Research

Preemption and Forecast Accuracy: A Structural Approach,  [Download]

       This paper examines how competition affects information provided by experts. I estimate a timing game played by financial analysts who produce earning forecasts. Over time, both the exogenous information available to the market and the information privately observed by each analyst become more precise. In choosing when to release their forecasts, analysts weigh whether to wait for more precise information in order to forecast more accurately, or to preempt their competitors by reducing the informational advantage enjoyed by rivals who have yet to issue their forecasts. I estimate the structural parameters that govern the arrival rate of exogenous public information and the accuracy of the analysts' private signals. These estimates allow me to assess the informational value of professional forecasters. I find that financial analysts produce 40 percent of the information on future earnings  made available to investors during the forecasting period. I perform a counterfactual experiment with fixed forecast dates to quantify the extent to which preemption affects forecast delay and forecast accuracy. Preemption reduces forecast delays substantially: without preemption, the average analyst would disclose her forecast eight days after the date observed in the data. Because earlier forecasts use less information, preemption diminishes the average forecast accuracy by 24 percent.

Structural Estimation of Expert Bias: the Case of Movie Critics (joint with Nicolas Dupuis), [Download]

    We develop the first structural estimation of reputational cheap-talk games using data on movie reviews released in the US between 2004 and 2013. We identify and estimate movies’ priors, as well as movie critics’ abilities and strategic biases. We find that critics adopt reporting strategies that are consistent with the predictions of the literature on reputational cheap-talk. The average conservatism bias for low prior movies lies between 8 and 11%, depending on the specifications of the model. The average conservatism bias for high prior movies ranges from 13 to 15%. Moreover, we find a significant, albeit small, effect of the reputation of the critics on their strategies, indicating that incentives to manipulate demand in order to prevent reputation updating are present in this industry. Our estimation takes into account and quantifies potential conflicts of interest that might arise when the movie critic belongs to the same media outlet as the film under review. Out-of-sample predictions confirm that movie critics do have reputational concerns. 

Avoiding Judgement by Recommending Inaction: Beliefs Manipulation and Reputational Concerns (joint with Nicolas Dupuis), [Download]{New Version January 2021}

To evaluate an expert, the audience needs to compare the prediction of the expert with the realized outcome. But the prediction often aects the amount of public

information about the outcome. This is typically the case when the expert has to predict the quality of an experience good or the return of an investment opportunity.

It results that the expert can manipulate her audience's ability to monitor the accuracy of her prediction. In a cheap talk framework, we study how the endogenous nature

of public information about the state of the world aects the information transmitted by an expert with reputational concerns. Our innovation consists in assuming that

the precision of the public information on the realized state increases monotonically with the audience's interim beliefs. In addition to the conservatism bias found in the

existing literature, our model predicts that: (i) the expert is less communicative when the prior is low; (ii) a higher initial reputation can make the expert less credible. (JEL

D82, D83, L15)

Experts and Conflicts of Interest: Evidence from FDA Advisory Committees (joint with Margaret Kyle)

    The Food and Drug Administration (FDA) relies on committees of experts to provide advice on the approval of new drugs and medical devices. The medical experts who participate may have financial ties to the firms whose products they are evaluating. For example, they may be researchers who have received financial support from pharmaceutical companies for clinical work, or who have received consulting or speaking fees. Experts with ties with the industry are often leading researchers in their fields, who are therefore better able to review clinical evidence and make correct approval decisions. However, amid growing concerns that conflicts of interest corrupt the judgment of FDA advisors, the FDA has introduced more

stringent conflict-of-interest rules in recent years. We investigate (1) whether financial ties  with the pharmaceutical industry affect the voting behavior of FDA advisors, (2) whether FDA advisors who work closely with pharmaceutical companies are more likely to assess correctly the quality of candidate drugs and devices, and (3) whether the potential bias due to conflict of interest is offset by the higher level of expertise of advisors with ties with the industry.

Note: All papers are available upon request. Do not hesitate to contact me using the email address: fanny.camara@tse-fr.eu