Endogenous growth models have reignited interest in institutional and path dependencies in the economic growth process. One reason for the interest in endogenous growth models is that they may explain why countries consistently grow at different rates. In this vein, it has been recently proposed that greater economic inequality reduces future economic growth. An important paper in this literature is by Torsten Persson and Guido Tabellini (1994), who will be referred to as PT. PT's model shows why it is reasonable to expect a negative relationship between inequality and future economic growth. Moreover, their empirical evidence is consistent with their contention. If PT's findings are robust to other data sets, there would be important policy implications. For example, they imply that policy makers should not only be concerned with the distributional implications of government policies for political and social reasons, but also because income distribution has long-run effects on economic growth. This indicates that greater U.S. income inequality since the early 1970's may have resulted in lower subsequent economic growth. However, PT's results are somewhat fragile to various specifications, suggesting that they should be replicated with different data sets and over different time periods (PT p. 617). With these implications in mind, this study employs data from a panel of U.S. states to further explore the relationship between economic growth and income inequality. In what follows, Section I summarizes PT's study and discusses how this comment extends their findings. The empirical implementation and results in Section II directly examine the link between overall income inequality and growth. Section III expands the analysis to alternative measures of income distribution and government policy. One emphasis in Section III is the distinction between how the overall income distribution (especially at the tails) influences economic growth from how the relative well-being of the median voter affects economic growth. Section IV provides some concluding discussion.

Manmade climate change (CC) has catastrophic consequences. The United States has already experienced wholesale population realignment due to climate as households have relocated to the Sunbelt and West. The irony is that people are moving toward the heat and major storms associated with CC. As CC intensifies, with high rates of internal US factor mobility, firms and households will likely again relocate to areas with higher utility and profits, reducing CC costs. Yet current research typically focuses on CC costs in a given location without considering this realignment. We propose several avenues to overcome such shortcomings in US CC modeling.