We examine the impact of distance on internet search, and the effect of the “local bias” in search on the stock market response around earnings announcements. We find significant local bias in search behavior. Motivated by theories explaining local bias, local information advantage, and familiarity bias, we predict and find that firms with higher local bias in search experience higher bid-ask spreads, lower trading volumes, and lower earnings response coefficients at the time of earnings announcements, consistent with non-local investors relying more than locals on public information announcements. Consistent with local information advantage, we find that in the week prior to the announcement, firms with higher local bias have higher bid-ask spreads, higher trading volumes, and returns that are more predictive of the coming earnings surprise. Consistent with familiarity bias, firms with higher local bias in search experience stronger post-earnings announcement drift. We use unique predictions, propensity score matching, and two-stage least squares to identify the effects of local bias separately from the effects of overall visibility. Overall, we show there is significant local bias in search, and that this local bias has a significant impact on the market response around earnings announcements.

Disclosure theory predicts that the likelihood of voluntary disclosures increases with the noise level in mandatory disclosures. We test this prediction by exploiting a unique setting where firms simultaneously provide two forecasts of the same metric—annual effective tax rates (ETRs). We find that managers are more likely to issue voluntary ETR forecasts when mandatory ETR forecasts contain more noise due to tax complexity, suggesting that managers resort to voluntary disclosure when mandatory disclosure constrains their ability to convey private information. Using analysts’ ETR forecast revisions to assess the informativeness of the two ETR forecasts, we find that both forecasts are incrementally informative. In addition, analysts weight voluntary ETR forecasts more heavily, especially when voluntary ETR forecasts are non-GAAP based and when discrete items are present. Overall, we provide evidence on the relation between and the informativeness of voluntary and mandatory disclosures by examining two competing forecasts issued simultaneously.

We find evidence that investors misprice information contained in book-tax differences (BTDs), measured as the ratio of taxable income to book income, TI/BI. Low TI/BI predicts worse earnings growth and abnormal stock returns than high TI/BI. We find that short sellers and insiders arbitrage BTD mispricing, but the arbitrage is imperfect because of constraints on short selling and insider trading. Under SFAS No. 109 the predictability is stronger for TEMP/BI, the temporary component of TI/BI, which reflects greater managerial discretion. The results are incremental to a large set of known accruals-based anomaly predictors. We suggest that a sunshine policy of disclosing a reconciliation of book and taxable incomes can reduce mispricing of BTDs and improve capital market resource allocation. Data Availability: Data are obtained from the public sources as indicated in the text.