We present evidence that several popular low-frequency measures of effective spread suffer from a volatility-induced bias and that volatility is the primary driver of the variation of these liquidity proxies. Using data for U.S. equities and major foreign exchange rates, we show that the bias arises when the effective spread is small relative to volatility. We document that the bias has become more acute over time and show that volatility-biased measures fail to replicate some well-known results in empirical finance. We conclude by providing guidance on the choice of low-frequency measures in empirical applications.

This paper provides a comprehensive survey of existing measures of uncertainty, risk, and volatility, noting their conceptual distinctions. It summarizes how they are constructed, their relative advantages in usage, and their effects on financial market and economic outcomes. The measures are divided into four categories based on the construction methodology: news-based, survey-based, econometric-based, and market-based measures. While heightened uncertainty is typically associated with negative real and financial outcomes, the magnitude of these effects and the interpretation of transmission channels crucially depend on identification considerations.