Companies’ earnings conference calls are perceived to be venues for sell‐side equity analysts to ask management questions. In this study, we examine another important conference call participant—the buy‐side analyst—that has been underexplored in the literature due to data limitations. Using a large sample of transcripts, we identify 3,834 buy‐side analysts from 701 institutional investment firms who participated (i.e., asked a question) in 13,332 conference calls to examine the determinants and implications of their participation. Buy‐side analysts are more likely to participate when sell‐side analyst coverage is low and dispersion in sell‐side earnings forecasts is high, consistent with buy‐side analysts participating when a company's information environment is poor. Institutional investors trade more of a company's stock in the quarters in which their buy‐side analysts participate in the call. Finally, we find evidence that buy‐side analyst participation is associated with company‐level absolute changes in future stock price, trading volume, institutional ownership, and short interest.

We take up Cochrane’s (2011) challenge to identify the firm characteristics that provide independent information about average U.S. monthly stock returns by simultaneously including 94 characteristics in Fama-MacBeth regressions that avoid overweighting microcaps and adjust for data-snooping bias. We find that while 12 characteristics are reliably independent determinants in non-microcap stocks from 1980 to 2014 as a whole, return predictability sharply fell in 2003 such that just two characteristics have been independent determinants since then. Outside of microcaps, the hedge returns to exploiting characteristics-based predictability also have been insignificantly different from zero since 2003. Received January 28, 2015; editorial decision November 28, 2016 by Editor Andrew Karolyi.

We apply the discontinuity methodology from the accounting literature to a political economy setting of GDP reporting and examine whether Chinese local governments manage regional GDP numbers. We find strong evidence of discontinuities around zero in the distribution of actual minus target GDP growth rates. The frequencies of just meeting or beating GDP growth targets are about five (four) times the frequencies of just missing targets at the prefecture (province) level. The results are stronger for governors with longer tenures and those without political connections to higher-level officials as well as for local governments with more resources under their control.

This study examines the effect of proximity on corporate fraud commitment using the introduction of high-speed rail (HSR) as an exogenous shock to travel time. We find that firms commit less corporate fraud after the introduction of an HSR route. A dynamic difference-in-differences (DiD) analysis shows that the effect of HSR introduction on fraud only occurs after the HSR route is launched, supporting the parallel trends assumption and confirming the causal relationship. Further analysis shows that the negative impact of HSR introduction on corporate fraud is more pronounced for firms that have higher information asymmetry or weaker monitoring mechanisms in the pre-HSR period. In addition, we find that HSR introduction increases corporate site visits by external monitors and that visits significantly reduce corporate misbehavior. Overall, our findings suggest that HSR introduction increases proximity and thereby reduces the information acquisition costs for outside monitors. As a result, outside monitors are in a better position to oversee firms, leading to decreased fraud commitment.

We document strikingly opposite time‐series patterns of analyst forecast errors (FEs) and associated market reactions, illustrating that analyst forecasts have become a less useful benchmark of the market's earnings expectations in recent years. The mean FE has increased from negative one to two cents in the 1990s to positive one to two cents in the 2010s, whereas average earnings announcement returns have declined from 0.30% in the 1990s to −0.30% in the 2010s, turning negative in the past 17 years. Underlying the time‐series pattern of increasing FEs is a secular trend where firms move away from just meeting or beating, to which the market reaction has become increasingly negative, toward a large beat, while the frequency of meeting or beating the consensus analyst forecast remains stable during the same period. We develop a parsimonious predictive model of earnings surprises based on peer and past analysts' FEs and find that our predicted FE closely mirrors reported FE, with the average value hovering around one to two cents in most years of the past two decades. The market reaction to “around zero” unexpected FE (FE minus predicted FE) is indistinguishable from zero over time, suggesting that our model serves as a good benchmark of the market's expectation. Our evidence has broad implications for appropriate earnings benchmarking, for the disappearing discontinuity of the earnings surprise distribution around zero, for earnings management to beat analysts' forecasts, for empirical designs when examining the earnings‐return relation, and for the disappearing earnings announcement premium.

