Tuesday, November 19th @ 11:00-12:30 PM (1011 Evans Hall)
The Ratio Problem
Frank Partnoy, UC Berkeley
ABSTRACT: We describe two problems – omitted variable bias and measurement error – that arise when a ratio is the dependent variable in a linear regression. First, we show how bias can arise from the omission of two variables based on a ratio’s denominator, and we describe tests for the degree of bias. As an example, we show that the familiar “inverse U” relationship between managerial ownership and Tobin’s Q is reversed when omitted variables are included. Second, we show how measurement error in the ratio denominator can lead to bias. We urge caution about using ratios as dependent variables. Working paper