Associate Professor of Public Policy, Goldman School of Public Policy, University of California at Berkeley
Analysts often examine the black-white test score gap conditional on family income. Typically only a current income measure is available. We argue that the gap conditional on permanent income is of greater interest, and we describe a method for identifying this gap using an auxiliary data set to estimate the relationship between current and permanent income. Current income explains only about half as much of the black-white test score gap as does permanent income, and the remaining gap in math achievement among families with the same permanent income is only 0.2 to 0.3 standard deviations in the CNLSY and ECLS samples. When we add permanent income to the controls used by Fryer and Levitt (2006), the unexplained gap in 3rd grade shrinks below 0.15 SDs, less than half of what is found with their controls.