994). In the present context, the concern is that the positive income effect on the SPEC is actually picking up the effect of economic growth on inequality, leading to higher SP spending.

However, in light of accumulated evidence from household survey data, the basic premise of this hypothesis can be questioned. Empirically, we see a far more mixed picture, with inequality decreasing roughly as often as it increases in growing economies.<sup>12</sup> These findings have been mainly from research on developing countries. However, a similar result is found when one includes high-income countries; in the global data set we use below, the correlation coefficient between the first difference of the log Gini index and the first difference of log GDP per capita is -0.09.<sup>13</sup> So, from what we know already, this hypothesis can also be dismissed.

> 9 <u>Han (2021)</u> finds that in authoritarian regimes that hold elections, redistributive policies are implemented in the runup to elections even when election results are predetermined.

> 10 See, for example, World Bank (2006) and Milanovic (2016).

> 11 We measure the ratio of the mean to the median, with both measured from the household surveys, as processed in the World Bank’s _<u>PovcalNet</u>_ site. While the ratio of the mean to the median is not strictly skewness (the third moment of the distribution), it is an intuitively appealing indicator. The ratio exceeds unity in all countries as one would expect.

> 12 <u>Ravallion (2016a, Chapter 8)</u> reviews the evidence on this point. Note that we refer here to relative inequality; absolute inequality tends to rise with growth; on this distinction and the evidence see Ravallion (2021).

> 13 For the levels regression with country fixed effects the partial correlation coefficient is -0.03.

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