This paper discusses two issues in the relationship between inequality and economic growth: the data and the econometrics. We first review the income inequality data set of Deininger and Squire (D&S), which, we argue, fails to provide either adequate or accurate coverage, whether through time or across countries. We then introduce our own measures of the inequality of manufacturing pay, based on UNIDO's Industrial Statistics. These provide indicators of pay inequality that are more stable, more reliable and in our view also more comparable across countries, than the D&S data. Turning to the fabled “Kuznets” relationship between inequality and economic development, we diagnose several common econometric problems in the literature, including measurement error and omitted variable bias. By taking steps to account for these problems, and by introducing a more complete panel data set based on pay inequalities, we seek more reliable inferences concerning the relationship between inequality, national income and economic growth. We find evidence that generally supports Kuznets' specification for industrializing countries: pay inequality tends to decline as per capita income increases, though with some tendency for the relationship to curve up for the richest countries. After 1981 two findings emerge. First, per capita GDP growth slowed dramatically in most countries, increasing inequality along the augmented Kuznets curve. Second, there is a global and macroeconomic effect that produces rising inequality in our data, independent of GDP or its changes. The timing of this effect suggests a link to the high real interest rates and global debt crisis of the period beginning in 1982. (JEL C23, D31, J31, O11 )