We hypothesize that a source of commonality in a stock's liquidity arises from the correlated liquidity demand of the stock's investors. Focusing on correlated trading of mutual funds, we find that stocks with high mutual fund ownership have comovements in liquidity about twice as large as those for stocks with low mutual fund ownership. Further analysis shows that the channels for these comovements derive from both common ownership across funds and funds' correlated liquidity shocks. We obtain inferences supporting causality from an exogenous flow shock for mutual funds in the aftermath of the 2003 mutual fund scandal.

We document that backfilling in the ExecuComp database introduces a data-conditioning bias that can affect inferences and make replicating previous work difficult. Although backfilling can be advantageous due to greater data coverage, if not addressed, the oversampling of firms with strong managerial incentives and higher subsequent returns leads to a significant upward bias in abnormal compensation, pay-for-performance sensitivity, and the magnitudes of several previously established relations. The bias also can lead to one misinterpreting the appropriate functional form of a relation and whether the data support one compensation theory over another. We offer methods to address this issue.

We hypothesize that a source of commonality in a stock’s liquidity arises from the correlated liquidity demand of the stock’s investors. Focusing on correlated trading of mutual funds, we find that stocks with high mutual fund ownership have comovements in liquidity about twice as large as those for stocks with low mutual fund ownership. Further analysis shows that the channels for these comovements derive from both common ownership across funds and funds’ correlated liquidity shocks. We obtain inferences supporting causality from an exogenous flow shock for mutual funds in the aftermath of the 2003 mutual fund scandal.

We document that backfilling in the ExecuComp database introduces a data-conditioning bias that can affect inferences and make replicating previous work difficult. Although backfilling can be advantageous due to greater data coverage, if not addressed, the oversampling of firms with strong managerial incentives and higher subsequent returns leads to a significant upward bias in abnormal compensation, pay-for-performance sensitivity, and the magnitudes of several previously established relations. The bias also can lead to one misinterpreting the appropriate functional form of a relation and whether the data support one compensation theory over another. We offer methods to address this issue. Received May 12, 2014; editorial decision May 10, 2016 by Editor David Hirshleifer.