Our general approach is to ask whether lagged publication-level advertising expenditures are correlated with the probability of receiving a media mention, controlling for all of the mutual fund and mutual fund family characteristics that publications might reasonably use to rank funds. Consider predicting positive mentions in a particular publication using the following specificatio Mention, t=a +?(Own-Publication Advertising t-1)+BZi, t-1+8k, t +Ei. here Mentionit equals one if fund i receives a positive mention in the publication in month t and zero otherwise, Own-Publication Advertising i t-1 measures lagged advertising expenditures in the publication by fund i's family, Zi t-1 contains numerous control variables, Sk. t is an investment objective-by-month fixed effect, and Eit is a fund-by-month disturbance term. To test whether advertising and content are related we estimate equation(1)and test whether i is statistically different from zero. The identifying assumption equired to give this test a causal interpretation is that advertising within a publication be uncorrelated with any unobserved fund characteristics that would cause its readers to want the publication to mention the advertisers fund. For products whose quality is partially or totally subjective, the fact that advertising is endogenous would lead us to seriously question this assumption. However, in the context of mutual funds, where er post product quality is objective and easil tified, we believe the assumption may be casona From a financial perspective, mutual fund investors should seek to maximize risk-adjusted returns on an after-expense basis. Therefore, within each investment objective, publications should seek to identify those funds with the highest expected future returns and the lowest expenses. Since Carhart [1997 finds low fund expenses to be a good predictor of future returns, we control for fund is lagged expense ratio. As other potential predictors of future returns, we include fund is log return over the prior twelve months, its lagged log return squared, and its Morningstar rating at the end of the prior calendar year. In addition to predictors of future returns, publications should also focus on the form of distribution S Mutual funds with multiple share classes can earn a different Morningstar rating for each share class. Therefore, to control for Morningstar rating we begin with five dummy variables that indicate whether one or more of fund i's share classes earned a Morningstar rating of one, two, three, four, or five stars. We then scale each dummy variable by the fraction of dollars under nanagement receiving each ratingOur general approach is to ask whether lagged publication-level advertising expenditures are correlated with the probability of receiving a media mention, controlling for all of the mutual fund and mutual fund family characteristics that publications might reasonably use to rank funds. Consider predicting positive mentions in a particular publication using the following specification: Mentioni,t = α + γ(Own-Publication Advertisingi,t−1 ) + βZi,t−1 + δk,t + εi,t, (1) where Mentioni,t equals one if fund i receives a positive mention in the publication in month t and zero otherwise, Own-Publication Advertisingi,t−1 measures lagged advertising expenditures in the publication by fund i’s family, Zi,t−1 contains numerous control variables, δk,t is an investment objective-by-month fixed effect, and εi,t is a fund-by-month disturbance term. To test whether advertising and content are related, we estimate equation (1) and test whether ˆγ is statistically different from zero. The identifying assumption required to give this test a causal interpretation is that advertising within a publication be uncorrelated with any unobserved fund characteristics that would cause its readers to want the publication to mention the advertiser’s fund. For products whose quality is partially or totally subjective, the fact that advertising is endogenous would lead us to seriously question this assumption. However, in the context of mutual funds, where ex post product quality is objective and easily quantified, we believe the assumption may be reasonable. From a financial perspective, mutual fund investors should seek to maximize risk-adjusted returns on an after-expense basis. Therefore, within each investment objective, publications should seek to identify those funds with the highest expected future returns and the lowest expenses. Since Carhart [1997] finds low fund expenses to be a good predictor of future returns, we control for fund i’s lagged expense ratio. As other potential predictors of future returns, we include fund i’s log return over the prior twelve months, its lagged log return squared, and its Morningstar rating at the end of the prior calendar year.8 In addition to predictors of future returns, publications should also focus on the form of distribution 8Mutual funds with multiple share classes can earn a different Morningstar rating for each share class. Therefore, to control for Morningstar rating we begin with five dummy variables that indicate whether one or more of fund i’s share classes earned a Morningstar rating of one, two, three, four, or five stars. We then scale each dummy variable by the fraction of dollars under management receiving each rating. 6