Speakers of strong future time reference (FTR) languages (e.g., English) are required to grammatically distinguish between future and present events, while speakers of weak-FTR languages (e.g., Chinese) are not. We hypothesize that speaking about the future in the present tense may result in the belief that adverse credit events are more imminent. Consistent with such a linguistic hypothesis, weak-FTR language firms are found to have higher precautionary cash holdings. We report additional supportive results from changes in the relative importance of different languages in a country's business domain, evidence from within one country with several distinct languages, and results related to changes following a severe financial crisis. Our evidence introduces a new explanation for heterogeneity in corporate savings behavior, provides insights about belief formation in firms, and adds to research on the effects of languages on economic outcomes.

We examine the effects of liquidity, default and personal taxes on the relative yields of Treasuries and municipals using a generalized model with liquidity risk. The municipal yield model includes liquidity as a state factor. Using a unique transaction dataset, we estimate the liquidity risk of municipals and its effect on bond yields. Empirical evidence shows that municipal bond yields are strongly affected by all three factors. The effects of default and liquidity risk on municipal yields increase with maturity and credit risk. Liquidity premium accounts for about 9–13% of municipal yields for AAA bonds, 9–15% for AA/A bonds and 8–19% for BBB bonds. A substantial portion of the maturity spread between long- and short-maturity municipal bonds is attributed to the liquidity premium. Ignoring the liquidity risk effect thus results in a severe underestimation of municipal bond yields. Conditional on the effects of default and liquidity risk, we obtain implicit tax rates very close to the statutory tax rates of high-income individuals and institutional investors. Furthermore, these implicit income tax rates are quite stable across bonds of different maturities. Results show that including liquidity risk in the municipal bond pricing model helps explain the muni puzzle.

This paper examines the implications of tax loss carryback incentives for corporate reporting decisions and capital market behavior. During the 1981 through 2010 sample period, we find that firms increase losses in order to claim a cash refund of recent tax payments before the option to do so expires, and we estimate that firms with tax refund-based incentives accelerate about $64.7 billion in losses. Tax-motivated loss shifting is reflected in both recurring and nonrecurring items and is more evident for financially constrained firms. Analysts do not generally incorporate tax-motivated loss shifting into their earnings forecasts, resulting in more negative analyst forecast errors for firms with tax-based incentives than for firms without. Holding earnings surprises constant, however, investors react less negatively to losses reported by firms with tax loss carryback incentives. Data Availability: Data are available from sources identified in the paper.

We investigate the generalizability of widely perceived notions that buy-side analysts try to influence or manipulate a firm’s stock price by praising or criticizing management during a public earnings conference call. Despite two institutional factors that make it difficult to detect empirically, we find some evidence of stock influence behavior by using a combination of data on conference call transcripts and trading by the institutions that employ the buy-side analysts. However, we also find evidence consistent with the null hypothesis that buy-side analysts are acquiring information rather than manipulating the stock price. Subsample analyses suggest that stock influence is more detectable among hedge funds, while information acquisition is the norm among traditional buy-and-hold institutions. The evidence we provide on each behavior should be of interest to firm managers who host conference calls, market participants who use conference calls to collect company information, as well as regulators who monitor for possible market manipulation.

We explore whether accounting fraud can be detected using the information of firms economically linked to a focal firm. Specifically, we examine whether customer information disclosed by a supplier firm, combined with customers’ accounting information, helps to detect the supplier’s revenue fraud. We first confirm the economic link between the supplier and customers by showing a strong positive correlation between the supplier’s sales growth and the growth rate of total customer purchases. We then introduce two variables based on customer accounting information—the discrepancy between supplier sales growth and customer purchase growth and customer excess purchases—and show that they are predictive of supplier revenue fraud. We conduct a battery of cross-sectional tests and generally find results to vary cross-sectionally in a predictable way. Finally, the out-of-sample tests indicate that adding the two variables to Dechow, Ge, Larson, and Sloan (2011) model increases fraud prediction accuracy.